Difference between revisions of "CH391L/S14/SmallRNAs"

From SynBioCyc
Jump to: navigation, search
(sRNAs in metabolic engineering)
(A robust gene expression control device inspired on sRNAs)
 
(37 intermediate revisions by one user not shown)
Line 1: Line 1:
=== Bacterial small RNAs: a powerful tool for metabolic engineering ===
+
=== Bacterial small RNAs: as a potential powerful tool for metabolic engineering ===
 
+
  
 
== Introduction ==
 
== Introduction ==
  
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. 
+
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.
  
 
== Bacterial small RNAs ==
 
== Bacterial small RNAs ==
  
[[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>]]
+
[[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>]]
  
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.  
+
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.  
  
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.  
+
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.  
  
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.
+
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>.
  
 
== sRNAs in Synthetic Biology  ==
 
== sRNAs in Synthetic Biology  ==
  
[[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>]]
+
[[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>]]
  
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).
+
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).
  
 
=== Designing a synthetic sRNA ===
 
=== Designing a synthetic sRNA ===
  
[[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.
+
[[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>]]
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>]]
+
  
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.
+
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.
  
 
=== sRNAs in metabolic engineering  ===
 
=== sRNAs in metabolic engineering  ===
  
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.  
+
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.  
 
+
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.
+
 
+
[[File:Table1Review.png|thumb|center|400px|Table 1<cite>Vazquez2013</cite>]]
+
 
+
== Control of E. coli cell localization within a consortium via the artificial manipulation of chemotaxis ==
+
 
+
[[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>]]
+
 
+
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.
+
 
+
== Engineering the intracellular chemotactic pathway vs the manipulation of chemoreceptor sensitivity  ==
+
 
+
The advantages and disadvantages of both approaches presented above are summarized in the following table (information taken from <cite>Mishler2010</cite> ):
+
  
{| class="wikitable"
+
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.  
|-
+
!  !! Intracellular engineering by RNA molecules  !! Chemoreceptor manipulation
+
|-
+
| Advantages || 1. Ability to introduce RNA molecules into organisms with minimal modification
+
2. Capability to evolve RNA molecules (riboswitches) to recognize a completely novel ligand
+
|| 1. Intracellular machinery remains in place facilitating adaptation responses
+
2. Response times are dictated by the native schemes and are expected to be lower than the RNA counterpart.  
+
  
|-
+
[[File:Table1Reviewa.png|thumb|center|1000 px|Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)<cite>Vazquez2013</cite>]]
| Disadvantages ||Longer response times since ligand has to diffuse inside the cell which translates into a reduced capacity of adaptation  || Reduced plasticity since chemoreceptors are limited by a structural scaffold and marginal range of modification is expected.
+
|-
+
|}
+
  
== Potential applications: the paradoxic “therapeutic bacterium” and more  ==
+
== A robust gene expression control device inspired on sRNAs ==
  
In a proof of concept of a medical application, Anderson et al. <cite>Anderson2006</cite> engineered E. coli to invade cancer cells depending on the local environment. The researchers control E. coli behavior by introducing the gene that allows cell invasion, ''inv'' gene, under the control of native promoters that act under specific conditions of hypoxia or cell density. By this approach they were able to control when and where cell invasion take place.  
+
[[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>]]
This example and the others described above enable the vision of almost surreal applications such as a “therapeutic E. coli” in which its chemoctactic activity is engineered to detect disease sites and then release drugs for whose production the organism had been rewired a priori. This means that the field of potential applications is unlimited in areas such as target cell therapy and regenerative medicine, drug delivery, and even other non-medical applications such as biosafety and anti-biofouling in pipes, boats, implantable devices and surgical instruments <cite>Vazquez2013</cite>.
+
  
== Engineering other types of motility ==
+
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.
  
''Synthetic Cilia-like structure engineered to help understand the functioning of biological cilia''
+
== Future directions for sRNAs in Synthetic Biology ==
  
Cilia are highly conserved eukaryotic structures essential for reproduction and survival of many biological organisms. In this work, Sanchez and collaborators <cite>Sanchez2011</cite>, molecularly engineered cilia to study how the biological version functions. The authors describe a minimal model system composed by densely packed, actively bending bundles of microtubules and molecular motors, spontaneously synchronize their beating patterns. This simplified in vitro model of eukaryotic cilia could bring insights into the beating of isolated cilia and the synchronization of their beatings.  
+
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.
  
== iGEM projects on chemotaxis ==
+
== sRNA-like iGEM projects ==
A couple of examples of iGEM projects associated with chemotaxis and motility engineering are as follows:
+
  
Back in 2012, team Göttingen developed a selection method to engineer a strain that they called “Homing  E. coli”. Through genetic manipulation and directed mutagenesis, they were able to optimize E. Coli’s capacity to quickly travel through a chemo-attractive gradient of aspartate. They identified FlhDC as a cellular factor for flagella enhancement and elongation, and created a library of receptors that they will soon explore to modify specificity of the receptor and, ultimately, motility of the E. Coli. Specifically they applied directed evolution to chemoreceptors by targeting five amino acid residues in the ligand binding site. In order to select for the appropriate phenotype, a new special "swimming" plate was developed by using a low concentration of agar (0.3%). Several tests were run to determine incubation times and temperature, nutrients and chemoattractant concentrations, and even the right strain. They chose BL21 cells in 0.3% swimming agar at 33 C for 1-2 days.  After determining the appropriate "swimming" assay, the team started investigating genes involved in the flagellar function of E. coli and their effect on bacterial motility when over-express from a plasmid. They found that gene ''yhjH'' had a relatively important positive effect in the "swimming" behavior of the cells since by over-expressing from plasmids, the ability of cells to brake was considerably diminished and biofilm formation appears to repressed. These results are in accordance to the functions that gene ''yhjH'' regulates in E. coli. ''fliC'' (flagellin) encodes for the structural protein that builds up the filament of the bacterial flagellum. By overexpressing it the authors observed a similar behavior to ''yhjH'' versions. A higher motility than the control was observed in general when overexpressing ''flhDC'' (master regulator of motility and chemotaxis), however inconsistent results prevent the authors from obtaining definitive conclusions. In general, by overexpressing genes such as ''yhjH'' (releases brake and spreads individual cells), ''fliC'' (makes stronger and elongated flagella) and ''flhDC'' (increases number of flagella), a relatively positive effect on E. coli motility was observed <cite>iGEMGottingen2012</cite>.  
+
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.  
  
In 2010, team UPO-Sevilla explored their capacity to concentrate populations of bacteria, or enhance a phenomena termed “Bacterial Crowding”. This fundamentally requires a strain (containing the Prh system) to sense a non-diffusive chemical attractant and subsequently release signals to attract other bacteria to crowd there. This team used two chemo-attractants: aspartate and salicylate, in the hope of demonstrating that they can induce crowding of a strain that is not chemo-sensitive to salicylate.
+
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.
  
 
==References==
 
==References==
Line 89: Line 61:
 
#DeLay2013 pmid=23362267
 
#DeLay2013 pmid=23362267
 
//A review on sRNA negative regulation.  
 
//A review on sRNA negative regulation.  
#Sharma 2012 pmid=23651005
+
#Sharma2012 pmid=23651005
 
//High-throughput method for the engineering of sRNAs.
 
//High-throughput method for the engineering of sRNAs.
 
#Hao2011 pmid=21742981
 
#Hao2011 pmid=21742981
Line 97: Line 69:
 
#Vazquez2013 pmid=24356572  
 
#Vazquez2013 pmid=24356572  
 
// A thorough review on synthetic regulatory RNAs.
 
// A thorough review on synthetic regulatory RNAs.
#iGEMGottingen2012 [http://2012.igem.org/Team:Goettingen/Project] http://2012.igem.org/Team:Goettingen/Project
+
#Isaacs2004 pmid=15208640
// A iGEM chemotaxis project for the engineering of "Homing Coli".
+
//A robust sRNA-inspired riboregulator.
#Sanchez2011 pmid=21778400
+
#Sakai2013 pmid=24328142
// Engineered cilia for studying biological motility.
+
//Effect of Hfq domain introduction into a synthetic sRNA.
#Adler1974 pmid=4598187
+
#Callura2012 pmid=22454498
// Paper describing thoroughly the chemotaxis phenomenon.
+
//A genetic switchboard based on an sRNA-like device.
 +
#Friedland2009 pmid=19478183
 +
//A transcriptional cascade based of an sRNA-like device that counts up to three.
 +
#iGEMDTU2011 [http://2011.igem.org/Team:DTU-Denmark/Project
 +
//sRNA system with a trap-RNA for chitibiose control.
 +
#iGEMOUC2012 [http://2012.igem.org/Team:OUC-China/Project/Overview
 +
//sRNA system for the prediction of red tide.
 +
#iGEMUU2012 [http://2012.igem.org/Team:Uppsala_University
 +
//sRNA system for the repression of resistance genes in bacteria.

Latest revision as of 18:27, 14 April 2014

Contents

Bacterial small RNAs: as a potential powerful tool for metabolic engineering

Introduction

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)[1]. The presence of these regulatory molecules appears to be ubiquitous as they have been discovered in a wide range of bacterial species [2][3]. 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.

Bacterial small RNAs

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.[4]

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)[1]. Lastly but more importantly, this class of sRNAs can interact with multiple mRNAs[5]. This property, in turn, enables the potential application of combinatorial gene knockdown in metabolic engineering.

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.

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[1]. Recent reports propose that Hfq can also exert negative regulation by delivering the sRNA-mRNA complex to the degradosome [3]. 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[6].

sRNAs in Synthetic Biology

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.[4]

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 [4]. 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).

Designing a synthetic sRNA

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.[7]

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.[7] (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. [8] (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.

sRNAs in metabolic engineering

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.[9] (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.

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.

Table 1. Recent synthetic sRNAs and their (potential) applications (basic devices)[4]

A robust gene expression control device inspired on sRNAs

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.[10]

Isaacs et al.[10] 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"[11] and a "switchboard"[12]. More recently, this cr-taRNA system has been used to test the influence of the Hfq assistance. Sakai et al.[6] 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.

Future directions for sRNAs in Synthetic Biology

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. [9] 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[4]. Finally, sRNAs have shown their potential use as metabolic target genes, as it can be confirmed from Na et al.[9] 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.

sRNA-like iGEM projects

The Denmark Technical University team in 2011 [13] 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.

Other teams such as the Ocean University of China iGEM 2012 [14] 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 [15] constructed synthetic sRNAs that can down regulated antibiotic resistance genes by engineering the binding domain of the sRNA Spot42.

References

Error fetching PMID 15487940:
Error fetching PMID 20980440:
Error fetching PMID 21925377:
Error fetching PMID 23362267:
Error fetching PMID 23651005:
Error fetching PMID 21742981:
Error fetching PMID 23334451:
Error fetching PMID 24356572:
Error fetching PMID 15208640:
Error fetching PMID 24328142:
Error fetching PMID 22454498:
Error fetching PMID 19478183:
  1. Error fetching PMID 15487940: [Gottesman2004]
    Comprehensive review on bacterial small RNAs
  2. Error fetching PMID 20980440: [Gottesman2011]
    A more recent review on bacterial small RNAs.
  3. Error fetching PMID 21925377: [Storz2011]
    Another recent review on bacterial small RNAs.
  4. Error fetching PMID 24356572: [Vazquez2013]
    A thorough review on synthetic regulatory RNAs.
  5. Error fetching PMID 23362267: [DeLay2013]
    A review on sRNA negative regulation.
  6. Error fetching PMID 24328142: [Sakai2013]
    Effect of Hfq domain introduction into a synthetic sRNA.
  7. Error fetching PMID 23651005: [Sharma2012]
    High-throughput method for the engineering of sRNAs.
  8. Error fetching PMID 21742981: [Hao2011]
    sRNA structure-function relationship.
  9. Error fetching PMID 23334451: [Na2013]
    sRNAs in metabolic engineering.
  10. Error fetching PMID 15208640: [Isaacs2004]
    A robust sRNA-inspired riboregulator.
  11. Error fetching PMID 19478183: [Friedland2009]
    A transcriptional cascade based of an sRNA-like device that counts up to three.
  12. Error fetching PMID 22454498: [Callura2012]
    A genetic switchboard based on an sRNA-like device.
  13. [http://2011.igem.org/Team:DTU-Denmark/Project [iGEMDTU2011]
    sRNA system with a trap-RNA for chitibiose control.
  14. [http://2012.igem.org/Team:OUC-China/Project/Overview [iGEMOUC2012]
    sRNA system for the prediction of red tide.
  15. [http://2012.igem.org/Team:Uppsala_University [iGEMUU2012]
    sRNA system for the repression of resistance genes in bacteria.
All Medline abstracts: PubMed | HubMed