Antifungal susceptibility and molecular characteristics of Cryptococcus spp. based on whole-genome sequencing in Zhejiang Province, China

• DOI: 10.3389/fmicb.2022.991703
• Publication Date: 2022-11-17T04:29:54Z
• Authors: Junli Zhang; Zhengan Wang; Yan Chen; Zhihui Zhou; Qing Yang; Ying Fu; Feng Zhao; Xi Li; Qiong Chen; Li Fang; Yan Jiang; Yunsong Yu
• Keywords: 0301 basic medicine; multilocus sequence typing (MLST); 0303 health sciences; 03 medical and health sciences; mating type (MAT); genotype; Cryptococcus neoformans; Cryptococcus gattii; antifungal susceptibility testing; Microbiology; QR1-502; 3. Good health

Cryptococcus spp. is a complex species that often causes cryptococcosis, which is one of the most common opportunistic infections in adults living with HIV and has very high morbidity and mortality rates. This study aimed to investigate the antifungal susceptibility profiles and epidemiological characteristics of the Cryptococcus neoformans species complex (CNSC) and the Cryptococcus gattii species complex (CGSC) in Zhejiang Province, China. A total of 177 CNSC and 3 CGSC isolates were collected, and antifungal susceptibility was tested by FUNGUS 3 and verified with an E-test. Moreover, multiple classification methods and genomic analyses were performed. The majority of the isolates (96.11%) were C. neoformans (formerly C. neoformans var. grubii) (ST5-VNI-A-α). Our study highlights that most of the patients with cryptococcosis were non-HIV patients in China, and nearly half of them did not have underlying diseases that led to immune insufficiency. Most of the Cryptococcus spp. isolates in this study were sensitive to common antifungal drugs. Two 5-flucytosine (5-FC)-resistant strains were identified, and FUR1 mutation was detected in the 5-FC-resistant isolates. Typing based on whole-genome sequencing (WGS) showed better discrimination than that achieved with multilocus sequence typing (MLST) and indicated a clear population structure. A phylogenetic analysis based on WGS included more genomic information than traditional classification methods.