Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. This study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

中文翻译：

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酿酒酵母有序和动态代谢的出现

微生物代谢是一个基本的细胞过程，涉及许多生化事件，并以其新兴特性而著称。虽然单个反应的分子细节已被越来越多地阐明，但人们尚不清楚这些反应如何定量地协调以产生集体细胞行为。在这里，我们开发了一个粗粒度、系统和动态的数学框架，它将代谢反应与信号转导和基因调控结合起来，以剖析酿酒酵母的新兴代谢特征。我们的框架机械地捕获了一组特征性细胞行为，包括克拉布特里效应、双轴转变、双轴滞后时间和营养改变环境下的差异生长。它还允许模块化扩展，以放大特定途径以获得详细的代谢概况。这项研究为酵母代谢行为提供了一个系统数学框架，为酵母生理学和代谢工程提供了见解。