Abstract
Affordable next-generation sequencing (NGS) technologies for hepatitis C virus (HCV) may potentially identify both viral genotype and resistance genetic motifs in the era of directly acting antiviral (DAA) therapies. This study compared the ability of highthroughput NGS methods to generate full-length, deep, HCV sequence data sets and evaluated their utility for diagnostics and clinical assessment. NGS methods using (i) unselected HCV RNA (metagenomics), (ii) preenrichment of HCV RNA by probe capture, and (iii) HCV preamplification by PCR implemented in four United Kingdom centers were compared. Metrics of sequence coverage and depth, quasispecies diversity, and detection of DAA resistance-associated variants (RAVs), mixed HCV genotypes, and other coinfections were compared using a panel of samples with different viral loads, genotypes, and mixed HCV genotypes/subtypes [geno(sub)types]. Each NGS method generated near-complete genome sequences from more than 90% of samples. Enrichment methods and PCR preamplification generated greater sequence depth and were more effective for samples with low viral loads. All NGS methodologies accurately identified mixed HCV genotype infections. Consensus sequences generated by different NGS methods were generally concordant, and majority RAVs were consistently detected. However, methods differed in their ability to detect minor populations of RAVs. Metagenomic methods identified human pegivirus coinfections. NGS provided a rapid, inexpensive method for generating whole HCV genomes to define infecting genotypes, RAVs, comprehensive viral strain analysis, and quasispecies diversity. Enrichment methods are particularly suited for high-throughput analysis while providing the genotype and information on potential DAA resistance.
| Original language | English |
|---|---|
| Pages (from-to) | 2470-2484 |
| Number of pages | 15 |
| Journal | Journal of Clinical Microbiology |
| Volume | 54 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2016 |
Bibliographical note
Funding Information:We acknowledge the contributions of Patricia Cane who established the PHE collaboration with STOP-HCV. We thank members of the PATHSEEK consortium and infrastructure funding from the MRC Centre for Medical Molecular Virology for their contributions to the project. We also thank Evguenia Svarovskaia (Gilead Sciences) for PCR sequencing primers and protocols. This work was funded by a grant from the Medical Research Council, United Kingdom (grant MR/K01532X/1). Samples were provided by HCV Research UK, funded through the Medical Research Foundation (grant C0365). This research was supported by core funding to the Wellcome Trust Centre for Human Genetics, provided by the Wellcome Trust (090532/Z/09/Z), and funding from PHE and the National Institute for Health Research (NIHR) Centre for Health Protection Research. The UCL work was funded by the FP7 PATHSEEK grant. E. Barnes is funded by the MRC as an MRC Senior Clinical Fellow, with additional support from the Oxford NHIR BRC and the Oxford Martin School. M. A. Ansari is funded by the Oxford Martin School. P. Klenerman is funded by the Oxford Martin School, NIHR Biomedical Research Centre, Oxford, United Kingdom, by the Wellcome Trust (091663MA), and by the NIH (U19AI082630). J. Breuer receives funding from the NIHR UCL/UCLH Biomedical research consortium.
Publisher Copyright:
Copyright © 2016 Thomson et al.
