Identification of Malassezia species from pityriasis versicolor lesions with a new multiplex PCR method.

Despite the fact that a range of molecular methods have been developed as tools for the diagnosis of Malassezia species, there are several drawbacks associated with them, such as inefficiency of differentiating all the species, high cost, and questionable reproducibility. In addition, most of the molecular methods require cultivation to enhance sensitivity. Therefore, alternative methods eliminating cultivation and capable of identifying species with high accuracy and reliability are needed. Herein, a multiplex polymerase chain reaction (PCR)-based method was especially developed for the detection of eleven Malassezia species. The multiplex PCR was standardized by incorporating a consensus forward primer, along with Malassezia species-specific reverse primers considering the sizes of the PCR products. In the method, the multiplex-PCR primer content is divided into three parts to circumvent the problem of increased nonspecific background resulting from the use of a large number of primers. DNA extraction protocol described by Harju and colleagues was modified using liquid nitrogen instead of -80 °C to break down the yeast membrane. By a modified extraction procedure followed by multiplex PCR and electrophoresis, the method enables identification and differentiation of Malassezia species from both of the samples obtained directly from skin and yeast colonies grown in culture. Fifty-five patients who were confirmed with pityriasis versicolor were enrolled in the study. Multiplex PCR detected and differentiated all 55 samples obtained directly from the patients' skin. However, 50 out of 55 samples yielded Malassezia colony in the culture. In addition, eight of 50 colonies were misdiagnosed or not completely differentiated by conventional methods based on the sequence analysis of eight colonies. The method is capable of identifying species with high accuracy and reliability. In addition, it is simple, quick, and cost-effective. More importantly, the method works efficiently for the diagnosis of Malassezia species obtained directly from patient samples.