Genome-scale metabolic modelling common cofactors metabolism in microorganisms.

J Biotechnol

State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China; The Laboratory of Food Microbial-Manufacturing Engineering, Jiangnan University, Wuxi 214122, China. Electronic address:

Published: June 2017

AI Article Synopsis

  • The icmNX6434 model was developed to study the roles of key cofactors (ATP/ADP, NAD(P)(H), and acetyl-CoA/CoA) in microbial metabolism, containing 6434 genes and 6877 reactions based on 14 industrial microbial strains.
  • This model helps identify how these cofactors influence cell growth and metabolism, emphasizing the need to optimize cofactor biosynthesis and minimize their use in non-essential processes.
  • Changes in the levels of these cofactors can trigger metabolic responses to various stresses, making the icmNX6434 valuable for understanding and enhancing microbial performance in industrial applications.

Article Abstract

The common cofactors ATP/ADP, NAD(P)(H), and acetyl-CoA/CoA are indispensable participants in biochemical reactions in industrial microbes. To systematically explore the effects of these cofactors on cell growth and metabolic phenotypes, the first genome-scale cofactor metabolic model, icmNX6434, including 6434 genes, 1782 metabolites, and 6877 reactions, was constructed from 14 genome-scale metabolic models of 14 industrial strains. The origin, consumption, and interactions of these common cofactors in microbial cells were elucidated by the icmNX6434 model, and they played important roles in cell growth. The essential cofactor modules contained 2480 genes and 2948 reactions; therefore, improving cofactor biosynthesis, directing these cofactors into essential metabolic pathways, as well as avoiding cofactor utilization during byproduct biosynthesis and futile cycles, are three ways to increase cell growth. The effects of these common cofactors on the distribution and rate of the carbon flux in four universal modes, as well as an optimized metabolic flux, could be obtained by manipulating cofactor availability and balance. Significant changes in the ATP, NAD(H), NADP(H), or acetyl-CoA concentrations triggered relevant metabolic responses to acidic, oxidative, heat, and osmotic stress. Globally, the model icmNX6434 provides a comprehensive platform to elucidate the physiological effects of these cofactors on cell growth, metabolic flux, and industrial robustness. Moreover, the results of this study are a further example of using a consensus genome-scale metabolic model to increase our understanding of key biological processes.

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Source
http://dx.doi.org/10.1016/j.jbiotec.2017.04.004DOI Listing

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