2.50
Hdl Handle:
http://hdl.handle.net/10033/48335
Title:
Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.
Authors:
Oberhardt, Matthew A; Puchałka, Jacek; Fryer, Kimberly E; Martins dos Santos, Vítor A P; Papin, Jason A
Abstract:
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.
Affiliation:
Department of Biomedical Engineering, University of Virginia Health System, Box 800759, Charlottesville, VA 22908, USA.
Citation:
Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. 2008, 190 (8):2790-803 J. Bacteriol.
Journal:
Journal of bacteriology
Issue Date:
Apr-2008
URI:
http://hdl.handle.net/10033/48335
DOI:
10.1128/JB.01583-07
PubMed ID:
18192387
Type:
Article
Language:
en
ISSN:
1098-5530
Appears in Collections:
Publications of the RG Systems and synthetic biology (SSBI)

Full metadata record

DC FieldValue Language
dc.contributor.authorOberhardt, Matthew A-
dc.contributor.authorPuchałka, Jacek-
dc.contributor.authorFryer, Kimberly E-
dc.contributor.authorMartins dos Santos, Vítor A P-
dc.contributor.authorPapin, Jason A-
dc.date.accessioned2009-02-02T15:11:37Z-
dc.date.available2009-02-02T15:11:37Z-
dc.date.issued2008-04-
dc.identifier.citationGenome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. 2008, 190 (8):2790-803 J. Bacteriol.en
dc.identifier.issn1098-5530-
dc.identifier.pmid18192387-
dc.identifier.doi10.1128/JB.01583-07-
dc.identifier.urihttp://hdl.handle.net/10033/48335-
dc.description.abstractPseudomonas 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.en
dc.language.isoenen
dc.subject.meshBacterial Proteinsen
dc.subject.meshComputational Biologyen
dc.subject.meshComputer Simulationen
dc.subject.meshGenes, Bacterialen
dc.subject.meshGenome, Bacterialen
dc.subject.meshHumansen
dc.subject.meshMetabolic Networks and Pathwaysen
dc.subject.meshPseudomonas aeruginosaen
dc.titleGenome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.en
dc.typeArticleen
dc.contributor.departmentDepartment of Biomedical Engineering, University of Virginia Health System, Box 800759, Charlottesville, VA 22908, USA.en
dc.identifier.journalJournal of bacteriologyen

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