Computer analysis of regulatory signals in complete bacterial genomes. PurR binding sites

Recognition of transcription regulatory sites is one of the most difficult problems of computational molecular biology. Small sample size and weak con servativity of signals in most cases do not allow for construction of relia ble recognition rules. Here we suggest a new approach to this problem based on simultaneous analysis of several related genomes. Therewith we assume t hat groups of coregulated genes are evolutionarily stable. Thus we choose i n each genome a set of genes having strong candidate sites in regulatory re gions and then select families of related genes. By the assumption, these f amilies are subject to the considered regulation. This approach was applied to analysis of purine regulons in Escherichia coil and Haemophilus influen zae. Transcription of these genes is regulated by PurR. We have identified PurR binding sites in the genome of H. influenzae and found a new family of E. coli and H. influenzae transport proteins regulated by PurR.