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C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

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Date 2017 Sep 28
PMID 28952565
Citations 4
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Abstract

Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, C Metabolic Flux Analysis (C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of C-MFA and illustrate how C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms.

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References
1.
Ferrer-Miralles N, Domingo-Espin J, Corchero J, Vazquez E, Villaverde A . Microbial factories for recombinant pharmaceuticals. Microb Cell Fact. 2009; 8:17. PMC: 2669800. DOI: 10.1186/1475-2859-8-17. View

2.
Gombert A, Moreira dos Santos M, Christensen B, Nielsen J . Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression. J Bacteriol. 2001; 183(4):1441-51. PMC: 95019. DOI: 10.1128/JB.183.4.1441-1451.2001. View

3.
Lu X, Vora H, Khosla C . Overproduction of free fatty acids in E. coli: implications for biodiesel production. Metab Eng. 2008; 10(6):333-9. DOI: 10.1016/j.ymben.2008.08.006. View

4.
Young J . INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics. 2014; 30(9):1333-5. PMC: 3998137. DOI: 10.1093/bioinformatics/btu015. View

5.
de Jong B, Shi S, Siewers V, Nielsen J . Improved production of fatty acid ethyl esters in Saccharomyces cerevisiae through up-regulation of the ethanol degradation pathway and expression of the heterologous phosphoketolase pathway. Microb Cell Fact. 2014; 13(1):39. PMC: 3995654. DOI: 10.1186/1475-2859-13-39. View