Towards a Computational Model of a Methane Producing Archaeum
| Autor: | Piyush Labhsetwar, Joseph R. Peterson, Petra R. A. Kohler, Ankur Jain, Jeremy R. Ellermeier, William W. Metcalf, Zaida Luthey-Schulten, Taekjip Ha |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Article Subject
Physiology Methanogenesis Reductase Microbiology Cofactor chemistry.chemical_compound Metabolic flux analysis Computer Simulation Methanosarcina acetivorans Ecology Evolution Behavior and Systematics biology Chemistry Methanol Methanosarcina biology.organism_classification Metabolic Flux Analysis QR1-502 Differential interference contrast microscopy Biochemistry biology.protein Methane Metabolic Networks and Pathways Research Article |
| Zdroj: | Archaea, Vol 2014 (2014) Archaea |
| ISSN: | 1472-3654 1472-3646 |
| Popis: | Progress towards a complete model of the methanogenic archaeumMethanosarcina acetivoransis 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 μm and 2.3 μm, 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. |
| Databáze: | OpenAIRE |
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