Development and validation of an in-house database for matrix-assisted laser desorption ionization-time of flight mass spectrometry-based yeast identification using a fast protein extraction procedure.

In recent studies evaluating the usefulness of the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based identification of yeasts for the routine diagnosis of fungal infections, preanalytical sample processing has emerged as a critical step for reliable MALDI-TOF MS outcomes, especially when the Bruker Daltonics Biotyper software was used. In addition, inadequate results often occurred due to discrepancies between the methods used for clinical testing and database construction. Therefore, we created an in-house MALDI-TOF MS library using the spectra from 156 reference and clinical yeast isolates (48 species in 11 genera), which were generated with a fast sample preparation procedure. After a retrospective validation study, our database was evaluated on 4,232 yeasts routinely isolated during a 6-month period and fast prepared for MALDI-TOF MS analysis. Thus, 4,209 (99.5%) of the isolates were successfully identified to the species level (with scores of ≥2.0), with 1,676 (39.6%) having scores of >2.3. For the remaining 23 (0.5%) isolates, no reliable identification (with scores of <1.7) was obtained. Interestingly, these isolates were almost always from species uniquely represented or not included in the database. As the MALDI-TOF MS results were, except for 23 isolates, validated without additional phenotypic or molecular tests, our proposed strategy can enhance the rapidity and accuracy of MALDI-TOF MS in identifying medically important yeast species. However, while continuous updating of our database will be necessary to enrich it with more strains/species of new and emerging yeasts, the present in-house MALDI-TOF MS library can be made publicly available for future multicenter studies.