BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.pdfhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708_urn.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.vcmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.scihttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.xpphttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.mhttps://www.ebi.ac.uk/biomodels/model/download/MODEL5662425708?filename=MODEL5662425708.pngprimaryOK200Molecular Systems BiologyNon-curatedL2V1https://www.ebi.ac.uk/biomodels/MODEL566242570816738551falseBioModelsSBMLModelsFeist2006 methanogenesis OptiPyruvate2006MODEL5662425708Non KineticAdam M Feist, Johannes C M Scholten, Bernhard Ø Palsson, Fred J Brockman, Trey IdekerAdam M Feist16738551, We present a genome-scale metabolic model for the archaeal methanogen Methanosarcina barkeri. We characterize the metabolic network and compare it to reconstructions from the prokaryotic, eukaryotic and archaeal domains. Using the model in conjunction with constraint-based methods, we simulate the metabolic fluxes and resulting phenotypes induced by different environmental and genetic conditions. This represents the first large-scale simulation of either a methanogen or an archaeal species. Model predictions are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for wild type and mutants of the methanogenic pathway have a high level of agreement with experimental findings. We further examine the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction, and determine a stoichiometry for the nitrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation and further uncover the metabolic characteristics of methanogenesis.. , 2. Department of Bioengineering, University of California--San Diego, La Jolla, CA 92092-0412, USA.msbforum@embo.orgNature Publishing GroupWe present a genome-scale metabolic model for the archaeal methanogen Methanosarcina barkeri. We characterize the metabolic network and compare it to reconstructions from the prokaryotic, eukaryotic and archaeal domains. Using the model in conjunction with constraint-based methods, we simulate the metabolic fluxes and resulting phenotypes induced by different environmental and genetic conditions. This represents the first large-scale simulation of either a methanogen or an archaeal species. Model predictions are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for wild type and mutants of the methanogenic pathway have a high level of agreement with experimental findings. We further examine the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction, and determine a stoichiometry for the nitrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation and further uncover the metabolic characteristics of methanogenesis.Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri.Feist Adam M AM, Scholten Johannes C M JC, Palsson Bernhard Ø BØ, Brockman Fred J FJ, Ideker Trey TfalseFeist2006_methanogenesis_OptiPyruvate This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. 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. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92. 2007-07-042005-01-012006-10-02MODEL566242570816738551MODEL5662425708GO:00159482208