A motif co-occurrence approach for genome-wide prediction of transcription-factor-binding sites in Escherichia coli

Various computational approaches have been developed for predicting cis-regulatory DNA elements in prokaryotic genomes. We describe a novel method for predicting transcription-factor-binding sites in Escherichia coli. Our method takes advantage of the principle that transcription factors frequently coregulate gene expression, but without requiring prior knowledge of which groups of genes are coregulated. Using position weight matrices for 49 known transcription factors, we examined spacings between pairs of matrix hits. These pairs were assigned probabilities according to the overrepresentation of their separation distance. The functions of many open reading frames (ORFs) downstream from predicted binding sites are unknown, and may correspond to novel regulon members. For five predictions, knockouts with mutated replacements of the predicted binding sites were created in E coli MG1655. Quantitative real-time PCR (RT-PCR) indicates that for each of the knockouts, at least one gene immediately downstream exhibits a statistically significant change in mRNA expression. This approach may be useful in analyzing binding sites in a variety of organisms.