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PubMed2000

Status of genome projects for nonpathogenic bacteria and archaea.

Since the first microbial genome was sequenced in 1995, 30 others have been completed and an additional 99 are known to be in progress. Although the early emphasis of microbial genomics was on human pathogens for obvious reasons, a significant number of sequencing projects have focused on nonpathogenic organisms, beginning with the release of the complete genome sequence of the archaeon Methanococcus jannaschii in 1996. The past 18 months have seen the completion of the genomes of several unusual organisms, including Thermotoga maritima, whose genome reveals extensive potential lateral transfer with archaea; Deinococcus radiodurans, the most radiation-resistant microorganism known; and Aeropyrum pernix, the first Crenarchaeota to be completely sequenced. Although the functional characterization of genomic data is still in its initial stages, it is likely that microbial genomics will have a significant impact on environmental, food, and industrial biotechnology as well as on genomic medicine.

Archaea↗
PubMed2004

Genome diversity in microbial eukaryotes.

The genomic peculiarities among microbial eukaryotes challenge the conventional wisdom of genome evolution. Currently, many studies and textbooks explore principles of genome evolution from a limited number of eukaryotic lineages, focusing often on only a few representative species of plants, animals and fungi. Increasing emphasis on studies of genomes in microbial eukaryotes has and will continue to uncover features that are either not present in the representative species (e.g. hypervariable karyotypes or highly fragmented mitochondrial genomes) or are exaggerated in microbial groups (e.g. chromosomal processing between germline and somatic nuclei). Data for microbial eukaryotes have emerged from recent genome sequencing projects, enabling comparisons of the genomes from diverse lineages across the eukaryotic phylogenetic tree. Some of these features, including amplified rDNAs, subtelomeric rDNAs and reduced genomes, appear to have evolved multiple times within eukaryotes, whereas other features, such as absolute strand polarity, are found only within single lineages.

Journal Article↗
PubMedDate not supplied

Using DNA microarrays to study host-microbe interactions.

Complete genomic sequences of microbial pathogens and hosts offer sophisticated new strategies for studying host-pathogen interactions. DNA microarrays exploit primary sequence data to measure transcript levels and detect sequence polymorphisms, for every gene, simultaneously. The design and construction of a DNA microarray for any given microbial genome are straightforward. By monitoring microbial gene expression, one can predict the functions of uncharacterized genes, probe the physiologic adaptations made under various environmental conditions, identify virulence-associated genes, and test the effects of drugs. Similarly, by using host gene microarrays, one can explore host response at the level of gene expression and provide a molecular description of the events that follow infection. Host profiling might also identify gene expression signatures unique for each pathogen, thus providing a novel tool for diagnosis, prognosis, and clinical management of infectious disease.

Algorithms↗
PubMed2003

Fitting the niche by genomic adaptation.

Studying microbial genomics has shown that the genomes of bacteria are extremely dynamic in evolutionary terms. Many research groups have linked the adaptation of an organism to a niche to large changes in genome size and content. A number of recent papers have underlined the degree to which the genomes of different organisms are a reflection of the opportunities and constraints imposed by their chosen niche.

Adaptation, Physiological↗
PubMed2001

Advances in genomics for microbial food fermentations and safety.

The exponentially growing collection of genomic sequence information, the high-throughput analysis of expression products, and the ability to order this information using advanced bioinformatics are expected to affect biotechnology and life sciences in a profound and unprecedented way. These developments offer many possibilities to improve the functionality of fermentations by food-grade microorganisms and to increase the microbial safety of foods. It will be necessary to combine functional studies with comparative genomics approaches to provide effective strategies for improving the functionality and safety of foods.

Computational Biology↗
PubMed2004

Genome sequencing and annotation: an overview.

Many microbial genome sequences have been determined, and more new genome projects are ongoing. Shotgun sequencing of randomly cloned short pieces of genomic DNA can provide a simple way of determining whole genome sequences. This process requires sequencing of many fragments, compilation of the separate sequences into one contiguous sequence, and careful editing of the assembled sequence. The genes present on the microbial genome are then predicted using clues derived from typical gene features, such as codon usage, ribosomal binding sequences, and bacterial initiation codons. Function of genes is predicted by homology searches performed against either public or well-established protein databases. This chapter discusses each of these stages in a genome-sequencing project.

Amino Acid Sequence↗
PubMed2004

Reverse methanogenesis: testing the hypothesis with environmental genomics.

Microbial methane consumption in anoxic sediments significantly impacts the global environment by reducing the flux of greenhouse gases from ocean to atmosphere. Despite its significance, the biological mechanisms controlling anaerobic methane oxidation are not well characterized. One current model suggests that relatives of methane-producing Archaea developed the capacity to reverse methanogenesis and thereby to consume methane to produce cellular carbon and energy. We report here a test of the "reverse-methanogenesis" hypothesis by genomic analyses of methane-oxidizing Archaea from deep-sea sediments. Our results show that nearly all genes typically associated with methane production are present in one specific group of archaeal methanotrophs. These genome-based observations support previous hypotheses and provide an informed foundation for metabolic modeling of anaerobic methane oxidation.

Anaerobiosis↗
PubMed2004

Rapid identification and mapping of insertion sequences in Escherichia coli genomes using vectorette PCR.

BACKGROUND: Insertion sequences (IS) are small DNA segments capable of transposing within and between prokaryotic genomes, often causing insertional mutations and chromosomal rearrangements. Although several methods are available for locating ISs in microbial genomes, they are either labor-intensive or inefficient. Here, we use vectorette PCR to identify and map the genomic positions of the eight insertion sequences (IS1, 2, 3, 4, 5, 30, 150, and 186) found in E. coli strain CGSC6300, a close relative of MG1655 whose genome has been sequenced. RESULTS: Genomic DNA from strain CGSC6300 was digested with a four-base cutter Rsa I and the resulting restriction fragments ligated onto vectorette units. Using IS-specific primers directed outward from the extreme ends of each IS and a vectorette primer, flanking DNA fragments were amplified from all but one of the 37 IS elements identified in the genomic sequence of MG1655. Purification and sequencing of the PCR products confirmed that they are IS-associated flanking DNA fragments corresponding to the known IS locations in the MG1655 genome. Seven additional insertions were found in strain CGSC6300 indicating that very closely related isolates of the same laboratory strain (the K12 isolate) may differ in their IS complement. Two other E. coli K12 derivatives, TD2 and TD10, were also analyzed by vectorette PCR. They share 36 of the MG1655 IS sites as well as having 16 and 18 additional insertions, respectively. CONCLUSION: This study shows that vectorette PCR is a swift, efficient, reliable method for typing microbial strains and identifying and mapping IS insertion sites present in microbial genomes. Unlike Southern hybridization and inverse PCR, our approach involves only one genomic digest and one ligation step. Vectorette PCR is then used to simultaneously amplify all IS elements of a given type, making it a rapid and sensitive means to survey IS elements in genomes. The ability to rapidly identify the IS complements of microbial genomes should facilitate subtyping closely related pathogens during disease outbreaks.

Bacterial Typing Techniques↗
PubMed2005

Computational detection of prokaryotic core promoters in genomic sequences.

The high-throughput sequencing of microbial genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable research attention in recent years. This paper addresses the development of a predictive model, known as the dependence decomposition weight matrix model (DDWMM), which was designed to detect the core promoter region, including the -10 region and the transcription start sites (TSSs), in prokaryotic genomic DNA sequences. This is an issue of some importance with regard to genome annotation efforts. Our predictive model captures the most significant dependencies between positions (allowing for non-adjacent as well as adjacent dependencies) via the maximal dependence decomposition (MDD) procedure, which iteratively decomposes data sets into subsets, based on the significant dependence between positions in the promoter region to be modeled. Such dependencies may be intimately related to biological and structural concerns, since promoter elements are present in a variety of combinations, which are separated by various distances. In this respect, the DDWMM may prove to be appropriate with regard to the detection of core promoter regions and TSSs in long microbial genomic contigs. In order to demonstrate the effectiveness of our predictive model, we applied 10-fold cross-validation experiments on the 607 experimentally-verified promoter sequences, which evidenced good performance in terms of sensitivity.

Base Sequence↗
PubMed2005

Visualization of comparative genomic analyses by BLAST score ratio.

BACKGROUND: The first microbial genome sequence, Haemophilus influenzae, was published in 1995. Since then, more than 400 microbial genome sequences have been completed or commenced. This massive influx of data provides the opportunity to obtain biological insights through comparative genomics. However few tools are available for this scale of comparative analysis. RESULTS: The BLAST Score Ratio (BSR) approach, implemented in a Perl script, classifies all putative peptides within three genomes using a measure of similarity based on the ratio of BLAST scores. The output of the BSR analysis enables global visualization of the degree of proteome similarity between all three genomes. Additional output enables the genomic synteny (conserved gene order) between each genome pair to be assessed. Furthermore, we extend this synteny analysis by overlaying BSR data as a color dimension, enabling visualization of the degree of similarity of the peptides being compared. CONCLUSIONS: Combining the degree of similarity, synteny and annotation will allow rapid identification of conserved genomic regions as well as a number of common genomic rearrangements such as insertions, deletions and inversions. The script and example visualizations are available at: http://www.microbialgenomics.org/BSR/.

Algorithms↗
PubMed1998

Comparing genomes in terms of protein structure: surveys of a finite parts list.

We give an overview of the emerging field of structural genomics, describing how genomes can be compared in terms of protein structure. As the number of genes in a genome and the total number of protein folds are both quite limited, these comparisons take the form of surveys of a finite parts list, similar in respects to demographic censuses. Fold surveys have many similarities with other whole-genome characterizations, e.g., analyses of motifs or pathways. However, structure has a number of aspects that make it particularly suitable for comparing genomes, namely the way it allows for the precise definition of a basic protein module and the fact that it has a better defined relationship to sequence similarity than does protein function. An essential requirement for a structure survey is a library of folds, which groups the known structures into 'fold families.' This library can be built up automatically using a structure comparison program, and we described how important objective statistical measures are for assessing similarities within the library and between the library and genome sequences. After building the library, one can use it to count the number of folds in genomes, expressing the results in the form of Venn diagrams and 'top-10' statistics for shared and common folds. Depending on the counting methodology employed, these statistics can reflect different aspects of the genome, such as the amount of internal duplication or gene expression. Previous analyses have shown that the common folds shared between very different microorganisms, i.e., in different kingdoms, have a remarkably similar structure, being comprised of repeated strand-helix-strand super-secondary structure units. A major difficulty with this sort of 'fold-counting' is that only a small subset of the structures in a complete genome are currently known and this subset is prone to sampling bias. One way of overcoming biases is through structure prediction, which can be applied uniformly and comprehensively to a whole genome. Various investigators have, in fact, already applied many of the existing techniques for predicting secondary structure and transmembrane (TM) helices to the recently sequenced genomes. The results have been consistent: microbial genomes have similar fractions of strands and helices even though they have significantly different amino acid composition. The fraction of membrane proteins with a given number of TM helices falls off rapidly with more TM elements, approximately according to a Zipf law. This latter finding indicates that there is no preference for the highly studied 7-TM proteins in microbial genomes. Continuously updated tables and further information pertinent to this review are available over the web at http://bioinfo.mbb.yale.edu/genome.

Amino Acid Sequence↗
PubMed2006

In-depth analyses of marine microbial community genomics.

Marine microbes have evolved to live along extreme environmental gradients, whether at the microscale, in proximity to particles or over the entire water column. Using community genomics, DeLong et al. highlight deduced biological differences that result from open-ocean depth gradients. The power of the large-insert libraries used is that both phylogeny and function can be inferred from the genetic material obtained--even for uncultured microbes. Together with complete genomes of marine isolates and advances in physiology and ecology, this study paves the way for ecosystems biology approaches to dynamics and controls of marine microbial populations.

Ecology↗
PubMed2005

Community genomics in microbial ecology and evolution.

It is possible to reconstruct near-complete, and possibly complete, genomes of the dominant members of microbial communities from DNA that is extracted directly from the environment. Genome sequences from environmental samples capture the aggregate characteristics of the strain population from which they were derived. Comparison of the sequence data within and among natural populations can reveal the evolutionary processes that lead to genome diversification and speciation. Community genomic datasets can also enable subsequent gene expression and proteomic studies to determine how resources are invested and functions are distributed among community members. Ultimately, genomics can reveal how individual species and strains contribute to the net activity of the community.

DNA↗
PubMed2003

Genome-scale microbial in silico models: the constraints-based approach.

Genome sequencing and annotation has enabled the reconstruction of genome-scale metabolic networks. The phenotypic functions that these networks allow for can be defined and studied using constraints-based models and in silico simulation. Several useful predictions have been obtained from such in silico models, including substrate preference, consequences of gene deletions, optimal growth patterns, outcomes of adaptive evolution and shifts in expression profiles. The success rate of these predictions is typically in the order of 70-90% depending on the organism studied and the type of prediction being made. These results are useful as a basis for iterative model building and for several practical applications.

Animals↗
PubMed2003

Microbial pathogen genomes - new strategies for identifying therapeutic and vaccine targets.

Efficient mining of genomic sequence information from multiple pathogens for therapeutic and vaccine targets requires efficient tools. Fortunately, robust methods applicable to whole genomes have been developed and applied in the past few years to identify genes essential for growth or virulence and to detect potential vaccine targets. Successful approaches to identify potential therapeutic targets include a variety of ingenious uses of nearly random transposon insertions, more directed methods such as antisense and insertion-duplication mutagenesis, and expression profiling facilitated by microarrays. Vaccine targets have been identified by gene fusion and expression experiments to discover gene products that are immunogenic in humans or animal models. All genome-wide methods require focused secondary assays to validate the findings, but these genomic methods excel at reducing to a manageable number the genes to be examined further. This editorial reviews the latest developments in genome-wide target identification tools.

Anti-Infective Agents↗
PubMed2006

AMIGOS: a method for the inspection of genomic organisation or structure and its application to characterise conserved gene arrangements.

In order to identify and to characterise gene clusters conserved in microbial genomes, the algorithm AMIGOS was developed. It is based on a categorisation of genes using a predefined set of gene functions (GFs). After the categorisation of all genes of a genome and based on their location on a replicon, distances between GFs were determined and stored in genome-specific matrices. These matrices were used to identify GF clusters like those strictly conserved in 13 archaeal, in 47 bacterial genomes and in the combination of the sets. Within the combined set of these 60 microbial genomes, there exist only two strictly conserved clusters harbouring two ribosomal genes each, namely those for L4, L23 and L22, L29. In order to characterise less strictly conserved GF clusters, content of genomes i.e. matrices were analysed pairwise. Resulting clusters were merged to (meta-) clusters if their content overlapped. A scoring system named cons(CL) was developed. It quantifies conservedness of cluster membership for individual GFs. For the genome of Escherichia coli it was shown that a grouping of cluster elements on cons(CL) values dissected the clusters into smaller sets. These sets were frequently overlapped by known transcriptional units (TUs). This finding justifies the usage of cons(CL) scores to predict TU membership of genes. In addition, cons(CL) values provide a sound basis for non-homologous gene annotation. Based on cons(CL) values, examples of conserved clusters containing annotated genes and single ones with unknown function are given.

Algorithms↗
PubMed2002

Bootstrap, Bayesian probability and maximum likelihood mapping: exploring new tools for comparative genome analyses.

BACKGROUND: Horizontal gene transfer (HGT) played an important role in shaping microbial genomes. In addition to genes under sporadic selection, HGT also affects housekeeping genes and those involved in information processing, even ribosomal RNA encoding genes. Here we describe tools that provide an assessment and graphic illustration of the mosaic nature of microbial genomes. RESULTS: We adapted the Maximum Likelihood (ML) mapping to the analyses of all detected quartets of orthologous genes found in four genomes. We have automated the assembly and analyses of these quartets of orthologs given the selection of four genomes. We compared the ML-mapping approach to more rigorous Bayesian probability and Bootstrap mapping techniques. The latter two approaches appear to be more conservative than the ML-mapping approach, but qualitatively all three approaches give equivalent results. All three tools were tested on mitochondrial genomes, which presumably were inherited as a single linkage group. CONCLUSIONS: In some instances of interphylum relationships we find nearly equal numbers of quartets strongly supporting the three possible topologies. In contrast, our analyses of genome quartets containing the cyanobacterium Synechocystis sp. indicate that a large part of the cyanobacterial genome is related to that of low GC Gram positives. Other groups that had been suggested as sister groups to the cyanobacteria contain many fewer genes that group with the Synechocystis orthologs. Interdomain comparisons of genome quartets containing the archaeon Halobacterium sp. revealed that Halobacterium sp. shares more genes with Bacteria that live in the same environment than with Bacteria that are more closely related based on rRNA phylogeny. Many of these genes encode proteins involved in substrate transport and metabolism and in information storage and processing. The performed analyses demonstrate that relationships among prokaryotes cannot be accurately depicted by or inferred from the tree-like evolution of a core of rarely transferred genes; rather prokaryotic genomes are mosaics in which different parts have different evolutionary histories. Probability mapping is a valuable tool to explore the mosaic nature of genomes.

Journal Article↗
PubMed2002

Bacterial genomics: the use of DNA microarrays and bacterial artificial chromosomes.

Immense amounts of genetic information are contained within microbial genomes. As the number of completely sequenced microbial genomes is increasing, functional and comparative genomic techniques will be employed for sequence analysis and gene characterization. Sequence comparison and expression profiling by DNA microarrays can determine phylogenetic relationships and identify genes while bacterial artificial chromosomes (BACs) allow the study of entire biochemical pathways and permit the expression of bacterial genes in a foreign host.

Anti-Bacterial Agents↗