Kluyveromyces_marxianus-GEM: The consensus genome-scale metabolic model of Kluyveromyces marxianus

• Brief Model Description:

This repository contains the current consensus genome-scale metabolic model of the ascomycetous yeast Kluyveromyces marxianus, named Kluyveromyces_marxianus-GEM. The model contains 4 compartments: extracellular, cytosol, mitochondrion and endoplasmic reticulum. 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: iOD907, yeast-GEM; Omic Source: genomics; Taxonomy: Kluyveromyces marxianus; Metabolic System: general metabolism; Bioreactor; Strain; Condition: aerobic, glucose-limited, defined media;

• Last update: 2019-11-16

• Main Model Descriptors:

Taxonomy	Template Model	Reactions	Metabolites	Genes
Kluyveromyces marxianus	iOD907	1913	1531	996

This repository is administered by Simonas Marcišauskas (@simas232), 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 (2016b 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: code/loadKmxModel.m
  • Saving: code/saveKmxModel.m
• In Python:
  • Loading: code/loadKmxModel.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 Code

• missingFields: Folder with functions for adding missing fields to the model.
• modelCuration: Folder with curation functions.
• otherChanges: Folder with other types of changes.
• increaseKmxVersion.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
• loadKmxModel.m: Loads the yeast model from the .xml file for MATLAB.
• loadKmxModel.py: Loads the yeast model from the .xml file for Python.
• saveKmxModel.m: Saves yeast model as a .xml, .yml and .txt file, and updates boundaryMets.txt and dependencies.txt.

Complementary Data

• biomassComposition: The detailed information about the biomass composition considered in the model.
• proteome: The list of all proteins for DMKU3-1042 strain. Useful when one wants to convert K. marxianus genes to S. cerevisiae and perform gene knockout simulations.

Citation

Marcišauskas S, Ji B, Nielsen J (2019). Reconstruction and analysis of a Kluyveromyces marxianus genome-scale metabolic model. BMC Bioinformatics 20:551. doi:10.1186/s12859-019-3134-5

Contributing

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

Contributors

• Simonas Marcišauskas (@simas232), Chalmers University of Technology, Sweden

More from SysBio Chalmers

For more recently published genome-scale models and systems biology related software from the Systems and Synthetic Biology group at Chalmers University of Technology, please visit the GitHub page. For more information and publications by the Systems and Synthetic Biology please visit SysBio.