The functional landscape bound to the transcription factors of Escherichia coli K-12. (October 2015) - Pérez-Rueda, Ernesto; Tenorio-Salgado, Silvia; Huerta-Saquero, Alejandro; Balderas-Martínez, Yalbi I.; Moreno-Hagelsieb, Gabriel
Graphical abstract: DNA-binding transcription factors of Escherichia coli K-12 were analyzed to evaluate its structural and functional diversity. Highlights: DNA-binding transcription factors were searched in the complete genome of Escherichia coli K-12 by sequence comparisons. TFs deposited in RegulonDB were used as seeds to identify hypothetical TFs. Duplication events increase the size of the regulatory network in this bacterium. Potential target genes were predicted to uncharacterized TFs. Probable regulatory interactions were identified between well-known and uncharacterized TFs. Abstract: Motivated by the experimental evidences accumulated in the last ten years and based on information deposited in RegulonDB, literature look up, and sequence analysis, we analyze the repertoire of 304 DNA-binding Transcription factors (TFs) in Escherichia coli K-12. These regulators were grouped in 78 evolutionary families and are regulating almost half of the total genes in this bacterium. In structural terms, 60% of TFs are composed by two-domains, 30% are monodomain, and 10% three- and four-structural domains. As previously noticed, the most abundant DNA-binding domain corresponds to the winged helix-turn-helix, with few alternative DNA-binding structures, resembling the hypothesis of successful protein structures with the emergence of new ones at low scales. In summary, we identified and described the characteristics associated to the DNA-binding TF in E. coli K-12. We also identified twelve functional modules based on a co-regulated gene matrix. Finally, diverse regulons were predicted based on direct associations between the TFs and potential regulated genes. This analysis should increase our knowledge about the gene regulation in the bacterium E. coli K-12, and provide more additional clues for comprehensive modelling of transcriptional regulatory networks in other bacteria.