Defining the Plasticity of Transcription Factor Binding Sites by Deconstructing DNA Consensus Sequences: The PhoP-Binding Sites among Gamma/Enterobacteria

Abstract

Transcriptional regulators recognize specific DNA sequences. Because these sequences are embedded in the background of genomic DNA, it is hard to identify the key cis-regulatory elements that determine disparate patterns of gene expression. The detection of the intra- and inter-species differences among these sequences is crucial for understanding the molecular basis of both differential gene expression and evolution. Here, we address this problem by investigating the target promoters controlled by the DNA-binding PhoP protein, which governs virulence and Mg ²⁺ homeostasis in several bacterial species. PhoP is particularly interesting; it is highly conserved in different gamma/enterobacteria, regulating not only ancestral genes but also governing the expression of dozens of horizontally acquired genes that differ from species to species. Our approach consists of decomposing the DNA binding site sequences for a given regulator into families of motifs ( i.e., termed submotifs) using a machine learning method inspired by the “ Divide & Conquer” strategy. By partitioning a motif into sub-patterns, computational advantages for classification were produced, resulting in the discovery of new members of a regulon, and alleviating the problem of distinguishing functional sites in chromatin immunoprecipitation and DNA microarray genome-wide analysis. Moreover, we found that certain partitions were useful in revealing biological properties of binding site sequences, including modular gains and losses of PhoP binding sites through evolutionary turnover events, as well as conservation in distant species. The high conservation of PhoP submotifs within gamma/enterobacteria, as well as the regulatory protein that recognizes them, suggests that the major cause of divergence between related species is not due to the binding sites, as was previously suggested for other regulators. Instead, the divergence may be attributed to the fast evolution of orthologous target genes and/or the promoter architectures resulting from the interaction of those binding sites with the RNA polymerase.

Author Summary

The diversity of life forms frequently results from small changes in the regulatory systems that control gene expression. These changes often occur in cis-elements relevant to transcriptional regulation that are difficult to discern, as they are short, and are embedded in a genomic background that does not play a direct role in gene expression, or that consists of disparate sequences such as those from horizontally acquired genes. We devised a machine-learning method that significantly improves the identification of these elements, uncovering families of binding site motifs ( i.e., “submotifs”), instead of a single consensus recognized by a transcriptional regulator. The method can also incorporate other cis-elements to fully describe promoter architectures. Far from being just a computational convenience, ChIP-chip and custom expression microarray experiments for the PhoP regulon validated the high conservation and modular evolution of submotifs throughout the gamma/enterobacteria. This suggests that the major cause of divergence between species is not due to the binding sites, as was previously suggested for other regulators. Instead, the divergence may be attributed to the fast evolution of orthologous and horizontally-acquired target genes, and/or to the uncovered promoter architectures governing the interaction between the regulator and the RNA polymerase.