Identification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNAPredict2

被引:142
作者
Livny, Jonathan
Brencic, Anja
Lory, Stephen
Waldor, Matthew K.
机构
[1] Tufts Univ, Sch Med, Dept Mol Biol & Microbiol, Boston, MA 02111 USA
[2] Howard Hughes Med Inst, Boston, MA 02111 USA
[3] Harvard Univ, Sch Med, Dept Microbiol & Mol Genet, Boston, MA 02115 USA
关键词
D O I
10.1093/nar/gkl453
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
sRNAs are small, non-coding RNA species that control numerous cellular processes. Although it iswidely accepted that sRNAs are encoded by most if not all bacteria, genome-wide annotations for sRNA-encoding genes have been conducted in only a few of the nearly 300 bacterial species sequenced to date. To facilitate the efficient annotation of bacterial genomes for sRNA-encoding genes, we developed a program, sRNAPredict2, that identifies putative sRNAs by searching for co-localization of genetic features commonly associated with sRNA-encoding genes. Using sRNAPredict2, we conducted genome-wide annotations for putative sRNA-encoding genes in the intergenic regions of 11 diverse pathogens. In total, 2759 previously unannotated candidate sRNA loci were predicted. There was considerable range in the number of sRNAs predicted in the different pathogens analyzed, raising the possibility that there are species-specific differences in the reliance on sRNA-mediated regulation. Of 34 previously unannotated sRNAs predicted in the opportunistic pathogen Pseudomonas aeruginosa, 31 were experimentally tested and 17 were found to encode sRNA transcripts. Our findings suggest that numerous genes have been missed in the current annotations of bacterial genomes and that, by using improved bioinformatic approaches and tools, much remains to be discovered in 'intergenic' sequences.
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页码:3484 / 3493
页数:10
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