Multilocus variable-number tandem-repeat analysis for investigation of Clostridium difficile transmission in Hospitals

多位点可变数目串联重复序列分析用于调查医院内艰难梭菌的传播

阅读:6
作者:Jane W Marsh, Mary M O'Leary, Kathleen A Shutt, A William Pasculle, Stuart Johnson, Dale N Gerding, Carlene A Muto, Lee H Harrison

Abstract

Clostridium difficile is a major cause of antibiotic-associated gastrointestinal illness. Recently, an increased incidence of hospital-acquired infections with severe outcomes has been reported in North America and Europe. Current molecular-typing methods for detection of outbreaks and nosocomial transmission are labor-intensive, subjective, or insufficiently discriminatory to differentiate between closely related strains. This report describes the development of multilocus variable-number tandem-repeat (VNTR) analysis (MLVA) for molecular subtyping of C. difficile. Seven VNTR loci were identified from the C. difficile 630 genome by screening an isolate collection of various restriction endonuclease analysis (REA) types. The stability of the loci for short-term epidemiologic investigations was determined by performing MLVA on consecutive isolates of the same REA type from individual patients collected over as many as 90 days. Validation of MLVA for molecular genotyping was performed by direct comparison with REA results obtained from Hines Veterans Affairs Hospital on a combined collection of 40 C. difficile isolates from two different sources. The ability of MLVA to detect outbreaks was demonstrated on a collection of tertiary-care hospital isolates from a defined C. difficile outbreak in 2001. MLVA successfully clustered C. difficile isolates of the same REA type and discriminated isolates of unique REA type. Thus, MLVA is an objective, portable genotyping method that permits reliable detection of C. difficile outbreaks and can aid epidemiologic investigations of nosocomial transmission.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。