Epidemiological Characterisation and Molecular Identification of Dermatophyte Infec-tions Isolated from Outpatient Clinics of The Dermatology Department at Zliten Medi-cal Center, Libya
Abstract
Dermatophytes are keratinophilic fungus causing superficial infections of skin, nail and hair. In recent decades, the prevalence has internationally increased, affecting about 25% of populations in different countries around the World. The aim of this study was to identify different species of dermatophytes causing dermatophytosis in patients infected with fungal skin infections using morphological, microscopic, and molecular diagnostic methods with use of Polymerase Chain Reaction (PCR) techniques. In this study a total of 100 clinical samples from skin, hair, and nails were collected from patients attending Zliten Medical Center over the period of time from 01.01.2022 until 30.5.2022. Samples were examined microscopically using Potassium Hydroxide (KOH) 10%-20% and cultured on Sabouraud Dextrose Agar (SDA), Potato Dextrose Agar (PDA), and Dermatophyte Test Medium (DTM). Fungal isolates from positive Cultures were further investigated with PCR. Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 25. Only 22% of total samples show positivity for KOH. A 12 species were identified, with Trichophyton violaceum (25%) and Microsporum canis (20%) being the most common, followed by Trichophyton tonsurans (10%) and several less frequent species. It is worth noting, that Microsporum canis was more frequently affecting children under 11 years old und occurred more frequently in People having domestic animals. Molecular confirmation using real-time PCR (ITS1–S4 primers) showed 80% PCR positivity among culture isolates. Eight species were fully PCR-confirmed, while others showed variable detection rates. Overall, PCR has confirmed that T. violaceum and M. canis were the predominant dermatophytes in this study. The importance of this study lies in its emphasizing of the effectiveness and feasibility of using molecular identification technology for the accurate identification and early diagnosis of dermatophyte infections.