PNNL

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.