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Title: Genome-scale modeling and in silico analysis of ethanologenic bacteria Zymomonas mobilis
Authors: Widiastuti, H.
Kim, J.Y.
Selvarasu, S.
Karimi, I.A. 
Kim, H.
Seo, J.-S.
Lee, D.-Y. 
Keywords: Bioethanol
Constraints-based flux analysis
Genome-scale metabolic network
Industrial systems biotechnology
Zymomonas mobilis
Issue Date: Mar-2011
Citation: Widiastuti, H., Kim, J.Y., Selvarasu, S., Karimi, I.A., Kim, H., Seo, J.-S., Lee, D.-Y. (2011-03). Genome-scale modeling and in silico analysis of ethanologenic bacteria Zymomonas mobilis. Biotechnology and Bioengineering 108 (3) : 655-665. ScholarBank@NUS Repository.
Abstract: Bioethanol has been recognized as a potential alternative energy source. Among various ethanol-producing microbes, Zymomonas mobilis has acquired special attention due to its higher ethanol yield and tolerance. However, cellular metabolism in Z. mobilis remains unclear, hindering its practical application for bioethanol production. To elucidate such physiological characteristics, we reconstructed and validated a genome-scale metabolic network (iZM363) of Z. mobilis ATCC31821 (ZM4) based on its annotated genome and biochemical information. The phenotypic behaviors and metabolic states predicted by our genome-scale model were highly consistent with the experimental observations of Z. mobilis ZM4 strain growing on glucose as well as NMR-measured intracellular fluxes of an engineered strain utilizing glucose, fructose, and xylose. Subsequent comparative analysis with Escherichia coli and Saccharomyces cerevisiae as well as gene essentiality and flux coupling analyses have also confirmed the functional role of pdc and adh genes in the ethanologenic activity of Z. mobilis, thus leading to better understanding of this natural ethanol producer. In future, the current model could be employed to identify potential cell engineering targets, thereby enhancing the productivity of ethanol in Z. mobilis. Biotechnol. Bioeng. 2011; 108:655-665. © 2010 Wiley Periodicals, Inc.
Source Title: Biotechnology and Bioengineering
ISSN: 00063592
DOI: 10.1002/bit.22965
Appears in Collections:Staff Publications

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