Journal of Fungi (Jun 2024)

Identification of Food Spoilage Fungi Using MALDI-TOF MS: Spectral Database Development and Application to Species Complex

  • Nolwenn Rolland,
  • Victoria Girard,
  • Valérie Monnin,
  • Sandrine Arend,
  • Guillaume Perrin,
  • Damien Ballan,
  • Rachel Beau,
  • Valérie Collin,
  • Maëlle D’Arbaumont,
  • Amélie Weill,
  • Franck Deniel,
  • Sylvie Tréguer,
  • Audrey Pawtowski,
  • Jean-Luc Jany,
  • Jérôme Mounier

DOI
https://doi.org/10.3390/jof10070456
Journal volume & issue
Vol. 10, no. 7
p. 456

Abstract

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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.

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