A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism
Artikel i vetenskaplig tidskrift, 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.

Författare

Hongzhong Lu

Chalmers, Biologi och bioteknik, Systembiologi

Feiran Li

Chalmers, Biologi och bioteknik, Systembiologi

Benjamín José Sánchez

Chalmers, Biologi och bioteknik, Systembiologi

Zhengming Zhu

Chalmers, Biologi och bioteknik, Systembiologi

Jiangnan University

Gang Li

Chalmers, Biologi och bioteknik, Systembiologi

Iván Domenzain Del Castillo Cerecer

Chalmers, Biologi och bioteknik, Systembiologi

Simonas Marcisauskas

Chalmers, Biologi och bioteknik, Systembiologi

Petre Mihail Anton

CSBI

Dimitra Lappa

Chalmers, Biologi och bioteknik, Systembiologi

Christian Lieven

Danmarks Tekniske Universitet (DTU)

Moritz Emanuel Beber

Danmarks Tekniske Universitet (DTU)

N. Sonnenschein

Danmarks Tekniske Universitet (DTU)

Eduard Kerkhoven

Chalmers, Biologi och bioteknik, Systembiologi

Jens B Nielsen

Danmarks Tekniske Universitet (DTU)

Chalmers, Biologi och bioteknik, Systembiologi

BioInnovation Institute

Nature Communications

2041-1723 (ISSN)

Vol. 10 1 3586

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Reglerteknik

Datavetenskap (datalogi)

DOI

10.1038/s41467-019-11581-3

Mer information

Senast uppdaterat

2019-11-07