A molecular approach for the rapid, selective and sensitive detection of Exophiala jeanselmei in environmental samples: development and performance assessment of a real-time PCR assay

作者：Libert X; Chasseur C; Packeu A; Bureau F; Roosens N H; De Keersmaecker S J C^*

来源：Applied Microbiology and Biotechnology, 2016, 100(3): 1377-1392.

DOI：10.1007/s00253-015-7175-z

• Black yeast
• Detection
• Environment
• Exophiala jeanselmei
• Real-time PCR
• Molecular method

Exophiala jeanselmei is an opportunistic pathogenic black yeast growing in humid environments such as water reservoirs of air-conditioning systems. Because this fungal contaminant could be vaporized into the air and subsequently cause health problems, its monitoring is recommended. Currently, this monitoring is based on culture and microscopic identification which are complex, sometimes ambiguous and time-demanding, i.e., up to 21 days. Therefore, molecular, culture-independent methods could be more advantageous for the monitoring of E. jeanselmei. In this study, we developed a SYBR (R) green real-time PCR assay based on the internal transcribed spacer 2 from the 18S ribosomal DNA complex for the specific detection of E. jeanselmei. The selectivity (100 %), PCR efficiency (95.5 %), dynamic range and repeatability of this qPCR assay were subsequently evaluated. The limit of detection for this qPCR assay was determined to be 1 copy of genomic DNA of E. jeanselmei. Finally, water samples collected from cooling reservoirs were analyzed using this qPCR assay to deliver a proof of concept for the molecular detection of E. jeanselmei in environmental samples. The results obtained by molecular analysis were compared with those of classical methods (i.e., culture and microscopic identification) used in routine analysis and were 100 % matching. This comparison demonstrated that this SYBR (R) green qPCR assay can be used as a molecular alternative for monitoring and routine investigation of samples contaminated by E. jeanselmei, while eliminating the need for culturing and thereby considerably decreasing the required analysis time to 2 days.

• 出版日期2016-2