MALDI-TOF MS-based identification of black yeasts of the genus Exophiala

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OZHAK-BAYSAN B., Ogunc D., Dogen A., İLKİT M. M., SYBREN DE HOOG G.

MEDICAL MYCOLOGY, cilt.53, sa.4, ss.347-352, 2015 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 53 Sayı: 4
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1093/mmy/myu093
  • Dergi Adı: MEDICAL MYCOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.347-352
  • Anahtar Kelimeler: black yeasts, database, ITS sequencing, MALDI mass spectrometry, species, DESORPTION IONIZATION-TIME, MASS-SPECTROMETRY, FILAMENTOUS FUNGI, DERMATITIDIS
  • Akdeniz Üniversitesi Adresli: Evet

Özet

In this study, we investigated the applicability of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification of Exophiala species. The analysis included a total of 110 Exophiala isolates, including 15 CBS strains representing 4 species, Exophiala dermatitidis (61), E. phaeomuriformis (36), E. crusticola (9), and E. heteromorpha (4), that had been previously identified based on internal transcribed spacer (ITS) regions. We also compared the relative efficacies of Sabouraud glucose agar (SGA) and Columbia agar (CA) for use in MALDI-TOF MS. Remarkably, we obtained a log-score value a parts per thousand yen2.0 by using either SGA or CA for all 15 CBS strains, indicating species-level identification. The remaining 95 Exophiala strains were identified to the genus or species levels, with identification rates of 96.8% and 90.5%, using SGA or CA, respectively. Most of the E. dermatitidis (100% and 92.9%), E. phaeomuriformis (80.6% and 83.9%), E. crusticola (50% and 100%), and E. heteromorpha (100% and 100%) isolates were correctly identified using SGA or CA, respectively. Furthermore, 58.9% and 26.3% of the strains had log-score values of a parts per thousand yen2.0 by using SGA and CA, respectively. Our results indicate that MALDI-TOF MS is a rapid and reliable technique with high rates of correct taxonomic identification.