Comparative genomics and evolution of regulons of the Lacl-family transcription factors

DNA-binding trascription factors (TFs) are essential components of transcriptional regulatory networks in bacteria. Lacl-family TFs (Lacl-TFs) are broadly distributed among certain lineages of bacteria. The majority of characterized Lacl-TFs sense sugar effectors and regulate carbohydrate utilization genes. The comparative genomics approaches enable in silico identification of TF-binding sites and reulon reconstruction. To study the function and evolution of Lacl-TFs, we performed genomics-based reconstruction and comparative analysis of their regulations. For over 1300 Lacl-TFs from over 270 bacterial genomies, we predicted their congnated DNA-binding mostifs and identified taged genes. Using the genome context and metabolic subsystem analyses of reconstructed teguions, we tentatively assigned funtional roles and predicted condidtate effectors fo 78 and 67% of the analyzed Lacl-TFs, respectively. Nearly 90% of the studid Lacl-TFs are local regulators of sugar utilization pathways, wherreas the remaining 125 global regulators control large and diverse sets of metabolic genes. The golobal Lacl-TFs include the previously known regulators CcpA in Firmicutes, FruR in Enterobacteria, and PurR in Gammaproteobacteria, as well as the three novel regulator-GluR, GapR, and PckR-that are predicted to control the central carbohydrate metabolism in three lieages of Alphaproteobacteria. Phylogenetic analysis of regulators combined with the reconstructed regulons provides a model of evolutionary diversitication of the Lacl protein family. The obtained genomic collection of in silico reconstructed Lacl-TF regulons n bacteria is available in the RegPrecise database (http://regprecise.lbl.gov.) It provides a framework for future structural and functional classification of the Lacl 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.