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Model-guided in silico overexpression of adhe gene predicts increased ethanol production in escherichia coli from xylose

Mienda, Bashir Sajo and Omar, Mohd. Shahir Shamsir (2015) Model-guided in silico overexpression of adhe gene predicts increased ethanol production in escherichia coli from xylose. Bioengineering And Bioscience, 3 (3). pp. 39-43. ISSN 2332-0028

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Official URL: http://www.dx.doi.org/10.13189/bb.2015.030302

Abstract

Escherichia coli systems metabolic engineering has progressed significantly in guiding future metabolic engineering targets for the production of bioethanol using different carbon sources. However, the use of xylose as substrate coupled with overexpression of E. coli native adhE using parsimonious enzyme usage (pFBA) algorithm with the OptFlux interface remained largely underexplored. Here, we show for the first time that in silico overexpression of the adhE and under expression of pflA lead to 2 fold increase in ethanol production from xylose using the E. coli GEM. The results indicate that 2 NADH molecules have been generated by under expression of pflA and ldhA. Furthermore, the triple overexpression of the native adhE/ b1241 using xylose as the substrate might have increased the consumption of NADH generated in the cell that lead to 2 fold increase in ethanol production with a growth rate that was 90.8% of the wild-type model. On the bases of these findings, we hypothesize that E. coli native adhE preferred xylose as substrate when overexpressed to achieve cellular redox balance by oxidizing NADH generated in increasing ethanol production. This study informs other studies that model-guided biological insight could be applied in identifying metabolic engineering targets, paving way for a comprehensive biological inquiry on the role of the E. coli native adhE overexpression in enhancing ethanol production using xylose as a solitary carbon source.

Item Type:Article
Uncontrolled Keywords:alcohol dehydrogenase, e. coli genome scale model, ethanol production
Subjects:Q Science > Q Science (General)
Divisions:Biosciences and Medical Engineering
ID Code:60336
Deposited By: Haliza Zainal
Deposited On:24 Jan 2017 02:54
Last Modified:14 Sep 2021 08:32

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