Here we determine the complete genomic sequence of the gram negative, gamma-Proteobacterium Vibrio cholerae El Tor N16961 to be 4,033,460 base pairs (bp). The genome consists of two circular chromosomes of 2,961,146 bp and 1,072,314 bp that together encode 3,885 open reading frames. The vast majority of recognizable genes for essential cell functions (such as DNA replication, transcription, translation and cell-wall biosynthesis) and pathogenicity (for example, toxins, surface antigens and adhesins) are located on the large chromosome. In contrast, the small chromosome contains a larger fraction (59%) of hypothetical genes compared with the large chromosome (42%), and also contains many more genes that appear to have origins other than the gamma-Proteobacteria. The small chromosome also carries a gene capture system (the integron island) and host 'addiction' genes that are typically found on plasmids; thus, the small chromosome may have originally been a megaplasmid that was captured by an ancestral Vibrio species. The V. cholerae genomic sequence provides a starting point for understanding how a free-living, environmental organism emerged to become a significant human bacterial pathogen.

Virulence and immunity are poorly understood in Mycobacterium tuberculosis. We sequenced the complete genome of the M. tuberculosis clinical strain CDC1551 and performed a whole-genome comparison with the laboratory strain H37Rv in order to identify polymorphic sequences with potential relevance to disease pathogenesis, immunity, and evolution. We found large-sequence and single-nucleotide polymorphisms in numerous genes. Polymorphic loci included a phospholipase C, a membrane lipoprotein, members of an adenylate cyclase gene family, and members of the PE/PPE gene family, some of which have been implicated in virulence or the host immune response. Several gene families, including the PE/PPE gene family, also had significantly higher synonymous and nonsynonymous substitution frequencies compared to the genome as a whole. We tested a large sample of M. tuberculosis clinical isolates for a subset of the large-sequence and single-nucleotide polymorphisms and found widespread genetic variability at many of these loci. We performed phylogenetic and epidemiological analysis to investigate the evolutionary relationships among isolates and the origins of specific polymorphic loci. A number of these polymorphisms appear to have occurred multiple times as independent events, suggesting that these changes may be under selective pressure. Together, these results demonstrate that polymorphisms among M. tuberculosis strains are more extensive than initially anticipated, and genetic variation may have an important role in disease pathogenesis and immunity.

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The complete genome sequence of Caulobacter crescentus was determined to be 4,016,942 base pairs in a single circular chromosome encoding 3,767 genes. This organism, which grows in a dilute aquatic environment, coordinates the cell division cycle and multiple cell differentiation events. With the annotated genome sequence, a full description of the genetic network that controls bacterial differentiation, cell growth, and cell cycle progression is within reach. Two-component signal transduction proteins are known to play a significant role in cell cycle progression. Genome analysis revealed that the C. crescentus genome encodes a significantly higher number of these signaling proteins (105) than any bacterial genome sequenced thus far. Another regulatory mechanism involved in cell cycle progression is DNA methylation. The occurrence of the recognition sequence for an essential DNA methylating enzyme that is required for cell cycle regulation is severely limited and shows a bias to intergenic regions. The genome contains multiple clusters of genes encoding proteins essential for survival in a nutrient poor habitat. Included are those involved in chemotaxis, outer membrane channel function, degradation of aromatic ring compounds, and the breakdown of plant-derived carbon sources, in addition to many extracytoplasmic function sigma factors, providing the organism with the ability to respond to a wide range of environmental fluctuations. C. crescentus is, to our knowledge, the first free-living α-class proteobacterium to be sequenced and will serve as a foundation for exploring the biology of this group of bacteria, which includes the obligate endosymbiont and human pathogen Rickettsia prowazekii , the plant pathogen Agrobacterium tumefaciens , and the bovine and human pathogen Brucella abortus .

Operon structure is an important organization feature of bacterial genomes. Many sets of genes occur in the same order on multiple genomes; these conserved gene groupings represent candidate operons. This study describes a computational method to estimate the likelihood that such conserved gene sets form operons. The method was used to analyze 34 bacterial and archaeal genomes, and yielded more than 7600 pairs of genes that are highly likely (P: >/= 0.98) to belong to the same operon. The sensitivity of our method is 30-50% for the Escherichia coli genome. The predicted gene pairs are available from our World Wide Web site http://www.tigr.org/tigr-scripts/operons/operons.cgi.

No abstract

As the pace of genome sequencing has accelerated, the need for highly accurate gene prediction systems has grown. Computational systems for identifying genes in prokaryotic genomes have sensitivities of 98-99% or higher (Delcher et al., Nucleic Acids Res., 27, 4636-4641, 1999). These accuracy figures are calculated by comparing the locations of verified stop codons to the predictions. Determining the accuracy of start codon prediction is more problematic, however, due to the relatively small number of start sites that have been confirmed by independent, non-computational methods. Nonetheless, the accuracy of gene finders at predicting the exact gene boundaries at both the 5' and 3' ends of genes is of critical importance for microbial genome annotation, especially in light of the important signaling information that is sometimes found on the 5' end of a protein coding region. In this paper we propose a probabilistic method to improve the accuracy of gene identification systems at finding precise translation start sites. The new system, RBSfinder, is tested on a validated set of genes from Escherichia coli, for which it improves the accuracy of start site locations predicted by computational gene finding systems from the range 67-77% to 90% correct.

We have implemented and tested a frozen density matrix (FDM) approximation to the basic divide and conquer (DC) semiempirical algorithm. Molecular dynamics and Monte Carlo simulations were performed to estimate the advantages of the method. Results were compared to those obtained from the original DC method and the combined quantum mechanical/molecular mechanical (QM/MM) method. We found that the FDM approximation speeds DC calculations up significantly, while only introducing small errors. We also found that the FDM DC scheme performs better that the standard QM/MM approach in terms of defining the electronic and structural properties of the systems studied herein.