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PubMed2000

Microbial genome analysis: insights into virulence, host adaptation and evolution.

Genome analysis of microbial pathogens has provided unique insights into their virulence, host adaptation and evolution. Common themes have emerged, including lateral gene transfer among enteric pathogens, genome decay among obligate intracellular pathogens and antigenic variation among mucosal pathogens. The advent of post-genomic approaches and the sequencing of the human genome will enable scientists to investigate the complex and dynamic interplay between host and pathogen. This wealth of information will catalyse the development of new intervention strategies to reduce the burden of microbial-related disease.

Adaptation, Physiological↗
PubMed2005

Global divergence of microbial genome sequences mediated by propagating fronts.

We model the competition between homologous recombination and point mutation in microbial genomes, and present evidence for two distinct phases, one uniform, the other genetically diverse. Depending on the specifics of homologous recombination, we find that global sequence divergence can be mediated by fronts propagating along the genome, whose characteristic signature on genome structure is elucidated, and apparently observed in closely related Bacillus strains. Front propagation provides an emergent, generic mechanism for microbial "speciation," and suggests a classification of microorganisms on the basis of their propensity to support propagating fronts.

Bacillus↗
PubMed2003

MBGD: microbial genome database for comparative analysis.

MBGD is a workbench system for comparative analysis of completely sequenced microbial genomes. The central function of MBGD is to create an orthologous gene classification table using precomputed all-against-all similarity relationships among genes in multiple genomes. In MBGD, an automated classification algorithm has been implemented so that users can create their own classification table by specifying a set of organisms and parameters. This feature is especially useful when the user's interest is focused on some taxonomically related organisms. The created classification table is stored into the database and can be explored combining with the data of individual genomes as well as similarity relationships among genomes. Using these data, users can carry out comparative analyses from various points of view, such as phylogenetic pattern analysis, gene order comparison and detailed gene structure comparison. MBGD is accessible at http://mbgd.genome.ad.jp/.

Algorithms↗
PubMed2001

Microbial genomes: dealing with diversity.

We have now complete genome sequences of several pairs of closely related prokaryotes (conspecific strains or congeneric species). Surprisingly, even strains of the same species can differ by as much as 20% in gene content. Conceptual and methodological approaches for dealing with such diversity are now being developed, and should transform microbial genomics.

Evolution, Molecular↗
PubMed2006

Microbial genomics and drug discovery: exploring innovative routes of drug discovery in the postgenomic era.

The impact of microbial genomics on the development of new antibiotics has been surprisingly minimal to date. Although many potential targets for novel antimicrobials have been identified through genomics, the identification of inhibitory molecules that also possess drug-like properties has been a severe challenge. This feature will discuss several possible confounding issues and solution paths in the search for new antibiotics that are active against the threat of drug-resistant pathogens.

Anti-Bacterial Agents↗
PubMed2003

Evolutionary implications of microbial genome tetranucleotide frequency biases.

We compared nucleotide usage pattern conservation for related prokaryotes by examining the representation of DNA tetranucleotide combinations in 27 representative microbial genomes. For each of the organisms studied, tetranucleotide usage departures from expectations (TUD) were shared between related organisms using both Markov chain analysis and a zero-order Markov method. Individual strains, multiple chromosomes, plasmids, and bacteriophages share TUDs within a species. TUDs varied between coding and noncoding DNA. Grouping prokaryotes based on TUD profiles resulted in relationships with important differences from those based on 16S rRNA phylogenies, which may reflect unequal rates of evolution of nucleotide usage patterns following divergence of particular organisms from a common ancestor. By both symmetrical tree distance and likelihood analysis, phylogenetic trees based on TUD profiles demonstrate a level of congruence with 16S rRNA trees similar to that of both RpoA and RecA trees. Congruence of these trees indicates that there exists phylogenetic signal in TUD patterns, most prominent in coding region DNA. Because relationships demonstrated in TUD-based analyses utilize whole genomes, they should be considered complementary to phylogenies based on single genetic elements, such as 16S rRNA.

Chromosome Mapping↗
PubMed2004

In search of RNase P RNA from microbial genomes.

A simple procedure has been developed to quickly retrieve and validate the DNA sequence encoding the RNA subunit of ribonuclease P (RNase P RNA) from microbial genomes. RNase P RNA sequences were identified from 94% of bacterial and archaeal complete genomes where previously no RNase P RNA was annotated. A sequence was found in camelpox virus, highly conserved in all orthopoxviruses (including smallpox virus), which could fold into a putative RNase P RNA in terms of conserved primary features and secondary structure. New structure features of RNase P RNA that enable one to distinguish bacteria from archaea and eukarya were found. This RNA is yet another RNA that can be a molecular criterion to divide the living world into three domains (bacteria, archaea, and eukarya). The catalytic center of this RNA, and its detection from some environmental whole genome shotgun sequences, is also discussed.

Base Sequence↗
PubMed2005

Specialized microbial databases for inductive exploration of microbial genome sequences.

BACKGROUND: The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. METHODS: The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. RESULTS: Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore http://bioinfo.hku.hk/genochore.html, a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. CONCLUSION: This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison.

Algorithms↗
PubMed2001

General method of rapid Smith/Birnstiel mapping adds for gap closure in shotgun microbial genome sequencing projects: application to Pseudomonas putida KT2440.

A physical mapping strategy has been developed to verify and accelerate the assembly and gap closure phase of a microbial genome shotgun-sequencing project. The protocol was worked out during the ongoing Pseudomonas putida KT2440 genome project. A macro-restriction map was constructed by linking probe hybridisation of SwaI- or I-CeuI-restricted chromosomes to serve as a backbone for the quick quality control of sequence and contig assemblies. The library of PCR-generated SwaI linking probes was derived from the sequence assembly after 3- and 6-fold genome coverage. In order to support gap closure in regions with ambiguous assemblies such as the repetitive sequence of the seven ribosomal operons, high-resolution Smith/Birnstiel maps were generated by Southern hybridisation of pulsed-field gel electrophoresis-separated rare-cutter complete/frequent-cutter partial digestions with rare-cutter fragment end probes. Overall 1.5 Mb of the 6.1 Mb P.putida KT2440 genome has been subjected to high-resolution physical mapping in order to align assemblies generated from shotgun sequencing.

DNA, Bacterial↗
PubMed2002

Horizontal gene transfer in microbial genome evolution.

Horizontal gene transfer is the collective name for processes that permit the exchange of DNA among organisms of different species. Only recently has it been recognized as a significant contribution to inter-organismal gene exchange. Traditionally, it was thought that microorganisms evolved clonally, passing genes from mother to daughter cells with little or no exchange of DNA among diverse species. Studies of microbial genomes, however, have shown that genomes contain genes that are closely related to a number of different prokaryotes, sometimes to phylogenetically very distantly related ones. (Doolittle et al., 1990, J. Mol. Evol. 31, 383-388; Karlin et al., 1997, J. Bacteriol. 179, 3899-3913; Karlin et al., 1998, Annu. Rev. Genet. 32, 185-225; Lawrence and Ochman, 1998, Proc. Natl. Acad. Sci. USA 95, 9413-9417; Rivera et al., 1998, Proc. Natl. Acad. Sci. USA 95, 6239-6244; Campbell, 2000, Theor. Popul. Biol. 57 71-77; Doolittle, 2000, Sci. Am. 282, 90-95; Ochman and Jones, 2000, Embo. J. 19, 6637-6643; Boucher et al. 2001, Curr. Opin., Microbiol. 4, 285-289; Wang et al., 2001, Mol. Biol. Evol. 18, 792-800). Whereas prokaryotic and eukaryotic evolution was once reconstructed from a single 16S ribosomal RNA (rRNA) gene, the analysis of complete genomes is beginning to yield a different picture of microbial evolution, one that is wrought with the lateral movement of genes across vast phylogenetic distances. (Lane et al., 1988, Methods Enzymol. 167, 138-144; Lake and Rivera, 1996, Proc. Natl. Acad. Sci. USA 91, 2880-2881; Lake et al., 1999, Science 283, 2027-2028).

Archaea↗
PubMed2025

Microbial genomic database of the Yangtze River, the third-longest river on Earth.

Microbes play an important role in mediating the nutrient cycling in the river ecosystem as a hotspot for biogeochemical processes. Due to scattered sampling efforts, however, there is a lack of a systematic study of the diversity of prokaryotic genomes in the Yangtze River, the third longest river on Earth. Here, we collected 602 metagenomic datasets of water, sediment and riparian soil samples spanning the Upper, Middle, and Lower basins of the Yangtze River over a 6,300 km continuum. We reconstructed 8,110 qualified genomes represented by 927 species-level genomes at the 95% ANI threshold, spanning 31 bacterial and five archaeal phyla. We further showed that more than half of these species (61.3% ~ 82.4%) were novel according to the genomic comparison against the curated databases, greatly expanding the known diversity of river prokaryotes. This dataset depicts an overview of microbial genomic diversity in the Yangtze River and provides a resource for in-depth investigation of metabolic potential, ecology, and evolution of riverine microbiomes.

Rivers↗
PubMed2004

Update of microbial genome programs for bacteria and archaea.

Since the Haemophilus influenzae genome sequence was completed in 1995, 172 other prokaryotic genomes have been completely sequenced, while 508 projects are underway. Besides pathogens, organisms important in several other fields, such as biotechnology and bioremediation, have also been sequenced. Institutions choose the organisms they wish to sequence according to the importance that these species represent to them, the availability of the microbes, and based on the similarity of a species of interest with others that have been sequenced previously. Improvements in sequencing techniques and in associated methodologies have been achieved; however, scientists need to continue working on the development of this field. In Brazil, a multicentered, centrally coordinated and research-focused network was adopted and successfully used for the sequencing of several important organisms. We analyzed the current status of microbial genomes, the trends for criteria used to choose new sequencing projects, the future of microbial sequencing, and the Brazilian genome network.

Brazil↗
PubMed1998

Constructing multigenome views of whole microbial genomes.

We have designed and implemented a system to carry out cross-genome comparisons of open reading frames (ORFs) from multiple genomes. This implementation includes a genome profiling system that allows us to explore pairwise comparisons at different levels of match similarity and ask biologically motivated queries involving number and identity of ORFs, their function, functional category, distribution in genomes or in biological domains, and statistics on their matches and match families. This analysis required precise definition of new classification terms and concepts. We define the terms genomic signature, summary signature, biologic domain signature, domain class, match level, match family, and extended match family, then use these terms to define concepts, including genomically universal proteins and proteins characteristics of sets of genomes. We initiate an analysis based on automated FASTA (Pearson, 1996) comparison of 22,419 conceptually translated protein sequences from nine microbial genomes.

Amino Acid Sequence↗
PubMed2006

An environmental signature for 323 microbial genomes based on codon adaptation indices.

BACKGROUND: Codon adaptation indices (CAIs) represent an evolutionary strategy to modulate gene expression and have widely been used to predict potentially highly expressed genes within microbial genomes. Here, we evaluate and compare two very different methods for estimating CAI values, one corresponding to translational codon usage bias and the second obtained mathematically by searching for the most dominant codon bias. RESULTS: The level of correlation between these two CAI methods is a simple and intuitive measure of the degree of translational bias in an organism, and from this we confirm that fast replicating bacteria are more likely to have a dominant translational codon usage bias than are slow replicating bacteria, and that this translational codon usage bias may be used for prediction of highly expressed genes. By analyzing more than 300 bacterial genomes, as well as five fungal genomes, we show that codon usage preference provides an environmental signature by which it is possible to group bacteria according to their lifestyle, for instance soil bacteria and soil symbionts, spore formers, enteric bacteria, aquatic bacteria, and intercellular and extracellular pathogens. CONCLUSION: The results and the approach described here may be used to acquire new knowledge regarding species lifestyle and to elucidate relationships between organisms that are far apart evolutionarily.

Bacteria↗
PubMed2004

An array of diverse microbial genomes.

Methods for comparing gene frequencies across large, epidemiologically defined bacterial collections are limited. A novel microarray technology has been developed called 'library on a slide'. In this technology, hundreds of entire microbial genomes are arrayed, rather than sequences of a single genome or sets of genes. These slides can then be probed for the presence of specific genes allowing researchers to draw inferences regarding important differences between related strains that differ in their pathogenic potential.

Bacteria↗
PubMed2006

Use of single-point genome signature tags as a universal tagging method for microbial genome surveys.

We developed single-point genome signature tags (SP-GSTs), a generally applicable, high-throughput sequencing-based method that targets specific genes to generate identifier tags from well-defined points in a genome. The technique yields identifier tags that can distinguish between closely related bacterial strains and allow for the identification of microbial community members. SP-GSTs are determined by three parameters: (i) the primer designed to recognize a conserved gene sequence, (ii) the anchoring enzyme recognition sequence, and (iii) the type IIS restriction enzyme which defines the tag length. We evaluated the SP-GST method in silico for bacterial identification using the genes rpoC, uvrB, and recA and the 16S rRNA gene. The best distinguishing tags were obtained with the restriction enzyme Csp6I upstream of the 16S rRNA gene, which discriminated all organisms in our data set to at least the genus level and most organisms to the species level. The method was successfully used to generate Csp6I-based tags upstream of the 16S rRNA gene and allowed us to discriminate between closely related strains of Bacillus cereus and Bacillus anthracis. This concept was further used successfully to identify the individual members of a defined microbial community.

Bacillus anthracis↗
PubMed2003

Statistical bioinformatic methods in microbial genome analysis.

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.

Computational Biology↗