https://www.synbiocyc.org/wiki/api.php?action=feedcontributions&user=Ajv684&feedformat=atomSynBioCyc - User contributions [en]2024-03-29T05:33:32ZUser contributionsMediaWiki 1.21.1https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/Bioremediation%26caffeinatedcoliTalk:CH391L/S14/Bioremediation&caffeinatedcoli2014-04-18T13:50:10Z<p>Ajv684: </p>
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<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 17:15, 14 April 2014 (CDT) The grammar in the bioattenuation section needs to be improved. In a couple of places throughout the article you use "nature" instead of "natural" "in its nature state" should be "in its natural state"... (phytoremediation)<br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 17:15, 14 April 2014 (CDT) Good use of examples and covering the potential modes of bioremediation. I would like to know more about the "natural" bioremediation... what types of bacteria are used? What are the relevant pathways?<br />
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*--[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 08:50, 18 April 2014 (CDT)Nice job Chen. Except for the grammar mistakes that Dennis already mentioned in general your wiki introduces very well this topic to a lay reader. It's well organized and comprehensive. My critique mainly is that of the need of a smoother transition between the caffeinated E. Coli and bioremediation. I see a lot of strategies in common but in you wiki it looks a bit disconnected. Other than that great job. <br />
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--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 17:12, 17 April 2014 (CDT)* Nathan's wiki critique<br />
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'''Overall Format and structure: '''<br />
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Nice layout, practical and generally easy to follow. There were many examples of bioremediation discussed and this wiki discussed an extensive breadth regarding the topic. Overall, the wiki seemed very focused and structured. <br />
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'''Introduction and background material:'''<br />
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The introduction to this wiki was very succinct and precise. It gave a clear overview of the topics that were to be discussed in greater detail later in the wiki. I was able to understand the general underlying concept of bioremediation simply by reading the introduction. <br />
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'''Methods and main body/concepts:'''<br />
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The descriptions of the different methods were good. They gave a thorough description of what the methods entailed and how it worked. However, I think it would be beneficial to the readers if you gave real examples of how these methods of bioremediation are being used around the world. Perhaps discussing how well each method works and sharing success stories would help this wiki. Also, I think it would have been helpful to discuss the future direction of bioremediation and the problems that must be overcome. Lastly, I would like to have seen how microorganisms help increase efficiency and biocompatability of the plants. <br />
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'''Relation to iGEM and future directions:'''<br />
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There wasn't much about the future direction of bioremediation. I think an additional section focusing on the future of this topic would be beneficial. <br />
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'''Figures, Figure legends, and citations:'''<br />
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The figures were very helpful in understanding the topics that were discussed. <br />
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----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/ArtemisininTalk:CH391L/S14/Artemisinin2014-04-18T13:44:02Z<p>Ajv684: </p>
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<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 17:10, 14 April 2014 (CDT) Nice article, Liz. My one main critique is that the first figure seems a bit blurry. Can you get a better resolution photo?<br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 17:10, 14 April 2014 (CDT) It might be nice to add something about similar pathways or attempts to make similar or other natural product molecules in bacteria...<br />
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*--[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 08:44, 18 April 2014 (CDT)Very good job Liz. Very easy to read, comprehensive and interesting wiki. I learned a lot from this article. My main concern is that most of the techniques if not all that have been used to optimize the production of this molecule are traditional metabolic/genetic engineering techniques and I don't see a lot of innovation in terms of synthetic biology tools but that's just my opinion and I might have the wrong take on this. <br />
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--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:48, 18 April 2014 (CDT) Mindy's Critique<br />
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'''Overall Format and structure:''' The overall format and structure was very well laid out. The brief introduction gives a succinct explanation of what is to follow, and the rest of the paragraphs follow an order that makes sense. The tone is appropriate, and the overall wording is as well. The only comment for this portion would be that the article is extremely technical, but unfortunately due to the nature of the topic, this seems rather unavoidable. Overall this was a very good wiki.<br />
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'''Introduction and background material:''' The one line description at first seemed odd, but once taken in context with the history made complete sense; it is a quick way to introduce the topic such that it can be interpreted by the reader in a single glance and yet still provide meaningful information. The history section provides context for the rest of the article, which is very helpful. It introduces the compound, its uses and the problem with obtaining it. The only thing that might be added is a sentence about the impact of malaria that would give readers a sense of the compound's importance, but this is not completely necessary.<br />
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'''Methods and main body/concepts:''' I found no issues with the main body of the article- it is extremely well explained and thorough. It provides a complete picture of the semisynthesis process, which is the focus of this class since that is the portion related to synthetic biology. Inclusion of the figures made it understandable and complemented it well.<br />
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'''Relation to iGEM and future directions:''' The future directions section was good, it indicated what could be developed further and also the level of difficulty involved. The “Other Strategies” section was also a nice addition, because it gave the reader a sense of how important the semisynthesis pathway was in the ability to create useful amount of the drug. The iGEM section was remarkably short, but it is possible that this information is all that was available. If there is a link available to the information that was found, or if there is any sort of diagram available, this might add to the section in a positive way.<br />
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'''Figures, Figure legends, and citations:''' In the very first line it might be advantageous to have a small figure of the actual structure of Artemisinin so the reader doesn't have to go looking for it in the synthesis pathways below. All other legends were extremely helpful and well described in the legends. There were ample and proper citations, and each citation had a very clear indicator beneath that described what it referenced. <br />
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----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/NitrogenFixationRefactoringTalk:CH391L/S14/NitrogenFixationRefactoring2014-04-18T13:39:41Z<p>Ajv684: </p>
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<div>*--[[User:Aeg2338|Alejandro Gutierrez]] ([[User talk:Aeg2338|talk]]) 08:00, 18 April 2014 (CDT) Good page overall. The breakdown of how the process works was pretty easy to follow. One thing I noticed was that you left a bullet point, "introduction of pathway into cereal crops". It would be nice to see what that would be, if possible.<br />
*--[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 08:33, 18 April 2014 (CDT)very well written wiki. It was easy to understand and easy to read. There are a few typos throughout so I'd suggest to go over it with a close eye and correct them. As far as contents it looks good enough to me I'd probably add a bit more experimental details but that's more my personal preference. I think in general it was well broken down and well explained. Also I think the wiki would benefit it figures had a little more expanded captions.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/NitrogenFixationRefactoringTalk:CH391L/S14/NitrogenFixationRefactoring2014-04-18T13:33:56Z<p>Ajv684: </p>
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<div>*--[[User:Aeg2338|Alejandro Gutierrez]] ([[User talk:Aeg2338|talk]]) 08:00, 18 April 2014 (CDT) Good page overall. The breakdown of how the process works was pretty easy to follow. One thing I noticed was that you left a bullet point, "introduction of pathway into cereal crops". It would be nice to see what that would be, if possible.<br />
*----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 08:33, 18 April 2014 (CDT)very well written wiki. It was easy to understand and easy to read. There are a few typos throughout so I'd suggest to go over it with a close eye and correct them. As far as contents it looks good enough to me I'd probably add a bit more experimental details but that's more my personal preference. I think in general it was well broken down and well explained.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:52:42Z<p>Ajv684: </p>
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<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)anywhere I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)I added a new section and I hope I was able to answer your questions. In general, this methodology has been used not in a wide manner except for a few examples and much less when talking about metabolic engineering. <br />
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*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Sorry, I did not mention in the wiki that at least three works out of the list have been addressed in different sections. I added a note to refer to the table whenever I addressed a work listed in it. Sorry I did not format the table to be presented in a more friendly format but it was just going to take me long time to do that and I just wanted to give a grasp of how many works have addressed this specific topic in the last 10 years. <br />
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*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Ella, yeah there is examples of sRNAs that have this dual ability e.g. DsrA. I added this to the section Future directions. They usually have two different binding regions in the same sRNA. <br />
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*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Gabriel, just corrected that of the first person. I added the definition of metabolic engineering. <br />
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*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:19, 14 April 2014 (CDT)Thanks Liz, I corrected most of the grammar mistakes to the best of my knowledge. I added a future directions section and I hope I am able to answer most of your questions. <br />
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--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:25, 14 April 2014 (CDT)Thanks Drew, very good feedback. I corrected grammar mistakes but did not have time to address the evolutionary issue, sorry. I know there is at least one publication regarding that that I came across and in general the binding regions are highly conserved and bear some evolutionary plasticity. I am unsure as to what the implications in synthetic biology would be though and that's also why I do not feel confident to include this in the wiki. As for miRNAs I have added that mention in the introduction. <br />
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--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:25, 14 April 2014 (CDT)Thanks Chen. I corrected that of the first person style but I did not remove words from the figure captions since some of them are very complicated. What I did in contrast is to increase the size of the figures to make them more appropriate to the same of the captions. <br />
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--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
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'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
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'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
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'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
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'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
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'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
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**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:52, 14 April 2014 (CDT)Thanks Ashley, I appreciate your feedback. I went over most of your comments and modify the wiki accordingly.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:27:53Z<p>Ajv684: /* A robust gene expression control device inspired on sRNAs */</p>
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<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
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== Introduction ==<br />
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Bacterial small RNAs (sRNAs) are gene regulatory entities, analogous to their counterparts in eukaryotes micro RNAs, that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications.<br />
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== Bacterial small RNAs ==<br />
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[[File:Figure1review.png|thumb|left|1000 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
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sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
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Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
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A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
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== sRNAs in Synthetic Biology ==<br />
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[[File:Figure2review.png|thumb|right|800 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
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sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
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=== Designing a synthetic sRNA ===<br />
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[[File:Figure3review.png|thumb|left|600 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
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Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
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=== sRNAs in metabolic engineering ===<br />
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Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
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As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|1000 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:27:32Z<p>Ajv684: /* sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities, analogous to their counterparts in eukaryotes micro RNAs, that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications.<br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|1000 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|800 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|600 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:26:41Z<p>Ajv684: /* sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities, analogous to their counterparts in eukaryotes micro RNAs, that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications.<br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|1000 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|1000 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|1000 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:26:12Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities, analogous to their counterparts in eukaryotes micro RNAs, that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications.<br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|1000 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:25:52Z<p>Ajv684: /* Introduction */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities, analogous to their counterparts in eukaryotes micro RNAs, that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications.<br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:25:05Z<p>Ajv684: </p>
<hr />
<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)anywhere I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)I added a new section and I hope I was able to answer your questions. In general, this methodology has been used not in a wide manner except for a few examples and much less when talking about metabolic engineering. <br />
<br />
*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Sorry, I did not mention in the wiki that at least three works out of the list have been addressed in different sections. I added a note to refer to the table whenever I addressed a work listed in it. Sorry I did not format the table to be presented in a more friendly format but it was just going to take me long time to do that and I just wanted to give a grasp of how many works have addressed this specific topic in the last 10 years. <br />
<br />
*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Ella, yeah there is examples of sRNAs that have this dual ability e.g. DsrA. I added this to the section Future directions. They usually have two different binding regions in the same sRNA. <br />
<br />
*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Gabriel, just corrected that of the first person. I added the definition of metabolic engineering. <br />
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*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:19, 14 April 2014 (CDT)Thanks Liz, I corrected most of the grammar mistakes to the best of my knowledge. I added a future directions section and I hope I am able to answer most of your questions. <br />
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--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:25, 14 April 2014 (CDT)Thanks Drew, very good feedback. I corrected grammar mistakes but did not have time to address the evolutionary issue, sorry. I know there is at least one publication regarding that that I came across and in general the binding regions are highly conserved and bear some evolutionary plasticity. I am unsure as to what the implications in synthetic biology would be though and that's also why I do not feel confident to include this in the wiki. As for miRNAs I have added that mention in the introduction. <br />
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--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:25, 14 April 2014 (CDT)Thanks Chen. I corrected that of the first person style but I did not remove words from the figure captions since some of them are very complicated. What I did in contrast is to increase the size of the figures to make them more appropriate to the same of the captions. <br />
----<br />
--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
<br />
'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
<br />
'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
<br />
'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
<br />
'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
<br />
'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
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----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:20:03Z<p>Ajv684: </p>
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<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthesize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:19:36Z<p>Ajv684: </p>
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<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)anywhere I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)I added a new section and I hope I was able to answer your questions. In general, this methodology has been used not in a wide manner except for a few examples and much less when talking about metabolic engineering. <br />
<br />
*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Sorry, I did not mention in the wiki that at least three works out of the list have been addressed in different sections. I added a note to refer to the table whenever I addressed a work listed in it. Sorry I did not format the table to be presented in a more friendly format but it was just going to take me long time to do that and I just wanted to give a grasp of how many works have addressed this specific topic in the last 10 years. <br />
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*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Ella, yeah there is examples of sRNAs that have this dual ability e.g. DsrA. I added this to the section Future directions. They usually have two different binding regions in the same sRNA. <br />
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*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Gabriel, just corrected that of the first person. I added the definition of metabolic engineering. <br />
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*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:19, 14 April 2014 (CDT)Thanks Liz, I corrected most of the grammar mistakes to the best of my knowledge. I added a future directions section and I hope I am able to answer most of your questions. <br />
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--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
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--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
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----<br />
--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
<br />
'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
<br />
'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
<br />
'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
<br />
'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
<br />
'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
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----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:17:30Z<p>Ajv684: /* sRNAs in metabolic engineering */</p>
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<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
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sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
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=== Designing a synthetic sRNA ===<br />
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[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
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Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
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=== sRNAs in metabolic engineering ===<br />
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Metabolic engineering is an enabling technology for strain optimization towards the production enhancement of biotechnological substances. As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
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As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
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[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
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== A robust gene expression control device inspired on sRNAs ==<br />
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[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
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Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
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== Future directions for sRNAs in Synthetic Biology ==<br />
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To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
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== sRNA-like iGEM projects ==<br />
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The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
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Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:16:09Z<p>Ajv684: </p>
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<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)anywhere I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
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*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)I added a new section and I hope I was able to answer your questions. In general, this methodology has been used not in a wide manner except for a few examples and much less when talking about metabolic engineering. <br />
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*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Sorry, I did not mention in the wiki that at least three works out of the list have been addressed in different sections. I added a note to refer to the table whenever I addressed a work listed in it. Sorry I did not format the table to be presented in a more friendly format but it was just going to take me long time to do that and I just wanted to give a grasp of how many works have addressed this specific topic in the last 10 years. <br />
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*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Ella, yeah there is examples of sRNAs that have this dual ability e.g. DsrA. I added this to the section Future directions. They usually have two different binding regions in the same sRNA. <br />
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*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:16, 14 April 2014 (CDT)Thanks Gabriel, just corrected that of the first person. I added the definition of metabolic engineering. <br />
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*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
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--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
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--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
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----<br />
--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
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'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
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'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
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'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
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'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
<br />
'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
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----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:10:54Z<p>Ajv684: /* Future directions for sRNAs in Synthetic Biology */</p>
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<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
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== Introduction ==<br />
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Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
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[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
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sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
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Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
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A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
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== sRNAs in Synthetic Biology ==<br />
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[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
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sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
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=== Designing a synthetic sRNA ===<br />
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[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
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Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Examples of sRNA-inspired devices date back to 2004 and since then several artificial sRNA-like devices have been created, in its majority aiming for gene silencing applications. However, these pioneering examples, although claimed to have been inspired over natural sRNAs did not exploit in full sRNA features as sRNA were still very novel molecules. Recently, works such as the ones listed in Table 1 have been exploiting more deeply sRNA features for the gene silencing purposes. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:07:54Z<p>Ajv684: </p>
<hr />
<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)anywhere I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:07, 14 April 2014 (CDT)I added a new section and I hope I was able to answer your questions. In general, this methodology has been used not in a wide manner except for a few examples and much less when talking about metabolic engineering. <br />
<br />
*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
<br />
*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
<br />
*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
<br />
*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
<br />
--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
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--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
<br />
----<br />
--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
<br />
'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
<br />
'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
<br />
'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
<br />
'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
<br />
'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
<br />
----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:05:58Z<p>Ajv684: /* Future directions for sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
To date, sRNA synthetic systems remain as a widely unexplored field moreover when referring to metabolic engineering applications. Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/Talk:CH391L/S14/SmallRNAsTalk:CH391L/S14/SmallRNAs2014-04-14T18:04:53Z<p>Ajv684: </p>
<hr />
<div>*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Jorge, there are a few grammar/typos located throughout the article. In particular, the introduction and the "sRNAs in metabolic engineering" were sections where the errors interfered with my understanding of the section.<br />
**----[[User:Ajv684|Jorge Vazquez ]] ([[User talk:Ajv684|talk]]) 13:04, 14 April 2014 (CDT)I corrected most of them I think and now the wiki should be in a much better shape. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) Also, since you have written a review on this topic (ref #4), make sure you are not "self-plagiarizing" anywhere in the article. Make any quotes from that article very obvious, and keep them to a minimum. Remember, this includes verbatim copying as well as copying with minor changes.<br />
**--anywhere where I mentioned and idea that I had already mentioned in my review has been properly cited. There are no written fragments with high similarity to my review but still the ideas and concepts have been properly cited. Figures and legends are identical to the review and other papers but have been properly cited as well. <br />
<br />
*--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 08:13, 9 April 2014 (CDT) I would like to see a future directions sections that expands on current work and possible future work. From your wiki article, I don't have a full appreciation of how commonly this methodology is being currently used... are there other current examples? <br />
<br />
*You provide a nice table, but you don't really describe these works. At least a couple of them should be addressed in either the "current research" or "future directions" sections.<br />
<br />
*--[[User:Ew6977|Ella Watkins ]] ([[User talk:Ew6977|talk]]) 11:59, 10 April 2014 (CDT) "In addition, '''sRNA capacity to simultaneously multiple genes''' has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology." The bolded part, I am not sure if it is supposed to say multiply? Also, I understand that sRNAs bind to mRNAs and can affect what happens to the mRNA (inhibiting, leading to degredation, etc.) but can one sRNA have multiple effects? For example one sRNA activates one mRNA and inhibits a different one? Or is that not how they work? Do they all have one specific action (i.e. activation, inhibition...) and act on different mRNA with the same action?<br />
<br />
*--[[User:gas2342|Gabriel Suarez]] ([[User talk:gas2342|talk]]) 04:20, 11 April 2014 (CDT) I really liked the overall structure and comprehensive coverage of sRNAs in your wiki report. Writing is clear and very easy to follow. I also liked that figures are very well described. Maybe it shocked me a little bit that the article is written in first person "In this article I will...", but I guess that's ok. It might be good give a brief description of what is meant by "metabolic engineering", that way it should transition better into that subject in the section of "sRNAs in metabolic engineering". BTW, great presentation!<br />
<br />
*--[[User:Eg25529|Liz]] ([[User talk:Eg25529|talk]]) 07:17, 11 April 2014 (CDT)Agreed with comments above about grammar in the Introduction, not really sure what part Ella has in bold means. (Orthogonally= orthogonality?) Also, I think something more like "This article will focus on..." could get the point across in a better way. I think you should reword later uses of first person in a similar (or not) way. Figures should be larger- especially given such descriptive captions. Small typos and word choice (berak, synthetize, diversity to variety or "diverse mechanism" kind of thing, so =to, ) issues to be fixed. Overall, you do a great job explaining the terms and important concepts associated with this field. As far as any missing information, what I would like to see a little more of is maybe how this technology developed, and like Dennis said kind of where it is going now. You do mention the work of Sharma et al but I guess my question would be - was this a huge breakthrough? How did their progress fit in the history of general progress on knowledge/ synthesis of sRNA? And of course you include the table and Hao, but maybe a highlight of one or two more especially interesting papers would emphasize how interesting this is. Great job overall- obviously you're really knowledgeable on the subject!<br />
<br />
--[[User:Dst465|drewtack]] ([[User talk:Dst465|talk]]) 07:49, 11 April 2014 (CDT)Disclosure: i have not read comments above, sorry if I'm repeating. This is as I go through. I think you mean orthogonality in the intro, not orthogonally? and what type of specific sRNAs are you talking about at the end of the intro? The next section I feel should at least ''mention'' miRNAs, or whatever the eukaryote equivalent is. Additionally, maybe some mention in their role in evolution? I don't know, this could be way off, but I feel like I've heard these are highly susceptible to mutation, and have a less significant impact when mutated, so they are a driver of evolution. Or I might be completely wrong here. Your table is blurry no matter what, making it very difficult to read. Everything else looks pretty good. One thing I might mention sylistically is that your captions are '''long''', especially in comparison to the size of your images. It looks silly, if you just made your images bigger, it would appear that they justify such large captions, and I think your captions are appropriate, just the images are a little undersized.<br />
<br />
--[[User:Chen-Hsun Tsai|Chen-Hsun Tsai]] ([[User talk:Chen-Hsun Tsai|talk]]) 11:20, 14 April 2014 (CDT) I think this is a very well written wikipage, with many well described examples of sRNAs mechanisms. I only have two things: first I think there are too many words in the figure captions, maybe you can describe the figures in the main text instead. Second is the first-person style, it connects the paragraphs well but it also makes the article more like a presentation, not a wiki. <br />
<br />
----<br />
--[[User:Dennis Mishler|Dennis Mishler]] ([[User talk:Dennis Mishler|talk]]) 07:54, 11 April 2014 (CDT) Ashley's critique<br />
<br />
'''Overall Format and structure: '''<br />
Very well formatted and structured. The introduction is simple yet encapsulates the basic idea of some of the functions of sRNAs. Maybe it would help to expand the figures, specifically in the first section, as I think they are very helpful.<br />
<br />
'''Introduction and background material:'''<br />
I like the introduction as it gives a good, brief overview of what sRNAs are and why they’re important. There are a few grammatical errrors that I would recommend fixing though:<br />
“These RNAs are in… genes and thus are essential for an organism’s survival under different extreme environmental conditions”<br />
I would also suggest rewording the sentence starting with “Their high modularity and orthogonally” <br />
“In addition, the capacity of sRNA molecules” <br />
I would also recommend trying to find a different word for “enabled”<br />
It may be helpful to bold the statement “Hereafter, I will refer to them simply as sRNAs” as it is a very important sentence in terms of the reader taking away correct information from the rest of the article. Also, if you have this sentence in the article, then perhaps it may help the flow of the article to take away the last sentence of the introduction “Hereby I will… biology.”<br />
Towards the middle of the paper, there is a lot of nomenclature being used that, perhaps, a non-expert would have trouble understanding without looking the terms up.<br />
<br />
'''Methods and main body/concepts:'''<br />
The article was very easy to follow and explained concepts clearly. There were a few grammar mistakes though, some of which I have listed below:<br />
“sRNAs can be classified as cis…”<br />
“This property, in turn, …”<br />
“Trans-encoded… addition to mRNAs; an example…”<br />
“…a diversity diverse array of mechanisms…”<br />
Under “Designing a synthetic sRNA”:<br />
“They were able so successfully able to identify sRNA…”<br />
“…Correlation between structure and function…”<br />
Under “sRNAs in metabolic engineering”:<br />
“…developing an alternative methodology…”<br />
<br />
'''Relation to iGEM and future directions:'''<br />
Very interesting and it seems pretty thorough. One thing I would recommend is that although the iGEM projects are cited in the bibliography, it may be good to include citations in the paragraph itself.<br />
<br />
'''Figures, Figure legends, and citations:'''<br />
The figures were very helpful throughout the article, and the captions were all very well worded and helped explain the topics at hand. A diverse array of citations is found throughout the article, though I believe there are citations missing regarding the Ocean and Uppsala Universities’ iGEM project (though, granted, the two projects were mentioned very briefly).<br />
<br />
----</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T18:01:34Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== Future directions for sRNAs in Synthetic Biology ==<br />
<br />
Definitely the work carried out by Na et al. <cite>Na2013</cite> is a methodology for strain optimization with a great potential to be widely exploited in the metabolic engineering field. It is expected that this method will continue to be refined and standardized with the vision of using it in combination with traditional strain optimization techniques to enhance metabolic engineering ability to increase the production of relevant substances at the industrial scale. Although this work represents a great leap in the use of sRNA-based strategies in metabolic engineering, it did not exploit a very useful capability of sRNAs just yet: multi-targeting. In lieu of the recent interest in sRNA, it is plausible to expect that researches will start working on DsrA-like systems. DsRA is a sRNA that can control two target mRNAs at once as it activates production of RpoS mRNA (the stationary phase sigma factor) and inhibits H-NS (histone-like nucleoid-structuring protein) translation. This astonishing ability to repress and enhance the production of two different mRNAs a the same time seems of great relevance since for strain optimization some genes are turned on and some are turned down simultaneously for an overall increase in the production of the molecule of interest. To date, there are no examples of such an artificial sRNA with this dual capability. These promising perspectives at the same time are in the need of enabling technologies, the development of rational design approaches is of great relevance to assist on the sRNA rational design<cite>Vazquez2013</cite>. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.<cite>Na2013</cite> work, they were able to identify genes involved in the metabolic pathway of the metabolites of interest that were not expected to have an effect in the overall production. In addition, the fine-tuning capabilities of sRNA-like systems allows for the partial repression of essential genes without the negative consequence of inviable cells. <br />
<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:42:41Z<p>Ajv684: /* sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> (ref. 104 in Table 1) generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:41:55Z<p>Ajv684: /* sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> (ref. 72 in Table 1) developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:40:26Z<p>Ajv684: /* sRNAs in metabolic engineering */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> (ref. 68 in Table 1) generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:39:12Z<p>Ajv684: /* References */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.<br />
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview<br />
//sRNA system for the prediction of red tide.<br />
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University<br />
//sRNA system for the repression of resistance genes in bacteria.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:37:20Z<p>Ajv684: /* sRNA-like iGEM projects */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of China iGEM 2012 <cite>iGEMOUC2012</cite> team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team <cite>iGEMUU2012</cite> constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:34:43Z<p>Ajv684: /* sRNA-like iGEM projects */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 <cite>iGEMDTU2011</cite> used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:32:18Z<p>Ajv684: /* References */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#Callura2012 pmid=22454498<br />
//A genetic switchboard based on an sRNA-like device.<br />
#Friedland2009 pmid=19478183<br />
//A transcriptional cascade based of an sRNA-like device that counts up to three. <br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:30:10Z<p>Ajv684: /* A robust gene expression control device inspired on sRNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device e.g. a "cell that counts"<cite>Friedland2009</cite> and a "switchboard"<cite>Callura2012</cite>. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:26:50Z<p>Ajv684: /* sRNAs in Synthetic Biology */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonality can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting of natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes an Hfq domain and a transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates. Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able to successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths shown by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. Specifically, the authors of this work selected the MicC sRNA scaffold, that includes the Hfq-binding site, and modify the binding domain by the introduction of anti-sequences of genes involved in the metabolic pathway of either cadaverine or tyrosine. Subsequently, they created a library of anti-sense RNAs and isolated the strains with higher production of the target molecules. Finally, used what they called forward engineering, to fine-tune the production optimization of these two metabolites by binding energy. They identified genes not expected to affect the titer of these metabolites but that are involved in the metabolic pathway regulation. This last realization represents a advantage over other traditional metabolic engineering approaches. In addition, this sRNA-based approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. However, it is expected that this field will soon explode to produce numerous works and even applications aiming for more efficient strain optimization techniques for the production of biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:12:56Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA<cite>Gottesman2004</cite>. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction, gene expression control could potentially be greatly improved since the gene repression dynamic range is enhanced. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable increase in its gene silencing capabilities<cite>Sakai2013</cite>.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:09:25Z<p>Ajv684: /* Bacterial small RNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as it will be shown in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability of sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:07:12Z<p>Ajv684: /* Bacterial small RNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). '''This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.''' This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:05:53Z<p>Ajv684: /* Bacterial small RNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). === This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs. === This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:05:26Z<p>Ajv684: /* Bacterial small RNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). = This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs. = This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-14T17:04:43Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes and thus are essential for an organism's survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonality have raised interest among synthetic biologists towards the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously target single or multiple genes with high specificity has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. <br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified as cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over a single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs; an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). =This article will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, they will be referred simply as sRNAs.= This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T19:18:49Z<p>Ajv684: /* sRNAs in metabolic engineering */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/File:Table1Reviewa.pngFile:Table1Reviewa.png2014-04-07T19:17:58Z<p>Ajv684: </p>
<hr />
<div></div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T19:17:14Z<p>Ajv684: /* sRNAs in metabolic engineering */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Reviewa.png|thumb|center|800 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/File:Table1Review.pngFile:Table1Review.png2014-04-07T19:15:45Z<p>Ajv684: Ajv684 uploaded a new version of &quot;File:Table1Review.png&quot;: Reverted to version as of 17:53, 7 April 2014</p>
<hr />
<div></div>Ajv684https://www.synbiocyc.org/wiki/index.php/File:Table1Review.pngFile:Table1Review.png2014-04-07T19:14:50Z<p>Ajv684: Ajv684 uploaded a new version of &quot;File:Table1Review.png&quot;</p>
<hr />
<div></div>Ajv684https://www.synbiocyc.org/wiki/index.php/File:Table1Review.pngFile:Table1Review.png2014-04-07T19:14:26Z<p>Ajv684: Ajv684 uploaded a new version of &quot;File:Table1Review.png&quot;</p>
<hr />
<div></div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:58:18Z<p>Ajv684: /* A robust gene expression control device inspired on sRNAs */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|300 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity.<br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:52:07Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|800 px|Figure 4. Trans-activation mechanism and results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/File:Isaacs.pngFile:Isaacs.png2014-04-07T18:51:17Z<p>Ajv684: </p>
<hr />
<div></div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:50:37Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
[[File:Isaacs.png|thumb|right|200 px|Figure 4. Trans-activation mechanism and<br />
results. (a) The artificial riboregulator system has the following proposed mechanism: (i) the 5′ linear region of the taRNA (gray) recognizes a YUNR consensus sequence (UUGG)27 on the loop (gray) of crRNA, (ii) pairing between complementary nucleotides occurs in the presence of an unstable loop-tail complex and destabilizes the hairpin stem-loop that obstructs ribosomal recognition of the RBS (blue) and (iii) a stable intermolecular RNA duplex structure forms. The resulting RNA duplex exposes the RBS and allows translation to occur. (b,c) Mfold-predicted28 structures of taR12 (b) and crR12 (c) variants (same color scheme as Fig. 2). (d) Proposed taR12-crR12 interaction that exposes the RBS, which is 5–6 bp downstream of the taRNA-crRNA duplex formation. (e,f) Flow-cytometric results of taR10-crR10 (e) and taR12-crR12 (f) riboregulator systems. Autofluorescence measurements (–C, negative control; cells lacking GFP) are in black and GFP expression of positive control (+ C; cells without cis sequence) cultures are in blue. The red curve represents cis-repressed cultures (no arabinose, 30 ng/ml aTc) and the green curve depicts cells containing high levels of taRNA (0.25% arabinose) and crRNA (30 ng/ml aTc). Of note, the taR12-crR12 riboregulator (f) showed both greater cis repression and higher trans activation than the taR10-crR10 riboregulator (e). Interestingly, both riboregulator variants possess the same sequence and predicted structure in the loop and share 12 of the first 13 potential duplex pairs in the cis stem, indicating that specificity of interaction emanates from slight changes in sequences of the cis elements. In the Supplementary Notes online, we describe various rational attempts to increase the dynamic range of the taR12-crR12 riboregulator pair.<cite>Isaacs2004</cite>]]<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system (Figure 4). This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.<br />
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project<br />
//sRNA system with a trap-RNA for chitibiose control.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:42:57Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.<br />
#Sakai2013 pmid=24328142 <br />
//Effect of Hfq domain introduction into a synthetic sRNA.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:38:26Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.<cite>Isaacs2004</cite> developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.<cite>Sakai2013</cite> introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.<br />
#Isaacs2004 pmid=15208640<br />
//A robust sRNA-inspired riboregulator.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:30:51Z<p>Ajv684: /* References */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.(ref) developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al. (ref) introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T18:28:54Z<p>Ajv684: /* Bacterial small RNAs: a powerful tool for metabolic engineering */</p>
<hr />
<div>=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.(ref) developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al. (ref) introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma 2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T17:57:23Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: a powerful tool for metabolic engineering ===<br />
<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.(ref) developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al. (ref) introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma 2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.</div>Ajv684https://www.synbiocyc.org/wiki/index.php/CH391L/S14/SmallRNAsCH391L/S14/SmallRNAs2014-04-07T17:56:34Z<p>Ajv684: </p>
<hr />
<div>=== Bacterial small RNAs: a powerful tool for metabolic engineering ===<br />
<br />
<br />
== Introduction ==<br />
<br />
Bacterial small RNAs (sRNAs) are gene regulatory entities that range from 21 to 400 nucleotides in size. These RNAs are in charge of controlling expression of stress-response genes thus are essential for organism survival under different extreme environmental conditions (e.g. nutrient availability, osmolarity, pH and temperature)<cite>Gottesman2004</cite>. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species <cite>Gottesman2011</cite><cite>Storz2011</cite>. Their high modularity and orthogonally have risen interest among synthetic biologists for the construction of sRNA-like devices. In addition, sRNA capacity to simultaneously multiple genes has enabled the vision of sRNAs as a powerful tool for metabolic engineering applications. Hereby I will focus on a specific type of sRNA and its presence in synthetic biology. <br />
<br />
== Bacterial small RNAs ==<br />
<br />
[[File:Figure1review.png|thumb|left|200 px|Figure 1: Gene Expression control mechanisms by bacterial sRNAs. (A) Transcription attenuation/enhancement. (A) sRNA binds to its target mRNA and causes a structural reconfiguration upon base-pairing, ultimately enhancing or attenuating transcription by the polymerase. (B) Translational control. Translational control is imparted by sRNAs in various ways: (1) A sRNA base-pairs to its target mRNA sequestering the Ribosome-Binding Site (RBS) and directly prevents translation initiation by the ribosomes. (2) A sRNA binds to the target mRNA at a distance from the RBS and the target mRNA suffers a structural change that indirectly affects ribosome binding. sRNA binding to its target can also enhance or inhibit mRNA decay by changing interactions with exonucleases and/or endonucleases.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs can be classified in cis-encoded and trans-encoded. The former refers to those that are transcribed from the complementary strand of the genes that they target. This class represents the minority of the sRNAs that have been identified up to now. Additionally, cis-encoded sRNAs usually exert a tight control over single target messenger RNA (mRNA). In contrast, trans-encoded sRNAs are transcribed from loci in the genome that are distant from where their mRNA targets are encoded. This class accounts for the great majority of sRNAs discovered to date. An astonishing feature is that these molecules can bind their mRNA partners by a minimal base-pairing requirement (8-9 nucleotides)<cite>Gottesman2004</cite>. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs<cite>DeLay2013</cite>. This property in turn enables the potential application of combinatorial gene knockdown in metabolic engineering. <br />
<br />
Trans-encoded sRNAs can target proteins in addition to mRNAs, an example of that are sRNAs such as CsrB/C and 6S RNA. When controlling mRNA expression this class of sRNAs uses a diversity of mechanisms. They can (1) base-pair to their target mRNAs to enhance or attenuate transcription (Figure 1A), (2) directly block (Figure 1B i), or indirectly enhance or inhibit translation (Figure 1B ii), (3) sequester proteins (not shown), or (4) directly lead to mRNA and protein degradation (Figure 1B iii). In this article I will exclusively focus on those sRNAs that are trans-encoded and only target mRNAs. Hereafter, I will refer to them simply as sRNAs. This class of sRNAs, as aforementioned, accounts for the majority of discovered sRNAs and can target multiple genes. Consequently, these sRNAs have attracted much interest among the Synthetic Biology community as I will show in the remainder of this article. <br />
<br />
A particular feature that this class of sRNAs exhibits is the interaction with a major chaperone protein called Hfq. These interactions have been mainly observed in gram-negative bacteria. Hfq action leads to the stability sRNAs, assists their binding to target mRNAs and stabilizes interactions sRNA-mRNA (ref 43). Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome <cite>Storz2011</cite>. By engineering Hfq interaction gene expression control could potentially be greatly improved by enhancing its dynamic range. In addition, the introduction of Hfq domains into an already constructed sRNA-like device could bring about a very valuable multiple-target capability.<br />
<br />
== sRNAs in Synthetic Biology ==<br />
<br />
[[File:Figure2review.png|thumb|right|200 px|Figure 2: Composability of sRNAs as a strategy for the synthesis of artificial RNA devices. sRNAs are regulators of high modularity. An sRNA-based regulator can be broken down in two main parts: a sensor (target binding domain) and a stabilizer (that can include an Hfq-binding site and the transcriptional termination domain). In the context of a genetic device, the sRNA binds an mRNA target. In this case, the 5′ UTR of the target mRNA acts as an adaptor that transmits the signal to the gene reporter actuator. The combination of the sRNA and mRNA target comprises a functional synthetic device.<cite>Vazquez2013</cite>]]<br />
<br />
sRNAs are highly composable, (composability is the ability of a system to berak down in units due to the system modularity and recombine in different configurations to satisfy specific human requirements), tunable and their orthogonallity can be designed a priori. In general, a variety of strategies have been used to synthetize sRNAs that include rational design, model-driven computational design, in vivo and in vitro molecular evolution and selection and, harvesting natural parts <cite>Vazquez2013</cite>. Efforts have focused on preserving the sRNA scaffold, which includes a Hfq domain and transcriptional terminator, and engineering the binding domain (see Figure 2 for a schematics of sRNA breakdown).<br />
<br />
=== Designing a synthetic sRNA ===<br />
<br />
[[File:Figure3review.png|thumb|left|200 px|Figure 2: Artificial sRNA screening strategy and library design. (a) Schematic illustration of the artificial sRNA screening strategy. A reporter vector with the target mRNA leader sequence fused to gfpuv is cotransformed with a partially randomized artificial sRNA expression library and plated on agar plates.<br />
Colonies with weaker fluorescence are picked and characterized. (b) Artificial sRNA library based on the Spot42 sRNA scaffold (yellow box). The antisense domain in Spot42 (identified for galK) is shown in gray, and the bases that were shown to interact with Hfq are indicated in bold.5 Degenerate bases (N) were inserted between the vector-derived sequence (50-ACUCGAG-30) and the sRNA scaffold.<cite>Sharma2012</cite>]]<br />
<br />
Three factors likely influence sRNAs ability to regulate gene expression: kinetics of binding, extension and energy of binding as well as the types and number of mRNAs that a given sRNA can bind. Based on these factors Sharma et al.<cite>Sharma2012</cite> developed a high-throughput strategy for the engineering of synthetic sRNAs. In their approach, the Hfq domain was left unchanged and a library of randomized binding domains was generated. A natural 5’ UTR was fused to a reporter gene (GFP) and the researchers selected for the repression of this gene. They were able so successfully identify sRNA candidates that repress ompF and fliC mRNAs. Interestingly, the authors observed that the artificial constructs repressing the ompF exhibit important similarities in the features shown by the natural ompF repressor, the sRNA MicF (Figure 3). A recent work studied the free-energy of the complex sRNA-mRNA and found an important correlation between structure-function in sRNAs. Hao et al. <cite>Hao2011</cite> generated numerous mutants of the sRNA RyhB and tested in vivo their gene control function. They concluded that when using a thermodynamic model to compute the free-energy of the mRNA-sRNA complex, these values exponentially correlated to the gene silencing strengths showed by the mutants.<br />
<br />
=== sRNAs in metabolic engineering ===<br />
<br />
As aforementioned, sRNAs are ideal candidates for developing and alternative methodology for the combinatorial knockdown of genes in metabolic engineering. Towards these purposes, Na et al.<cite>Na2013</cite> generated a library of artificial sRNAs that target a diversity of chromosomal gene targets. Then, by a combinatorial approach they isolated a strain that was able to substantially increase cadaverine production and tyrosine production. This approach is generalizable to other bacterial strains. The strategies proposed by the authors possess important advantages over traditional gene knockouts methodologies due to the ability to fine-tune gene silencing, target multiple genes, easy-implementation and the ability to modulate gene expression without modifying those genes. These strategies avoid the burdensome generation of strain libraries. <br />
<br />
As it can be confirmed from table 1, there are very few examples of the use of sRNAs for metabolic engineering applications. I believe this field will soon explode to produce numerous works and even applications aiming to better strain optimization techniques even for biotechnologically relevant molecules. <br />
<br />
[[File:Table1Review.png|thumb|center|800 px|Table 1<cite>Vazquez2013</cite>]]<br />
<br />
== Control of E. coli cell localization within a consortium via the artificial manipulation of chemotaxis ==<br />
<br />
[[File:FigureX chemotaxis.png|thumb|right|200px|Figure 5:An engineered cell consortium consisting of two interacting strains that produce a mutually interdependent chemotactic response. The red cell is sensitive to molecules that are produced by the blue cell, and the blue cell is sensitive to compounds produced by the red cell..<cite>Mishler2010</cite>]]<br />
<br />
In a representative example, Goldberg et al. <cite>Goldberg2009</cite> in the same study described in section above exploited the “hitchhiker” effect observed in which cells lacking the enzymatic activity can be induced to motility by cells that produce the proper ligand. They engineered two E. coli strains to form a consortium in which each of them can produce the ligand that induces chemotaxis in the other strain. Specifically, one strain was engineered to produce the native aspartate chemoreceptor and penicillin acylase, the other strain was designed to express a PAA-responsive mutant chemoreceptor and asparaginase II. The observed behavior of the consortium was that of an “AND” Boolean gate since when each strain was isolated and put in contact with the appropriate ligands, no chemotaxis was observed. In contrast, when the two strains were plated in close proximity, the two chemical signals were present and the strains were motile (Figure 5). This research work advances the possibility of utilizing these engineered strains in a real environment since bacterial populations are usually better fit to thrive when living in consortia.<br />
<br />
== A robust gene expression control device inspired on sRNAs ==<br />
<br />
Isaacs et al.(ref) developed a riboregulator system showing an enhanced dynamic range. This riboregulator design is inspired on the DsrA-RpoS sRNA system. This system has pioneered the field of rational design of sRNA-like systems and seeded a variety of applications based upon this same device (ref). More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al. (ref) introduced a Hfq domain into the taRNA and found improved results in gene expression control suggesting that in vivo Hfq enhances the inherent sRNA regulatory capacity. Other examples of recently engineered sRNA-like devices are shown in Table 2 and Figure 3. <br />
<br />
== sRNA-like iGEM projects ==<br />
<br />
The Denmark Technical University team in 2011 used a bioinformatics approach to confirm the structural features present in an sRNA e.g. binding domain, Hfq domain, transcription terminator and linker region. They investigated the sRNA system chitobiose that requires the presence of another sRNA called trap-RNA (in this case chiXR) to release the silencing imparted by chiX on its target mRNA chiP. This work represents an interesting confirmation experiment of what had been already reported in the literature since they inserted chiP in a plasmid a showed that its expression was regulated by chiX and when changing the complementary binding region the regulation is removed. <br />
<br />
Other teams such as the Ocean University of Chine iGEM 2012 team aimed to develop a decision-making device based on sRNA regulation to predict when red tide is going to happen. In another example, Uppsala University iGEM 2012 team constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42. <br />
<br />
<br />
==References==<br />
<biblio><br />
#Gottesman2004 pmid=15487940<br />
//Comprehensive review on bacterial small RNAs<br />
#Gottesman2011 pmid=20980440<br />
//A more recent review on bacterial small RNAs.<br />
#Storz2011 pmid=21925377 <br />
//Another recent review on bacterial small RNAs.<br />
#DeLay2013 pmid=23362267<br />
//A review on sRNA negative regulation. <br />
#Sharma 2012 pmid=23651005<br />
//High-throughput method for the engineering of sRNAs.<br />
#Hao2011 pmid=21742981<br />
//sRNA structure-function relationship.<br />
#Na2013 pmid=23334451<br />
//sRNAs in metabolic engineering. <br />
#Vazquez2013 pmid=24356572 <br />
// A thorough review on synthetic regulatory RNAs.</div>Ajv684