Dissecting network motifs by identifying promoter features that govern differential gene expression

One of the biggest challenges in genomics is the elucidation of the design principles controlling gene expression. Current approaches examine promoter sequences for particular features, such as the presence of binding sites for a transcriptional regulator, and identify recurrent relationships among these features termed network motifs. To define the expression dynamics of a group of genes, the strength of the connections in a network must be specified, and these are determined by the cis-promoter features participating in the regulation. Approaches that homogenize features among promoters (e.g., relying on consensuses to describe the various promoter features) and even across species hamper the discovery of the key differences that distinguish promoters that are co-regulated by the same transcriptional regulator. Thus, we have developed a an approach based on fuzzy logic expressions to analyze proteobacterial genomes for promoter features that is specifically designed to account for the variability in sequence, location and topology intrinsic to differential gene expression. We applied our method to characterize network motifs controlled by the PhoP/PhoQ regulatory system of Escherichia coli and Salmonella enterica serovar Typhimurium. We identify key features that that enable the PhoP protein to produce differential regulation in target genes, reflecting distinct kinetic patterns even for the same type of network motif. These findings could not have been uncovered just by inspecting network architecture. We show that the same approach can be generalized to model other regulatory systems.