biostudies-otherUnknown190Nicolas Le NovèreJournal of bacteriology2790-2803https://www.ebi.ac.uk/biostudies/studies/MODEL1507180020biostudies-other18192387Nicolas Le NovèrefalseOberhardt2008 - Genome-scale metabolic network of Pseudomonas aeruginosa (iMO1056)<notes xmlns="http://www.sbml.org/sbml/level3/version1/core"> <body xmlns="http://www.w3.org/1999/xhtml"> <div class="dc:title">Oberhardt2008 - Genome-scale metabolicnetwork of Pseudomonas aeruginosa (iMO1056)</div><div class="dc:bibliographicCitation"> <p>This model is described in the article:</p> <div class="bibo:title"> <a href="http://identifiers.org/pubmed/18192387" title="Access to this publication">Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.</a> </div> <div class="bibo:authorList">Oberhardt MA, Puchałka J, Fryer KE, Martins dos Santos VA, Papin JA.</div> <div class="bibo:Journal">J. Bacteriol. 2008 Apr; 190(8): 2790-2803</div> <p>Abstract:</p> <div class="bibo:abstract"> <p>Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.</p> </div></div><div class="dc:publisher"> <p>This model is hosted on <a href="http://www.ebi.ac.uk/biomodels/">BioModels Database</a> and identified by: <a href="http://identifiers.org/biomodels.db/MODEL1507180020">MODEL1507180020</a>.</p> <p>To cite BioModels Database, please use: <a href="http://identifiers.org/pubmed/20587024" title="Latest BioModels Database publication">BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models</a>.</p></div><div class="dc:license"> <p>To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to <a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0 Public Domain Dedication</a> for more information.</p></div></body> </notes>2015-07-18T00:00:00Z2025-07-15T09:10:48.654Z2025-03-30T21:57:54.932ZMODEL150718002018192387MAMO_0000009null