A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism
Journal article, 2019

Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide a platform for model simulations and integrative analysis of omics data. This study introduces Yeast8 and an associated ecosystem of models that represent a comprehensive computational resource for performing simulations of the metabolism of Saccharomyces cerevisiae––an important model organism and widely used cell-factory. Yeast8 tracks community development with version control, setting a standard for how GEMs can be continuously updated in a simple and reproducible way. We use Yeast8 to develop the derived models panYeast8 and coreYeast8, which in turn enable the reconstruction of GEMs for 1,011 different yeast strains. Through integration with enzyme constraints (ecYeast8) and protein 3D structures (proYeast8DB), Yeast8 further facilitates the exploration of yeast metabolism at a multi-scale level, enabling prediction of how single nucleotide variations translate to phenotypic traits.

Author

Hongzhong Lu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Feiran Li

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Benjamín José Sánchez

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Zhengming Zhu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Jiangnan University

Gang Li

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Iván Domenzain Del Castillo Cerecer

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Simonas Marcisauskas

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Petre Mihail Anton

CSBI

Dimitra Lappa

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Christian Lieven

Technical University of Denmark (DTU)

Moritz Emanuel Beber

Technical University of Denmark (DTU)

N. Sonnenschein

Technical University of Denmark (DTU)

Eduard Kerkhoven

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Jens B Nielsen

Technical University of Denmark (DTU)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

BioInnovation Institute

Nature Communications

2041-1723 (ISSN) 20411723 (eISSN)

Vol. 10 1 3586

Subject Categories

Bioinformatics (Computational Biology)

Control Engineering

Computer Science

DOI

10.1038/s41467-019-11581-3

More information

Latest update

11/7/2019