Dictyosteliumdiscoideum–Mycobacterium marinum infection model: a powerful high-throughput screening platform for anti-infective compounds
Tuberculosis is among the world's deadliest diseases, causing approximately 2 million deaths annually. The urgent need for new antitubercular drugs has been intensified by the rise of drug-resistant strains. Despite recent advancements, most hits identified through traditional target-based screening approaches exhibit limited efficacy <i>in vivo</i>. Consequently, there is a growing demand for whole-cell-based approaches that utilize host-pathogen systems directly. The <i>Dictyostelium discoideum</i>-<i>Mycobacterium marinum</i> host-pathogen system is a well-established and powerful alternative model system for studying mycobacterial infections. In this article, we present a phenotypic host-pathogen assay protocol that monitors <i>M. marinum</i> during infection of the amoeba <i>D. discoideum</i>. This assay is characterized by its scalability for high-throughput screening, robustness, and ease of manipulation, making it an effective system for compound screening. Notably, this system provides dual readouts: bacterial load via a bioluminescent <i>M. marinum</i> strain and host survival and growth via a fluorescent <i>D. discoideum</i> strain, enabling further host characterization by quantifying growth inhibition and potential cytotoxicity. Finally, the assay was benchmarked against selected antibiotics and anti-infectives, and IC<sub>50</sub>s and MIC values were calculated where applicable, demonstrating its ability to differentiate between antibiotics and anti-infective compounds.
Authors
- Thierry Soldati (ORCID: https://orcid.org/0000-0002-2056-7931)
- Jahn Nitschke (ORCID: https://orcid.org/0000-0003-3838-0945)
- Nabil Hanna (ORCID: https://orcid.org/0000-0002-3288-5486)
Institutions
- University of Geneva (CH)
Publication Details
- Journal
- Frontiers in Microbiology
- Published
- 2025-07-04
- DOI
- https://doi.org/10.3389/fmicb.2025.1612354
- Citations
- 4
- Primary Topic
- Mycobacterium research and diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 5.42
Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Université de Genève