Insights into horizontal acquisition patterns of dormancy and reactivation regulon genes in mycobacterial species using a partitioning-based framework

Horizontal Gene Transfer (HGT) events, initially thought to be rare in Mycobacterium tuberculosis, have recently been shown to be involved in the acquisition of virulence operons in M. tuberculosis. We have developed a new partitioning framework based HGT prediction algorithm, called Grid3M, and applied the same for the prediction of HGTs in Mycobacteria. Validation and testing using simulated and real microbial genomes indicated better performance of Grid3M as compared with other widely used HGT prediction methods. Specific analysis of the genes belonging to dormancy/reactivation regulons across 14 mycobacterial genomes indicated that horizontal acquisition is specifically restricted to important accessory proteins. The results also revealed Burkholderia species to be a probable source of HGT genes belonging to these regulons. The current study provides a basis for similar analyses investigating the functional/evolutionary aspects of HGT genes in other pathogens. A database of Grid3M predicted HGTs in completely sequenced genomes is available at https://metagenomics.atc.tcs.com/Grid3M/ .     

Predicting regulons and their cis-regulatory motifs by comparative genomics

We have combined and compared three techniques for predicting functional interactions based on comparative genomics (methods based on conserved operons, protein fusions and correlated evolution) and optimized these methods to predict coregulated sets of genes in 24 complete genomes, including Saccharomyces cerevisiae, Caernorhabditis elegans and 22 prokaryotes. The method based on conserved operons was the most useful for this purpose. Upstream regions of the genes comprising these predicted regulons were then used to search for regulatory motifs in 22 prokaryotic genomes using the motif-discovery program AlignACE. Many significant upstream motifs, including five known Escherichia coli regulatory motifs, were identified in this manner. The presence of a significant regulatory motif was used to refine the members of the predicted regulons to generate a final set of predicted regulons that share significant regulatory elements.     

Comparative genomics analysis of NtcA regulons in cyanobacteria: regulation of nitrogen assimilation and its coupling to photosynthesis

We have developed a new method for prediction of cis-regulatory binding sites and applied it to predicting NtcA regulated genes in cyanobacteria. The algorithm rigorously utilizes concurrence information of multiple binding sites in the upstream region of a gene and that in the upstream regions of its orthologues in related genomes. A probabilistic model was developed for the evaluation of prediction reliability so that the prediction false positive rate could be well controlled. Using this method, we have predicted multiple new members of the NtcA regulons in nine sequenced cyanobacterial genomes, and showed that the false positive rates of the predictions have been reduced on an average of 40-fold compared to the conventional methods. A detailed analysis of the predictions in each genome showed that a significant portion of our predictions are consistent with previously published results about individual genes. Intriguingly, NtcA promoters are found for many genes involved in various stages of photosynthesis. Although photosynthesis is known to be tightly coordinated with nitrogen assimilation, very little is known about the underlying mechanism. We postulate for the fist time that these genes serve as the regulatory points to orchestrate these two important processes in a cyanobacterial cell.     

Exploration and grading of possible genes from 183 bacterial strains by a common protocol to identification of new genes: Gene Trek in Prokaryote Space (GTPS).

A large number of complete microorganism genomes has been sequenced and submitted to the public database and then incorporated into our complete genome database, Genome Information Broker (GIB, http://gib.genes.nig.ac.jp/). However, when comparative genomics is carried out, researchers must be aware that there are protein-coding genes not confirmed by homology or motif search and that reliable protein-coding genes are missing. Therefore, we developed a protocol (Gene Trek in Prokaryote Space, GTPS) for finding possible protein-coding genes in bacterial genomes. GTPS assigns a degree of reliability to predicted protein-coding genes. We first systematically applied the protocol to the complete genomes of all 123 bacterial species and strains that were publicly available as of July 2003, and then to those of 183 species and strains available as of September 2004. We found a number of incorrect genes and several new ones in the genome data in question. We also found a way to estimate the total number of orthologous genes in the bacterial world.     

Selection for unequal densities of sigma70 promoter-like signals in different regions of large bacterial genomes

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.