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 3586Subject Categories
Bioinformatics (Computational Biology)
Control Engineering
Computer Science
DOI
10.1038/s41467-019-11581-3