Biology Department, Brookhaven National Laboratory, Upton, New York 11973, USA; email:
Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, USA; email:
Annu Rev Plant Biol. 2020 Apr 29;71:303-326. doi: 10.1146/annurev-arplant-050718-100221. Epub 2020 Feb 4.
Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.
植物代谢的数学建模使植物科学界能够理解植物代谢的组织,深入了解代谢功能,并获得用于代谢操纵的工程策略。在各种建模方法中,代谢途径分析可以剖析核心代谢的各个部分的基本功能模式,例如光呼吸,并揭示经典的代谢途径定义如何具有重叠的功能。在植物中使用基于约束的建模的许多研究中,目前有许多计算工具可用于分析大规模和基因组规模的代谢网络。对于 C 代谢通量分析,同位素稳态的原理已被用于研究异养植物组织,而非稳态同位素标记方法适用于光自养和次生代谢的研究。酶动力学模型详细探讨了途径,我们讨论了确定或估计动力学参数的不同方法。在这篇综述中,我们描述了植物代谢建模的最新进展和挑战。