IVANDOMENZAIN/GECKO

Toolbox for including enzyme constraints on a genome-scale model.

About GECKO 3

The GECKO toolbox enhances a Genome-scale model to account for Enzyme Constraints, using Kinetics and Omics. The resulting enzyme-constrained model (ecModel) can be used to perform simulations where enzyme allocation is either drawn from a total protein pool, or constrained by measured protein levels from proteomics data.

💡 In the GECKO folder, protocol.m contains instructions on how to reconstruct and analyze an ecModel for S. cerevisiae. This demonstrates how many of GECKO's functions can be used.

Note: Regarding code and model compatibility with earlier GECKO versions, see Previous versions: GECKO 1 and 2.

Citation

• A GECKO 3 publication is currently under consideration, citation information will appear here in due course.
• For GECKO release 2, please cite Domenzain et al. (2022) doi:10.1038/s41467-022-31421-1.
• For GECKO release 1, please cite Sánchez et al. (2017) doi:10.15252/msb.20167411.

Getting started

Required software

• MATLAB version 2019b or later, no additional MathWorks toolboxes are required.
• RAVEN Toolbox version 2.7.12 or later. The RAVEN Toolbox Wiki contains installation instructions for both RAVEN and Gurobi. Briefly, RAVEN is either downloaded via git clone, as ZIP-archive from GitHub, or installed as a MATLAB AddOn. After finishing all installation instructions, the user should run installation checks in MATLAB with: checkInstallation.
• Gurobi Optimizer is recommended for simulations (free academic license available). Alternatively, the open-source GNU Linear Programming Kit (distributed with RAVEN) or SoPlex as part of the SCIP Optimization Suite can be used.
• Docker for running DLKcat. Installation instructions are available at https://docs.docker.com/get-docker .

Installation

• The preferred way to download GECKO is via git clone:

git clone --depth=1 https://github.com/SysBioChalmers/GECKO

• Alternatively, a ZIP-archive can be directly downloaded from GitHub. The ZIP-archive should be extracted to a disk location where the user has read- and write-access rights.

• After git clone or extracting the ZIP-archive, the user should navigate in MATLAB to the GECKO folder. GECKO can then be installed with the command that adds GECKO (sub-)folders to the MATLAB path::

  cd('C:\path\to\GECKO') % Modify to match GECKO folder and operating system
  GECKOInstaller.install

• If desired, a removal command is available as::

  GECKOInstaller.uninstall

All set! 🚀

Previous versions: GECKO 1 and 2

Due to significant refactoring of the code, GECKO version 3 is largely not backwards compatible with earlier GECKO versions.

• Most notably, GECKO 3 ecModels have an .ec structure containing all enzyme and kcat information.
• In addition, in GECKO 3 enzymes are incorporated in the S-matrix as MW/kcat, while in GECKO 1 and 2 this was 1/kcat (where the MW was instead considered in the protein exchange reactions).
• GECKO 3 ecModels can be stored in YAML file format that retains all model content.
• Most functions in GECKO 3 do not work on ecModels generated with GECKO versions 1 or 2.
• ecModels generated in GECKO 3 do not work with functions from GECKO versions 1 or 2.
• At this moment, there are no Python functions to work with GECKO 3 formatted ecModels.
• The last GECKO 2 release (2.0.3) is available here.
• The gecko2 branch remains available for any potential fixes.

Contributing

Contributions are always welcome! Please read the contributing guidelines to get started.