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PMID: 27385709 Published · ppublish English Comparative Study Evaluation Study Journal Article Multicenter Study

Comparison of Next-Generation Sequencing Technologies for Comprehensive Assessment of Full-Length Hepatitis C Viral Genomes.

Journal of clinical microbiology ·Vol. 54 ·No. 10 ·2016-00-00 ·Pages 2470-84

Thomson E, Ip CL, Badhan A, Christiansen MT, Adamson W, Ansari MA, Bibby D, Breuer J, Brown A, Bowden R, Bryant J, Bonsall D, Da Silva Filipe A, Hinds C, Hudson E, Klenerman P, Lythgow K, Mbisa JL, McLauchlan J, Myers R, Piazza P, Roy S, Trebes A, Sreenu VB, Witteveldt J, STOP-HCV Consortium, Barnes E, Simmonds P

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 high-throughput 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.

MeSH Terms
Drug Resistance, Viral Genome, Viral Genotype Hepacivirus/classification,genetics Hepatitis C/diagnosis,virology High-Throughput Nucleotide Sequencing/methods Humans Sequence Analysis, DNA/methods United Kingdom
Authors & Affiliations
28 authors, click to expand affiliations / ORCID
Thomson Emma
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Ip Camilla L C
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Badhan Anjna
Virus Reference Department, Public Health England, London, United Kingdom.
Christiansen Mette T
University College London (UCL), Division of Infection and Immunity, London, United Kingdom.
Adamson Walt
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Ansari M Azim
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Bibby David ORCID
Virus Reference Department, Public Health England, London, United Kingdom.
Breuer Judith
University College London (UCL), Division of Infection and Immunity, London, United Kingdom.
Brown Anthony
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Bowden Rory
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Bryant Josie ORCID
University College London (UCL), Division of Infection and Immunity, London, United Kingdom.
Bonsall David
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Da Silva Filipe Ana
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Hinds Chris
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Hudson Emma
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Klenerman Paul
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Lythgow Kieren
Virus Reference Department, Public Health England, London, United Kingdom.
Mbisa Jean L
Virus Reference Department, Public Health England, London, United Kingdom.
McLauchlan John
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Myers Richard
Virus Reference Department, Public Health England, London, United Kingdom.
Piazza Paolo
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Roy Sunando
University College London (UCL), Division of Infection and Immunity, London, United Kingdom.
Trebes Amy
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
Sreenu Vattipally B
MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom.
Witteveldt Jeroen
Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.
STOP-HCV Consortium
Barnes Eleanor
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom ellie.barnes@ndm.ox.ac.uk.
Simmonds Peter
Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.
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Article Info
Journal
Journal of clinical microbiology
Abbr.
J Clin Microbiol
ISSN
1098-660X
Published
2016-00-00
Epub
2016-00-06
Pages
2470-84
Language
English
Region
United States
NLM ID
7505564
PMCID
PMC5035407
Subset
IM
Grants
Medical Research Council · MC_UU_12014/1 · United Kingdom
Medical Research Council · G0801822 · United Kingdom
Department of Health · 14/02/17 · United Kingdom
Medical Research Council · MR/K010239/1 · United Kingdom
Wellcome Trust · 091663 · United Kingdom
Medical Research Council · MR/K01532X/1 · United Kingdom
Wellcome Trust · United Kingdom
Medical Research Council · MC_EX_UU_G1000717 · United Kingdom
NIAID NIH HHS · U19 AI082630 · United States
Medical Research Council · MC_UU_12014/12 · United Kingdom
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