Abstract
DNA-binding transcription factors (TFs) are essential components of transcriptional regulatory networks in bacteria. LacI-family TFs (LacI-TFs) are broadly distributed among certain lineages of bacteria. The majority of characterized LacI-TFs sense sugar effectors and regulate carbohydrate utilization genes. The comparative genomics approaches enable in silico identification of TF-binding sites and regulon reconstruction. To study the function and evolution of LacI-TFs, we performed genomics-based reconstruction and comparative analysis of their regulons. For over 1300 LacI-TFs from over 270 bacterial genomes, we predicted their cognate DNA-binding motifs and identified target genes. Using the genome context and metabolic subsystem analyses of reconstructed regulons, we tentatively assigned functional roles and predicted candidate effectors for 78 and 67% of the analyzed LacI-TFs, respectively. Nearly 90% of the studied LacI-TFs are local regulators of sugar utilization pathways, whereas the remaining 125 global regulators control large and diverse sets of metabolic genes. The global LacI-TFs include the previously known regulators CcpA in Firmicutes, FruR in Enterobacteria, and PurR in Gammaproteobacteria, as well as the three novel regulators—GluR, GapR, and PckR—that are predicted to control the central carbohydrate metabolism in three lineages of Alphaproteobacteria. Phylogenetic analysis of regulators combined with the reconstructed regulons provides a model of evolutionary diversification of the LacI protein family. The obtained genomic collection of in silico reconstructed LacI-TF regulons in bacteria is available in the RegPrecise database (http://regprecise.lbl.gov). It provides a framework for future structural and functional classification of the LacI protein family and identification of molecular determinants of the DNA and ligand specificity. The inferred regulons can be also used for functional gene annotation and reconstruction of sugar catabolic networks in diverse bacterial lineages.
Highlights
Evolution of regulatory interactions in bacteria can be approached from three directions
The second approach is to consider a taxon of a relatively low level and to use comparative genomics to predict as many regulatory interactions as possible. This has been done for γ-Proteobacteria from the Shewanella genus (Rodionov et al, 2011); Firmicutes closely related to Bacillus subtilis (Leyn et al, 2013) and Staphylococcus aureus (Ravcheev et al, 2011); two families of lactic acid bacteria from the Lactobacillales order (Ravcheev et al, 2013b); hyperthermophilic bacteria related to Thermotoga maritima (Rodionov et al, 2013); human gut habitant Bacteroides thetaiotaomicron; and related organisms (Ravcheev et al, 2013a)
The comparative genomics workflow for regulon reconstruction implemented in the RegPredict Web server (Novichkov et al, 2010) and the RegPrecise database (Novichkov et al, 2013) includes three steps: (i) selection of a taxonomic group of related bacteria; (ii) selection of a subset of diverse genomes that represent a given group; and (iii) reconstruction of regulons in the selected genomes
Summary
Evolution of regulatory interactions in bacteria can be approached from three directions. The second approach is to consider a taxon of a relatively low level (genus or family) and to use comparative genomics to predict as many regulatory interactions as possible. This has been done for γ-Proteobacteria from the Shewanella genus (Rodionov et al., 2011); Firmicutes closely related to Bacillus subtilis (Leyn et al, 2013) and Staphylococcus aureus (Ravcheev et al, 2011); two families of lactic acid bacteria from the Lactobacillales order (Ravcheev et al, 2013b); hyperthermophilic bacteria related to Thermotoga maritima (Rodionov et al, 2013); human gut habitant Bacteroides thetaiotaomicron; and related organisms (Ravcheev et al, 2013a). An important side product of such studies is functional annotation of hypothetical proteins by assigning them, via co-regulation, to known metabolic pathways and other functional subsystems (Rodionov, 2007; Gelfand and Rodionov, 2008)
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