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ABSTRACT: Bacterial small RNAs (sRNAs) are a class of structural RNAs that often regulate mRNA targets via post-transcriptional base pair interactions. We determined features that discriminate functional from non-functional interactions and assessed the influence of these features on genome-wide target predictions. For this purpose, we compiled a set of 71 experimentally verified sRNA-target pairs from Escherichia coli and Salmonella enterica. Furthermore, we collected full-length 5' untranslated regions by using genome-wide experimentally verified transcription start sites. Only interaction sites in sRNAs, but not in targets, show significant sequence conservation. In addition to this observation, we found that the base pairing between sRNAs and their targets is not conserved in general across more distantly related species. A closer inspection of RybB and RyhB sRNAs and their targets revealed that the base pairing complementarity is only conserved in a small subset of the targets. In contrast to conservation, accessibility of functional interaction sites is significantly higher in both sRNAs and targets in comparison to non-functional sites. Based on the above observations, we successfully used the following constraints to improve the specificity of genome-wide target predictions: the region of interaction initiation must be located in (1) highly accessible regions in both interaction partners and (2) unstructured conserved sRNA regions derived from reliability profiles of multiple sRNA alignments. Aligned sequences of homologous sRNAs, functional and non-functional targets, and a supplementary document with supplementary tables, figures and references are available at http://www. bioinf.uni-freiburg.de/Supplements/srna-interact-feat.
RNA biology 07/2012; 9(7):954-65. · 5.56 Impact Factor
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ABSTRACT: Quorum sensing, a cell-to-cell communication system based on small signal molecules, is employed by the human pathogen Pseudomonas aeruginosa to regulate virulence and biofilm development. Moreover, regulation by small trans-encoded RNAs has become a focal issue in studies of virulence gene expression of bacterial pathogens. In this study, we have identified the small RNA PhrS as an activator of PqsR synthesis, one of the key quorum-sensing regulators in P. aeruginosa. Genetic studies revealed a novel mode of regulation by a sRNA, whereby PhrS uses a base-pairing mechanism to activate a short upstream open reading frame to which the pqsR gene is translationally coupled. Expression of phrS requires the oxygen-responsive regulator ANR. Thus, PhrS is the first bacterial sRNA that provides a regulatory link between oxygen availability and quorum sensing, which may impact on oxygen-limited growth in P. aeruginosa biofilms.
Molecular Microbiology 03/2011; 80(4):868-85. · 5.01 Impact Factor
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ABSTRACT: Predicting RNA-RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA-RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA-RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences.
PETcofold's ability to predict RNA-RNA interactions was evaluated on a carefully curated dataset of 32 bacterial small RNAs and their targets, which was manually extracted from the literature. For evaluation of both RNA-RNA interaction and structure prediction, we were able to extract only a few high-quality examples: one vertebrate small nucleolar RNA and four bacterial small RNAs. For these we show that the prediction can be improved by our comparative approach. Furthermore, PETcofold was evaluated on controlled data with phylogenetically simulated sequences enriched for covariance patterns at the interaction sites. We observed increased performance with increased amounts of covariance.
The program PETcofold is available as source code and can be downloaded from http://rth.dk/resources/petcofold.
Bioinformatics 11/2010; 27(2):211-9. · 5.47 Impact Factor
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ABSTRACT: Small non-coding RNAs (sRNAs) are key players in prokaryotic metabolic circuits, allowing the cell to adapt to changing environmental conditions. Regulatory interference by sRNAs in cellular metabolism is often facilitated by the Sm-like protein Hfq. A search for novel sRNAs in A. baylyi intergenic regions was performed by a biocomputational screening. One candidate, Aar, encoded between trpS and sucD showed Hfq dependency in Northern blot analysis. Aar was expressed strongly during stationary growth phase in minimal medium; in contrast, in complex medium, strongest expression was in the exponential growth phase. Whereas over-expression of Aar in trans did not affect bacterial growth, seven mRNA targets predicted by two in silico approaches were upregulated in stationary growth phase. All seven mRNAs are involved in A. baylyi amino acid metabolism. A putative binding site for Lrp, the global regulator of branched-chain amino acids in E. coli, was observed within the aar gene. Both facts imply an Aar participation in amino acid metabolism.
Archives of Microbiology 09/2010; 192(9):691-702. · 1.43 Impact Factor
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ABSTRACT: The Freiburg RNA tools web server integrates three tools for the advanced analysis of RNA in a common web-based user interface. The tools IntaRNA, ExpaRNA and LocARNA support the prediction of RNA-RNA interaction, exact RNA matching and alignment of RNA, respectively. The Freiburg RNA tools web server and the software packages of the stand-alone tools are freely accessible at http://rna.informatik.uni-freiburg.de.
Nucleic Acids Research 05/2010; 38(Web Server issue):W373-7. · 8.03 Impact Factor
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ABSTRACT: Many regulatory non-coding RNAs (ncRNAs) function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting these RNA interactions is essential for functional studies of putative ncRNAs or for the design of artificial RNAs. Many ncRNAs show clear signs of undergoing compensating base changes over evolutionary time. Here, we postulate that a non-negligible part of the existing RNA-RNA interactions contain preserved but covarying patterns of interactions.
We present a novel method that takes compensating base changes across the binding sites into account. The algorithm works in two steps on two pre-generated multiple alignments. In the first step, individual base pairs with high reliability are found using the PETfold algorithm, which includes evolutionary and thermodynamic properties. In step two (where high reliability base pairs from step one are constrained as unpaired), the principle of cofolding is combined with hierarchical folding. The final prediction of intra- and inter-molecular base pairs consists of the reliabilities computed from the constrained expected accuracy scoring, which is an extended version of that used for individual multiple alignments.
We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNA-RNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach.
Algorithms for Molecular Biology 01/2010; 5:22. · 1.35 Impact Factor
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ABSTRACT: MOTIVATION: Prochlorococcus possesses the smallest genome of all sequenced photoautotrophs. Although the number of regulatory proteins in the genome is very small, the relative number of small regulatory RNAs is comparable with that of other bacteria. The compact genome size of Prochlorococcus offers an ideal system to search for targets of small RNAs (sRNAs) and to refine existing target prediction algorithms. RESULTS: Target predictions for the cyanobacterial sRNA Yfr1 were carried out with INTARNA in Prochlorococcus MED4. The ultraconserved Yfr1 sequence motif was defined as the putative interaction seed. To study the impact of Yfr1 on its predicted mRNA targets, a reporter system based on green fluorescent protein (GFP) was applied. We show that Yfr1 inhibits the translation of two predicted targets. We used mutation analysis to confirm that Yfr1 directly regulates its targets by an antisense interaction sequestering the ribosome binding site, and to assess the importance of interaction site accessibility.
Bioinformatics 10/2009; 26(1):1-5. · 5.47 Impact Factor
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ABSTRACT: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches.
We introduce INTARNA, a new general and fast approach to the prediction of RNA-RNA interactions incorporating accessibility of target sites as well as the existence of a user-definable seed. We successfully applied INTARNA to the prediction of bacterial sRNA targets and determined the exact locations of the interactions with a higher accuracy than competing programs.
http://www.bioinf.uni-freiburg.de/Software/
Bioinformatics 11/2008; 24(24):2849-56. · 5.47 Impact Factor
