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. In this paper, we develop a computer program (CSRNA_FIND) designed to locate potential CsrA-regulating small RNAs in bacteria. Using CSRNA_FIND to search the genomes of bacteria having homologs of CsrA, we identify all the experimentally known CsrA-regulating small RNAs and also make predictions for several novel small RNAs. We have verified experimentally our predictions for two CsrA-regulating small RNAs in Vibrio fischeri. As more genomes are sequenced, CSRNA_FIND can be used to locate the corresponding small RNAs that regulate CsrA homologs. This work thus opens up several avenues of research in understanding the mode of CsrA regulation through small RNAs in bacteria.

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. In this work, we develop a computer code (CSRA_TARGET) implementing this approach, which leads to predictions for several novel targets in Escherichia coli and Pseudomonas aeruginosa. The predicted targets in other bacteria, specifically Salmonella enterica serovar Typhimurium, Pectobacterium carotovorum and Legionella pneumophila, also include global regulators that control virulence in these pathogens, unraveling intricate indirect regulatory roles for CsrA/RsmA. We have experimentally validated four predicted RsmA targets in P. aeruginosa. The sequence-based approach developed in this work can thus lead to several testable predictions for direct targets of CsrA homologs, thereby complementing and accelerating efforts to unravel global regulation by this important family of proteins.

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Regulation by microRNAs (miRNAs) and modulation of miRNA activity are critical components of diverse cellular processes. Recent research has shown that miRNA-based regulation of the tumor suppressor gene PTEN can be modulated by the expression of other miRNA targets acting as competing endogenous RNAs (ceRNAs). However, the key sequence-based features enabling a transcript to act as an effective ceRNA are not well understood and a quantitative model associating statistical significance to such features is currently lacking. To identify and assess features characterizing target recognition by PTEN-regulating miRNAs, we analyze multiple datasets from PAR-CLIP experiments in conjunction with RNA-Seq data. We consider a set of miRNAs known to regulate PTEN and identify high-confidence binding sites for these miRNAs on the 3′ UTR of protein coding genes. Based on the number and spatial distribution of these binding sites, we calculate a set of probabilistic features that are used to make predictions for novel ceRNAs of PTEN. Using a series of experiments in human prostate cancer cell lines, we validate the highest ranking prediction (TNRC6B) as a ceRNA of PTEN. The approach developed can be applied to map ceRNA networks of critical cellular regulators and to develop novel insights into crosstalk between different pathways involved in cancer.