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Microbial genomics: present and future.
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New antibiotic discovery, novel screens, novel targets and impact of microbial genomics.
The clinical need for new classes of antibiotic continues to grow, as drug resistance erodes the efficacy of current therapies. Historically, most antibiotics were discovered by random screening campaigns, but over the past 20 years, this strategy has largely failed to deliver a sufficient range of chemical diversity to keep pace with changing clinical profiles. A more rational approach to drug hunting has been greatly potentiated by the availability of bacterial genomic information. The rapid progress in sequencing and analysis of these small, prokaryotic genomes has enabled the concomitant development of powerful new technologies that are already enhancing the potential utility of genomic information. The future promises versatile and precise tools to understand what makes a successful antibiotic and moreover the means to identify and evaluate novel classes of drug.
Findings emerging from complete microbial genome sequences.
Sixteen microorganisms, including one eukaryote, four archaeons, and 11 eubacteria, have been completely sequenced and published. More than 50 genomes are scheduled to be completed by the year 2000. This explosive growth of information is forcing change in many scientific disciplines (e.g. bioinformatics and molecular genetics), spawning new fields, and even changing the way scientific information is used and shared. Novel, global genome sequence comparisons seem slow to appear but the infrastructure for these projects is being built, and we expect exciting developments in the near future.
Microbial genome sequencing and pathogenesis.
The year 1997 saw the publication of the complete nucleotide sequence of Helicobacter pylori and Escherichia coli. It is conceivable that the complete nucleotide sequence for all the major human bacterial pathogens will be available by the end of the century. Database alignments have been used to ascribe the putative functions of open reading frames in the sequenced isolates and to define the differences between bacterial species at the nucleotide level. The most striking finding from all genome projects has been the high proportion of open reading frames that have no known function. Experimental data demonstrating the utility of the genome sequencing projects are only just beginning to emerge.
Microbial genomics as a guide to drug discovery and structural elucidation: ECO-02301, a novel antifungal agent, as an example.
Analysis of the genome of Streptomyces aizunensis NRRL B-11277 indicated its potential to produce a compound of novel and highly predictable structure. The structure was predicted with sufficient accuracy to allow straightforward detection of the specific metabolite in HPLC profiles of fermentation extracts and hence to guide the isolation. The spectroscopic work was reduced to a confirmation of structure rather than a first principle determination. The compound, ECO-02301 (1), demonstrated potent antifungal activity. This work exemplifies not only the discovery of novel antibiotics from well-characterized organisms but also the utility of genomics as a further tool, complementary to spectroscopy, to enable rapid determination of complex structures.
Transposome insertional mutagenesis and direct sequencing of microbial genomes.
Preformed transposase-transposon complexes called 'Transposomes' have been electroporated into bacterial cells. The magnesium dependent process of insertion of the transposable element into bacterial chromosomal DNA occurs in vivo. The transposition efficiency of a Transposome containing a kanamycin marker was between 1.0 x 10(4) and 1.0 x 10(7) kanamycin resistant clones per microgram of transposon DNA in three gram-negative enteric bacterial species. Transposon integration sites were examined by direct genome sequencing of chromosomal DNA. Genomic DNA was isolated from transposition clones and directly cycle sequenced with primers specific for the ends of the transposon. The precise location of genome interruption for a transposition clone was identified by homology to known genes or sequences. Mutant phenotypes were rapidly correlated with genomic insertions sites.
Microbial genomes opened up.
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Biodiversity: microbial genomes multiply.
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Web alert. Microbial genomics.
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Functional analysis of gapped microbial genomes: amino acid metabolism of Thiobacillus ferrooxidans.
A gapped genome sequence of the biomining bacterium Thiobacillus ferrooxidans strain ATCC23270 was assembled from sheared DNA fragments (3.2-times coverage) into 1,912 contigs. A total of 2,712 potential genes (ORFs) were identified in 2.6 Mbp (megabase pairs) of Thiobacillus genomic sequence. Of these genes, 2,159 could be assigned functions by using the WIT-Pro/EMP genome analysis system, most with a high degree of certainty. Nine hundred of the genes have been assigned roles in metabolic pathways, producing an overview of cellular biosynthesis, bioenergetics, and catabolism. Sequence similarities, relative gene positions on the chromosome, and metabolic reconstruction (placement of gene products in metabolic pathways) were all used to aid gene assignments and for development of a functional overview. Amino acid biosynthesis was chosen to demonstrate the analytical capabilities of this approach. Only 10 expected enzymatic activities, of the nearly 150 involved in the biosynthesis of all 20 amino acids, are currently unassigned in the Thiobacillus genome. This result compares favorably with 10 missing genes for amino acid biosynthesis in the complete Escherichia coli genome. Gapped genome analysis can therefore give a decent picture of the central metabolism of a microorganism, equivalent to that of a complete sequence, at significantly lower cost.
GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.
Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
Prediction of operons in microbial genomes.
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.
SIDDBASE: a database containing the stress-induced DNA duplex destabilization (SIDD) profiles of complete microbial genomes.
Prokaryotic genomic DNA is generally negatively supercoiled in vivo. Many regulatory processes, including the initiation of transcription, are known to depend on the superhelical state of the DNA substrate. The stresses induced within DNA by negative superhelicity can destabilize the DNA duplex at specific sites. Various experiments have either shown or suggested that stress-induced DNA duplex destabilization (SIDD) is involved in specific regulatory mechanisms governing a variety of biological processes. We have developed methods to evaluate the SIDD properties of DNA sequences, including complete chromosomes. This analysis predicts the locations where the duplex becomes destabilized under superhelical stress. Previous studies have shown that the SIDD-susceptible sites predicted in this way occur at rates much higher than expected at random in transcriptional regulatory regions, and much lower than expected in coding regions. Analysis of the SIDD profiles of 42 bacterial genomes chosen for their diversity confirms this pattern. Predictions of SIDD sites have been used to identify potential genomic regulatory regions, and suggest both possible regulatory mechanisms involving stress-induced destabilization and experimental tests of these mechanisms. Here we describe the SIDDBASE database which enables users to retrieve and visualize the results of SIDD analyses of completely sequenced prokaryotic and archaeal genomes, together with their annotations. SIDDBASE is available at www.gc.ucdavis.edu/benham/siddbase.
Evolutionary instability of operon structures disclosed by sequence comparisons of complete microbial genomes.
Gene orders have been shown to be generally unstable by comprehensive analyses in several complete genomes. In this study, we examined instability of genome structures within operons, where functionally related genes are clustered. We compared gene orders of known operons obtained from Escherichia coli and Bacillus subtilis with corresponding those of operons in 11 complete genome sequences. We found that in many cases, gene orders within operons could be shuffled frequently during evolution, although several operon structures, such as ribosomal protein operons, were well conserved. This suggests that shuffling of a genome structure is virtually neutral in long-term evolution. Moreover, degrees of instability of the operon structures depended on the genomes examined. Variation in degrees of instability of the genome structures was likely to be related to differences in amounts of insertion sequences. Effects on transcription regulation are also discussed in association with operon destruction.
Microbial genome sequencing: a new era for research on enteric pathogens.
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Cloning and assembly strategies in microbial genome projects.
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