MYCOLab Ai Logo - gold and army green

Identification of Challenging Dermatophyte Species Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Summary

This study shows that a specialized technique called MALDI-TOF mass spectrometry can accurately identify fungal skin infections by analyzing protein patterns. Researchers created a customized library of local fungal species that, when combined with commercial databases, improved identification accuracy from 16% to 91%. This advancement helps doctors quickly identify the exact type of fungal infection patients have, enabling faster and more appropriate treatment decisions.

Background

MALDI-TOF MS is widely used for bacterial and yeast identification but is less frequently applied to filamentous fungi due to inconsistent performance and limited commercial libraries. Dermatophytes pose diagnostic challenges due to morphological similarities and lack of standardized identification methods.

Objective

This study aimed to validate the efficiency of MALDI-TOF MS-based dermatophyte identification using the Bruker Biotyper system by establishing and evaluating an in-house reference library combined with commercial libraries for improved species-level identification.

Results

The expanded library achieved 90.7% (107/118) species-level identification accuracy compared to only 16.1% (19/118) by the Bruker library alone. Identification rates ranged from 88.0-100% for Trichophyton species, 100% for Microsporum canis, and 75.0-100% for Nannizzia species, with statistically significant improvements demonstrated across most species.

Conclusion

The study validates an efficient, standardized MALDI-TOF MS protocol for routine dermatophyte identification and demonstrates that supplementing commercial libraries with in-house reference spectra from regional isolates is critical for accurate species-level identification of challenging dermatophytes in clinical laboratories.
  • Published in:Journal of Fungi (Basel),
  • Study Type:Validation Study,
  • Source: PMID: 39997401
Scroll to Top