Use of genome-scale metabolic models for understanding microbial physiology
Journal article, 2010

The exploitation of microorganisms in industrial, medical, food and environmental biotechnology requires a comprehensive understanding of their physiology. The availability of genome sequences and accumulation of high-throughput data allows gaining understanding of microbial physiology at the systems level, and genome-scale metabolic models represent a valuable framework for integrative analysis of metabolism of microorganisms. Genome-scale metabolic models are reconstructed based on a combination of genome sequence information and detailed biochemical information, and these reconstructed models can be used for analyzing and simulating the operation of metabolism in response to different stimuli. Here we discuss the requirement for having detailed physiological insight in order to exploit microorganisms for production of fuels, chemicals and pharmaceuticals. We further describe the reconstruction process of genome-scale metabolic models and different algorithms that can be used to apply these models to gain improved insight into microbial physiology. (C) 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

escherichia-coli

Algorithm

transcriptional regulation

information-retrieval

Genome-scale metabolic model

Reconstruction

Microbial

flux-balance analysis

essential genes

yeast

intracellular environment

framework

amino-acids

optimization

physiology

cell-envelope

Author

Liming Liu

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Rasmus Ågren

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Sergio Velasco

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

FEBS Letters

0014-5793 (ISSN)

Vol. 584 12 2556-2564

Subject Categories

Industrial Biotechnology

Areas of Advance

Life Science Engineering (2010-2018)

DOI

10.1016/j.febslet.2010.04.052

More information

Created

10/8/2017