Validation of an expanded, in-house library and an optimized preparation method for the identification of fungal isolates using MALDI-TOF mass spectrometry

Abstract The goal of this study was to validate an optimized sample preparation method for filamentous fungal isolates coupled with the use of an in-house library for the identification of moulds using Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) in a multicenter context. For that purpose, three Spanish microbiology laboratories participated in the identification of 97 fungal isolates using MALDI-TOF MS coupled with the Filamentous Fungi library 3.0 (Bruker Daltonics) and an in-house library containing 314 unique fungal references. The isolates analyzed belonged to 25 species from the genus Aspergillus, Fusarium, Scedosporium/Lomentospora, the Mucorales order and the Dermatophytes group. MALDI-TOF MS identification was carried out from hyphae resuspended in water and ethanol. After a high-speed centrifugation step, the supernatant was discarded and the pellet submitted to a standard protein extraction step. The protein extract was analyzed with the MBT Smart MALDI Biotyper system (Bruker Daltonics). The rate of accurate, species-level identification obtained ranged between 84.5% and 94.8% and the score values were 1.8 for 72.2–94.9% of the cases. Two laboratories failed to identify only one isolate of Syncephalastrum sp. and Trichophyton rubrum, respectively and three isolates could not be identified in the third center (F. proliferatum, n = 1; T.interdigitale, n = 2). In conclusion, the availability of an effective sample preparation method and an extended database allowed high rates of correct identification of fungal species using MALDI-TOF MS. Some species, such as Trichophyton spp. are still difficult to identify. Although further improvements are still required, the developed methodology allowed the reliable identification of most fungal species. Lay Summary MALDI-TOF mass spectrometry has been improved as a diagnostic method for the rapid and reliable identification of filamentous fungi by means of the creation of an expanded database containing reference protein spectra of the most clinically impacting fungal species.