A bioinformatics based approach to discover small RNA genes in the Escherichia coli genome

A small RNA serving both the Hfq and CsrA regulons

The abundant RNA-binding proteins CsrA and Hfq each impact bacterial physiology by working in conjunction with small RNAs to control large post-transcriptional regulons. The small RNAs involved were considered mechanistically distinct, regulating mRNAs either directly through Hfq-mediated base-pairing or indirectly by sequestering the global translational repressor CsrA. In this issue of Genes & Development, Jørgensen and colleagues (pp. 1132-1145) blur these distinctions with a dual-mechanism small RNA that acts through both Hfq and CsrA to regulate the formation of bacterial biofilms.

Mutations in the Escherichia coli ribosomal protein L22 selectively suppress the expression of a secreted bacterial virulence factor

Mutations in the ribosomal protein L22 that impair peptide-mediated translation arrest in Escherichia coli have been shown to reduce the expression of several genes, including secA, which encodes an ATPase that drives protein export via the Sec pathway. Here, we used a comparative proteomic approach to obtain insight into the global effects of the L22(Δ82-84) mutation on gene expression and protein synthesis. While the mutation did not affect or modestly affected the level of most soluble proteins, it dramatically reduced the level of antigen 43 (Ag43), a secreted virulence factor that promotes autoaggregation. The reduced protein concentration correlated with a sharp decrease in the abundance and stability of Ag43 mRNA. We found that the overexpression of secA or the inactivation of genes that encode presecretory and membrane proteins restored Ag43 production in the L22 mutant strain. Furthermore, impairment of the Sec pathway in a wild-type strain reduced Ag43 production but did not significantly affect the synthesis of other presecretory proteins. Taken together, these results indicate that Ag43 gene expression is exquisitely sensitive to the status of the Sec machinery and strongly suggest that the L22 mutation decreases the Ag43 concentration indirectly by reducing secA expression. Our results imply the existence of a novel regulatory mechanism in which the efficiency of protein export is coupled to gene expression and help to explain the modulation of SecA synthesis that has been observed in response to secretion stress.

Prediction of candidate small non-coding RNAs in Agrobacterium by computational analysis

Small non-coding RNAs with important regulatory roles are not confined to eukaryotes. Recent work has uncovered a growing number of bacterial small RNAs (sRNAs), some of which have been shown to regulate critical cellular processes. Computational approaches, in combination with molecular experiments, have played an important role in the identification of these sRNAs. At present, there is no information on the presence of small non-coding RNAs and their genes in the Agrobacterium tumefaciens genome. To identify potential sRNAs in this important bacterium, deep sequencing of the short RNA populations isolated from Agrobacterium tumefaciens C58 was carried out. From a data set of more than 10,000 short sequences, 16 candidate sRNAs have been tentatively identified based on computational analysis. All of these candidates can form stem-loop structures by RNA folding predictions and the majority of the secondary structures are rich in GC base pairs. Some are followed by a short stretch of U residues, indicative of a rho-independent transcription terminator, whereas some of the short RNAs are found in the stem region of the hairpin, indicative of eukaryotic-like sRNAs. Experimental strategies will need to be used to verify these candidates. The study of an expanded list of candidate sRNAs in Agrobacterium will allow a more complete understanding of the range of roles played by regulatory RNAs in prokaryotes.

Computational small RNA prediction in bacteria

Bacterial, small RNAs were once regarded as potent regulators of gene expression and are now being considered as essential for their diversified roles. Many small RNAs are now reported to have a wide array of regulatory functions, ranging from environmental sensing to pathogenesis. Traditionally, noncoding transcripts were rarely detected by means of genetic screens. However, the availability of approximately 2200 prokaryotic genome sequences in public databases facilitates the efficient computational search of those molecules, followed by experimental validation. In principle, the following four major computational methods were applied for the prediction of sRNA locations from bacterial genome sequences: (1) comparative genomics, (2) secondary structure and thermodynamic stability, (3) ‘Orphan’ transcriptional signals and (4) ab initio methods regardless of sequence or structure similarity; most of these tools were applied to locate the putative genomic sRNA locations followed by experimental validation of those transcripts. Therefore, computational screening has simplified the sRNA identification process in bacteria. In this review, a plethora of small RNA prediction methods and tools that have been reported in the past decade are discussed comprehensively and assessed based on their attributes, compatibility, and their prediction accuracy.

A comparison of dense transposon insertion libraries in the Salmonella serovars Typhi and Typhimurium

Salmonella Typhi and Typhimurium diverged only ∼50 000 years ago, yet have very different host ranges and pathogenicity. Despite the availability of multiple whole-genome sequences, the genetic differences that have driven these changes in phenotype are only beginning to be understood. In this study, we use transposon-directed insertion-site sequencing to probe differences in gene requirements for competitive growth in rich media between these two closely related serovars. We identify a conserved core of 281 genes that are required for growth in both serovars, 228 of which are essential in Escherichia coli. We are able to identify active prophage elements through the requirement for their repressors. We also find distinct differences in requirements for genes involved in cell surface structure biogenesis and iron utilization. Finally, we demonstrate that transposon-directed insertion-site sequencing is not only applicable to the protein-coding content of the cell but also has sufficient resolution to generate hypotheses regarding the functions of non-coding RNAs (ncRNAs) as well. We are able to assign probable functions to a number of cis-regulatory ncRNA elements, as well as to infer likely differences in trans-acting ncRNA regulatory networks.

Computational discovery and RT-PCR validation of novel Burkholderia conserved and Burkholderia pseudomallei unique sRNAs

BACKGROUND

The sRNAs of bacterial pathogens are known to be involved in various cellular roles including environmental adaptation as well as regulation of virulence and pathogenicity. It is expected that sRNAs may also have similar functions for Burkholderia pseudomallei, a soil bacterium that can adapt to diverse environmental conditions, which causes the disease melioidosis and is also able to infect a wide variety of hosts.

RESULTS

By integrating several proven sRNA prediction programs into a computational pipeline, available Burkholderia spp. genomes were screened to identify sRNA gene candidates. Orthologous sRNA candidates were then identified via comparative analysis. From the total prediction, 21 candidates were found to have Rfam homologs. RT-PCR and sequencing of candidate sRNA genes of unknown functions revealed six putative sRNAs which were highly conserved in Burkholderia spp. and two that were unique to B. pseudomallei present in a normal culture conditions transcriptome. The validated sRNAs include potential cis-acting elements associated with the modulation of methionine metabolism and one B. pseudomallei-specific sRNA that is expected to bind to the Hfq protein.

CONCLUSIONS

The use of the pipeline developed in this study and subsequent comparative analysis have successfully aided in the discovery and shortlisting of sRNA gene candidates for validation. This integrated approach identified 29 B. pseudomallei sRNA genes - of which 21 have Rfam homologs and 8 are novel.

BSRD: a repository for bacterial small regulatory RNA

In bacteria, small regulatory non-coding RNAs (sRNAs) are the most abundant class of post-transcriptional regulators. They are involved in diverse processes including quorum sensing, stress response, virulence and carbon metabolism. Recent developments in high-throughput techniques, such as genomic tiling arrays and RNA-Seq, have allowed efficient detection and characterization of bacterial sRNAs. However, a comprehensive repository to host sRNAs and their annotations is not available. Existing databases suffer from a limited number of bacterial species or sRNAs included. In addition, these databases do not have tools to integrate or analyse high-throughput sequencing data. Here, we have developed BSRD (http://kwanlab.bio.cuhk.edu.hk/BSRD), a comprehensive bacterial sRNAs database, as a repository for published bacterial sRNA sequences with annotations and expression profiles. BSRD contains over nine times more experimentally validated sRNAs than any other available databases. BSRD also provides combinatorial regulatory networks of transcription factors and sRNAs with their common targets. We have built and implemented in BSRD a novel RNA-Seq analysis platform, sRNADeep, to characterize sRNAs in large-scale transcriptome sequencing projects. We will update BSRD regularly.

Evolutionary patterns of non-coding RNAs

A plethora of new functions of non-coding RNAs (ncRNAs) have been discovered in past few years. In fact, RNA is emerging as the central player in cellular regulation, taking on active roles in multiple regulatory layers from transcription, RNA maturation, and RNA modification to translational regulation. Nevertheless, very little is known about the evolution of this "Modern RNA World" and its components. In this contribution, we attempt to provide at least a cursory overview of the diversity of ncRNAs and functional RNA motifs in non-translated regions of regular messenger RNAs (mRNAs) with an emphasis on evolutionary questions. This survey is complemented by an in-depth analysis of examples from different classes of RNAs focusing mostly on their evolution in the vertebrate lineage. We present a survey of Y RNA genes in vertebrates and study the molecular evolution of the U7 snRNA, the snoRNAs E1/U17, E2, and E3, the Y RNA family, the let-7 microRNA (miRNA) family, and the mRNA-like evf-1 gene. We furthermore discuss the statistical distribution of miRNAs in metazoans, which suggests an explosive increase in the miRNA repertoire in vertebrates. The analysis of the transcription of ncRNAs suggests that small RNAs in general are genetically mobile in the sense that their association with a hostgene (e.g. when transcribed from introns of a mRNA) can change on evolutionary time scales. The let-7 family demonstrates, that even the mode of transcription (as intron or as exon) can change among paralogous ncRNA.

A complex network of small non-coding RNAs regulate motility in Escherichia coli

Small Hfq-dependent non-coding regulatory RNAs (sRNAs) that alter mRNA stability and expression by pairing with target mRNAs have increasingly been shown to be important in influencing the behaviour of bacteria. In Escherichia coli, flhD and flhC, which encode the master regulator of flagellar synthesis, are co-transcribed from a promoter that is regulated by multiple transcription factors that respond to different environmental cues. Here, we show that the 5' untranslated region (5' UTR) of the flhDC mRNA also serves as a hub to integrate additional environmental cues into the decision to make flagella. Four sRNAs, ArcZ, OmrA, OmrB and OxyS, negatively regulated and one sRNA, McaS, positively regulated motility and flhDC expression by base-pairing with the 5' UTR of this mRNA. Another sRNA, MicA, positively regulated motility independent of regulation of flhDC. Furthermore, we demonstrate that the regulation of motility by the ArcB/A two component system is in part due to its regulation of ArcZ. flhDC is the first mRNA that has been shown to be both positively and negatively regulated by direct pairing to sRNAs. Moreover, both positive regulation by McaS and negative regulation by ArcZ require the same binding site in the flhDC mRNA.

A complex network of small non-coding RNAs regulate motility in Escherichia coli

Small Hfq-dependent non-coding regulatory RNAs (sRNAs) that alter mRNA stability and expression by pairing with target mRNAs have increasingly been shown to be important in influencing the behaviour of bacteria. In Escherichia coli, flhD and flhC, which encode the master regulator of flagellar synthesis, are co-transcribed from a promoter that is regulated by multiple transcription factors that respond to different environmental cues. Here, we show that the 5' untranslated region (5' UTR) of the flhDC mRNA also serves as a hub to integrate additional environmental cues into the decision to make flagella. Four sRNAs, ArcZ, OmrA, OmrB and OxyS, negatively regulated and one sRNA, McaS, positively regulated motility and flhDC expression by base-pairing with the 5' UTR of this mRNA. Another sRNA, MicA, positively regulated motility independent of regulation of flhDC. Furthermore, we demonstrate that the regulation of motility by the ArcB/A two component system is in part due to its regulation of ArcZ. flhDC is the first mRNA that has been shown to be both positively and negatively regulated by direct pairing to sRNAs. Moreover, both positive regulation by McaS and negative regulation by ArcZ require the same binding site in the flhDC mRNA.

An atlas of Hfq-bound transcripts reveals 3' UTRs as a genomic reservoir of regulatory small RNAs

The small RNAs associated with the protein Hfq constitute one of the largest classes of post-transcriptional regulators known to date. Most previously investigated members of this class are encoded by conserved free-standing genes. Here, deep sequencing of Hfq-bound transcripts from multiple stages of growth of Salmonella typhimurium revealed a plethora of new small RNA species from within mRNA loci, including DapZ, which overlaps with the 3' region of the biosynthetic gene, dapB. Synthesis of the DapZ small RNA is independent of DapB protein synthesis, and is controlled by HilD, the master regulator of Salmonella invasion genes. DapZ carries a short G/U-rich domain similar to that of the globally acting GcvB small RNA, and uses GcvB-like seed pairing to repress translation of the major ABC transporters, DppA and OppA. This exemplifies double functional output from an mRNA locus by the production of both a protein and an Hfq-dependent trans-acting RNA. Our atlas of Hfq targets suggests that the 3' regions of mRNA genes constitute a rich reservoir that provides the Hfq network with new regulatory small RNAs.

A survey of application: genomics and genetic programming, a new frontier

The aim of this paper is to provide an introduction to the rapidly developing field of genetic programming (GP). Particular emphasis is placed on the application of GP to genomics. First, the basic methodology of GP is introduced. This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation. Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications.

Novel iron-regulated and Fur-regulated small regulatory RNAs in Aggregatibacter actinomycetemcomitans

Iron can regulate biofilm formation via non-coding small RNA (sRNA). To determine if iron-regulated sRNAs are involved in biofilm formation by the periodontopathogen Aggregatibacter actinomycetemcomitans, total RNA was isolated from bacteria cultured with iron supplementation or chelation. Transcriptional analysis demonstrated that the expression of four sRNA molecules (JA01-JA04) identified by bioinformatics was significantly upregulated in iron-limited medium compared with iron-rich medium. A DNA fragment encoding each sRNA promoter was able to titrate Escherichia coli ferric uptake regulator (Fur) from a Fur-repressible reporter fusion in an iron uptake regulator titration assay. Cell lysates containing recombinant AaFur shifted the mobility of sRNA-specific DNAs in a gel shift assay. Potential targets of these sRNAs, determined in silico, included genes involved in biofilm formation. The A. actinomycetemcomitans overexpressing JA03 sRNA maintained a rough phenotype on agar, but no longer adhered to uncoated polystyrene or glass, although biofilm determinant gene expression was only modestly decreased. In summary, these sRNAs have the ability to modulate biofilm formation, but their functional target genes remain to be confirmed.

The csgD mRNA as a hub for signal integration via multiple small RNAs

The transcription factor CsgD governing the production of curli fimbriae and cellulose is a key player in the complex regulatory circuit that decides whether Escherichia coli form biofilms. The csgD gene itself is tightly controlled at the level of transcription by a large array of DNA-binding proteins, but what happens after transcription is less understood. In this issue of Molecular Microbiology, Jørgensen et al. (2012), Mika et al. (2012) and Thomason et al. (2012) report on small RNAs (McaS, RprA and GcvB) that together with the RNA-chaperone Hfq regulate the mRNAs of csgD and other biofilm genes, and illustrate the burgeoning concept that the 5' region of bacterial mRNA serves as a hub for sRNA-mediated signal integration at the post-transcriptional level.

A small RNA that regulates motility and biofilm formation in response to changes in nutrient availability in Escherichia coli

In bacteria, many small regulatory RNAs (sRNAs) are induced in response to specific environmental signals or stresses and act by base-pairing with mRNA targets to affect protein translation or mRNA stability. In Escherichia coli, the gene for the sRNA IS061/IsrA, here renamed McaS, was predicted to reside in an intergenic region between abgR, encoding a transcription regulator and ydaL, encoding a small MutS-related protein. We show that McaS is a ∼95nt transcript whose expression increases over growth, peaking in early-to-mid stationary phase, or when glucose is limiting. McaS uses three discrete single-stranded regions to regulate mRNA targets involved in various aspects of biofilm formation. McaS represses csgD, the transcription regulator of curli biogenesis and activates flhD, the master transcription regulator of flagella synthesis leading to increased motility, a process not previously reported to be regulated by sRNAs. McaS also regulates pgaA, a porin required for the export of the polysaccharide poly β-1,6-N-acetyl-d-glucosamine. Consequently, high levels of McaS result in increased biofilm formation while a strain lacking mcaS shows reduced biofilm formation. Based on our observations, we propose that, in response to limited nutrient availability, increasing levels of McaS modulate steps in the progression to a sessile lifestyle.

A conserved RpoS-dependent small RNA controls the synthesis of major porin OmpD

A remarkable feature of many small non-coding RNAs (sRNAs) of Escherichia coli and Salmonella is their accumulation in the stationary phase of bacterial growth. Several stress response regulators and sigma factors have been reported to direct the transcription of stationary phase-specific sRNAs, but a widely conserved sRNA gene that is controlled by the major stationary phase and stress sigma factor, σ(S) (RpoS), has remained elusive. We have studied in Salmonella the conserved SdsR sRNA, previously known as RyeB, one of the most abundant stationary phase-specific sRNAs in E. coli. Alignments of the sdsR promoter region and genetic analysis strongly suggest that this sRNA gene is selectively transcribed by σ(S). We show that SdsR down-regulates the synthesis of the major Salmonella porin OmpD by Hfq-dependent base pairing; SdsR thus represents the fourth sRNA to regulate this major outer membrane porin. Similar to the InvR, MicC and RybB sRNAs, SdsR recognizes the ompD mRNA in the coding sequence, suggesting that this mRNA may be primarily targeted downstream of the start codon. The SdsR-binding site in ompD was localized by 3'-RACE, an experimental approach that promises to be of use in predicting other sRNA-target interactions in bacteria.

Metatranscriptomic analysis of microbes in an Oceanfront deep-subsurface hot spring reveals novel small RNAs and type-specific tRNA degradation

Studies of small noncoding RNAs (sRNAs) have been conducted predominantly using culturable organisms, and the acquisition of further information about sRNAs from global environments containing uncultured organisms now is very important. In this study, hot spring water (57°C, pH 8.1) was collected directly from the underground environment at depths of 250 to 1,000 m in Yunohama, Japan, and small RNA sequences obtained from the environment were analyzed. A phylogenetic analysis of both archaeal and bacterial 16S rRNA gene sequences was conducted, and the results suggested the presence of unique species in the environment, corresponding to the Archaeal Richmond Mine Acidophilic Nanoorganisms (ARMAN) group and three new Betaproteobacteria. A metatranscriptomic analysis identified 64,194 (20,057 nonredundant) cDNA sequences. Of these cDNAs, 90% were either tRNAs, tRNA fragments, rRNAs, or rRNA fragments, whereas 2,181 reads (10%) were classified as previously uncharacterized putative candidate sRNAs. Among these, 15 were particularly abundant, 14 of which showed no sequence similarity to any known noncoding RNA, and at least six of which form very stable RNA secondary structures. The analysis of a large number of tRNA fragments suggested that unique relationships exist between the anticodons of the tRNAs and the sites of tRNA degradation. Previous bacterial tRNA degradation studies have been limited to specific organisms, such as Escherichia coli and Streptomyces coelicolor, and the current results suggest that specific tRNA decay occurs more frequently than previously expected.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

Conservation and Occurrence of Trans-Encoded sRNAs in the Rhizobiales

Post-transcriptional regulation by trans-encoded sRNAs, for example via base-pairing with target mRNAs, is a common feature in bacteria and influences various cell processes, e.g., response to stress factors. Several studies based on computational and RNA-seq approaches identified approximately 180 trans-encoded sRNAs in Sinorhizobium meliloti. The initial point of this report is a set of 52 trans-encoded sRNAs derived from the former studies. Sequence homology combined with structural conservation analyses were applied to elucidate the occurrence and distribution of conserved trans-encoded sRNAs in the order of Rhizobiales. This approach resulted in 39 RNA family models (RFMs) which showed various taxonomic distribution patterns. Whereas the majority of RFMs was restricted to Sinorhizobium species or the Rhizobiaceae, members of a few RFMs were more widely distributed in the Rhizobiales. Access to this data is provided via the RhizoGATE portal [1,2].

EcoBrowser: a web-based tool for visualizing transcriptome data of Escherichia coli

Background

Escherichia coli has been extensively studied as a prokaryotic model organism whose whole genome was determined in 1997. However, it is difficult to identify all the gene products involved in diverse functions by using whole genome sequencesalone. The high-resolution transcriptome mapping using tiling arrays has proved effective to improve the annotation of transcript units and discover new transcripts of ncRNAs. While abundant tiling array data have been generated, the lack of appropriate visualization tools to accommodate and integrate multiple sources of data has emerged.

Findings

EcoBrowser is a web-based tool for visualizing genome annotations and transcriptome data of E. coli. Important tiling array data of E. coli from different experimental platforms are collected and processed for query. An AJAX based genome browser is embedded for visualization. Thus, genome annotations can be compared with transcript profiling and genome occupancy profiling from independent experiments, which will be helpful in discovering new transcripts including novel mRNAs and ncRNAs, generating a detailed description of the transcription unit architecture, further providing clues for investigation of prokaryotic transcriptional regulation that has proved to be far more complex than previously thought.

Conclusions

With the help of EcoBrowser, users can get a systemic view both from the vertical and parallel sides, as well as inspirations for the design of new experiments which will expand our understanding of the regulation mechanism.

Functional characterization of bacterial sRNAs using a network biology approach

Small RNAs (sRNAs) are important components of posttranscriptional regulation. These molecules are prevalent in bacterial and eukaryotic organisms, and involved in a variety of responses to environmental stresses. The functional characterization of sRNAs is challenging and requires highly focused and extensive experimental procedures. Here, using a network biology approach and a compendium of gene expression profiles, we predict functional roles and regulatory interactions for sRNAs in Escherichia coli. We experimentally validate predictions for three sRNAs in our inferred network: IsrA, GlmZ, and GcvB. Specifically, we validate a predicted role for IsrA and GlmZ in the SOS response, and we expand on current knowledge of the GcvB sRNA, demonstrating its broad role in the regulation of amino acid metabolism and transport. We also show, using the inferred network coupled with experiments, that GcvB and Lrp, a transcription factor, repress each other in a mutually inhibitory network. This work shows that a network-based approach can be used to identify the cellular function of sRNAs and characterize the relationship between sRNAs and transcription factors.

Deep sequencing reveals as-yet-undiscovered small RNAs in Escherichia coli

BACKGROUND

In Escherichia coli, approximately 100 regulatory small RNAs (sRNAs) have been identified experimentally and many more have been predicted by various methods. To provide a comprehensive overview of sRNAs, we analysed the low-molecular-weight RNAs (< 200 nt) of E. coli with deep sequencing, because the regulatory RNAs in bacteria are usually 50-200 nt in length.

RESULTS

We discovered 229 novel candidate sRNAs (≥ 50 nt) with computational or experimental evidence of transcription initiation. Among them, the expression of seven intergenic sRNAs and three cis-antisense sRNAs was detected by northern blot analysis. Interestingly, five novel sRNAs are expressed from prophage regions and we note that these sRNAs have several specific characteristics. Furthermore, we conducted an evolutionary conservation analysis of the candidate sRNAs and summarised the data among closely related bacterial strains.

CONCLUSIONS

This comprehensive screen for E. coli sRNAs using a deep sequencing approach has shown that many as-yet-undiscovered sRNAs are potentially encoded in the E. coli genome. We constructed the Escherichia coli Small RNA Browser (ECSBrowser; http://rna.iab.keio.ac.jp/), which integrates the data for previously identified sRNAs and the novel sRNAs found in this study.

Genome-wide detection of novel regulatory RNAs in E. coli

The intergenic regions in bacterial genomes can contain regulatory leader sequences and small RNAs (sRNAs), which both serve to modulate gene expression. Computational analyses have predicted the presence of hundreds of these noncoding regulatory RNAs in Escherichia coli; however, only about 80 have been experimentally validated. By applying a deep-sequencing approach, we detected and quantified the vast majority of the previously validated regulatory elements and identified 10 new sRNAs and nine new regulatory leader sequences in the intergenic regions of E. coli. Half of the newly discovered sRNAs displayed enhanced stability in the presence of the RNA-binding protein Hfq, which is vital to the function of many of the known E. coli sRNAs. Whereas previous methods have often relied on phylogenetic conservation to identify regulatory leader sequences, only five of the newly discovered E. coli leader sequences were present in the genomes of other enteric species. For those newly identified regulatory elements having orthologs in Salmonella, evolutionary analyses showed that these regions encoded new noncoding elements rather than small, unannotated protein-coding transcripts. In addition to discovering new noncoding regulatory elements, we validated 53 sRNAs that were previously predicted but never detected and showed that the presence, within intergenic regions, of σ(70) promoters and sequences with compensatory mutations that maintain stable RNA secondary structures across related species is a good predictor of novel sRNAs.

Role of polynucleotide phosphorylase in sRNA function in Escherichia coli

In Escherichia coli, many small noncoding regulatory RNAs (sRNAs) post-transcriptionally regulate gene expression by base-pairing to mRNAs in a process that is mediated by the RNA chaperone Hfq. Binding of the sRNA to the mRNA can lead to increased or decreased mRNA stability and/or translation. It is not known if proteins other than Hfq are necessary for this process. In order to identify additional genes required for the post-transcriptional regulation of gene expression by Hfq-dependent sRNAs, we developed a novel combined genetic selection and screen for mutants defective in sRNA regulation. In our combined genetic selection and screen, we isolated hfq mutants and mutants in pnp, encoding polynucleotide phosphorylase (PNPase). We show that loss-of-function mutations in pnp result in a decreased stability of several sRNAs including RyhB, SgrS, and CyaR and also decrease both the negative and positive regulation by sRNAs. The defect in stability of CyaR and in negative and positive regulation are suppressed by deletion mutations in RNase E. Altogether, our results suggest that the lack of sRNA-mediated regulation in the absence of an active form of PNPase is due to the rapid turnover of sRNA resulting from an increase in RNase E activity and/or an increase in access of other ribonucleases to sRNAs.

An integrated approach for finding overlooked genes in Shigella

BACKGROUND

The completion of numerous genome sequences introduced an era of whole-genome study. However, many genes are missed during genome annotation, including small RNAs (sRNAs) and small open reading frames (sORFs). In order to improve genome annotation, we aimed to identify novel sRNAs and sORFs in Shigella, the principal etiologic agents of bacillary dysentery.

METHODOLOGY/PRINCIPAL FINDINGS

We identified 64 sRNAs in Shigella, which were experimentally validated in other bacteria based on sequence conservation. We employed computer-based and tiling array-based methods to search for sRNAs, followed by RT-PCR and northern blots, to identify nine sRNAs in Shigella flexneri strain 301 (Sf301) and 256 regions containing possible sRNA genes. We found 29 candidate sORFs using bioinformatic prediction, array hybridization and RT-PCR verification. We experimentally validated 557 (57.9%) DOOR operon predictions in the chromosomes of Sf301 and 46 (76.7%) in virulence plasmid.We found 40 additional co-expressed gene pairs that were not predicted by DOOR.

CONCLUSIONS/SIGNIFICANCE

We provide an updated and comprehensive annotation of the Shigella genome. Our study increased the expected numbers of sORFs and sRNAs, which will impact on future functional genomics and proteomics studies. Our method can be used for large scale reannotation of sRNAs and sORFs in any microbe with a known genome sequence.

The transposon-like Correia elements encode numerous strong promoters and provide a potential new mechanism for phase variation in the meningococcus

Neisseria meningitidis is the primary causative agent of bacterial meningitis. The genome is rich in repetitive DNA and almost 2% is occupied by a diminutive transposon called the Correia element. Here we report a bioinformatic analysis defining eight subtypes of the element with four distinct types of ends. Transcriptional analysis, using PCR and a lacZ reporter system, revealed that two ends in particular encode strong promoters. The activity of the strongest promoter is dictated by a recurrent polymorphism (Y128) at the right end of the element. We highlight examples of elements that appear to drive transcription of adjacent genes and others that may express small non-coding RNAs. Pair-wise comparisons between three meningococcal genomes revealed that no more than two-thirds of Correia elements maintain their subtype at any particular locus. This is due to recombinational class switching between elements in a single strain. Upon switching subtype, a new allele is available to spread through the population by natural transformation. This process may represent a hitherto unrecognized mechanism for phase variation in the meningococcus. We conclude that the strain-to-strain variability of the Correia elements, and the large number of strong promoters encoded by them, allows for potentially widespread effects within the population as a whole. By defining the strength of the promoters encoded by the eight subtypes of Correia ends, we provide a resource that allows the transcriptional effects of a particular subtype at a given locus to be predicted.

Bacterial antisense RNAs: how many are there, and what are they doing?

Antisense RNAs encoded on the DNA strand opposite another gene have the potential to form extensive base-pairing interactions with the corresponding sense RNA. Unlike other smaller regulatory RNAs in bacteria, antisense RNAs range in size from tens to thousands of nucleotides. The numbers of antisense RNAs reported for different bacteria vary extensively, but hundreds have been suggested in some species. If all of these reported antisense RNAs are expressed at levels sufficient to regulate the genes encoded opposite them, antisense RNAs could significantly impact gene expression in bacteria. Here, we review the evidence for these RNA regulators and describe what is known about the functions and mechanisms of action for some of these RNAs. Important considerations for future research as well as potential applications are also discussed.

Tiling array analysis of UV treated Escherichia coli predicts novel differentially expressed small peptides

Background

Despite comprehensive investigation, the Escherichia coli SOS response system is not yet fully understood. We have applied custom designed whole genome tiling arrays to measure UV invoked transcriptional changes in E. coli. This study provides a more complete insight into the transcriptome and the UV irradiation response of this microorganism.

Results

We detected a number of novel differentially expressed transcripts in addition to the expected SOS response genes (such as sulA, recN, uvrA, lexA, umuC and umuD) in the UV treated cells. Several of the differentially expressed transcripts might play important roles in regulation of the cellular response to UV damage. We have predicted 23 novel small peptides from our set of detected non-gene transcripts. Further, three of the predicted peptides were cloned into protein expression vectors to test the biological activity. All three constructs expressed the predicted peptides, in which two of them were highly toxic to the cell. Additionally, a remarkably high overlap with previously in-silico predicted non-coding RNAs (ncRNAs) was detected. Generally we detected a far higher transcriptional activity than the annotation suggests, and these findings correspond with previous transcription mappings from E. coli and other organisms.

Conclusions

Here we demonstrate that the E. coli transcriptome consists of far more transcripts than the present annotation suggests, of which many transcripts seem important to the bacterial stress response. Sequence alignment of promoter regions suggest novel regulatory consensus sequences for some of the upregulated genes. Finally, several of the novel transcripts identified in this study encode putative small peptides, which are biologically active.

Proteome-wide alterations in Escherichia coli translation rates upon anaerobiosis

Enzyme reprofiling in bacteria during adaptation from one environmental condition to another may be regulated by both transcription and translation. However, little is known about the contribution of translational regulation. Recently, we have developed a pulse labeling method using the methionine analog azidohomoalanine to determine the relative amounts of proteins synthesized by Escherichia coli in a brief time frame upon a change in environmental conditions. Here we present an extension of our analytical strategy, which entails measuring changes in total protein levels on the same time scale as new protein synthesis. This allows identification of stable and labile proteins and demonstrates that altered levels of most newly synthesized proteins are the result of a change in translation rate rather than degradation rate. With this extended strategy, average relative translation rates for 10 min immediately after a switch from aerobiosis to anaerobiosis were determined. The majority of proteins with increased synthesis rates upon an anaerobic switch are involved in glycolysis and pathways aimed at preventing glycolysis grinding to a halt by a cellular redox imbalance. Our method can be used to compare relative translation rates with relative mRNA levels at the same time. Discrepancies between these parameters may reveal genes whose expression is regulated by translation rather than by transcription. This may help unravel molecular mechanism underlying changes in translation rates, e.g. mediated by small regulatory RNAs.

sRNAscanner: a computational tool for intergenic small RNA detection in bacterial genomes

Background

Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement.

Methodology/Principal Findings

Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5′-ends of these six Northern-supported sRNA candidates were successfully mapped using 5′-RACE analysis.

Conclusions/Significance

We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that ∼40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

Recognition and discrimination of target mRNAs by Sib RNAs, a cis-encoded sRNA family

Five Sib antitoxin RNAs, members of a family of cis-encoded small regulatory RNAs (sRNAs) in Escherichia coli, repress their target mRNAs, which encode Ibs toxins. This target repression occurs only between cognate sRNA–mRNA pairs with an exception of ibsA. We performed co-transformation assays to assess the ability of SibC derivatives to repress ibsC expression, thereby revealing the regions of SibC that are essential for ibsC mRNA recognition. SibC has two target recognition domains, TRD1 and TRD2, which function independently. The target site for TRD1 is located within the ORF of ibsC, whereas the target site for TRD2 is located in the translational initiation region. The TRD1 sequence is sufficient to repress ibsC expression. In contrast, TRD2 requires a specific structure in addition to the recognition sequence. An in vitro structural probing analysis showed that the initial interactions at these two recognition sites allowed base-pairing to progress into the flanking sequences. Displacement of the TRD1 and TRD2 domains of SibC by the corresponding domains of SibD changed the target specificity of SibC from ibsC to ibsD, suggesting that these two elements modulate the cognate target recognition of each Sib RNA by discriminating among non-cognate ibs mRNAs.

Genomic SELEX for Hfq-binding RNAs identifies genomic aptamers predominantly in antisense transcripts

An unexpectedly high number of regulatory RNAs have been recently discovered that fine-tune the function of genes at all levels of expression. We employed Genomic SELEX, a method to identify protein-binding RNAs encoded in the genome, to search for further regulatory RNAs in Escherichia coli. We used the global regulator protein Hfq as bait, because it can interact with a large number of RNAs, promoting their interaction. The enriched SELEX pool was subjected to deep sequencing, and 8865 sequences were mapped to the E. coli genome. These short sequences represent genomic Hfq-aptamers and are part of potential regulatory elements within RNA molecules. The motif 5′-AAYAAYAA-3′ was enriched in the selected RNAs and confers low-nanomolar affinity to Hfq. The motif was confirmed to bind Hfq by DMS footprinting. The Hfq aptamers are 4-fold more frequent on the antisense strand of protein coding genes than on the sense strand. They were enriched opposite to translation start sites or opposite to intervening sequences between ORFs in operons. These results expand the repertoire of Hfq targets and also suggest that Hfq might regulate the expression of a large number of genes via interaction with cis-antisense RNAs.

Genome-wide detection of predicted non-coding RNAs in Rhizobium etli expressed during free-living and host-associated growth using a high-resolution tiling array

Background

Non-coding RNAs (ncRNAs) play a crucial role in the intricate regulation of bacterial gene expression, allowing bacteria to quickly adapt to changing environments. In the past few years, a growing number of regulatory RNA elements have been predicted by computational methods, mostly in well-studied γ-proteobacteria but lately in several α-proteobacteria as well. Here, we have compared an extensive compilation of these non-coding RNA predictions to intergenic expression data of a whole-genome high-resolution tiling array in the soil-dwelling α-proteobacterium Rhizobium etli.

Results

Expression of 89 candidate ncRNAs was detected, both on the chromosome and on the six megaplasmids encompassing the R. etli genome. Of these, 11 correspond to functionally well characterized ncRNAs, 12 were previously identified in other α-proteobacteria but are as yet uncharacterized and 66 were computationally predicted earlier but had not been experimentally identified and were therefore classified as novel ncRNAs. The latter comprise 17 putative sRNAs and 49 putative cis-regulatory ncRNAs. A selection of these candidate ncRNAs was validated by RT-qPCR, Northern blotting and 5' RACE, confirming the existence of 4 ncRNAs. Interestingly, individual transcript levels of numerous ncRNAs varied during free-living growth and during interaction with the eukaryotic host plant, pointing to possible ncRNA-dependent regulation of these specialized processes.

Conclusions

Our data support the practical value of previous ncRNA prediction algorithms and significantly expand the list of candidate ncRNAs encoded in the intergenic regions of R. etli and, by extension, of α-proteobacteria. Moreover, we show high-resolution tiling arrays to be suitable tools for studying intergenic ncRNA transcription profiles across the genome. The differential expression levels of some of these ncRNAs may indicate a role in adaptation to changing environmental conditions.

Small stress response proteins in Escherichia coli: proteins missed by classical proteomic studies

Proteins of 50 or fewer amino acids are poorly characterized in all organisms. The corresponding genes are challenging to reliably annotate, and it is difficult to purify and characterize the small protein products. Due to these technical limitations, little is known about the abundance of small proteins, not to mention their biological functions. To begin to characterize these small proteins in Escherichia coli, we assayed their accumulation under a variety of growth conditions and after exposure to stress. We found that many small proteins accumulate under specific growth conditions or are stress induced. For some genes, the observed changes in protein levels were consistent with known transcriptional regulation, such as ArcA activation of the operons encoding yccB and ybgT. However, we also identified novel regulation, such as Zur repression of ykgMO, cyclic AMP response protein (CRP) repression of azuC, and CRP activation of ykgR. The levels of 11 small proteins increase after heat shock, and induction of at least 1 of these, YobF, occurs at a posttranscriptional level. These results show that small proteins are an overlooked subset of stress response proteins in E. coli and provide information that will be valuable for determining the functions of these proteins.

Specific and pleiotropic patterns of mRNA regulation by ArcZ, a conserved, Hfq-dependent small RNA

The small RNA, ArcZ (previously RyhA/SraH), was discovered in several genome-wide screens in Escherichia coli and Salmonella. Its high degree of genomic conservation, its frequent recovery by shotgun sequencing, and its association with the RNA chaperone, Hfq, identified ArcZ as an abundant enterobacterial 'core' small RNA, yet its function remained unknown. Here, we report that ArcZ acts as a post-transcriptional regulator in Salmonella, repressing the mRNAs of the widely distributed sdaCB (serine uptake) and tpx (oxidative stress) genes, and of STM3216, a horizontally acquired methyl-accepting chemotaxis protein (MCP). Both sdaCB and STM3216 are regulated by sequestration of the ribosome binding site. In contrast, the tpx mRNA is targeted in the coding sequence (CDS), arguing that CDS targeting is more common than appreciated. Transcriptomic analysis of an arcZ deletion strain further argued for the existence of a distinct set of Salmonella loci specifically regulated by ArcZ. In contrast, increased expression of the sRNA altered the steady-state levels of > 16% (> 750) of all Salmonella mRNAs, and rendered the bacteria non-motile. Deep sequencing detected a dramatically changed profile of Hfq-bound sRNAs and mRNAs, suggesting that the unprecedented pleiotropic effects by a single sRNA might in part be caused by altered post-transcriptional regulation.

De novo computational prediction of non-coding RNA genes in prokaryotic genomes

Motivation: The computational identification of non-coding RNA (ncRNA) genes represents one of the most important and challenging problems in computational biology. Existing methods for ncRNA gene prediction rely mostly on homology information, thus limiting their applications to ncRNA genes with known homologues.

Results: We present a novel de novo prediction algorithm for ncRNA genes using features derived from the sequences and structures of known ncRNA genes in comparison to decoys. Using these features, we have trained a neural network-based classifier and have applied it to Escherichia coli and Sulfolobus solfataricus for genome-wide prediction of ncRNAs. Our method has an average prediction sensitivity and specificity of 68% and 70%, respectively, for identifying windows with potential for ncRNA genes in E.coli. By combining windows of different sizes and using positional filtering strategies, we predicted 601 candidate ncRNAs and recovered 41% of known ncRNAs in E.coli. We experimentally investigated six novel candidates using Northern blot analysis and found expression of three candidates: one represents a potential new ncRNA, one is associated with stable mRNA decay intermediates and one is a case of either a potential riboswitch or transcription attenuator involved in the regulation of cell division. In general, our approach enables the identification of both cis- and trans-acting ncRNAs in partially or completely sequenced microbial genomes without requiring homology or structural conservation.

Availability: The source code and results are available at http://csbl.bmb.uga.edu/publications/materials/tran/.

Contact:xyn@bmb.uga.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

RNA search with decision trees and partial covariance models

The use of partial covariance models to search for RNA family members in genomic sequence databases is explored. The partial models are formed from contiguous subranges of the overall RNA family multiple alignment columns. A binary decision-tree framework is presented for choosing the order to apply the partial models and the score thresholds on which to make the decisions. The decision trees are chosen to minimize computation time subject to the constraint that all of the training sequences are passed to the full covariance model for final evaluation. Computational intelligence methods are suggested to select the decision tree since the tree can be quite complex and there is no obvious method to build the tree in these cases. Experimental results from seven RNA families shows execution times of 0.066-0.268 relative to using the full covariance model alone. Tests on the full sets of known sequences for each family show that at least 95 percent of these sequences are found for two families and 100 percent for five others. Since the full covariance model is run on all sequences accepted by the partial model decision tree, the false alarm rate is at least as low as that of the full model alone.

Gains and unexpected lessons from genome-scale promoter mapping

Potential promoters in the genome of Escherichia coli were searched by pattern recognition software PlatProm and classified on the basis of positions relative to gene borders. Beside the expected promoters located in front of the coding sequences we found a considerable amount of intragenic promoter-like signals with a putative ability to drive either antisense or alternative transcription and revealed unusual genomic regions with extremely high density of predicted transcription start points (promoter ‘islands’), some of which are located in coding sequences. PlatProm scores converted into probability of RNA polymerase binding demonstrated certain correlation with the enzyme retention registered by ChIP-on-chip technique; however, in ‘dense’ regions the value of correlation coefficient is lower than throughout the entire genome. Experimental verification confirmed the ability of RNA polymerase to interact and form multiple open complexes within promoter ‘island’ associated with appY, yet transcription efficiency was lower than might be expected. Analysis of expression data revealed the same tendency for other promoter ‘islands’, thus assuming functional relevance of non-productive RNA polymerase binding. Our data indicate that genomic DNA of E. coli is enriched by numerous unusual promoter-like sites with biological role yet to be understood.

CsrA interacting small RNAs in Haemophilus spp genomes: a theoretical analysis

The csrA is a carbon storage regulator gene that encodes a protein with multiple RNA interaction sites. Bacterial non-coding small RNAs like csrB, csrC and their counterparts in diverse bacterial genus are identified to control the regulatory activities of CsrA and its orthologs. An attempt has been made in this study to identify 'novel' non-coding small RNAs that are involved in the regulatory activities of csrA gene. All CsrA-interacting small RNAs are computationally fingerprinted to have multiple occurrence of 7-nucleotide CsrA interacting repeats [CAGGA(U/A/C)G] along with a 18-nucleotide upstream binding site. However, in several of the genomes like Haemophilus spp, the upstream binding site is not identified. The current methodology overcomes this difficulty by identifying small RNA-specific orphan transcriptional units within the intergenic regions of the genome. The results could identify all known CsrA-interacting small RNAs in E. coli, Vibrio cholerae and Pseudomonas aeruginosa genomes and additionally has picked six new possible CsrA-interacting small RNA regions in E. coli. Our computational analysis indicates that known rygD and rprA sRNAs in E. coli could possibly interact with CsrA proteins. The study is extended to three of the Haemophilus genomes that could identify seven new possible CsrA interacting small RNAs.

Identification of small noncoding RNAs in Helicobacter pylori by a bioinformatics-based approach

Small noncoding RNAs (sRNAs) are a group of regulatory RNA molecules normally without a protein-coding function. In recent years, the importance of sRNAs as mediators of gene expression in bacteria has begun to be recognized. More than 70 sRNAs have been known in Escherichia coli. However, little is known about sRNAs in Helicobacter pylori, a human pathogen associated with gastric diseases. Here, we systematically identified sRNAs in the H. pylori genome by a computational approach based on gene location, sequence conservation, promoter and terminator search, and secondary structure. Among a total of six candidate sRNAs initially predicted, two novel sRNAs (IG-443 and IG-524) were confirmed by Northern blot and reverse transcription-polymerase chain reaction (RT-PCR). Virtually, they were a class of natural antisense transcripts, which were complementary to partial sequences of the following genes: flagellar motor switch gene (fliM) and fumarase (fumC). Taken together, the results indicate that there exist novel sRNAs in H. pylori and these RNAs might play a potential role in regulating gene expression.

Poly(A)-assisted RNA decay and modulators of RNA stability

In Escherichia coli, RNA degradation is orchestrated by the degradosome with the assistance of complementary pathways and regulatory cofactors described in this chapter. They control the stability of each transcript and regulate the expression of many genes involved in environmental adaptation. The poly(A)-dependent degradation machinery has diverse functions such as the degradation of decay intermediates generated by endoribonucleases, the control of the stability of regulatory non coding RNAs (ncRNAs) and the quality control of stable RNA. The metabolism of poly(A) and mechanism of poly(A)-assisted degradation are beginning to be understood. Regulatory factors, exemplified by RraA and RraB, control the decay rates of subsets of transcripts by binding to RNase E, in contrast to regulatory ncRNAs which, assisted by Hfq, target RNase E to specific transcripts. Destabilization is often consecutive to the translational inactivation of mRNA. However, there are examples where RNA degradation is the primary regulatory step.

sRNAMap: genomic maps for small non-coding RNAs, their regulators and their targets in microbial genomes

Small non-coding RNAs (sRNAs) carry out a variety of biological functions and affect protein synthesis and protein activities in prokaryotes. Recently, numerous sRNAs and their targets were identified in Escherichia coli and in other bacteria. It is crucial to have a comprehensive resource concerning the annotation of small non-coding RNAs in microbial genomes. This work presents an integrated database, namely sRNAMap, to collect the sRNA genes, the transcriptional regulators of sRNAs and the sRNA target genes by integrating a variety of biological databases and by surveying literature. In this resource, we collected 397 sRNAs, 62 regulators/sRNAs and 60 sRNAs/targets in 70 microbial genomes. Additionally, more valuable information of the sRNAs, such as the secondary structure of sRNAs, the expressed conditions of sRNAs, the expression profiles of sRNAs, the transcriptional start sites of sRNAs and the cross-links to other biological databases, are provided for further investigation. Besides, various textual and graphical interfaces were designed and implemented to facilitate the data access in sRNAMap. sRNAMap is available at http://sRNAMap.mbc.nctu.edu.tw/.

The Crp-activated small noncoding regulatory RNA CyaR (RyeE) links nutritional status to group behavior

Small noncoding regulatory RNAs (sRNAs) play a key role in regulating the expression of many genes in Escherichia coli and other bacteria. Many of the sRNAs identified in E. coli bind to mRNAs in an Hfq-dependent manner and stimulate or inhibit translation of the mRNAs. Several sRNAs are regulated by well-studied global regulators. Here, we report characterization of the CyaR (RyeE) sRNA, which was previously identified in a global search for sRNAs in E. coli. We demonstrated that CyaR is positively regulated by the global regulator Crp under conditions in which cyclic AMP levels are high. We showed by using microarray analysis and Northern blotting that several genes are negatively regulated by CyaR, including ompX, encoding a major outer membrane protein; luxS, encoding the autoinducer-2 synthase; nadE, encoding an essential NAD synthetase; and yqaE, encoding a predicted membrane protein with an unknown function. Using translational lacZ fusions to yqaE, ompX, nadE, and luxS, we demonstrated that the negative regulation of these genes by CyaR occurs at the posttranscriptional level and is direct. Different portions of a highly conserved 3' region of CyaR are predicted to pair with sequences near the ribosome binding site of each of these targets; mutations in this sequence affected regulation, and compensatory mutations in the target mRNA restored regulation, confirming that there is direct regulation by the sRNA. These results provide insight into the mechanisms by which Crp negatively regulates genes such as luxS and ompX and provide a link between catabolite repression, quorum sensing, and nitrogen assimilation in E. coli.

Small RNA gene identification and mRNA target predictions in bacteria

MOTIVATION

Bacterial small ribonucleic acids (sRNAs) that are not ribosomal and transfer or messenger RNAs were initially identified in the sixties, whereas their molecular functions are still under active investigation today. It is now widely accepted that most play central roles in gene expression regulation in response to environmental changes. Interestingly, some are also implicated in bacterial virulence. Functional studies revealed that a large subset of these sRNAs act by an antisense mechanism thanks to pairing interactions with dedicated mRNA targets, usually around their translation start sites, to modulate gene expression at the posttranscriptional level. Some sRNAs modulate protein activity or mimic the structure of other macromolecules. In the last few years, in silico methods have been developed to detect more bacterial sRNAs. Among these, computational analyses of the bacterial genomes by comparative genomics have predicted the existence of a plethora of sRNAs, some that were confirmed to be expressed in vivo. The prediction accuracy of these computational tools is highly variable and can be perfectible. Here we review the computational studies that have contributed to detecting the sRNA gene and mRNA targets in bacteria and the methods for their experimental testing. In addition, the remaining challenges are discussed.

Prediction of Sinorhizobium meliloti sRNA genes and experimental detection in strain 2011

BACKGROUND

Small non-coding RNAs (sRNAs) have emerged as ubiquitous regulatory elements in bacteria and other life domains. However, few sRNAs have been identified outside several well-studied species of gamma-proteobacteria and thus relatively little is known about the role of RNA-mediated regulation in most other bacterial genera. Here we have conducted a computational prediction of putative sRNA genes in intergenic regions (IgRs) of the symbiotic alpha-proteobacterium S. meliloti 1021 and experimentally confirmed the expression of dozens of these candidate loci in the closely related strain S. meliloti 2011.

RESULTS

Our first sRNA candidate compilation was based mainly on the output of the sRNAPredictHT algorithm. A thorough manual sequence analysis of the curated list rendered an initial set of 18 IgRs of interest, from which 14 candidates were detected in strain 2011 by Northern blot and/or microarray analysis. Interestingly, the intracellular transcript levels varied in response to various stress conditions. We developed an alternative computational method to more sensitively predict sRNA-encoding genes and score these predicted genes based on several features to allow identification of the strongest candidates. With this novel strategy, we predicted 60 chromosomal independent transcriptional units that, according to our annotation, represent strong candidates for sRNA-encoding genes, including most of the sRNAs experimentally verified in this work and in two other contemporary studies. Additionally, we predicted numerous candidate sRNA genes encoded in megaplasmids pSymA and pSymB. A significant proportion of the chromosomal- and megaplasmid-borne putative sRNA genes were validated by microarray analysis in strain 2011.

CONCLUSION

Our data extend the number of experimentally detected S. meliloti sRNAs and significantly expand the list of putative sRNA-encoding IgRs in this and closely related alpha-proteobacteria. In addition, we have developed a computational method that proved useful to predict sRNA-encoding genes in S. meliloti. We anticipate that this predictive approach can be flexibly implemented in many other bacterial species.

Deep sequencing analysis of small noncoding RNA and mRNA targets of the global post-transcriptional regulator, Hfq

Recent advances in high-throughput pyrosequencing (HTPS) technology now allow a thorough analysis of RNA bound to cellular proteins, and, therefore, of post-transcriptional regulons. We used HTPS to discover the Salmonella RNAs that are targeted by the common bacterial Sm-like protein, Hfq. Initial transcriptomic analysis revealed that Hfq controls the expression of almost a fifth of all Salmonella genes, including several horizontally acquired pathogenicity islands (SPI-1, -2, -4, -5), two sigma factor regulons, and the flagellar gene cascade. Subsequent HTPS analysis of 350,000 cDNAs, derived from RNA co-immunoprecipitation (coIP) with epitope-tagged Hfq or control coIP, identified 727 mRNAs that are Hfq-bound in vivo. The cDNA analysis discovered new, small noncoding RNAs (sRNAs) and more than doubled the number of sRNAs known to be expressed in Salmonella to 64; about half of these are associated with Hfq. Our analysis explained aspects of the pleiotropic effects of Hfq loss-of-function. Specifically, we found that the mRNAs of hilD (master regulator of the SPI-1 invasion genes) and flhDC (flagellar master regulator) were bound by Hfq. We predicted that defective SPI-1 secretion and flagellar phenotypes of the hfq mutant would be rescued by overexpression of HilD and FlhDC, and we proved this to be correct. The combination of epitope-tagging and HTPS of immunoprecipitated RNA detected the expression of many intergenic chromosomal regions of Salmonella. Our approach overcomes the limited availability of high-density microarrays that have impeded expression-based sRNA discovery in microorganisms. We present a generic strategy that is ideal for the systems-level analysis of the post-transcriptional regulons of RNA-binding proteins and for sRNA discovery in a wide range of bacteria.

Biocomputational prediction of small non-coding RNAs in Streptomyces

Background

The first systematic study of small non-coding RNAs (sRNA, ncRNA) in Streptomyces is presented. Except for a few exceptions, the Streptomyces sRNAs, as well as the sRNAs in other genera of the Actinomyces group, have remained unstudied. This study was based on sequence conservation in intergenic regions of Streptomyces, localization of transcription termination factors, and genomic arrangement of genes flanking the predicted sRNAs.

Results

Thirty-two potential sRNAs in Streptomyces were predicted. Of these, expression of 20 was detected by microarrays and RT-PCR. The prediction was validated by a structure based computational approach. Two predicted sRNAs were found to be terminated by transcription termination factors different from the Rho-independent terminators. One predicted sRNA was identified computationally with high probability as a Streptomyces 6S RNA. Out of the 32 predicted sRNAs, 24 were found to be structurally dissimilar from known sRNAs.

Conclusion

Streptomyces is the largest genus of Actinomyces, whose sRNAs have not been studied. The Actinomyces is a group of bacterial species with unique genomes and phenotypes. Therefore, in Actinomyces, new unique bacterial sRNAs may be identified. The sequence and structural dissimilarity of the predicted Streptomyces sRNAs demonstrated by this study serve as the first evidence of the uniqueness of Actinomyces sRNAs.