In silico analysis reveals substantial variability in the gene contents of the gamma proteobacteria LexA-regulon

Abstract

Motivation: Motif-prediction algorithm capabilities for the analysis of bacterial regulatory networks and the prediction of new regulatory sites can be greatly enhanced by the use of comparative genomics approaches. In this study, we make use of a consensus-building algorithm and comparative genomics to conduct an in-depth analysis of the LexA-regulon of gamma proteobacteria, and we use the inferred results to study the evolution of this regulatory network and to examine the usefulness of the control sequences and gene contents of regulons in phylogenetic analysis.

Results: We show, for the first time, the substantial heterogeneity that the LexA-regulon of gamma proteobacteria displays in terms of gene content and we analyze possible branching points in its evolution. We also demonstrate the feasibility of using regulon-related information to derive sound phylogenetic inferences.