Applied Microbiology and Biotechnology

, Volume 97, Issue 2, pp 519–539

Genome-scale metabolic model in guiding metabolic engineering of microbial improvement

Authors

  • Chuan Xu
    • College of Biological and Environmental EngineeringZhejiang University of Technology
    • Department of Bioinformatics, College of Life SciencesZhejiang University
  • Lili Liu
    • Department of Bioinformatics, College of Life SciencesZhejiang University
  • Zhao Zhang
    • Department of Bioinformatics, College of Life SciencesZhejiang University
    • Watson Institute of Genome SciencesZhejiang University
  • Danfeng Jin
    • Department of Bioinformatics, College of Life SciencesZhejiang University
    • Institute of MicrobiologyZhejiang University
  • Juanping Qiu
    • College of Biological and Environmental EngineeringZhejiang University of Technology
    • Department of Bioinformatics, College of Life SciencesZhejiang University
    • Watson Institute of Genome SciencesZhejiang University
Mini-Review

DOI: 10.1007/s00253-012-4543-9

Cite this article as:
Xu, C., Liu, L., Zhang, Z. et al. Appl Microbiol Biotechnol (2013) 97: 519. doi:10.1007/s00253-012-4543-9

Abstract

In the past few decades, despite all the significant achievements in industrial microbial improvement, the approaches of traditional random mutation and selection as well as the rational metabolic engineering based on the local knowledge cannot meet today’s needs. With rapid reconstructions and accurate in silico simulations, genome-scale metabolic model (GSMM) has become an indispensable tool to study the microbial metabolism and design strain improvements. In this review, we highlight the application of GSMM in guiding microbial improvements focusing on a systematic strategy and its achievements in different industrial fields. This strategy includes a repetitive process with four steps: essential data acquisition, GSMM reconstruction, constraints-based optimizing simulation, and experimental validation, in which the second and third steps are the centerpiece. The achievements presented here belong to different industrial application fields, including food and nutrients, biopharmaceuticals, biopolymers, microbial biofuel, and bioremediation. This strategy and its achievements demonstrate a momentous guidance of GSMM for metabolic engineering breeding of industrial microbes. More efforts are required to extend this kind of study in the meantime.

Keywords

Genome-scale metabolic model Systems biology Metabolic engineering Microbial improvement Industrial application

Copyright information

© Springer-Verlag Berlin Heidelberg 2012