Investigating hepatitis C virus heterogeneity in a high prevalence setting using heteroduplex tracking analysis

Abstract

Hepatitis C virus (HCV) infection is very common among chronic hemodialysis patients. In the past, blood transfusion appeared to be the primary risk factor; however evidence of nosocomial HCV transmission in the hemodialysis setting has recently been reported. This report describes a molecular investigation of HCV isolates obtained from a population of 670 patients attending six different Seattle-King County based hemodialysis centers in order to identify potential common source infections. 733 serum specimens were collected from hemodialysis patients in 1992 and 1996, and were tested for HCV antibodies and RNA. Overall, 115 of 670 (17%) patients were positive for HCV RNA, and thus were considered actively infected by HCV. HCV genotype was determined in all cases by restriction fragment length polymorphism, and 93 patients were found to be infected by HCV genotype 1. HCV envelope genes were amplified from the 93 patients with genotype 1 infection, and were studied in further detail by heteroduplex tracking analysis (HTA) using genotype 1a and 1b specific probes derived from the envelope 1 (E1) and envelope 2 (E2) genes. Genetic relatedness between pairs of HCV envelope genes was estimated by calculating the degree of gel shift relative to homoduplex controls. Nucleotide sequencing and phylogenetic analysis was used to confirm genetic relatedness detected by HTA. When HTA was performed using the E1 gene probe, 12 apparently related infections were detected; 10 of 12 (83%) of these infections were confirmed as truly related using the gold standard method of nucleotide sequencing plus phylogenetic analysis. Using an E2 gene probe, 24 infections were apparently related, but only six (25%) were confirmed by sequencing. As a control, 41 envelope genes, which were unrelated by HTA, were sequenced; 0 of 41 (0%) were truly related. In summary, HTA provides a rapid and effective molecular technique for screening HCV genetic relatedness in population-based studies, and should prove valuable in future studies of HCV molecular epidemiology. © 2001 Elsevier Science B.V.