eLignin is a curated database of scientific knowledge on microbial degradation of lignin and lignin-derived aromatic compounds. It aims to bring the literature together in a searchable resource to support exploration of the organisms, substrates, pathways, reactions, enzymes, genes, transporters, and references that describe microbial lignin catabolism.
The app can be reached online at https://elignin.serve.scilifelab.se/, or deployed on your local computer (as described below).
eLignin curates empirically reported data from the scientific literature on microorganisms that degrade lignin or metabolize the aromatic compounds it breaks down into, along with the substrates, pathways, reactions, enzymes, and genes involved. It also infers some relationships not explicitly reported in the primary sources; see Data Assumptions for how. eLignin does not include genetically engineered strains. All data in eLignin was added from scientific litterature through manual curation.
The eLignin database was originally developed during a research project on lignin valorisation at Lund University, funded by the Swedish Foundation for Strategic Research (2015–2020). The original eLignin version was deployed from 2016 through 2023 as a closed-source LAMP application. This repository refactors the original eLignin dataset into an open-source, single-container Django application. As part of this work, the eLignin data is released as open-source, human-readable flat files under data/.
The research project in which eLignin was originally developed has finished and new data is not actively added to the database. This single-container repository primarily serves to preserve the project as open-source code and make it available. However, we welcome data contributions and fact-checking corrections.
In addition to the online deployment of eLignin at https://elignin.serve.scilifelab.se/, you can download and run eLignin locally on your own computer.
You will first need to install Docker on your computer. For convenient installation, we recommend Rancher Desktop or Docker Desktop.
Clone the repository and go inside the created directory:
git clone https://github.com/brinkdp/eLignin.git
cd eLigninThen spin up the container with:
docker-compose -f docker-compose.yaml up --build -dThe eLignin web app will be available at http://localhost:8000
Main citations:
If you have used eLignin in your research, we would be grateful if you would cite the following publication:
- Brink, D. P., Ravi, K., Lidén, G. and Gorwa-Grauslund, M. F. (2019). Mapping the diversity of microbial lignin catabolism: experiences from the eLignin database. Applied Microbiology and Biotechnology (DOI: 10.1007/s00253-019-09692-4)
If you want to cite the software and/or the curated dataset (TSV files in data/) in this GitHub repository, please cite the following Zenodo archive in additon to the above publication (Brink et al. 2019):
- Brink, D. P. (2026). The eLignin Microbial Database: a resource for studying microbial lignin degradation [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21935223
Related publication:
We would also like to point users toward the original literature review that eventually led to the creation of the eLignin database:
- Abdelaziz, O. Y., Brink, D. P., Prothmann, J., Ravi, K., Sun, M., García-Hidalgo, J., Sandahl, M., Hulteberg, C. P., Turner, C., Lidén, G. and Gorwa-Grauslund, M. F. (2016). Biological valorization of low molecular weight lignin. Biotechnology Advances, 34 (8), 1318–1346 (DOI: 10.1016/j.biotechadv.2016.10.001)
The code in this repository is MIT-licensed (see LICENSE). The curated data under data/ is licensed separately, under Creative Commons Attribution 4.0 International (CC BY 4.0) (see data/LICENSE). Reuse of the data with attribution is welcome; see the Citation section above for how to cite it.
Found any errors in the data? Have new data that might fit with the scope of the database? Please open an issue!
If you would like to submit a correction directly, the curated data lives as plain tab-separated files in data/ — one per table, with pathway structures as JSON-LD alongside them. Fixing a molecular formula or adding a missing DOI means editing one line in one file and opening a pull request; no SQL, Django, or database tooling required. See data/README.md for the format.
For a larger addition, see the detailed contribute/README.md guide and its annotated pathway template.
The following describes how the GitHub repository is organized. This is mainly aimed at developers and not something that is needed to know in order to run and use the app.
| Path | Purpose |
|---|---|
core/ | Main Django application: data models, views, templates, static assets, and management commands. |
elignin/ | Project-level Django configuration, including settings, URLs, and ASGI/WSGI entry points. |
data/ | Version-controlled source of truth for the curated TSV and pathway JSON-LD data. |
tests/ | Unit, data-integrity, and Docker-backed integration tests. |
contribute/ | Contributor instructions and templates for adding pathway data. |
docs/ | Developer and maintainer documentation. |
eLignin relies on the following software and assets (in additon to general dependencies such as Django and other Python libraries):
Images of chemical compounds are sourced from the PubChem REST API (Kin et al., 2025)
Metabolic pathways are visualized with Cytoscape.js (MIT license; Franz et al., 2016), using the Dagre (MIT license) layout algorithm via the cytoscape.js-dagre (MIT license) extension.
The BioPAX Level 3 ontology (Demir et al., 2010) is used for representing metabolic pathways and reactions (see the Level 3 specification document).
The icons used in the web app come from Bootstrap Icons (MIT license).s
References:
Demir E, Cary MP, Paley S, et al. (2010). The BioPAX community standard for pathway data sharing. Nature Biotechnology. 28 (9), 935–942 (DOI: 10.1038/nbt.1666)
Franz M, Lopes CT, Huck G, Dong Y, Sumer O, Bader GD. (2016). Cytoscape.js: a graph theory library for visualisation and analysis. Bioinformatics. 32 (2), 309–311 (DOI: 10.1093/bioinformatics/btv557)
Kim S, Chen J, Cheng T, et al. (2025). PubChem 2025 update. Nucleic Acids Research. 53 (D1), D1516–D1525 (DOI: 10.1093/nar/gkae1059)