Objective: Fungal nail infection (onychomycosis) is a common disease in all communities consisting about ۵۰ percent of nail disorders.
Yeasts are one of the important causative agents of onychomycosis.
Identification of the yeast species is important in the epidemiological and therapeutical point of views. The aim of the present study is the precise species identification of the pathogenic yeast isolated from fungal nail infections, using the DNA-based methods.
Materials and Methods: The isolates were preliminary studied according to study of morphological characteristics. For species identification, the genomic DNA of each sample was extracted by boiling method and the ITS region of ribosomal DNA was amplified by polymerase chain reaction (PCR). The amplified DNA was digested by the restriction enzyme MspI and each isolate was identified according to the electrophoretic patterns. A new enzymatic profile was used for final differentiation of Candida albicans and C. dubliniensis. A few of yeast isolates were identified by using ITS-sequensin.
Results: C. albicans with the prevalence of ۴۵.۶% was the most common isolate, followed by C. parapsilosis with ۲۲.۵% and C. tropicalis with ۲۱.۸%. The less common species were C. glabrata, C. krusei, C. kefyr, C. lusitaniae, C. guilliermondii and C. pulcherrima that consisted ۲.۷۲%, ۲%, ۱.۳۶%,
۰.۶۸% and ۰.۶۸% of the isolates, respectively. No C. dubliniensis was found among C. albicans isolates. Two isolates (۱.۳۶%) were identified as Trichosporon spp. The most common group of the patients was in the age range of ۴۰-۷۰ years old and the majority (۸۳.۲%) of the patients were women with finger nail infections.
Conclusion: Although C. albicans is still the most prevalent isolates of nail candidiasis, the increasing number of non-albicans species is notable. The study showed that for identification of some rare species, the routine phenotypical approaches are not efficient and application of the ITS-PCR-RFLP can improve the level of differentiation up to ۹۸%. The remaining isolates can be identified by more expensive methods such as sequencing.
