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Comparison of PCR-RFLP with 21-plex PCR and rDNA Sequencing for Identification of Clinical Yeast Isolates

Non- albicans Candida species and other rare yeasts have emerged as major opportunistic pathogens in fungal infections. Identification of opportunistic yeasts in developing countries is mainly performed by phenotypic assay, which are time-consuming and prone to errors. The aim of the present study w...

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Bibliographic Details
Published in:Mycopathologia (1975) 2021-05, Vol.186 (2), p.213-220
Main Authors: Kord, Mohammad, Elmimoghaddam, Ahmad, Hashemi, Seyed Jamal, Reziae, Sassan, Daie Ghazvini, Roshanak, Salehi, Mohammadreza, Abdollahi, Alireza, Ahmadi, Ali, Getso, Muhammad Ibrahim, Boekhout, Teun, Khodavaisy, Sadegh
Format: Article
Language:English
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Summary:Non- albicans Candida species and other rare yeasts have emerged as major opportunistic pathogens in fungal infections. Identification of opportunistic yeasts in developing countries is mainly performed by phenotypic assay, which are time-consuming and prone to errors. The aim of the present study was to evaluate PCR-RFLP as a routinely used identification technique for the most clinically important Candida species in Iran and make a comparison with a novel multiplex PCR, called 21-plex PCR. One hundred and seventy-three yeast isolates from clinical sources were selected and identified with sequence analysis of the D1/D2 domains of rDNA (LSU rDNA) sequencing as the gold standard method. The results were compared with those obtained by PCR-RFLP using MspI restriction enzyme and the 21-plex PCR. PCR-RFLP correctly identified 93.4% of common pathogenic Candida species ( C. albicans , C. glabrata , C. parapsilosis , C. tropicalis , and P. kudriavsevii (=  C. krusei )) and was able to identify 45.5% of isolates of the uncommon yeast species compared to the D1/D2 rDNA sequencing. Compared with PCR-RFLP, all common Candida species and 72.7% of uncommon yeast species were correctly identified by the 21-plex PCR. The application of the 21-plex PCR assay as a non-sequence-based molecular method for the identification of common and rare yeasts can reduce turnaround time and costs for the identification of clinically important yeasts and can be applied in resource-limited settings.
ISSN:0301-486X
1573-0832
DOI:10.1007/s11046-020-00522-0