7 research outputs found
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The Automatic Selection of TFBS Score Threshold in Comparative Genomics Approach
Reconstruction of transcriptional regulatory networks is one of the major challenges facing the bioinformatics community in view of constantly growing number of complete genomes. The comparative genomics approach has been successfully used for the analysis of the transcriptional regulation of many metabolic systems in various bacterial taxa. The key step in this approach is, given a position weight matrix, find an optimal threshold for the search of potential binding sites in genomes. Here we demonstrate that this problem is tightly bound to a problem of discovering the optimal content of regulon and suggest an approach to solve both problems simultaneousl
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Web-based Tool for Fast and Accurate de novo Inference of Regulons in the Sets of Closely Related Bacterial Genomes
One of the major challenges for the bioinformatics community in view of constantly growing number of complete genomes is providing effective tools to enable high-quality reconstruction of transcriptional regulatory networks (TRN). Definition of a particular TRN includes specification of which transcription factors (TF) bind to TF-binding sites (TFBS) in the promoter regions of which genes and what is the integrated effect of all these TFs on the expression of al these genes. Reconstruction of TRNs helps to better understand the metabolism and functions of bacteria. Among different approaches that are used for TRN reconstruction are an expression data-driven approach, and comparative genomic approaches that are either computing-driven, or subsystem (pathway) -driven. DNA microarrays, reporting gene expression, continue to be an important tool for high-throughput measurements on transcriptional levels, and machine-learning approaches were used to identify TRN (without a TFBS component) from a compendium of microarray expression profiles . However, in many cases the complexity of the interactions between regulons makes it difficult to distinguish between direct and indirect effects on transcription. Availability of a large number of complete genomes opens an opportunity to apply modern approaches of comparative genomics to expand the known regulons to yet uncharacterized organisms and to predict and describe new regulons with high precision
Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the <it>Shewanella</it> genus
<p>Abstract</p> <p>Background</p> <p>Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The <it>Shewanella</it> genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from <it>Escherichia coli</it> and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the <it>in silico</it> reconstruction of transcriptional regulatory networks in bacteria.</p> <p>Results</p> <p>To explore conservation and variations in the <it>Shewanella</it> transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 <it>Shewanella</it> genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and <it>Pseudomonas</it> spp.. Multiple variations in regulatory strategies between the <it>Shewanella</it> spp. and <it>E. coli</it> include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).</p> <p>Conclusions</p> <p>We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 <it>Shewanella</it> genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in <it>S. oneidensis</it> MR-1. Analysis of correlations in gene expression patterns helps to interpret the reconstructed regulatory network. The inferred regulatory interactions will provide an additional regulatory constrains for an integrated model of metabolism and regulation in <it>S. oneidensis</it> MR-1.</p
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Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus.
BackgroundGenome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria.ResultsTo explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).ConclusionsWe tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S. oneidensis MR-1. Analysis of correlations in gene expression patterns helps to interpret the reconstructed regulatory network. The inferred regulatory interactions will provide an additional regulatory constrains for an integrated model of metabolism and regulation in S. oneidensis MR-1