The RNA-binding protein CsrA regulates the expression of hundreds of genes in several bacterial species, thus controlling virulence and other processes. However, the outcome of the CsrA-mRNA interactions is modulated by competing small RNAs and other factors through mechanisms that are only partially understood. Here, we show that CsrA accumulates in a dynamic membraneless compartment in cells of E. coli and other pathogenic species. In addition to CsrA, the compartment contains components of the RNA-degrading complex (degradosome), regulatory small RNAs, and selected mRNAs. Formation of the compartment is associated with a switch between promoting and repressing virulence gene expression by CsrA. We suggest that similar CsrA switches may be widespread in diverse bacteria.

Small RNAs (sRNAs) are major regulators of gene expression in bacteria, exerting their regulation primarily via base pairing with their target transcripts and modulating translation. Accumulating evidence suggest that sRNAs can also affect the stability of their target transcripts by altering their accessibility to endoribonucleases. Yet, the effects of sRNAs on transcript stability and the mechanisms underlying them have not been studied in wide scale. Here we employ large-scale RNA-seq-based methodologies in the model bacterium Escherichia coli to quantitatively study the functional interaction between a sRNA and an endoribonuclease in regulating gene expression, using the well-established sRNA, GcvB, and the major endoribonuclease, RNase E. Studying single and double mutants of gcvB and rne and analysing their RNA-seq results by the Double Mutant Cycle approach, we infer distinct modes of the interplay between GcvB and RNase E. Transcriptome-wide mapping of RNase E cleavage sites provides further support to the results of the RNA-seq analysis, identifying cleavage sites in targets in which the functional interaction between GcvB and RNase E is evident. Together, our results indicate that the most dominant mode of GcvB-RNase E functional interaction is GcvB enhancement of RNase E cleavage, which varies in its magnitude between different targets. Graphical Abstract

Hypervirulent Klebsiella pneumoniae (hvKp) can infect healthy individuals, in contrast to classical strains that commonly cause nosocomial infections. The recent convergence of hypervirulence with carbapenem-resistance in K. pneumoniae can potentially create `superbugs' that are challenging to treat. Understanding virulence regulation of hvKp is thus critical. Accumulating evidence suggest that posttranscriptional regulation by small RNAs (sRNAs) plays a role in bacterial virulence, but it has hardly been studied in K. pneumoniae. We applied RIL-seq to a prototypical clinical isolate of hvKp to unravel the Hfq-dependent RNA-RNA interaction (RRI) network. The RRI network is dominated by sRNAs, including predicted novel sRNAs, three of which we validated experimentally. We constructed a stringent subnetwork composed of RRIs that involve at least one hvKp virulence-associated gene and identified the capsule gene loci as a hub target where multiple sRNAs interact. We found that the sRNA OmrB suppressed both capsule production and hypermucoviscosity when overexpressed. Furthermore, OmrB base-pairs within kvrA coding region and partially suppresses translation of the capsule regulator KvrA. This agrees with current understanding of capsule as a major virulence and fitness factor. It emphasizes the intricate regulatory control of bacterial phenotypes by sRNAs, particularly of genes critical to bacterial physiology and virulence. Graphical Abstract

In bacteria, determination of the 3' termini of transcripts plays an essential role in regulation of gene expression, affecting the functionality and stability of the transcript. Several experimental approaches were developed to identify the 3' termini of transcripts, however, these were applied only to a limited number of bacteria and growth conditions. Here we present a straightforward approach to identify 3' termini from widely available RNA-seq data without the need for additional experiments. Our approach relies on the observation that the RNAtag-seq sequencing protocol results in overabundance of reads mapped to transcript 3' termini. We present TRS (Termini by Read Starts), a computational pipeline exploiting this property to identify 3' termini in RNAtag-seq data, and show that the identified 3' termini are highly reliable. Since RNAtag-seq data are widely available for many bacteria and growth conditions, our approach paves the way for studying bacterial transcription termination in an unprecedented scope. TRS is a new method for determining 3' transcript termini in bacteria, using data generated by the RNAtag-seq protocol. This methodology opens the door to study the evolution of transcription termini and their condition-dependent dynamics.

A main strategy of bacteria adapting to environmental changes is the remodeling of their transcriptome. Changes in the transcript levels of specific genes are due to combined effects of various regulators, including small RNAs (sRNAs). sRNAs are post-transcriptional regulators of gene expression that mainly control translation, but also directly and indirectly affect the levels of their target transcripts. Yet, the relative contribution of an sRNA to the total change in the transcript level of a gene upon an environmental change has not been assessed. We present a design of differential gene expression analysis by RNA-seq that allows extracting the contribution of an sRNA to the total change in the transcript level of each gene in response to an environmental change by fitting a linear model to the data. We exemplify this for the sRNA RyhB in cells growing under iron limitation and show a variation among genes in the relative contribution of RyhB to the change in their transcript level upon iron limitation, from subtle to very substantial. Extracting the relative contribution of an sRNA to the total change in expression of genes is important for understanding the integration of regulation by sRNAs with other regulatory mechanisms in the cell.

The envelope of Gram-negative bacteria is a vital barrier that must balance protection and nutrient uptake. Small RNAs are crucial regulators of the envelope composition and function. Here, using RIL-seq to capture the Hfq-mediated RNA-RNA interactome in Salmonella enterica, we discover envelope-related riboregulators, including OppX. We show that OppX acts as an RNA sponge of MicF sRNA, a prototypical porin repressor. OppX originates from the 5' UTR of oppABCDF, encoding the major inner-membrane oligopeptide transporter, and sequesters MicF's seed region to derepress the synthesis of the porin OmpF. Intriguingly, OppX operates as a true sponge, storing MicF in an inactive complex without affecting its levels or stability. Conservation of the opp-OppX-MicF-ompF axis in related bacteria suggests that it serves an important mechanism, adjusting envelope porosity to specific transport capacity. These data also highlight the resource value of this Salmonella RNA interactome, which will aid in unraveling RNA-centric regulation in enteric pathogens.

Small RNAs (sRNAs) exert their regulation posttranscriptionally by base pairing with their target mRNAs, often in association with the RNA chaperone protein Hfq. Here, integrating RNA-seq-based technologies and bioinformatics, we deciphered the Hfq-mediated sRNA-target interactome of enteropathogenic Escherichia coli (EPEC). The emerging network comprises hundreds of sRNA-mRNA pairs, including mRNAs of virulence-associated genes interacting with known sRNAs encoded within the core genome, as well as with newly found sRNAs encoded within pathogenicity islands. Some of the sRNAs affect multiple virulence genes, suggesting they function as hubs of virulence control. We further analyzed one such sRNA hub, MgrR, and one of its targets identified here, the major virulence-associated chaperon, cesT. We show that MgrR adjusts the level of EPEC cytotoxicity via regulation of CesT expression. Our results reveal an elaborate sRNA-mRNA interactome controlling the pathogenicity of EPEC and reinforce a role for sRNAs in the control of pathogen-host interaction.

The genomic revolution and subsequent advances in large-scale genomic and transcriptomic technologies highlighted hidden genomic treasures. Among them stand out non-coding small RNAs (sRNAs), shown to play important roles in post-transcriptional regulation of gene expression in both pro- and eukaryotes. Bacterial sRNA-encoding genes were initially identified in intergenic regions, but recent evidence suggest that they can be encoded within other, well-defined, genomic elements. This notion was strongly supported by data generated by RIL-seq, a RNA-seq-based methodology we recently developed for deciphering chaperon-dependent sRNA-target networks in bacteria. Applying RIL-seq to Hfq-bound RNAs in Escherichia coli, we found that similar to 64% of the detected RNA pairs involved known sRNAs, suggesting that yet unknown sRNAs may be included in the similar to 36% remaining pairs. To determine the latter, we first tested and refined a set of quantitative features derived from RIL-seq data, which distinguish between Hfq-dependent sRNAs and ``other RNAs''. We then incorporated these features in a machine learning-based algorithm that predicts novel sRNAs from RIL-seq data, and identified high-scoring candidates encoded in various genomic regions, mostly intergenic regions and 3' untranslated regions, but also 5' untranslated regions and coding sequences. Several candidates were further tested and verified by northern blot analysis as Hfq-dependent sRNAs. Our study reinforces the emerging concept that sRNAs are encoded within various genomic elements, and provides a computational framework for the detection of additional sRNAs in Hfq RIL-seq data of E. coli grown under different conditions and of other bacteria manifesting Hfq-mediated sRNA-target interactions.

Bacterial small RNAs (sRNAs) are posttranscriptional regulators of gene expression that base pair with complementary sequences on target mRNAs, often in association with the chaperone Hfq. Here, using experimentally identified sRNA-target pairs, along with gene expression measurements, we assess basic principles of regulation by sRNAs. We show that the sRNA sequence dictates the target repertoire, as point mutations in the sRNA shift the target set correspondingly. We distinguish two subsets of targets: targets showing changes in expression levels under overexpression of their sRNA regulator and unaffected targets that interact more sporadically with the sRNA. These differences among targets are associated with their Hfq occupancy, rather than with the sRNA-target base-pairing potential. Our results suggest that competition among targets over Hfq binding plays a major role in the regulatory outcome, possibly awarding targets with higher Hfq binding efficiency an advantage in the competition over binding to the sRNA.