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New approaches to tackle a rising problem: Large-scale methods to study antifungal resistance

Summary

Fungal infections are becoming increasingly resistant to antifungal drugs, creating a serious public health challenge. Scientists are using advanced genetic sequencing and laboratory techniques to understand how fungi develop drug resistance and identify the specific genetic changes responsible. By cataloging resistance mutations and creating shared databases, researchers aim to develop better diagnostic tests and treatment strategies to combat these dangerous infections.

Background

Fungi are major pathogens causing millions of infections and deaths annually, with drug-resistant fungi representing an especially serious concern due to the limited number of available antifungal treatments. The rise in both intrinsic and acquired resistance in clinical and field isolates poses an alarming public health challenge in a ‘One Health’ context affecting humans, animals, and plants.

Objective

This review examines recent advances in genomics and large-scale experimental assays to identify mutations and mechanisms underlying antifungal resistance. The authors discuss progress in assembling databases of resistance-associated genes and variants, and explore how these resources can inform development of new diagnostic tools for clinical and field applications.

Results

Large-scale sequencing and experimental evolution have identified multiple genes and mechanisms mediating antifungal resistance including mutations in ERG11/CYP51, PDR1, FKS, and TUB genes. MAVEs have cataloged hundreds to thousands of protein variants and their effects on both resistance and fitness, revealing variable trade-offs depending on the drug target examined.

Conclusion

Integration of genomic, functional genomics, and systems biology approaches provides comprehensive understanding of antifungal resistance evolution and mechanisms. Development of centralized community databases and improved data integration frameworks will maximize the utility of these resources for clinical diagnostics and resistance surveillance.
  • Published in:PLoS Pathogens,
  • Study Type:Review,
  • Source: PMID: 39236046, DOI: 10.1371/journal.ppat.1012478
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