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Archaea. 2014 Mar 4;2014:898453. doi: 10.1155/2014/898453. eCollection 2014.

Towards a computational model of a methane producing archaeum.

Author information

1
Department of Chemistry, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.
2
Center for Biophysics and Computational Biology, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.
3
Department of Microbiology, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.
4
Center for Biophysics and Computational Biology, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA ; Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.
5
Department of Chemistry, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA ; Center for Biophysics and Computational Biology, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA ; Department of Physics, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.

Abstract

Progress towards a complete model of the methanogenic archaeum Methanosarcina acetivorans is reported. We characterized size distribution of the cells using differential interference contrast microscopy, finding them to be ellipsoidal with mean length and width of 2.9  μ m and 2.3  μ m, respectively, when grown on methanol and 30% smaller when grown on acetate. We used the single molecule pull down (SiMPull) technique to measure average copy number of the Mcr complex and ribosomes. A kinetic model for the methanogenesis pathways based on biochemical studies and recent metabolic reconstructions for several related methanogens is presented. In this model, 26 reactions in the methanogenesis pathways are coupled to a cell mass production reaction that updates enzyme concentrations. RNA expression data (RNA-seq) measured for cell cultures grown on acetate and methanol is used to estimate relative protein production per mole of ATP consumed. The model captures the experimentally observed methane production rates for cells growing on methanol and is most sensitive to the number of methyl-coenzyme-M reductase (Mcr) and methyl-tetrahydromethanopterin:coenzyme-M methyltransferase (Mtr) proteins. A draft transcriptional regulation network based on known interactions is proposed which we intend to integrate with the kinetic model to allow dynamic regulation.

PMID:
24729742
PMCID:
PMC3960522
DOI:
10.1155/2014/898453
[Indexed for MEDLINE]
Free PMC Article

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