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Title: Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri

Abstract

We present a genome-scale metabolic reconstruction for the archaeal methanogen Methanosarcina barkeri. This reconstruction represents the first large-scale, predictive model of a methanogen and an archael species. We characterize this reconstruction and compare it to those from the prokaryotic, eukaryotic, and archael domains. We further apply constraint-based methods to stimulate the metabolic fluxes and resulting phenotypes under different environmental and genetic conditions. These results are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for mutants of the methanogenic pathway were found to have a high level of agreement with experimental findings. The active reactions and pathways under selected growth conditions are presented and characterized. We also examined the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an in silico analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation, and further uncover the metabolic characteristics of methanogenesis.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
896062
Report Number(s):
PNNL-SA-52250
TRN: US200703%%488
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Molecular Systems Biology, 2
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; EFFICIENCY; GENETICS; HYDROGENASES; MUTANTS; SIMULATION; SUBSTRATES; archael metabolism; metabolic modeling; methanogenesis; Methanosarcina barkeri; network reconstruction

Citation Formats

Feist, Adam, Scholten, Johannes C., Palsson, Bernard O., Brockman, Fred J., and Ideker, Trey. Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri. United States: N. p., 2006. Web. doi:10.1038/msb4100046.
Feist, Adam, Scholten, Johannes C., Palsson, Bernard O., Brockman, Fred J., & Ideker, Trey. Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri. United States. doi:10.1038/msb4100046.
Feist, Adam, Scholten, Johannes C., Palsson, Bernard O., Brockman, Fred J., and Ideker, Trey. Tue . "Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri". United States. doi:10.1038/msb4100046.
@article{osti_896062,
title = {Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri},
author = {Feist, Adam and Scholten, Johannes C. and Palsson, Bernard O. and Brockman, Fred J. and Ideker, Trey},
abstractNote = {We present a genome-scale metabolic reconstruction for the archaeal methanogen Methanosarcina barkeri. This reconstruction represents the first large-scale, predictive model of a methanogen and an archael species. We characterize this reconstruction and compare it to those from the prokaryotic, eukaryotic, and archael domains. We further apply constraint-based methods to stimulate the metabolic fluxes and resulting phenotypes under different environmental and genetic conditions. These results are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for mutants of the methanogenic pathway were found to have a high level of agreement with experimental findings. The active reactions and pathways under selected growth conditions are presented and characterized. We also examined the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an in silico analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation, and further uncover the metabolic characteristics of methanogenesis.},
doi = {10.1038/msb4100046},
journal = {Molecular Systems Biology, 2},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 31 00:00:00 EST 2006},
month = {Tue Jan 31 00:00:00 EST 2006}
}