Abstract
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a rapid and accurate method to identify microorganisms in clinical laboratories. This study isolates yeast-like microorganisms in the oral washes that are collected from non-bedridden nursing home residents, using CHROMagar Candida plates, and identifies them using Bruker MALDI-TOF MS. The ribosomal DNA sequences of the isolates are then examined. Three hundred and twenty yeast isolates are isolated from the oral washes. Candida species form the majority (78.1%), followed by Trichosporon/Cutaneotrichosporon species (8.8%). Bruker MALDI-TOF MS gives a high-level confidence, with a log(score) value of ≥1.8, and identifies 96.9% of the isolates. There are six inconclusive results (1.9%), and those sequences are verified as rare clinical species, including Candida ethanolica, Cutaneotrichosporon jirovecii, Exophiala dermatitidis, and Fereydounia khargensis. Almost all of the isolates have a regular color on the CHROMagar Candida plates. If the colonies are grouped by color on the plates, a specific dominant yeast species is present in each color group, except for purple or orange isolates. In conclusion, MALDI-TOF MS is verified as a fast, accurate and practical method to analyze oral yeasts in elderly subjects.
Highlights
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDITOF MS) is a rapid and accurate method to identify microorganisms in a clinical microbiology laboratory [1,2,3]
The results demonstrate that the Bruker MALDI-TOF MS is an effective and highly specific method for the identification of oral yeast
All the fresh colonies of those isolates were subjected to Bruker MALDI-TOF MS (Figure 1)
Summary
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDITOF MS) is a rapid and accurate method to identify microorganisms in a clinical microbiology laboratory [1,2,3]. The peak profiles that are generated by Bruker MALDI-TOF MS are matched to reference libraries using the integrated patterns matching algorithm, BioTyper software (Bruker Daltonics, Bremen, Germany). This gives an arbitrary score value of 0 to 3.0 to represent the similarity between the sample and the reference spectrum. A log(score) of ≥2.0 represents successful identification of a species, and a score of 1.7 to 2.0 is acceptable for Microorganisms 2021, 9, 142. Scores higher than 1.8 represent highly-accurate yeast identification [4,5]
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