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Nucleic Acids Research 2006 34(12):3484-3493; doi:10.1093/nar/gkl453
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Published online 27 July 2006

Nucleic Acids Research, 2006, Vol. 34, No. 12 3484-3493
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commerical use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article

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

Jonathan Livny*, Anja Brencic1, Stephen Lory1 and Matthew K. Waldor

Department of Molecular Biology and Microbiology, Tufts University School of Medicine and Howard Hughes Medical Institute 136 Harrison Avenue, Boston, MA 02111, USA 1 Department of Microbiology and Molecular Genetics, Harvard Medical School 200 Longwood Avenue, Boston, MA 02115, USA

*To whom correspondence should be addressed. Tel: +1 617 909 8804; Fax: +1 617 636 2723; Email: jonathan.livny{at}tufts.edu

Received March 24, 2006. Revised June 12, 2006. Accepted June 13, 2006.

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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