Dataset Information

Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.

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.

SUBMITTER: Oberhardt MA

PROVIDER: S-EPMC2293256 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.

Oberhardt Matthew A MA Puchałka Jacek J Fryer Kimberly E KE Martins dos Santos Vítor A P VA Papin Jason A JA

Journal of bacteriology 20080111 8

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 ...[more]

PMID: 18192387

Similar Datasets

Project description:UnlabelledPseudomonas aeruginosa uses N-acyl-homoserine lactone (AHL)-dependent quorum sensing (QS) systems to control the expression of secreted effectors. These effectors can be crucial to the ecological fitness of the bacterium, playing roles in nutrient acquisition, microbial competition, and virulence. In this study, we investigated the metabolic consequences of AHL-dependent QS by monitoring the metabolic profile(s) of a lasI rhlI double mutant (unable to make QS signaling molecules) and its wild-type progenitor as they progressed through the growth curve. Analysis of culture supernatants by (1)H-nuclear magnetic resonance ((1)H-NMR) spectroscopy revealed that at the point where AHL concentrations peaked in the wild type, the metabolic footprints (i.e., extracellular metabolites) of the wild-type and lasI rhlI mutant diverged. Subsequent gas chromatography-mass spectrometry (GC-MS)-based analysis of the intracellular metabolome revealed QS-dependent perturbations in around one-third of all identified metabolites, including altered concentrations of tricarboxylic acid (TCA) cycle intermediates, amino acids, and fatty acids. Further targeted fatty acid methyl ester (FAME) GC-MS-based profiling of the cellular total fatty acid pools revealed that QS leads to changes associated with decreased membrane fluidity and higher chemical stability. However, not all of the changes we observed were necessarily a direct consequence of QS; liquid chromatography (LC)-MS analyses revealed that polyamine levels were elevated in the lasI rhlI mutant, perhaps a response to the absence of QS-dependent adaptations. Our data suggest that QS leads to a global readjustment in central metabolism and provide new insight into the metabolic changes associated with QS during stationary-phase adaptation.ImportanceQuorum sensing (QS) is a transcriptional regulatory mechanism that allows bacteria to coordinate their gene expression profile with the population cell density. The opportunistic human pathogen Pseudomonas aeruginosa uses QS to control the production of secreted virulence factors. In this study, we show that QS elicits a global "metabolic rewiring" in P. aeruginosa. This metabolic rerouting of fluxes is consistent with a variety of drivers, ranging from altered QS-dependent transcription of "metabolic genes" through to the effect(s) of global "metabolic readjustment" as a consequence of QS-dependent exoproduct synthesis, as well as a general stress response, among others. To our knowledge, this is the first study of its kind to assess the global impact of QS on the metabolome.

Dataset Information

Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.

Publications

Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets