Abundant oligonucleotides common to most bacteria

DistAMo: A Web-Based Tool to Characterize DNA-Motif Distribution on Bacterial Chromosomes

Short DNA motifs are involved in a multitude of functions such as for example chromosome segregation, DNA replication or mismatch repair. Distribution of such motifs is often not random and the specific chromosomal pattern relates to the respective motif function. Computational approaches which quantitatively assess such chromosomal motif patterns are necessary. Here we present a new computer tool DistAMo (Distribution Analysis of DNA Motifs). The algorithm uses codon redundancy to calculate the relative abundance of short DNA motifs from single genes to entire chromosomes. Comparative genomics analyses of the GATC-motif distribution in γ-proteobacterial genomes using DistAMo revealed that (i) genes beside the replication origin are enriched in GATCs, (ii) genome-wide GATC distribution follows a distinct pattern, and (iii) genes involved in DNA replication and repair are enriched in GATCs. These features are specific for bacterial chromosomes encoding a Dam methyltransferase. The new software is available as a stand-alone or as an easy-to-use web-based server version at http://www.computational.bio.uni-giessen.de/distamo.

The human gut microbiome and its dysfunctions through the meta-omics prism

The microorganisms inhabiting the human gut are abundant (10(14) cells) and diverse (approximately 500 species per individual). It is now acknowledged that the microbiota has coevolved with its host to achieve a symbiotic relationship, leading to physiological homeostasis. The gut microbiota ensures vital functions, such as food digestibility, maturation of the host immune system, and protection against pathogens. Over the last few decades, the gut microbiota has also been associated with numerous diseases, such as inflammatory bowel disease, irritable bowel syndrome, obesity, and metabolic diseases. In most of these pathologies, a microbial dysbiosis has been found, indicating shifts in the taxonomic composition of the gut microbiota and changes in its functionality. Our understanding of the influence of the gut microbiota on human health is still growing. Working with microorganisms residing in the gut is challenging since most of them are anaerobic and a vast majority (approximately 75%) are uncultivable to date. Recently, a wide range of new approaches (meta-omics) has been developed to bypass the uncultivability and reveal the intricate mechanisms that sustain gut microbial homeostasis. After a brief description of these approaches (metagenomics, metatranscriptomics, metaproteomics, and metabolomics), this review will discuss the importance of considering the gut microbiome as a structured ecosystem and the use of meta-omics to decipher dysfunctions of the gut microbiome in diseases.

Co-evolution of segregation guide DNA motifs and the FtsK translocase in bacteria: identification of the atypical Lactococcus lactis KOPS motif

Bacteria use the global bipolarization of their chromosomes into replichores to control the dynamics and segregation of their genome during the cell cycle. This involves the control of protein activities by recognition of specific short DNA motifs whose orientation along the chromosome is highly skewed. The KOPS motifs act in chromosome segregation by orienting the activity of the FtsK DNA translocase towards the terminal replichore junction. KOPS motifs have been identified in γ-Proteobacteria and in Bacillus subtilis as closely related G-rich octamers. We have identified the KOPS motif of Lactococcus lactis, a model bacteria of the Streptococcaceae family harbouring a compact and low GC% genome. This motif, 5′-GAAGAAG-3, was predicted in silico using the occurrence and skew characteristics of known KOPS motifs. We show that it is specifically recognized by L. lactis FtsK in vitro and controls its activity in vivo. L. lactis KOPS is thus an A-rich heptamer motif. Our results show that KOPS-controlled chromosome segregation is conserved in Streptococcaceae but that KOPS may show important variation in sequence and length between bacterial families. This suggests that FtsK adapts to its host genome by selecting motifs with convenient occurrence frequencies and orientation skews to orient its activity.

In silico method to predict functional similarity between two RecA orthologs

RecA is a highly conserved bacterial protein that plays crucial roles in many cellular processes and hence is a potential target in the chemotherapy of bacterial infections. An understanding of the functional similarity between RecA proteins from different bacterial species should yield further insights into the biochemistry of RecA protein, along with the potential for new approaches to facilitate the improvement of RecA-targeted drugs. In this technical note, the authors present an in silico method based on tri-oligonucleotide usage correlations (TOUC) to predict the functional similarity between two RecA orthologs. The TOUC values analyzed in this study are in good agreement with the available experimental results. This method should prove useful in guiding future experimental efforts aimed at furthering our understanding of the biochemistry of RecA proteins and subsequent development of new drugs that modulate RecA biological activities in bacteria.

High-quality annotation of promoter regions for 913 bacterial genomes

MOTIVATION

The number of bacterial genomes being sequenced is increasing very rapidly and hence, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The present work addresses this requirement and presents a generic method applicable across organisms.

RESULTS

Relative stability of the DNA double helical sequences has been used to discriminate promoter regions from non-promoter regions. Based on the difference in stability between neighboring regions, an algorithm has been implemented to predict promoter regions on a large scale over 913 microbial genome sequences. The average free energy values for the promoter regions as well as their downstream regions are found to differ, depending on their GC content. Threshold values to identify promoter regions have been derived using sequences flanking a subset of translation start sites from all microbial genomes and then used to predict promoters over the complete genome sequences. An average recall value of 72% (which indicates the percentage of protein and RNA coding genes with predicted promoter regions assigned to them) and precision of 56% is achieved over the 913 microbial genome dataset.

AVAILABILITY

The binary executable for 'PromPredict' algorithm (implemented in PERL and supported on Linux and MS Windows) and the predicted promoter data for all 913 microbial genomes are available at http://nucleix.mbu.iisc.ernet.in/prombase/.