A sequence-based approach for prediction of CsrA/RsmA targets in bacteria with experimental validation in Pseudomonas aeruginosa.

CsrA/RsmA homologs are an extensive family of ribonucleic acid (RNA)-binding proteins that function as global post-transcriptional regulators controlling important cellular processes such as secondary metabolism, motility, biofilm formation and the production and secretion of virulence factors in diverse bacterial species. While direct messenger RNA binding by CsrA/RsmA has been studied in detail for some genes, it is anticipated that there are numerous additional, as yet undiscovered, direct targets that mediate its global regulation. To assist in the discovery of these targets, we propose a sequence-based approach to predict genes directly regulated by these regulators.

Computational approaches for the discovery of bacterial small RNAs.

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 experiments, have played an important role in the discovery of these sRNAs. In this article, we first give an overview of different computational approaches for genome-wide prediction of sRNAs.

Prediction of CsrA-regulating small RNAs in bacteria and their experimental verification in Vibrio fischeri.

The role of small RNAs as critical components of global regulatory networks has been highlighted by several recent studies. An important class of such small RNAs is represented by CsrB and CsrC of Escherichia coli, which control the activity of the global regulator CsrA. Given the critical role played by CsrA in several bacterial species, an important problem is the identification of CsrA-regulating small RNAs.