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A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189
With a genome size of approximately 580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers t...
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Published in: | PLoS computational biology 2009-02, Vol.5 (2), p.e1000285-e1000285 |
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description | With a genome size of approximately 580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms. |
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The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1000285</identifier><identifier>PMID: 19214212</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Automation ; Biomass ; Computational Biology/Metabolic Networks ; Computational Biology/Systems Biology ; Genes, Essential ; Genetics and Genomics/Bioinformatics ; Genome, Bacterial ; Genomes ; Genomics ; Metabolites ; Metabolome - genetics ; Metabolomics - methods ; Models, Biological ; Mycoplasma genitalium - genetics ; Mycoplasma genitalium - metabolism ; Nutrigenomics ; Organisms</subject><ispartof>PLoS computational biology, 2009-02, Vol.5 (2), p.e1000285-e1000285</ispartof><rights>Suthers et al. 2009</rights><rights>2009 Suthers et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Suthers PF, Dasika MS, Kumar VS, Denisov G, Glass JI, et al. (2009) A Genome-Scale Metabolic Reconstruction of Mycoplasma genitalium, iPS189. 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Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms.</description><subject>Automation</subject><subject>Biomass</subject><subject>Computational Biology/Metabolic Networks</subject><subject>Computational Biology/Systems Biology</subject><subject>Genes, Essential</subject><subject>Genetics and Genomics/Bioinformatics</subject><subject>Genome, Bacterial</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Metabolites</subject><subject>Metabolome - genetics</subject><subject>Metabolomics - methods</subject><subject>Models, Biological</subject><subject>Mycoplasma genitalium - genetics</subject><subject>Mycoplasma genitalium - metabolism</subject><subject>Nutrigenomics</subject><subject>Organisms</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVUUtv1DAQjhCIPuAfIMiJE1n8jnNBqipoKxWBBJyt8dhZvHLixU4q9d-TZQO0pxmNv8eMv6p6RcmG8pa-36U5jxA3e7RhQwkhTMsn1SmVkjctl_rpg_6kOitlR8jSdup5dUI7RgWj7LS6vqi3fkyDbwpC9PXgJ7ApBqyzxzSWKc84hTTWqa8_32PaRygDHDhhghjm4V0dvn6juntRPeshFv9yrefVj08fv19eN7dfrm4uL24bFJ2aGlTCt0TaDpwkkgqrrLNSOOdIyxlzjiOC6EDLzgFt0XEtettqZG1newH8vHpz1N3HVMz6CcVQTplQWop2QdwcES7BzuxzGCDfmwTB_BmkvDWQp4DRG6a9FhKQWzjswAEQnV58tetb4GzR-rC6zXbwDv04ZYiPRB-_jOGn2aY7wxTny32LwNtVIKdfsy-TGUJBHyOMPs3FKNUxwalagOIIxJxKyb7_Z0KJOQT-91ZzCNysgS-01w8X_E9aE-a_Ae-dqv4</recordid><startdate>20090201</startdate><enddate>20090201</enddate><creator>Suthers, Patrick F</creator><creator>Dasika, Madhukar S</creator><creator>Kumar, Vinay Satish</creator><creator>Denisov, Gennady</creator><creator>Glass, John I</creator><creator>Maranas, Costas D</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20090201</creationdate><title>A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189</title><author>Suthers, Patrick F ; 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The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. 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subjects | Automation Biomass Computational Biology/Metabolic Networks Computational Biology/Systems Biology Genes, Essential Genetics and Genomics/Bioinformatics Genome, Bacterial Genomes Genomics Metabolites Metabolome - genetics Metabolomics - methods Models, Biological Mycoplasma genitalium - genetics Mycoplasma genitalium - metabolism Nutrigenomics Organisms |
title | A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189 |
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