Loading...
Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.
Oberhardt, Matthew A ; Puchałka, Jacek ; Fryer, Kimberly E ; Martins dos Santos, Vítor A P ; Papin, Jason A
Oberhardt, Matthew A
Puchałka, Jacek
Fryer, Kimberly E
Martins dos Santos, Vítor A P
Papin, Jason A
Citations
Altmetric:
Advisors
Editors
Other Contributors
Issue Date
2008-04
Submitted date
Files
Loading...
original manuscript
Adobe PDF, 3.38 MB
Other Titles
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.
Citation
Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. 2008, 190 (8):2790-803 J. Bacteriol.
Publisher
Journal
PubMed ID
PubMed Central ID
Additional Links
Embedded video
Type
Article
Language
en
Description
Series/Report no.
ISSN
1098-5530
