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

Summary

This study shows that MALDI-TOF mass spectrometry is an effective method for quickly identifying skin fungal infections caused by dermatophytes. By combining commercial reference databases with a custom library created from local isolates, researchers achieved 90.7% accurate identification compared to only 16.1% using the commercial database alone. This improved method could help doctors diagnose and treat fungal skin infections more quickly and accurately in clinical laboratories.

Background

MALDI-TOF MS is widely used for bacterial and yeast identification but less frequently applied to filamentous fungi due to inconsistent performance and limitations of commercial libraries. Dermatophytes are key fungal pathogens causing various skin infections, and accurate species-level identification is important for epidemiological data and infection control.

Objective

This study aimed to validate the efficiency of MALDI-TOF MS-based dermatophyte identification using the Bruker Biotyper system by establishing an in-house reference library and evaluating its performance compared to commercial libraries alone.

Results

The expanded library achieved 90.7% accuracy (107/118 isolates) at species level compared to 16.1% with Bruker library alone. For Trichophyton species, the expanded library identified 88.0-100% of isolates; for Nannizzia, 75.0-100%; and for Microsporum canis, 100% at log score cutoff of 1.7.

Conclusion

The standardized MALDI-TOF MS protocol combined with an in-house reference library significantly improves dermatophyte identification accuracy. The in-house library supplements commercial databases to overcome limitations and improve identification of challenging species, making MALDI-TOF MS a practical tool for routine clinical dermatophyte identification.
  • Published in:Journal of Fungi,
  • Study Type:Validation Study,
  • Source: 10.3390/jof11020107; PMID: 39997401
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