Comprehensive understanding of Saccharomyces cerevisiae phenotypes with whole-cell model WM_S288C

Biotechnol Bioeng. 2020 May;117(5):1562-1574. doi: 10.1002/bit.27298. Epub 2020 Feb 13.

Abstract

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.

Keywords: Saccharomyces cerevisiae; cell growth; predict phenotypes; whole-cell model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Extracellular Space / metabolism
  • Genome, Fungal / genetics
  • Genotype
  • Models, Biological*
  • Phenotype
  • Saccharomyces cerevisiae* / cytology
  • Saccharomyces cerevisiae* / genetics
  • Saccharomyces cerevisiae* / growth & development
  • Saccharomyces cerevisiae* / metabolism