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Comparative genomics and evolution of transcriptional regulons in Proteobacteria
Comparative genomics approaches are broadly used for analysis of transcriptional regulation in bacterial genomes. In this work, we identified binding sites and reconstructed regulons for 33 orthologous groups of transcription factors (TFs) in 196 reference genomes from 21 taxonomic groups of Proteob...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343134/ https://www.ncbi.nlm.nih.gov/pubmed/28348857 http://dx.doi.org/10.1099/mgen.0.000061 |
Sumario: | Comparative genomics approaches are broadly used for analysis of transcriptional regulation in bacterial genomes. In this work, we identified binding sites and reconstructed regulons for 33 orthologous groups of transcription factors (TFs) in 196 reference genomes from 21 taxonomic groups of Proteobacteria. Overall, we predict over 10 600 TF binding sites and identified more than 15 600 target genes for 1896 TFs constituting the studied orthologous groups of regulators. These include a set of orthologues for 21 metabolism-associated TFs from Escherichia coli and/or Shewanella that are conserved in five or more taxonomic groups and several additional TFs that represent non-orthologous substitutions of the metabolic regulators in some lineages of Proteobacteria. By comparing gene contents of the reconstructed regulons, we identified the core, taxonomy-specific and genome-specific TF regulon members and classified them by their metabolic functions. Detailed analysis of ArgR, TyrR, TrpR, HutC, HypR and other amino-acid-specific regulons demonstrated remarkable differences in regulatory strategies used by various lineages of Proteobacteria. The obtained genomic collection of in silico reconstructed TF regulons contains a large number of new regulatory interactions that await future experimental validation. The collection provides a framework for future evolutionary studies of transcriptional regulatory networks in Bacteria. It can be also used for functional annotation of putative metabolic transporters and enzymes that are abundant in the reconstructed regulons. |
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