Advances in the development of constraint-based genome-scale metabolic network models.

Jingru Zhou; Peng Liu; Jianye Xia; Yingping Zhuang

Return

Advances in the development of constraint-based genome-scale metabolic network models.

Author: Jingru ZHOU ¹ ; Peng LIU ¹ ; Jianye XIA ¹ ; Yingping ZHUANG ¹
Author Information

1. State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China.
Publication Type:Review
Keywords: constrained methods; genome-scale metabolic network model; mathematical modeling; multi-omics; thermodynamics
MeSH: Genome/genetics*; Metabolic Engineering; Metabolic Networks and Pathways/genetics*; Models, Biological; Proteomics
From: Chinese Journal of Biotechnology 2021;37(5):1526-1540
CountryChina
Language:Chinese
Abstract: Genome-scale metabolic network model (GSMM) is becoming an important tool for studying cellular metabolic characteristics, and remarkable advances in relevant theories and methods have been made. Recently, various constraint-based GSMMs that integrated genomic, transcriptomic, proteomic, and thermodynamic data have been developed. These developments, together with the theoretical breakthroughs, have greatly contributed to identification of target genes, systems metabolic engineering, drug discovery, understanding disease mechanism, and many others. This review summarizes how to incorporate transcriptomic, proteomic, and thermodynamic-constraints into GSMM, and illustrates the shortcomings and challenges of applying each of these methods. Finally, we illustrate how to develop and refine a fully integrated GSMM by incorporating transcriptomic, proteomic, and thermodynamic constraints, and discuss future perspectives of constraint-based GSMM.