Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Metabolic and Biomolecular Engineering National Research Laboratory, Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Systems Biology and Medicine Laboratory, KAIST, Daejeon, 34141, Republic of Korea.
Genome Biol. 2019 Jun 13;20(1):121. doi: 10.1186/s13059-019-1730-3.
Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for entire metabolic genes in an organism, and can be simulated to predict metabolic fluxes for various systems-level metabolic studies. Since the first GEM for Haemophilus influenzae was reported in 1999, advances have been made to develop and simulate GEMs for an increasing number of organisms across bacteria, archaea, and eukarya. Here, we review current reconstructed GEMs and discuss their applications, including strain development for chemicals and materials production, drug targeting in pathogens, prediction of enzyme functions, pan-reactome analysis, modeling interactions among multiple cells or organisms, and understanding human diseases.
基因组规模代谢模型(GEMs)在计算上描述了生物体中整个代谢基因的基因-蛋白-反应关联,并且可以进行模拟以预测各种系统水平代谢研究的代谢通量。自 1999 年首次报道流感嗜血杆菌的第一个 GEM 以来,已经取得了进展,以开发和模拟越来越多的生物体的 GEM,包括细菌、古细菌和真核生物。在这里,我们回顾了当前重建的 GEM,并讨论了它们的应用,包括用于化学品和材料生产的菌株开发、病原体中的药物靶向、酶功能预测、泛反应组分析、多个细胞或生物体之间的相互作用建模以及人类疾病的理解。