Identification of medically important yeasts by sequence analysis of the internal transcribed spacer and D1/D2 region of the large ribosomal subunit; [Identificación de levaduras de interés médico mediante análisis de secuencia del espaciador interno transcrito y de la región D1/D2 de la subunidad ribosómica grande]

Background: The prevalence of opportunistic yeast infections has increased in recent decades as the result of an increasing immunocompromised patient population. Aims: To evaluate ribosomal RNA (rRNA) gene sequence to identify medically important yeast species, to investigate the performance of both the rRNA gene internal transcribed spacer (ITS) and D1/D2 region in identifying clinically relevant yeasts, and to compare these results with those of a standard phenotypic method. Methods: Both regions from 50 yeast strains, comprising 45 clinical isolates and 5 reference strains, were amplified using PCR and then sequenced. The sequences were compared to reference data available from the GenBank database of the National Center for Biotechnology Information using the BLASTn tool. Results: Using ID32C, 88% (44/50) of all strains were identified accurately at the species level, although 6% were misidentified; two Candida eremophila isolates were identified as Candida glabrata and Candida tropicalis, and one Saprochaete clavata isolate was identified as Saprochaete capitata. Two of the four isolates identified by phenotypic methods as Trichosporon asahii were defined so by analyzing the ITS region, but the remaining two were not distinguishable from closely related species. Based on the D1/D2 region, these four isolates had 100% sequence identity with T. asahii, Trichosporon japonicum, and Trichosporon asteroides. The isolate identified as Trichosporon inkin using ID32C could not be distinguished from Trichosporon ovoides by analyzing the ITS and D1/D2 regions. Conclusions: Identifying medically important yeasts by sequencing the ITS and D1/D2 region is a rapid and reliable alternative to conventional identification methods. For a diagnostic algorithm, we suggest a two-step procedure integrating conventional methods (e.g. microscopic morphology on corn meal agar with Tween® 80 and API ID32C®) and sequence analysis of the ITS and D1/D2 region. © 2019 Asociación Española de Micología