High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions

Experimental identification and characterization of 97 novel npcRNA candidates in Salmonella enterica serovar Typhi

We experimentally identified and characterized 97 novel, non-protein-coding RNA candidates (npcRNAs) from the human pathogen Salmonella enterica serovar Typhi (hereafter referred to as S. typhi). Three were specific to S. typhi, 22 were restricted to Salmonella species and 33 were differentially expressed during S. typhi growth. We also identified Salmonella Pathogenicity Island-derived npcRNAs that might be involved in regulatory mechanisms of virulence, antibiotic resistance and pathogenic specificity of S. typhi. An in-depth characterization of S. typhi StyR-3 npcRNA showed that it specifically interacts with RamR, the transcriptional repressor of the ramA gene, which is involved in the multidrug resistance (MDR) of Salmonella. StyR-3 interfered with RamR–DNA binding activity and thus potentially plays a role in regulating ramA gene expression, resulting in the MDR phenotype. Our study also revealed a large number of cis-encoded antisense npcRNA candidates, supporting previous observations of global sense–antisense regulatory networks in bacteria. Finally, at least six of the npcRNA candidates interacted with the S. typhi Hfq protein, supporting an important role of Hfq in npcRNA networks. This study points to novel functional npcRNA candidates potentially involved in various regulatory roles including the pathogenicity of S. typhi

Large-scale computational and statistical analyses of high transcription potentialities in 32 prokaryotic genomes

This article compares 32 bacterial genomes with respect to their high transcription potentialities. The σ70 promoter has been widely studied for Escherichia coli model and a consensus is known. Since transcriptional regulations are known to compensate for promoter weakness (i.e. when the promoter similarity with regard to the consensus is rather low), predicting functional promoters is a hard task. Instead, the research work presented here comes within the scope of investigating potentially high ORF expression, in relation with three criteria: (i) high similarity to the σ70 consensus (namely, the consensus variant appropriate for each genome), (ii) transcription strength reinforcement through a supplementary binding site—the upstream promoter (UP) element—and (iii) enhancement through an optimal Shine-Dalgarno (SD) sequence. We show that in the AT-rich Firmicutes’ genomes, frequencies of potentially strong σ70-like promoters are exceptionally high. Besides, though they contain a low number of strong promoters (SPs), some genomes may show a high proportion of promoters harbouring an UP element. Putative SPs of lesser quality are more frequently associated with an UP element than putative strong promoters of better quality. A meaningful difference is statistically ascertained when comparing bacterial genomes with similarly AT-rich genomes generated at random; the difference is the highest for Firmicutes. Comparing some Firmicutes genomes with similarly AT-rich Proteobacteria genomes, we confirm the Firmicutes specificity. We show that this specificity is neither explained by AT-bias nor genome size bias; neither does it originate in the abundance of optimal SD sequences, a typical and significant feature of Firmicutes more thoroughly analysed in our study