Typing of hepatitis C virus (HCV) isolates is currently a prerequisite for adequate tailoring of antiviral combination therapy. In many diagnostic laboratories, there seems to be a tendency toward convenient and time-saving procedures utilizing amplification products, which are already available from preceding qualitative or quantitative HCV ribonucleic acid (RNA) assays. In this context, we evaluated the performance characteristics of a combination of techniques, i.e., transcription-mediated amplification-line probe assay (TMA-LiPA), which links highly sensitive TMA of HCV RNA to the VERSANT HCV Genotype Assay (version 1). A total of 100 clinical samples were genotyped by TMA-LiPA. The obtained results were compared to those recorded by the original, nested reverse transcription (RT)-polymerase chain reaction (PCR)-based VERSANT assay, the core-related GEN-ETI-K DEIA, and phylogenetic analyses of partial sequences from the HCV core and NS5B regions. TMA-LiPA assigned the correct genotype to all 100 HCV isolates. For subtyping of genotype 1 and 2 isolates, TMA-LiPA only showed discriminatory powers of 82% and 53%, respectively. Thus, TMA-LiPA in our hands turned out as a convenient and time-saving routine procedure for HCV typing which currently provides sufficient information for clinical purposes. Like all 5'untranslated region (UTR)-based assays, the technique is limited, however, in its potentials to resolve the complexity of existing HCV subtypes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.