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

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.

Development and application of MALDI-TOF MS for identification of food spoilage fungi.

Filamentous fungi are frequently involved in food spoilage and cause important food losses and substantial economic damage. Their rapid and accurate identification is a key step to better manage food safety and quality. In recent years, MALDI-TOF MS has emerged as a powerful tool to identify microorganisms and has successfully been applied to the identification of filamentous fungi especially in the clinical context. The aim of this study was to implement a spectral database representative of food spoilage molds. To this end, after application of a standardized extraction protocol, 6477 spectra were acquired from 618 fungal strains belonging to 136 species and integrated in the VITEK MS database. The performances of this database were then evaluated by cross-validation and ∼95% of correct identification to the species level was achieved, independently of the cultivation medium and incubation time. The database was also challenged with external isolates belonging to 52 species claimed in the database and 90% were correctly identified to the species level. To our best knowledge, this is the most comprehensive database of food-relevant filamentous fungi developed to date. This study demonstrates that MALDI-TOF MS could be an alternative to conventional techniques for the rapid and reliable identification of spoilage fungi in food and industrial environments.

A MALDI-TOF MS database with broad genus coverage for species-level identification of Brucella.

Brucella are highly infectious bacterial pathogens responsible for a severely debilitating zoonosis called brucellosis. Half of the human population worldwide is considered to live at risk of exposure, mostly in the poorest rural areas of the world. Prompt diagnosis of brucellosis is essential to prevent complications and to control epidemiology outbreaks, but identification of Brucella isolates may be hampered by the lack of rapid and cost-effective methods. Nowadays, many clinical microbiology laboratories use Matrix-Assisted Laser Desorption Ionization-Time Of Flight mass spectrometry (MALDI-TOF MS) for routine identification. However, lack of reference spectra in the currently commercialized databases does not allow the identification of Brucella isolates. In this work, we constructed a Brucella MALDI-TOF MS reference database using VITEK MS. We generated 590 spectra from 84 different strains (including rare or atypical isolates) to cover this bacterial genus. We then applied a novel biomathematical approach to discriminate different species. This allowed accurate identification of Brucella isolates at the genus level with no misidentifications, in particular as the closely related and less pathogenic Ochrobactrum genus. The main zoonotic species (B. melitensis, B. abortus and B. suis) could also be identified at the species level with an accuracy of 100%, 92.9% and 100%, respectively. This MALDI-TOF reference database will be the first Brucella database validated for diagnostic and accessible to all VITEK MS users in routine. This will improve the diagnosis and control of brucellosis by allowing a rapid identification of these pathogens.

A Simple and Safe Protocol for Preparing Brucella Samples for Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Analysis.

We describe a simple protocol to inactivate the biosafety level 3 (BSL3) pathogens Brucella prior to their analysis by matrix-assisted laser desorption ionization-time of flight mass spectrometry. This method is also effective for several other bacterial pathogens and allows storage, and eventually shipping, of inactivated samples; therefore, it might be routinely applied to unidentified bacteria, for the safety of laboratory workers.