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

Abstract

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.

Engineering of membrane phospholipid component enhances salt stress tolerance in Saccharomyces cerevisiae

“…Reverse engineering of cds1 and cho1 was applied to enhance salt stress tolerance, consistent with the demonstration using whole‐genome sequencing in an evolutionary strain that mutation of pyruvate kinase is essential for restoring cell growth and that reintroduction of pyruvate kinase contributes to cell growth (Yu et al, ). Different from traditional metabolic engineering, reverse engineering can quickly locate the key target via metabolic model prediction (Lu et al, ) and multiple omics approaches (Walker et al, ), rather than extensive screening of metabolic pathway genes. Furthermore, membrane‐lipid‐associated genes reported to influence stress tolerance include cis‐trans isomerase Cti (Tan et al, ), PS synthase PssA (Tan et al, ), and desaturase Ole1 (Degreif et al, ).…”

RBA for eukaryotic cells: foundations and theoretical developments

“…Actually, we notice that in genome-scale metabolic models, organelles are usually integrated only through the localization of metabolites. In the latest release of the yeast consensus model [8], the localization of some reactions is added in the reaction name as an annotation. However, the biomass reaction typically integrates the composition of the whole-cell, without distinguishing the composition of organelles.…”

Enzyme-constrained models and omics analysis of Streptomyces coelicolor reveal metabolic changes that enhance heterologous production

“…Hosting the model on GitHub has many advantages: 1) Open access and contribution; 2) Version control; 3) Continuous quality control with memote (Lieven et al, 2018); 4) Continuous development and improvement; 5) New improvements released instantly (no publication lag time); 6) Complete documentation of model reconstruction. Such an approach has historic precedents: model reconstruction as a community effort has been a success for the human GEM (Thiele et al, 2013), baker's yeast (Aung et al, 2013;Dobson et al, 2010;Heavner et al, 2012Heavner et al, , 2013Herrgård et al, 2008;Lu et al, 2019) and Chinese Hamster Ovary cells (Hefzi et al, 2016). The recent developments in S. coelicolor model and strain improvements in different research groups prove that it is an opportune time now to join forces in the Streptomyces modelling efforts as well.…”