Long Christopher P, Antoniewicz Maciek R
Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, Newark DE 19716, USA.
Curr Opin Chem Eng. 2018 Dec;22:209-215. doi: 10.1016/j.coche.2018.11.001. Epub 2018 Nov 26.
Adaptive laboratory evolution (ALE) has emerged as a powerful tool in basic microbial research and strain development. In the context of metabolic science and engineering, it has been applied to study gene knockout responses, expand substrate ranges, improve tolerance to process conditions, and to improve productivity via designed growth coupling. In recent years, advancements in ALE methods and systems biology measurement technologies, particularly genome sequencing and C metabolic flux analysis (C-MFA), have enabled detailed study of the mechanisms and dynamics of evolving metabolism. In this review, we discuss a range of studies that have applied flux analysis to adaptively evolved strains, as well as modeling frameworks developed to predict and interpret evolved fluxes. These efforts link mutations to fitness-enhanced phenotypes, identify bottlenecks and approaches to resolve them, and address systems concepts such as optimality.
适应性实验室进化（ALE）已成为基础微生物研究和菌株开发中的一种强大工具。在代谢科学与工程领域，它已被应用于研究基因敲除反应、扩大底物范围、提高对工艺条件的耐受性以及通过设计生长偶联提高生产力。近年来，ALE方法和系统生物学测量技术的进步，特别是基因组测序和C代谢通量分析（C-MFA），使得对代谢进化的机制和动态进行详细研究成为可能。在本综述中，我们讨论了一系列将通量分析应用于适应性进化菌株的研究，以及为预测和解释进化通量而开发的建模框架。这些工作将突变与适应性增强的表型联系起来，识别瓶颈及其解决方法，并涉及诸如最优性等系统概念。
