Development of a Multiplex qPCR to Detect and Identify Cryptococcus neoformans and Cryptococcus gattii
Year: 2025
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide Background: Atypical clinical symptoms often lead to missed diagnosis or misdiagnosis of cryptococcal infection. Cryptococcus neoformans and Cryptococcus gattii exhibit similar clinical manifestations but different treatment cycles and prognoses. Methods: A multiplex qPCR was developed to detect and identify two fungi, which are based on the IGS-1 region gene of Cryptococcus neoformans ( Cn-IGS-1 ) and Cryptococcus gattii ( Cg-IGS-1 ), and ribonuclease P (RNP) gene. The amplification efficiency, precision, specificity, and detection sensitivity were determined. The detection sensitivity of the multiplex qPCR was compared with Indian ink staining, culture, and lateral flow immunochromatographic assay (LFA). The impact of standing time on the detection was measured. Results: The results showed that the amplification efficiency of Cn-IGS-1, Cg-IGS-1, and RNP genes was 97.7%, 96.5%, and 98.8%, respectively. The limits of detection of Cn-IGS-1 and Cg-IGS-1 genes were 20.251 and 18.943 copies/reaction, respectively. The coefficients of variation were both less than 5%, and the specificity was 100%. Additionally, the minimum detection limits of the multiplex qPCR for Cryptococcus neoformans and Cryptococcus gattii simulated samples were 8.881 and 2.084 cells/mL, respectively, while the minimum detection limits of Indian ink staining, culture, and LFA were 1.0 × 10 3 cells/mL, 1.0 × 10 1 cells/mL, and 1.0 × 10 4 cells/mL, respectively. The concentration of Cryptococcus neoformans decreased gradually in the supernatant with the prolongation of standing time. Conclusions: The multiplex qPCR can detect and distinguish Cryptococcus neoformans from Cryptococcus gattii, and it is more sensitive than Indian ink staining and LFA. Our multiplex qPCR assay realizes the early and accurate detection of cryptococcosis, indicating potential clinical application prospects.
Source: ACS Omega
Authors: Wei-Ming Ye, Xin-Qi Zheng, Yue Zhong, Wei-Jing Lin, Ning-Dai Chen, Yong-Jing Wang, Jiang-Xing Zhuang, Tian-Ci Yang
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,935
OpenAlex ID: W4416952522
