Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, The Pennsylvania State University, University Park, PA, USA.
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA.
Metab Eng. 2021 Jan;63:13-33. doi: 10.1016/j.ymben.2020.11.013. Epub 2020 Dec 10.
Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both external environmental factors and internal genotypic perturbations. The fundamental concepts of reaction stoichiometry, thermodynamics, and mass action kinetics have emerged as the foundational principles of many modeling frameworks designed to describe how and why organisms allocate resources towards both growth and bioproduction. This review focuses on the latest algorithmic advancements that have integrated these foundational principles into increasingly sophisticated quantitative frameworks.
理解生物体代谢和生长背后的控制原理是将其有效用作生物生产底盘的基础。代谢建模的一个中心目标是预测代谢和生长如何受到外部环境因素和内部基因型扰动的影响。反应计量学、热力学和质量作用动力学的基本概念已成为许多旨在描述生物体如何以及为何将资源分配到生长和生物生产的建模框架的基础原理。本综述重点介绍了将这些基础原理集成到越来越复杂的定量框架中的最新算法进展。
