More robust detection of motifs in coexpressed genes by using phylogenetic information.

BACKGROUND: Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of genes containing the motif versus the number lacking the motif might not be sufficiently high to allow detection by classical motif detection tools. To still recover motifs which are not significantly enriched but still present, we developed a procedure in which we use phylogenetic footprinting to first delineate all potential motifs in each gene. Then we mutually compare all detected motifs and identify the ones that are shared by at least a few genes in the data set as potential candidates. RESULTS: We applied our methodology to a compiled test data set containing known regulatory motifs and to two biological data sets derived from genome wide expression studies. By executing four consecutive steps of 1) identifying conserved regions in orthologous intergenic regions, 2) aligning these conserved regions, 3) clustering the conserved regions containing similar regulatory regions followed by extraction of the regulatory motifs and 4) screening the input intergenic sequences with detected regulatory motif models, our methodology proves to be a powerful tool for detecting regulatory motifs when a low signal to noise ratio is present in the input data set. Comparing our results with two other motif detection algorithms points out the robustness of our algorithm. CONCLUSION: We developed an approach that can reliably identify multiple regulatory motifs lacking a high degree of overrepresentation in a set of coexpressed genes (motifs belonging to sparsely connected hubs in the regulatory network) by exploiting the advantages of using both coexpression and phylogenetic information.

Functional analysis of luxS in the probiotic strain Lactobacillus rhamnosus GG reveals a central metabolic role important for growth and biofilm formation.

Quorum sensing is involved in the regulation of multicellular behavior through communication via small molecules. Given the high number and diversity of the gastrointestinal microbiota, it is postulated that members of this community communicate to coordinate a variety of adaptive processes. AI-2 is suggested to be a universal bacterial signaling molecule synthesized by the LuxS enzyme, which forms an integral part of the activated methyl cycle. We have previously reported that the well-documented probiotic strain Lactobacillus rhamnosus GG, a human isolate, produces AI-2-like molecules. In this study, we identified the luxS homologue of L. rhamnosus GG. luxS seems to be located in an operon with a yxjH gene encoding a putative cobalamin-independent methionine synthase. In silico analysis revealed a methionine-specific T box in the leader sequence of the putative yxjH-luxS operon. However, transcriptional analysis showed that luxS is expressed mainly as a monocistronic transcript. Construction of a luxS knockout mutant confirmed that the luxS gene is responsible for AI-2 production in L. rhamnosus GG. However, this mutation also resulted in pleiotropic effects on the growth of this fastidious strain. Cysteine, pantothenate, folic acid, and biotin could partially complement growth, suggesting a central metabolic role for luxS in L. rhamnosus GG. Interestingly, the luxS mutant also showed a defect in monospecies biofilm formation. Experiments with chemically synthesized (S)-4,5-dihydroxy-2,3-pentanedione, coculture with the wild type, and nutritional complementation suggested that the main cause of this defect has a metabolic nature. Moreover, our data indicate that suppressor mutations are likely to occur in luxS mutants of L. rhamnosus GG. Therefore, results of luxS-related studies should be carefully interpreted.