National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
National Energy R&D Center for Biorefinery, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China.
Biotechnol Adv. 2024 May-Jun;72:108319. doi: 10.1016/j.biotechadv.2024.108319. Epub 2024 Jan 26.
The construction of high-performance microbial cell factories (MCFs) is the centerpiece of biomanufacturing. However, the complex metabolic regulatory network of microorganisms poses great challenges for the efficient design and construction of MCFs. The genome-scale metabolic network models (GSMs) can systematically simulate the metabolic regulation process of microorganisms in silico, providing effective guidance for the rapid design and construction of MCFs. In this review, we summarized the development status of 16 important industrial microbial GSMs, and further outline the technologies or methods that continuously promote high-quality GSMs construction from five aspects: I) Databases and modeling tools facilitate GSMs reconstruction; II) evolving gap-filling technologies; III) constraint-based model reconstruction; IV) advances in algorithms; and V) developed visualization tools. In addition, we also summarized the applications of GSMs in guiding metabolic engineering from four aspects: I) exploring and explaining metabolic features; II) predicting the effects of genetic perturbations on metabolism; III) predicting the optimal phenotype; IV) guiding cell factories construction in practical experiment. Finally, we discussed the development of GSMs, aiming to provide a reference for efficiently reconstructing GSMs and guiding metabolic engineering.
构建高性能微生物细胞工厂(MCF)是生物制造的核心。然而,微生物复杂的代谢调控网络给 MCF 的高效设计和构建带来了巨大的挑战。基于基因组规模的代谢网络模型(GSM)可以在计算机上系统模拟微生物的代谢调控过程,为 MCF 的快速设计和构建提供有效的指导。在这篇综述中,我们总结了 16 种重要工业微生物 GSM 的发展现状,并进一步从五个方面概述了不断推动高质量 GSM 构建的技术或方法:I)数据库和建模工具促进 GSM 的重建;II)进化的填补缺口技术;III)基于约束的模型重建;IV)算法的进步;V)开发可视化工具。此外,我们还从四个方面总结了 GSM 在指导代谢工程中的应用:I)探索和解释代谢特征;II)预测遗传扰动对代谢的影响;III)预测最优表型;IV)指导实际实验中的细胞工厂构建。最后,我们讨论了 GSM 的发展,旨在为高效重建 GSM 和指导代谢工程提供参考。