Zhao Xin, Yang Xue, Mao Zhitao, Ma Hongwu
Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sheng Wu Gong Cheng Xue Bao. 2019 Oct 25;35(10):1914-1924. doi: 10.13345/j.cjb.190220.
Genome-scale metabolic network models have been successfully applied to guide metabolic engineering. However, the conventional flux balance analysis only considers stoichiometry and reaction direction constraints, and the simulation results cannot accurately describe certain phenomena such as overflow metabolism and diauxie growth on two substrates. Recently, researchers proposed new constraint-based methods to simulate the cellular behavior under different conditions more precisely by introducing new constraints such as limited enzyme content and thermodynamics feasibility. Here we review several enzyme-constrained models, giving a comprehensive introduction on the biological basis and mathematical representation for the enzyme constraint, the optimization function, the impact on the calculated flux distribution and their application in identification of metabolic engineering targets. The main problems in these existing methods and the perspectives on this emerging research field are also discussed. By introducing new constraints, metabolic network models can simulate and predict cellular behavior under various environmental and genetic perturbations more accurately, and thus can provide more reliable guidance to strain engineering.
基因组规模的代谢网络模型已成功应用于指导代谢工程。然而,传统的通量平衡分析仅考虑化学计量和反应方向约束,其模拟结果无法准确描述某些现象,如溢流代谢和在两种底物上的二次生长。最近,研究人员提出了基于新约束的方法,通过引入诸如有限酶含量和热力学可行性等新约束,更精确地模拟不同条件下的细胞行为。在此,我们综述了几种酶约束模型,全面介绍了酶约束的生物学基础和数学表示、优化函数、对计算通量分布的影响及其在代谢工程靶点识别中的应用。还讨论了这些现有方法中的主要问题以及对这个新兴研究领域的展望。通过引入新约束,代谢网络模型可以更准确地模拟和预测各种环境和遗传扰动下的细胞行为,从而为菌株工程提供更可靠的指导。