Comprehensive understanding of Saccharomyces cerevisiae phenotypes with whole-cell model WM_S288C
Artikel i vetenskaplig tidskrift, 2020

Biological network construction for Saccharomyces cerevisiae is a widely used approach for simulating phenotypes and designing cell factories. However, due to a complicated regulatory mechanism governing the translation of genotype to phenotype, precise prediction of phenotypes remains challenging. Here, we present WM_S288C, a computational whole-cell model that includes 15 cellular states and 26 cellular processes and which enables integrated analyses of physiological functions of Saccharomyces cerevisiae. Using WM_S288C to predict phenotypes of S. cerevisiae, the functions of 1140 essential genes were characterized and linked to phenotypes at five levels. During the cell cycle, the dynamic allocation of intracellular molecules could be tracked in real-time to simulate cell activities. Additionally, one-third of non-essential genes were identified to affect cell growth via regulating nucleotide concentrations. These results demonstrated the value of WM_S288C as a tool for understanding and investigating the phenotypes of S. cerevisiae.

Saccharomyces cerevisiae

predict phenotypes

cell growth

whole-cell model


Chao Ye

Jiangnan University

Nan Xu

Yangzhou University

Cong Gao

Jiangnan University

Gaoqiang Liu

Central South University of Forestry and Technology

Jianzhong Xu

Jiangnan University

Weiguo Zhang

Jiangnan University

Xiulai Chen

Jiangnan University

Jens B Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

Liming Liu

Jiangnan University

Biotechnology and Bioengineering

0006-3592 (ISSN) 1097-0290 (eISSN)

Vol. 117 5 1562-1574



Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)

Bioinformatik och systembiologi





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