Molecular Genetic Research Laboratory, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Biochem J. 2022 Mar 31;479(6):787-804. doi: 10.1042/BCJ20210596.
Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.
细胞通过调节跨组学网络来响应内部和外部条件改变其代谢，跨组学网络是一个具有多个组学层次的全局生化网络。代谢通量是代谢反应活性的直接度量，为理解复杂的跨组学网络提供了有价值的信息。在过去的几十年中，已经开发出了多种测定代谢通量的技术，包括 13C-代谢通量分析（13C-MFA）、通量平衡分析（FBA）和动力学建模。最近获得定量代谢通量和多组学数据的研究极大地促进了以代谢为中心的跨组学网络的定量理解和预测。在这篇综述中，我们介绍了 13C-MFA、FBA 和动力学建模作为确定定量代谢通量的主要技术，并讨论了它们的优缺点。我们还介绍了一些案例研究，旨在基于代谢通量的测定来理解复杂的以代谢为中心的跨组学网络。
