MALDI-TOF MS based identification of food-borne yeast isolates
Related Experiment Video
Updated: Apr 24, 2026
Evaluation of Microbial Safety of Dairies using Bacterial Proteomic Profiling via MALDI Approach
Published on: October 7, 2025
Melanie Pavlovic1, Anne Mewes1, Marzena Maggipinto1
1Bavarian Health and Food Safety Authority, Veterinaerstr. 2, 85764 Oberschleißheim, Germany.
Abstract:
In this study, food-borne yeast isolates (n=96), comprising at least 33 species, were identified using MALDI-TOF MS and conventional methods (API ID 32 C and Phoenix Yeast ID). Discrepancies of both methods were resolved by sequencing the ITS1-5.8S-rRNA-ITS2 region. For ten isolates, mainly classified to Rhodotorula and Trichosporon species, no clear final species identification was possible. 62 isolates were correctly identified to species level using either MALDI-TOF MS or conventional tests. 15 isolates were misidentified when applying conventional assays. In contrary, no species misidentifications were observed after MALDI-TOF MS based classification. In return, 16 isolates were not identifiable after matching their protein fingerprints against MALDI Biotyper 4.0.0.1 library. MALDI TOF MS in-house database update clearly improved the identification. In conclusion, the presented data suggest that MALDI-TOF MS is an appropriate platform for reliable classification and identification of food-borne yeast isolates.
Insights
Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) accurately identifies food-borne yeast species. This method proved more reliable than conventional assays, with database updates enhancing its performance for yeast identification.
Area of Science:
- Food Microbiology
- Yeast Taxonomy
- Analytical Chemistry
Background:
- Accurate identification of food-borne yeasts is crucial for food safety and quality control.
- Conventional identification methods can be time-consuming and prone to misidentification.
- Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) offers a rapid alternative for microbial identification.
Purpose of the Study:
- To evaluate the performance of MALDI-TOF MS compared to conventional methods for identifying food-borne yeast isolates.
- To assess the impact of database updates on MALDI-TOF MS identification accuracy.
- To resolve identification discrepancies using DNA sequencing of the ITS1-5.8S-rRNA-ITS2 region.
Main Methods:
- Identification of 96 food-borne yeast isolates using MALDI-TOF MS and conventional methods (API ID 32 C, Phoenix Yeast ID).
- Sequencing of the ITS1-5.8S-rRNA-ITS2 region for discrepancy resolution.
- Comparison of identification results between MALDI-TOF MS (with and without updated database) and conventional methods.
Main Results:
- MALDI-TOF MS achieved accurate species-level identification for 62 isolates, with no misidentifications observed.
- Conventional methods resulted in 15 misidentifications.
- An updated MALDI-TOF MS in-house database significantly improved identification rates, though 16 isolates remained unidentifiable against the commercial library.
Conclusions:
- MALDI-TOF MS is a reliable and accurate platform for the identification of food-borne yeast isolates.
- Updating the MALDI-TOF MS database enhances its discriminatory power for yeast identification.
- MALDI-TOF MS offers a significant advantage over conventional methods in terms of accuracy and speed for routine yeast identification in food microbiology.
