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Analysis of clinical and environmental Candida parapsilosis isolates by microsatellite genotyping—a tool for hospital infection surveillance

假丝酵母病 基因分型 基因型 爆发 打字 生物 微卫星 传输(电信) 多位点序列分型 分子流行病学 病毒学 微生物学 遗传学 抗真菌 等位基因 基因 电气工程 工程类
作者
Raquel Sabino,Paula Sampaio,Laura Rosado,Zélia Videira,Frédéric Grenouillet,Célia Pais
出处
期刊:Clinical Microbiology and Infection [Elsevier BV]
卷期号:21 (10): 954.e1-954.e8 被引量:43
标识
DOI:10.1016/j.cmi.2015.06.001
摘要

Candida parapsilosis emerged as an important opportunistic pathogen, causing candidaemia worldwide. Nosocomial outbreaks triggered by this species have been frequently described, particularly in cancer patients. For a better understanding of its epidemiology, several typing methods are used and microsatellite analysis has been reported as highly discriminant. The main objective of this work was to study C. parapsilosis isolates by application of microsatellite genotyping to distinguish epidemiologically related strains, compare clinical and environmental isolates and determine possible routes of dispersion of the isolates in the hospital setting. A total of 129 C. parapsilosis isolates from different origins, including hospital environment and hands of healthcare workers, were genotyped using four microsatellite markers. The isolates were recovered from different health institutions. Analysis of C. parapsilosis isolates from hospital environment showed great genotypic diversity; however, the same or very similar genotypes were also found. The same multilocus genotype was shared by isolates recovered from the hand of a healthcare worker, from the hospital environment and from patients of the same healthcare institution, suggesting that these could be possible routes of transmission and that infections due to C. parapsilosis may be mainly related with exogenous transmission to the patient. Examination of sequential isolates from the same patients showed that colonizing and bloodstream isolates had the same multilocus genotype in the majority of cases. We demonstrate that this typing method is able to distinguish clonal clusters from genetically unrelated genotypes and can be a valuable tool to support epidemiologic investigations in the hospital setting.
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