TY - JOUR
T1 - Genome-scale metabolic model in guiding metabolic engineering of microbial improvement
AU - Xu, Chuan
AU - Liu, Lili
AU - Zhang, Zhao
AU - Jin, Danfeng
AU - Qiu, Juanping
AU - Chen, Ming
N1 - Funding Information:
Acknowledgment The authors are grateful to the supports by the major special project of science and technology of Zhejiang province, China (No. 2008C12G2020010), the Fundamental Research Funds for the Central Universities, and the NSFC project, China (No. 30971743).
PY - 2013/1
Y1 - 2013/1
N2 - 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.
AB - 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.
KW - Genome-scale metabolic model
KW - Industrial application
KW - Metabolic engineering
KW - Microbial improvement
KW - Systems biology
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U2 - 10.1007/s00253-012-4543-9
DO - 10.1007/s00253-012-4543-9
M3 - Review article
C2 - 23188456
AN - SCOPUS:84873997973
SN - 0175-7598
VL - 97
SP - 519
EP - 539
JO - Applied Microbiology and Biotechnology
JF - Applied Microbiology and Biotechnology
IS - 2
ER -