This repository contains the consensus genome-scale metabolic model Sco-GEM for the antibiotic producer Streptomyces coelicolor A3(2), a representative species of soil-dwelling, filamentous and gram-positive actinobacterium harbouring enriched secondary metabolite biosynthesis gene clusters. As a well-known pharmaceutical and bioactive compound producer, S. coelicolor has been exploited for antibiotic and secondary metabolite production.
S. Sulheim, T. Kumelj, D. van Dissel, A. Salehzadeh-Yazdi, C. Du, G.P. van Wezel, K. Nieselt, E. Almaas, A. Wentzel, E.J. Kerkhoven (2020). Enzyme-constrained models and omics analysis of Streptomyces coelicolor reveal metabolic changes that enhance heterologous production. iScience, 23(9), 101525 doi:10.1016/j.isci.2020.101525, pmid:32942174
The Sco-GEM model distributed on this GitHub repository is continuously updated, with the latest releases available here. To get access to the models, data and code associated to the Sulheim et al. (2020) publication, use Sco-GEM release 1.2.1.
Utilisation: Predictive simulation; Multi-omics integrative analysis
Field: Metabolic-network reconstruction
Type of model: Curated reconstruction
Model source: iKS1317
Omic source: Genomics; Transcriptomics; Proteomics
Taxonomic name: Streptomyces coelicolor
Taxonomy ID: taxonomy:100226
Genome ID: insdc.gca:GCA_000203835.1
Metabolic system: General metabolism (primary and secondary)
Strain: A3(2)
Condition: Complex medium
Taxonomy | Template Model | Reactions | Metabolites | Genes | Memote score |
---|---|---|---|---|---|
Streptomyces coelicolor A3(2) | iKS1317 | 2599 | 2064 | 1775 | 72% |
To obtain Sco-GEM, clone it from master
in the GitHub repository, or just download the latest release.
Sco-GEM is distributed in SBML L3V1 FBCv1 format (model/Sco-GEM.xml
), and therefore works well with any appropriate constraint-based modelling package, such as cobrapy, RAVEN Toolbox and COBRA Toolbox. Installation instructions for each package are provided on their website, after which you can use their default functions for loading and exporting of the models:
cobrapy
import cobra
model = cobra.io.read_sbml_model('Sco-GEM.xml')
cobra.io.write_sbml_model(model, 'Sco-GEM.xml')
RAVEN Toolbox *
model = importModel('Sco-GEM.xml')
exportModel(model, 'Sco-GEM.xml')
COBRA Toolbox *
model = readCbModel('Sco-GEM.xml')
writeCbModel(model, 'Sco-GEM.xml')
* note that some annotation might be lost when exporting the model from RAVEN and COBRA Toolboxes
Development of the model is done via cobrapy, to ensure that model content is retained as much as possible (I/O through other software might result in undesired loss of annotation). Therefore, make sure you have Python 3.6+ installed.
Fork the Sco-GEM repository to your own GitHub account, and create a new branch from devel
.
In Python, create an environment with all requirements:
pip install -r requirements.txt # installs all dependencies
touch .env # creates a .env file for locating the root, required
Load the model using the default code specified above. Export the model with the export
function provided in the repository:
cd ./code
import export
export.export(model, formats = ['xml', 'yml'])
More information on contributing to Sco-GEM can be found in the contributing guidelines, read these to get started. Contributions are always welcome!