Dataset Information

Payne2021 - Pseudomonas aeruginosa UCBPP-PA14 metabolic model

ABSTRACT: Pseudomonas aeruginosa PA14 metabolic model

SUBMITTER: Mohammad Mazharul Islam

PROVIDER: MODEL2205060001 | BioModels | 2022-05-09

REPOSITORIES: BioModels

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			Action	DRS
	MODEL2205060001?filename=iPau21.xml	Xml

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Publications

An updated genome-scale metabolic network reconstruction of Pseudomonas aeruginosa PA14 to characterize mucin-driven shifts in bacterial metabolism.

Payne Dawson D DD Renz Alina A Dunphy Laura J LJ Lewis Taylor T Dräger Andreas A Papin Jason A JA

NPJ systems biology and applications 20211008 1

Mucins are present in mucosal membranes throughout the body and play a key role in the microbe clearance and infection prevention. Understanding the metabolic responses of pathogens to mucins will further enable the development of protective approaches against infections. We update the genome-scale metabolic network reconstruction (GENRE) of one such pathogen, Pseudomonas aeruginosa PA14, through metabolic coverage expansion, format update, extensive annotation addition, and literature-based cur ...[more]

PMID: 34625561

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Project description:Oberhardt2008 - Genome-scale metabolic network of Pseudomonas aeruginosa (iMO1056) This model is described in the article: Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. Oberhardt MA, Puchałka J, Fryer KE, Martins dos Santos VA, Papin JA. J. Bacteriol. 2008 Apr; 190(8): 2790-2803 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. This model is hosted on BioModels Database and identified by: MODEL1507180020. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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 CC0 Public Domain Dedication for more information.