yeast-GEM: The consensus genome-scale metabolic model of Saccharomyces cerevisiae

• Brief Model Description:

This repository contains the current consensus genome-scale metabolic model of Saccharomyces cerevisiae. It is the continuation of the legacy project yeastnet. For the latest release please click here.

• Model KeyWords:

GEM Category: species; Utilisation: experimental data reconstruction, multi-omics integrative analysis, in silico strain design, model template; Field: metabolic-network reconstruction; Type of Model: reconstruction, curated; Model Source: YeastMetabolicNetwork; Omic Source: genomics, metabolomics; Taxonomy: Saccharomyces cerevisiae; Metabolic System: general metabolism; Bioreactor; Strain: S288C; Condition: aerobic, glucose-limited, defined media;

• Last update: 2019-05-21

• Main Model Descriptors:

Taxonomy	Template Model	Reactions	Metabolites	Genes
Saccharomyces cerevisiae	Yeast 7.6	3991	2691	1149

This repository is administered by Benjamín J. Sánchez (@BenjaSanchez), Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology.

Installation

Required Software - User:

• Matlab user:
  • A functional Matlab installation (MATLAB 7.3 or higher).
  • The COBRA toolbox for MATLAB.
• Python user:
  • Python 2.7, 3.4, 3.5 or 3.6
  • cobrapy

Required Software - Contributor:

• Both of the previous Matlab requirements.
• The RAVEN toolbox for MATLAB.
• A git wrapper added to the search path.

Dependencies - Recommended Software:

• For Matlab, the libSBML MATLAB API (version 5.17.0 is recommended).
• Gurobi Optimizer for any simulations.

Installation Instructions

• For users: Clone it from master in the Github repo, or just download the latest release.
• For contributors: Fork it to your Github account, and create a new branch from devel.

Usage

Make sure to load/save the model with the corresponding wrapper functions!

• In Matlab:
  • Loading: complementaryScripts/loadYeastModel.m
  • Saving: complementaryScripts/saveYeastModel.m
• In Python:
  • Loading: complementaryScripts/loadYeastModel.py
  • Saving: currently unavailable

Model Files

The model is available in .xml, .txt, .yml, .mat and .xlsx (the last 2 extensions only in master). Additionally, the following 2 files are available:

• dependencies.txt: Tracks versions of toolboxes & SBML used for saving the model.
• boundaryMets.txt: Contains a list of all boundary metabolites in model, listing the id and name.

Complementary Scripts

• missingFields: Folder with functions for adding missing fields to the model.
• modelCuration: Folder with curation functions.
• otherChanges: Folder with other types of changes.
• increaseVersion.m: Updates the version of the model in version.txt and as metaid in the .xml file. Saves the model as .mat and as .xlsx
• loadYeastModel.m: Loads the yeast model from the .xml file for Matlab.
• loadYeastModel.py: Loads the yeast model from the .xml file for Python.
• saveYeastModel.m: Saves yeast model as a .xml, .yml and .txt file, and updates boundaryMets.txt and dependencies.txt.

Complementary Data

• databases: Yeast data from different databases (KEGG, SGD, swissprot, etc).
• modelCuration: Data files used for performing curations to the model. Mostly lists of new rxns, mets or genes added (or fixed) in the model.
• physiology: Data on yeast growth under different conditions, biomass composition, gene essentiality experiments, etc.

Citation

• All yeast-GEM releases are archived in Zenodo, for you to cite the specific version of yeast-GEM that you used in your study. Find the corresponding DOI here.

• Additionally, if you would like to cite the yeast-GEM project, you may also refer to the yeast 7 paper, and point to the new link in the text, e.g.: "The yeast consensus genome-scale model [Aung et al. 2013], which is currently being hosted at https://github.com/SysBioChalmers/yeast-GEM, [...]".

• Finally, if you would like to cite the idea of hosting a genome-scale model in Github, you may also refer to the RAVEN 2 paper, which mentions this idea and exemplifies it on Streptomyces_coelicolor-GEM.

Contributing

Contributions are always welcome! Please read the contributions guideline to get started.

Contributors

• Mihail Anton (@mihai-sysbio), Chalmers University of Technology, Sweden
• Moritz Beber (@Midnighter), Danish Technical University, Denmark
• Eduard J. Kerkhoven (@edkerk), Chalmers University of Technology, Sweden
• Dimitra Lappa (@demilappa), Chalmers University of Technology, Sweden
• Feiran Li (@feiranl), Chalmers University of Technology, Sweden
• Christian Lieven (@ChristianLieven), Danish Technical University, Denmark
• Hongzhong Lu (@hongzhonglu), Chalmers University of Technology, Sweden
• Simonas Marcišauskas (@simas232), Chalmers University of Technology, Sweden
• Thomas Pfau (@tpfau), University of Luxembourg, Luxembourg
• Benjamín J. Sánchez (@BenjaSanchez), Chalmers University of Technology, Sweden