Computer analysis of transcription regulatory patterns in completely sequenced bacterial genomes

Recognition of transcription regulation sites (operators) is a hard problem in computational molecular biology. In mast cases, small sample site and l ow degree of sequence conservation preclude the construction of reliable re cognition rules. We suggest an approach to this problem based on simultaneo us analysis of several related genomes. It appears that as long as a gene c oding for a transcription regulator is conserved in the compared bacterial genomes, the regulation of the respective group of genes (regulons) also te nds to be maintained. Thus a gene can be confidently predicted to belong to a particular regulon in case not only itself, but also its orthologs in ot her genomes have candidate operators in the regulatory regions. This provid es for a greater sensitivity of operator identification as even relatively weak signals are likely to be functionally relevant when conserved. We use this approach to analyze the purine (PurR), arginine (ArgR) and aromatic am ino acid (TrpR and TyrR) regulons of Escherichia coli and Haemophilus influ enzae. Candidate binding sites in regulatory regions of the respective H,in fluenzae genes are identified, a new family of purine transport proteins pr edicted to belong to the PurR regulon is described, and probable regulation of arginine transport by ArgR is demonstrated. Differences in the regulati on of some orthologous genes in E,coli and H.influenzae, in particular the apparent lack of the autoregulation of the purine repressor gene in H.influ enzae, are demonstrated.