BackgroundBacterial 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 FindingsHere 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/SignificanceWe 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/.

Genomic screens for small RNA candidates in Enterobacteriacae genomes were carried out with existing small RNA sequences, conserved flanking genes, and genomic backbone information. The small RNA sequences and contexts from E. coli K12 formed the basis of the search. Sequence identity identified 117 additional small RNA homologs in related genomes. Motifs of continuous sequence stretches added another 48 sRNA regions, termed partial homologs. However, this study is unique in identifying 160 nonhomologous sRNA loci in related genomes based on the conserved flanking gene synteny and the backbone retention information obtained from KEGG-SSDB. Gene synteny and genomic backbone continuity were observed to be correlated with all of the sRNAs in related genomes. This search is the first of its kind toward identification of functionally important regions using gene order and back-bone information. A disruption in flanking gene order or genomic backbone indicates a possible hotspot for alien gene pool integration. This study reports both occurrence of multiple copies of a sRNA and co-occurrence of different sRNAs between a pair of conserved flanking genes. In general, synteny and genomic backbone retention information can be added as additional search criteria toward the design of precise bioinformatics tools for sRNA, gene identification, and gene functional annotations in related genomes.

Small RNAs are bacterial counterparts of noncoding RNAs. Increasing evidence being added in the literature indicates that these small RNAs play major roles in prokaryotes both at the transcriptome and proteome levels. Based on comparative genomic studies, we present manually curated small RNA regions in 25 recently completed genomes from Enterobacteriaceae. The study is a continuation of our earlier work that uses the presence of small RNAs sandwiched between specific conserved flanking genes retaining genomic backbone and gene synteny. Based on this study, a total of 931 identified sRNA/sRNA regions are reported. This data contains 498 small RNA homologs, 80 putative small RNA regions containing partial stretches of homologous sequences, and 353 putative nonhomologous sRNA regions. This homologs/partial homologs includes, 84 putative small RNA homologous regions retaining at least one of the conserved flanking genes pair which may possibly act as hotspots for genetic pool insertion/deletion in genomes. Nonhomologous CsrB sRNA region reported by us in Yersinia pseudotuberculosis IP32953 has been experimentally confirmed by Kulkarni's group and sraH and ryeE sRNAs from Erwinia carotovora subsp. atroseptica SCRI1043 recently added to the Rfam database are indicative proof of our positive approach.

In the past few decades, scientists from all over the world have taken a keen interest in novel functional units such as small regulatory RNAs, small open reading frames, pseudogenes, transposons, integrase binding attB/attP sites, repeat elements within the bacterial intergenic regions (IGRs) and in the analysis of those “junk” regions for genomic complexity. Here we have developed a web server, named Junker, to facilitate the in-depth analysis of IGRs for examining their length distribution, four-quadrant plots, GC percentage and repeat details. Upon selection of a particular bacterial genome, the physical genome map is displayed as a multiple loci with options to view any loci of interest in detail. In addition, an IGR statistics module has been created and implemented in the web server to analyze the length distribution of the IGRs and to understand the disordered grouping of IGRs across the genome by generating the four-quadrant plots. The proposed web server is freely available at the URL http://pranag.physics.iisc.ernet.in/junker/.

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