Identification of Food Spoilage Fungi Using MALDI-TOF MS: Spectral Database Development and Application to Species
Nolwenn Rolland1,2, Victoria Girard1, Valérie Monnin1
1bioMérieux, R&D Microbiologie, Route de Port Michaud, F-38390 La Balme les Grottes, France.
Abstract:
Fungi, including filamentous fungi and yeasts, are major contributors to global food losses and waste due to their ability to colonize a very large diversity of food raw materials and processed foods throughout the food chain. In addition, numerous fungal species are mycotoxin producers and can also be responsible for opportunistic infections. In recent years, MALDI-TOF MS has emerged as a valuable, rapid and reliable asset for fungal identification in order to ensure food safety and quality. In this context, this study aimed at expanding the VITEK® MS database with food-relevant fungal species and evaluate its performance, with a specific emphasis on species differentiation within species complexes. To this end, a total of 380 yeast and mold strains belonging to 51 genera and 133 species were added into the spectral database including species from five species complexes corresponding to Colletotrichum acutatum, Colletotrichum gloeosporioides, Fusarium dimerum, Mucor circinelloides complexes and Aspergillus series nigri. Database performances were evaluated by cross-validation and external validation using 78 fungal isolates with 96.55% and 90.48% correct identification, respectively. This study also showed the capacity of MALDI-TOF MS to differentiate closely related species within species complexes and further demonstrated the potential of this technique for the routine identification of fungi in an industrial context.
Insights
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) enhances fungal identification in food safety. Expanding the VITEK® MS database improves accuracy, particularly for differentiating closely related species.
Area of Science:
- Food microbiology
- Analytical chemistry
- Mycology
Background:
- Fungi cause significant food loss and produce mycotoxins.
- Accurate fungal identification is crucial for food safety and quality.
- MALDI-TOF MS offers rapid and reliable fungal identification.
Purpose of the Study:
- Expand the VITEK® MS database with food-relevant fungal species.
- Evaluate the performance of the expanded database for fungal identification.
- Assess the ability of MALDI-TOF MS to differentiate species within complexes.
Main Methods:
- Added 380 yeast and mold strains (51 genera, 133 species) to the VITEK® MS database.
- Included species from five major fungal complexes (e.g., Aspergillus, Fusarium, Colletotrichum).
- Validated database performance using cross-validation and external testing with 78 isolates.
Main Results:
- Achieved 96.55% correct identification via cross-validation.
- Reached 90.48% correct identification in external validation.
- Demonstrated MALDI-TOF MS capability in differentiating closely related fungal species.
Conclusions:
- The expanded VITEK® MS database improves fungal identification accuracy.
- MALDI-TOF MS is effective for routine fungal identification in industrial settings.
- This technique aids in ensuring food safety and quality by enabling precise fungal detection.
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