The Growth-Coupling Suite is a framework for computing and analyzing strain designs that couple a target reaction to growth. gcOpt is used as the underlying optimization algorithm for deriving growth-coupled strain design solutions.
For a detailed installation manual, refer to the "docs" folder in this repository. The Growth Coupling Suite has been tested in Python >3.8. It is recommended to create a virtual python environment with, e.g., conda or virtualenv, for installing and using the Growth Coupling Suite.
- Clone/fork/download this repository
- Browse to the main directory of the repository and run
pip install .orpip install -e .(for code development purposes). This will install all packages (cf. requirements.txt) - (optional) If a heterologous reactiond database model needs to be built, run
python -c "from equilibrator_api import ComponentContribution; cc = ComponentContribution()"to initialize the equilibrator API (documentation)
Refer to and run the example scripts in 'examples' (conduct_gcOpt_optimization_parallel, conduct_gcOpt_optimization_single) for an introduction setting up and using the Growth Coupling Suite.
Once design solutions were found and analyzed with the StrainDesignAnalyzer (part of the Growth Coupling Suite), a summary including unique, valid strain designs and their metadata is saved in an Excel format to the specified location (cf. the parameter 'results_dir' of the 'growth_coupling_summary' function).
The first computation with a new model can be quite time consuming due to the curation of the heterologous reaction database, if heterologous insertions are allowed (num_addins>0 in the gcOpt_config_file). The database will automatically be saved for later applications of that model. A heterologous reaction database model can be manually built and saved beforehand by using the 'heterologous_reaction_processing' module. Refer to 'tests/create_heterologous_reaction_database_model.ipynb' for a respective example.
If you use the Growth-Coupling Suite in your research or find it helpful for your work, please cite the following paper:
Metabolic growth-coupling strategies for in vivo enzyme selection systems
Tobias B. Alter, Pascal A. Pieters, Colton J. Lloyd, Adam M. Feist, Emre Özdemir, Bernhard O. Palsson, Daniel C. Zielinski
Metabolic Engineering Communications, 2025
DOI or URL: https://doi.org/10.1016/j.mec.2025.e00257