Comparative study of direct polymerase chain reaction, microscopic examination and culture-based morphological methods for detection and identification of dermatophytes in nail and skin samples.

Autor: Uchida T; Department of Dermatology, School of Medicine, Showa University, Shinagawa-ku, Japan., Makimura K, Ishihara K, Goto H, Tajiri Y, Okuma M, Fujisaki R, Uchida K, Abe S, Iijima M
Jazyk: angličtina
Zdroj: The Journal of dermatology [J Dermatol] 2009 Apr; Vol. 36 (4), pp. 202-8.
DOI: 10.1111/j.1346-8138.2009.00624.x
Abstrakt: The positive rates of dermatophytes isolated and identified by conventional methods are rather low. Moreover, clinical isolates sometimes show atypical morphology, and in such cases microscopic methods are not applicable for identification. The present study was performed to assess the utility of specific polymerase chain reaction (PCR)-based methods for Trichophyton rubrum and Trichophyton mentagrophytes as diagnostic tools for dermatophytoses. Both conventional morphological identification and specific PCR methods based on the nuclear ribosomal internal transcribed spacer (ITS)1 DNA sequence were performed to identify dermatophyte species from clinical specimens of patients who visited Kawasaki Social Insurance Hospital between 16 May and 17 August 2005. Specific PCR methods were also directly applied to clinical specimens, and the results of the two methods were compared. The clinical samples examined consisted of 126 skin scale specimens and 80 nail specimens. The positive rates of culture isolation from clinical specimens were 67% and 33% for skin scale and nail specimens, respectively. In contrast, PCR analysis yielded a positive rate of 100% for clinical isolates from both skin scales and nails, and rates of 95% and 99% were obtained by direct application to clinical specimens. The results of the present study indicated that specific PCR is highly advantageous as a diagnostic tool for detection and identification of dermatophytes on direct application to skin scale or nail specimens.
Databáze: MEDLINE