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


Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • McCarthy, T; Lebeck, MG; Capuano, AW; Schnurr, DP; Gray, GC

Published Date

  • September 2009

Published In

Volume / Issue

  • 46 / 1

Start / End Page

  • 80 - 84

PubMed ID

  • 19577957

Pubmed Central ID

  • 19577957

Electronic International Standard Serial Number (EISSN)

  • 1873-5967

Digital Object Identifier (DOI)

  • 10.1016/j.jcv.2009.06.008


  • eng

Conference Location

  • Netherlands