The functional Hfq-binding module of bacterial sRNAs consists of a double or single hairpin preceded by a U-rich sequence and followed by a 3' poly(U) tail

Hfq-dependent sRNAs contain, at least, an mRNA base-pairing region, an Hfq-binding site, and a Rho-independent terminator. Recently, we found that the terminator poly(U) of Escherichia coli sRNAs is essential for Hfq binding and therefore for riboregulation. In this study, we tried to identify additional components within Hfq-binding sRNAs required for efficient Hfq binding by using SgrS as a model. We demonstrate by mutational and biochemical studies that an internal hairpin and an immediately upstream U-rich sequence also are required for efficient Hfq binding. We propose that the functional Hfq-binding module of SgrS consists of an internal hairpin preceded by a U-rich sequence and a Rho-independent terminator with a long poly(U) tail. We also show that the Rho-independent terminator alone can act as a functional Hfq-binding module when it is preceded by an internal U-rich sequence. The 3' region of most known sRNAs share the features corresponding to either a double- or single-hairpin-type Hfq-binding module. We also demonstrate that increasing the spacing between the base-pairing region and the Hfq-binding module reduces or impairs the silencing ability. These findings allowed us to design synthetic Hfq-binding sRNAs to target desired mRNAs.     

Identification of bacterial sRNA regulatory targets using ribosome profiling

Bacteria express large numbers of non-coding, regulatory RNAs known as ‘small RNAs’ (sRNAs). sRNAs typically regulate expression of multiple target messenger RNAs (mRNAs) through base-pairing interactions. sRNA:mRNA base-pairing often results in altered mRNA stability and/or altered translation initiation. Computational identification of sRNA targets is challenging due to the requirement for only short regions of base-pairing that can accommodate mismatches. Experimental approaches have been applied to identify sRNA targets on a genomic scale, but these focus only on those targets regulated at the level of mRNA stability. Here, we utilize ribosome profiling (Ribo-seq) to experimentally identify regulatory targets of the Escherichia coli sRNA RyhB. We not only validate a majority of known RyhB targets using the Ribo-seq approach, but also discover many novel ones. We further confirm regulation of a selection of known and novel targets using targeted reporter assays. By mutating nucleotides in the mRNA of a newly discovered target, we demonstrate direct regulation of this target by RyhB. Moreover, we show that Ribo-seq distinguishes between mRNAs regulated at the level of RNA stability and those regulated at the level of translation. Thus, Ribo-seq represents a powerful approach for genome-scale identification of sRNA targets.     

Identifying Hfq-binding small RNA targets in Escherichia coli

The Hfq-binding small RNAs (sRNAs) have recently drawn much attention as regulators of translation in Escherichia coli. We attempt to identify the targets of this class of sRNAs in genome scale and gain further insight into the complexity of translational regulation induced by Hfq-binding sRNAs. Using a new alignment algorithm, most known negatively regulated targets of Hfq-binding sRNAs were identified. The results also show several interesting aspects of the regulatory function of Hfq-binding sRNAs.     

Rewiring two-component signal transduction with small RNAs

Bacterial two-component systems (TCSs) and small regulatory RNAs (sRNAs) form densely interconnected networks that integrate and transduce information from the environment into fine-tuned changes of gene expression. Many TCSs control target genes indirectly through regulation of sRNAs, which in turn regulate gene expression by base-pairing with mRNAs or targeting a protein. Conversely, sRNAs may control TCS synthesis, thereby recruiting the TCS regulon to other regulatory networks. Several TCSs control expression of multiple homologous sRNAs providing the regulatory networks with further flexibility. These sRNAs act redundantly, additively or hierarchically on targets. The regulatory speed of sRNAs and their unique features in gene regulation make them ideal players extending the flexibility, dynamic range or timing of TCS signaling.     

Translational control and target recognition by Escherichia coli small RNAs in vivo

Small non-coding RNAs (sRNAs) are an emerging class of regulators of bacterial gene expression. Most of the regulatory Escherichia coli sRNAs known to date modulate translation of trans-encoded target mRNAs. We studied the specificity of sRNA target interactions using gene fusions to green fluorescent protein (GFP) as a novel reporter of translational control by bacterial sRNAs in vivo. Target sequences were selected from both monocistronic and polycistronic mRNAs. Upon expression of the cognate sRNA (DsrA, GcvB, MicA, MicC, MicF, RprA, RyhB, SgrS and Spot42), we observed highly specific translation repression/activation of target fusions under various growth conditions. Target regulation was also tested in mutants that lacked Hfq or RNase III, or which expressed a truncated RNase E (rne701). We found that translational regulation by these sRNAs was largely independent of full-length RNase E, e.g. despite the fact that ompA fusion mRNA decay could no longer be promoted by MicA. This is the first study in which multiple well-defined E.coli sRNA target pairs have been studied in a uniform manner in vivo. We expect our GFP fusion approach to be applicable to sRNA targets of other bacteria, and also demonstrate that Vibrio RyhB sRNA represses a Vibrio sodB fusion when co-expressed in E.coli.     

sTarPicker: a method for efficient prediction of bacterial sRNA targets based on a two-step model for hybridization

Background

Bacterial sRNAs are a class of small regulatory RNAs involved in regulation of expression of a variety of genes. Most sRNAs act in trans via base-pairing with target mRNAs, leading to repression or activation of translation or mRNA degradation. To date, more than 1,000 sRNAs have been identified. However, direct targets have been identified for only approximately 50 of these sRNAs. Computational predictions can provide candidates for target validation, thereby increasing the speed of sRNA target identification. Although several methods have been developed, target prediction for bacterial sRNAs remains challenging.

Results

Here, we propose a novel method for sRNA target prediction, termed sTarPicker, which was based on a two-step model for hybridization between an sRNA and an mRNA target. This method first selects stable duplexes after screening all possible duplexes between the sRNA and the potential mRNA target. Next, hybridization between the sRNA and the target is extended to span the entire binding site. Finally, quantitative predictions are produced with an ensemble classifier generated using machine-learning methods. In calculations to determine the hybridization energies of seed regions and binding regions, both thermodynamic stability and site accessibility of the sRNAs and targets were considered. Comparisons with the existing methods showed that sTarPicker performed best in both performance of target prediction and accuracy of the predicted binding sites.

Conclusions

sTarPicker can predict bacterial sRNA targets with higher efficiency and determine the exact locations of the interactions with a higher accuracy than competing programs. sTarPicker is available at http://ccb.bmi.ac.cn/starpicker/.     

Requirement of upstream Hfq-binding (ARN)x elements in glmS and the Hfq C-terminal region for GlmS upregulation by sRNAs GlmZ and GlmY{dagger}

Hfq is an important RNA-binding protein that helps bacteria adapt to stress. Its primary function is to promote pairing between trans-acting small non-coding RNAs (sRNAs) and their target mRNAs. Identification of essential Hfq-binding motifs in up-stream regions of rpoS and fhlA led us to ask the question whether these elements are a common occurrence among other Hfq-dependent mRNAs as well. Here, we confirm the presence of a similar (ARN)(x) motif in glmS RNA, a gene controlled by two sRNAs (GlmZ and GlmY) in an Hfq-dependent manner. GlmZ represents a canonical sRNA:mRNA pairing system, whereas GlmY is non-canonical, interfacing with the RNA processing protein YhbJ. We show that glmS interacts with both Hfq-binding surfaces in the absence of sRNAs. Even though two (ARN)(x) motifs are present, using a glmS:gfp fusion system, we determined that only one specific (ARN)(x) element is essential for regulation. Furthermore, we show that residues 66-72 in the C-terminal extension of Escherichia coli Hfq are essential for activation of GlmS expression by GlmY, but not with GlmZ. This result shows that the C-terminal extension of Hfq may be required for some forms of non-canonical sRNA regulation involving ancillary components such as additional RNAs or proteins.     

Hfq proximity and orientation controls RNA annealing

Regulation of bacterial gene networks by small non-coding RNAs (sRNAs) requires base pairing with messenger RNA (mRNA) targets, which is facilitated by Hfq protein. Hfq is recruited to sRNAs and mRNAs through U-rich- and A-rich-binding sites, respectively, but their distance from the sRNA–mRNA complementary region varies widely among different genes. To determine whether distance and binding orientation affect Hfq’s chaperone function, we engineered ‘toy’ RNAs containing strong Hfq-binding sites at defined distances from the complementary target site. We show that RNA annealing is fastest when the distal face of Hfq binds an A-rich sequence immediately 3′ of the target. This recruitment advantage is lost when Hfq binds >20 nt away from the target, but is partially restored by secondary structure that shortens this distance. Although recruitment through Hfq’s distal face accelerates RNA annealing, tight binding of six Us to Hfq’s proximal face inhibits annealing. Finally, we show that ectopic A-rich motifs dramatically accelerate base pairing between DsrA sRNA and a minimal rpoS mRNA in the presence of Hfq, demonstrating that proximity and orientation predict the activity of Hfq on long RNAs.     

Defining a role for Hfq in Gram-positive bacteria: evidence for Hfq-dependent antisense regulation in Listeria monocytogenes

Small trans-encoded RNAs (sRNAs) modulate the translation and decay of mRNAs in bacteria. In Gram-negative species, antisense regulation by trans-encoded sRNAs relies on the Sm-like protein Hfq. In contrast to this, Hfq is dispensable for sRNA-mediated riboregulation in the Gram-positive species studied thus far. Here, we provide evidence for Hfq-dependent translational repression in the Gram-positive human pathogen Listeria monocytogenes, which is known to encode at least 50 sRNAs. We show that the Hfq-binding sRNA LhrA controls the translation and degradation of its target mRNA by an antisense mechanism, and that Hfq facilitates the binding of LhrA to its target. The work presented here provides the first experimental evidence for Hfq-dependent riboregulation in a Gram-positive bacterium. Our findings indicate that modulation of translation by trans-encoded sRNAs may occur by both Hfq-dependent and -independent mechanisms, thus adding another layer of complexity to sRNA-mediated riboregulation in Gram-positive species.     

Molecular call and response: the physiology of bacterial small RNAs

The vital role of bacterial small RNAs (sRNAs) in cellular regulation is now well-established. Although many diverse mechanisms by which sRNAs bring about changes in gene expression have been thoroughly described, comparatively less is known about their biological roles and effects on cell physiology. Nevertheless, for some sRNAs, insight has been gained into the intricate regulatory interplay that is required to sense external environmental and internal metabolic cues and turn them into physiological outcomes. Here, we review examples of regulation by selected sRNAs, emphasizing signals and regulators required for sRNA expression, sRNA regulatory targets, and the resulting consequences for the cell. We highlight sRNAs involved in regulation of the processes of iron homeostasis (RyhB, PrrF, and FsrA) and carbon metabolism (Spot 42, CyaR, and SgrS).     

Hfq binding at RhlB-recognition region of RNase E is crucial for the rapid degradation of target mRNAs mediated by sRNAs in Escherichia coli

An RNA chaperon Hfq along with Hfq-binding sRNAs stably binds to RNase E in Escherichia coli. The role of the Hfq-RNase E interaction is to recruit RNase E to target mRNAs of sRNAs resulting in the rapid degradation of the mRNA-sRNA hybrid. The C-terminal scaffold region of RNase E is responsible for the interaction with Hfq. Here, we demonstrate that the scaffold region can be deleted up to residue 750 without losing the ability to cause the rapid degradation of target mRNAs mediated by Hfq/sRNAs. The truncated RNase E750 can still bind to Hfq although the truncation significantly reduces the Hfq-binding ability. We conclude that the subregion between 711 and 750 is sufficient for the functional interaction with Hfq to support the rapid degradation of ptsG mRNA although additional subregions within the scaffold are also involved in Hfq binding. Deletion of the 702-750 region greatly impairs the ability of RNase E to cause the degradation of ptsG mRNA. In addition, a polypeptide corresponding to the scaffold region binds to Hfq without the help of RNA. Finally, we demonstrate that overexpression of RhlB partially inhibits the Hfq binding to RNase E and the rapid degradation of ptsG mRNA.     

A survey of sRNA families in α-proteobacteria

We have performed a computational comparative analysis of six small non-coding RNA (sRNA) families in α-proteobacteria. Members of these families were first identified in the intergenic regions of the nitrogen-fixing endosymbiont S. meliloti by a combined bioinformatics screen followed by experimental verification. Consensus secondary structures inferred from covariance models for each sRNA family evidenced in some cases conserved motifs putatively relevant to the function of trans-encoded base-pairing sRNAs i.e., Hfq-binding signatures and exposed anti Shine-Dalgarno sequences. Two particular family models, namely αr15 and αr35, shared own sub-structural modules with the Rfam model suhB (RF00519) and the uncharacterized sRNA family αr35b, respectively. A third sRNA family, termed αr45, has homology to the cis-acting regulatory element speF (RF00518). However, new experimental data further confirmed that the S. meliloti αr45 representative is an Hfq-binding sRNA processed from or expressed independently of speF, thus refining the Rfam speF model annotation. All the six families have members in phylogenetically related plant-interacting bacteria and animal pathogens of the order of the Rhizobiales, some occurring with high levels of paralogy in individual genomes. In silico and experimental evidences predict differential regulation of paralogous sRNAs in S. meliloti 1021. The distribution patterns of these sRNA families suggest major contributions of vertical inheritance and extensive ancestral duplication events to the evolution of sRNAs in plant-interacting bacteria.