Molecular typing of clinical adenovirus specimens by an algorithm which permits detection of adenovirus coinfections and intermediate adenovirus strains

利用算法对临床腺病毒标本进行分子分型,该算法可以检测腺病毒混合感染和中间型腺病毒株。

阅读:1

Abstract

BACKGROUND: Epidemiological data suggest that clinical outcomes of human adenovirus (HAdV) infection may be influenced by virus serotype, coinfection with multiple strains, or infection with novel intermediate strains. In this report, we propose a clinical algorithm for detecting HAdV coinfection and intermediate strains. STUDY DESIGN: We PCR amplified and sequenced subregions of the hexon and fiber genes of 342 HAdV-positive clinical specimens obtained from 14 surveillance laboratories. Sequences were then compared with those from 52 HAdV prototypic strains. HAdV-positive specimens that showed nucleotide sequence identity with a corresponding prototype strain were designated as being of that strain. When hexon and fiber gene sequences disagreed, or sequence identity was low, the specimens were further characterized by viral culture, plaque purification, repeat PCR with sequencing, and genome restriction enzyme digest analysis. RESULTS: Of the 342 HAdV-positive clinical specimens, 328 (95.9%) were single HAdV strain infections, 12 (3.5%) were coinfections, and 2 (0.6%) had intermediate strains. Coinfected specimens and intermediate HAdV strains considered together were more likely to be associated with severe illness compared to other HAdV-positive specimens (OR=3.8; 95% CI=1.2-11.9). CONCLUSIONS: The majority of severe cases of HAdV illness cases occurred among immunocompromised patients. The analytic algorithm we describe here can be used to screen clinical specimens for evidence of HAdV coinfection and novel intermediate HAdV strains. This algorithm may be especially useful in investigating HAdV outbreaks and clusters of unusually severe HAdV disease.

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。