iMeGroCy-2-vs-iMeGroCy applications.

For unicellular organisms, the reproduction rate and growth are crucial fitness determinants and functional manifestations of the organism genotype. Using the budding yeast Saccharomyces cerevisiae as a model organism, we integrated metabolism, which provides energy and building blocks for growth, with cell mass growth and cell cycle progression into a low-granularity, multiscale (from cell to population) computational model. This model predicted that cells with constitutive respiration do not modulate cell size according to the growth conditions. We experimentally validated the model predictions using mutants with defects in the upper part of glycolysis or glucose transport. Plugging in molecular details of cellular subsystems allowed us to refine predictions from the cellular to the molecular level. Our hybrid multiscale modeling approach provides a framework for structuring molecular knowledge and predicting cell phenotypes under various genetic and environmental conditions.

对于单细胞生物而言，繁殖速率与生长状态是决定其适合度的关键因素，同时也是生物体基因型的功能性表征。本研究以出芽酵母（Saccharomyces cerevisiae）作为模式生物，将为细胞生长提供能量与物质基础的代谢过程，与细胞质量增长及细胞周期进程进行整合，构建了低粒度、多尺度（从单细胞到种群层面）的计算模型。该模型预测，组成型呼吸的细胞不会随生长环境条件调整自身细胞尺寸。我们通过使用糖酵解上游通路或葡萄糖转运存在缺陷的突变株，对模型预测结果开展了实验验证。引入细胞亚系统的分子细节后，我们可将预测精度从细胞层面细化至分子层面。本研究提出的混合多尺度建模方法，为结构化组织分子知识以及预测不同遗传与环境条件下的细胞表型提供了研究框架。