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Unlocking the potential of experimental evolution to study drug resistance in pathogenic fungi

Summary

Fungal infections are becoming harder to treat as fungi develop resistance to antifungal drugs. This review explains how scientists can use experimental evolution—growing fungi in controlled laboratory conditions while exposing them to drugs—to understand how and why resistance develops. By studying these evolutionary processes and using mathematical models to predict outcomes, researchers can develop better treatment strategies, including combination therapies and drug cycling approaches to prevent resistance from emerging.

Background

Antifungal drug resistance is an emerging global health threat. Traditional methods for studying resistance mechanisms, such as tracking clinical isolates or genome-wide association studies, have significant limitations including confounding variables and inability to isolate resistance-specific effects. Experimental evolution offers a complementary approach that allows controlled, long-term monitoring of resistance development.

Objective

This review highlights the potential of experimental evolution methods to study antifungal resistance in pathogenic fungi and advocates for broader application of these approaches in medical mycology. The authors propose incorporating evolutionary modelling to enhance understanding of resistance evolution and draw insights from bacteriology to advance fungal resistance research.

Results

The review identifies multiple innovative applications of experimental evolution beyond classical molecular mechanism studies, including studies of collateral sensitivity, metabolic state effects, drug tolerance, persistence, spatial heterogeneity, and multi-species interactions. Recent examples in Candida species and Aspergillus fumigatus demonstrate the discovery of novel resistance mechanisms, fitness trade-offs, and therapeutic targets through experimental evolution approaches.

Conclusion

Experimental evolution provides powerful complementary methods to traditional genomic approaches for studying antifungal resistance mechanisms and dynamics. Integration of evolutionary modelling with experimental evolution can enhance predictive understanding of resistance development, and broader adoption of these approaches in medical mycology is warranted to advance antifungal drug resistance research.
  • Published in:NPJ Antimicrobial Resistance,
  • Study Type:Review,
  • Source: PMID: 39843963
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