Dataset Information

Chavali2008 - Genome-scale metabolic network of Leishmania major (iAC560)

ABSTRACT: Chavali2008 - Genome-scale metabolic network of Leishmania major (iAC560) This model is described in the article: Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major. Chavali AK, Whittemore JD, Eddy JA, Williams KT, Papin JA. Mol. Syst. Biol. 2008; 4: 177 Abstract: Systems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of which were validated using published data with approximately 70% accuracy. Additionally, we generated hypothetical annotations to dozens of previously uncharacterized genes in the L. major genome and proposed a minimal medium for growth. We further demonstrated the utility of a network reconstruction with two proof-of-concept examples that yielded insight into robustness of the network in the presence of enzymatic inhibitors and delineation of promastigote/amastigote stage-specific metabolism. This reconstruction and the associated network analyses of L. major is the first of its kind for a protozoan. It can serve as a tool for clarifying discrepancies between data sources, generating hypotheses that can be experimentally validated and identifying ideal therapeutic targets. This model is hosted on BioModels Database and identified by: MODEL1507180059. 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.

SUBMITTER: Nicolas Le Novère

PROVIDER: MODEL1507180059 | BioModels | 2015-07-30

REPOSITORIES: BioModels

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Publications

Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major.

Chavali Arvind K AK Whittemore Jeffrey D JD Eddy James A JA Williams Kyle T KT Papin Jason A JA

Molecular systems biology 20080325

Systems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of whi ...[more]

PMID: 18364711

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Project description:Puchalka2008 - Genome-scale metabolic network of Pseudomonas putida (iJP815) This model is described in the article: Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology. Puchałka J, Oberhardt MA, Godinho M, Bielecka A, Regenhardt D, Timmis KN, Papin JA, Martins dos Santos VA. PLoS Comput. Biol. 2008 Oct; 4(10): e1000210 Abstract: A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13)C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential. This model is hosted on BioModels Database and identified by: MODEL1507180044. 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.

Dataset Information

Chavali2008 - Genome-scale metabolic network of Leishmania major (iAC560)

Publications

Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major.

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