Dataset Information

EcoGene: a genome sequence database for Escherichia coli K-12.

ABSTRACT: The EcoGene database provides a set of gene and protein sequences derived from the genome sequence of Escherichia coli K-12. EcoGene is a source of re-annotated sequences for the SWISS-PROT and Colibri databases. EcoGene is used for genetic and physical map compilations in collaboration with the Coli Genetic Stock Center. The EcoGene12 release includes 4293 genes. EcoGene12 differs from the GenBank annotation of the complete genome sequence in several ways, including (i) the revision of 706 predicted or confirmed gene start sites, (ii) the correction or hypothetical reconstruction of 61 frame-shifts caused by either sequence error or mutation, (iii) the reconstruction of 14 protein sequences interrupted by the insertion of IS elements, and (iv) pre-dictions that 92 genes are partially deleted gene fragments. A literature survey identified 717 proteins whose N-terminal amino acids have been verified by sequencing. 12 446 cross-references to 6835 literature citations and s are provided. EcoGene is accessible at a new website: http://bmb.med.miami.edu/EcoGene/EcoWeb. Users can search and retrieve individual EcoGene GenePages or they can download large datasets for incorporation into database management systems, facilitating various genome-scale computational and functional analyses.

SUBMITTER: Rudd KE

PROVIDER: S-EPMC102481 | biostudies-literature | 2000 Jan

REPOSITORIES: biostudies-literature

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EcoGene: a genome sequence database for Escherichia coli K-12.

Rudd K E KE

Nucleic acids research 20000101 1

The EcoGene database provides a set of gene and protein sequences derived from the genome sequence of Escherichia coli K-12. EcoGene is a source of re-annotated sequences for the SWISS-PROT and Colibri databases. EcoGene is used for genetic and physical map compilations in collaboration with the Coli Genetic Stock Center. The EcoGene12 release includes 4293 genes. EcoGene12 differs from the GenBank annotation of the complete genome sequence in several ways, including (i) the revision of 706 pred ...[more]

PMID: 10592181

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Project description:BackgroundConstraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology.ResultsWe present EcoCyc-18.0-GEM, a genome-scale model of the E. coli K-12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc-18.0-GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc-18.0-GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model's derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc-18.0-GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization.ConclusionSignificant advantages can be derived from the combination of model organism databases and flux balance modeling represented by MetaFlux. Interpretation of the EcoCyc database as a flux balance model results in a highly accurate metabolic model and provides a rigorous consistency check for information stored in the database.

Project description:Transposon-directed insertion site sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries, and therefore, it remains unclear whether the two methodologies are comparable. To address this, a high-density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false-positive identification of essential genes, statistical data analysis included corrections for both gene length and genome length. Through this analysis, new essential genes and genes previously incorrectly designated essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects, and fine-resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis data sets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.IMPORTANCE Incentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in Escherichia coli, we constructed a transposon mutant library of unprecedented density. Initial automated analysis of the resulting data revealed many discrepancies compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high-density TraDIS sequencing data for each putative essential gene for the E. coli model laboratory organism. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone, and provides a new standard for the analysis of TraDIS data.

Dataset Information

EcoGene: a genome sequence database for Escherichia coli K-12.

Publications

EcoGene: a genome sequence database for Escherichia coli K-12.

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