Vanoni Marco, Palumbo Pasquale, Papa Federico, Busti Stefano, Gotti Laura, Wortel Meike, Teusink Bas, Orlandi Ivan, Pessina Alex, Airoldi Cristina, Brambilla Luca, Vai Marina, Alberghina Lilia
SYSBIO Centre for Systems Biology, Milan, Italy.
Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy.
PLoS Comput Biol. 2025 Jul 21;21(7):e1013296. doi: 10.1371/journal.pcbi.1013296. eCollection 2025 Jul.
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,繁殖率和生长是至关重要的适应性决定因素,也是生物体基因型的功能表现。我们以出芽酵母酿酒酵母作为模式生物,将为生长提供能量和构建模块的代谢过程,与细胞质量增长和细胞周期进程整合到一个低粒度、多尺度(从细胞到群体)的计算模型中。该模型预测,组成型呼吸的细胞不会根据生长条件调节细胞大小。我们使用糖酵解上游或葡萄糖转运存在缺陷的突变体,通过实验验证了模型预测。纳入细胞子系统的分子细节使我们能够将预测从细胞水平细化到分子水平。我们的混合多尺度建模方法为构建分子知识以及预测各种遗传和环境条件下的细胞表型提供了一个框架。