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Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri
- Source :
- Molecular Systems Biology
- Publication Year :
- 2005
-
Abstract
- 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.
- Subjects :
- Hydrogenase
animal structures
Methanogenesis
ved/biology.organism_classification_rank.species
Metabolic network
Computational biology
network reconstruction
Genome
Models, Biological
General Biochemistry, Genetics and Molecular Biology
Article
metabolic modeling
Nitrogenase
General Immunology and Microbiology
biology
ved/biology
Applied Mathematics
archaeal metabolism
Genome project
methanogenesis
biology.organism_classification
Methanogen
Metabolism
Computational Theory and Mathematics
Biochemistry
Methanosarcina barkeri
General Agricultural and Biological Sciences
Oxidoreductases
Methane
Genome, Bacterial
Information Systems
Subjects
Details
- ISSN :
- 17444292
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Molecular systems biology
- Accession number :
- edsair.doi.dedup.....b5679c2b2af00a789ed8966b98f1f3fb