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Whole genome pyrosequencing of rare hepatitis C virus genotypes enhances subtype classification and identification of naturally occurring drug resistance variants


Newman, Ruchi M; Kuntzen, Thomas; Weiner, Brian; Berical, Andrew; Charlebois, Patrick; Kuiken, Carla; Murphy, Donald G; Simmonds, Peter; Bennett, Phil; Lennon, Niall J; Birren, Bruce W; Zody, Michael C; Allen, Todd M; Henn, Matthew R (2013). Whole genome pyrosequencing of rare hepatitis C virus genotypes enhances subtype classification and identification of naturally occurring drug resistance variants. Journal of Infectious Diseases, 208(1):17-31.

Abstract

Background. Infection with hepatitis C virus (HCV) is a burgeoning worldwide public health problem, with 170 million infected individuals and an estimated 20 million deaths in the coming decades. While 6 main genotypes generally distinguish the global geographic diversity of HCV, a multitude of closely related subtypes within these genotypes are poorly defined and may influence clinical outcome and treatment options. Unfortunately, the paucity of genetic data from many of these subtypes makes time-consuming primer walking the limiting step for sequencing understudied subtypes.Methods. Here we combined long-range polymerase chain reaction amplification with pyrosequencing for a rapid approach to generate the complete viral coding region of 31 samples representing poorly defined HCV subtypes.Results. Phylogenetic classification based on full genome sequences validated previously identified HCV subtypes, identified a recombinant sequence, and identified a new distinct subtype of genotype 4. Unlike conventional sequencing methods, use of deep sequencing also facilitated characterization of minor drug resistance variants within these uncommon or, in some cases, previously uncharacterized HCV subtypes.Conclusions. These data aid in the classification of uncommon HCV subtypes while also providing a high-resolution view of viral diversity within infected patients, which may be relevant to the development of therapeutic regimens to minimize drug resistance.

Abstract

Background. Infection with hepatitis C virus (HCV) is a burgeoning worldwide public health problem, with 170 million infected individuals and an estimated 20 million deaths in the coming decades. While 6 main genotypes generally distinguish the global geographic diversity of HCV, a multitude of closely related subtypes within these genotypes are poorly defined and may influence clinical outcome and treatment options. Unfortunately, the paucity of genetic data from many of these subtypes makes time-consuming primer walking the limiting step for sequencing understudied subtypes.Methods. Here we combined long-range polymerase chain reaction amplification with pyrosequencing for a rapid approach to generate the complete viral coding region of 31 samples representing poorly defined HCV subtypes.Results. Phylogenetic classification based on full genome sequences validated previously identified HCV subtypes, identified a recombinant sequence, and identified a new distinct subtype of genotype 4. Unlike conventional sequencing methods, use of deep sequencing also facilitated characterization of minor drug resistance variants within these uncommon or, in some cases, previously uncharacterized HCV subtypes.Conclusions. These data aid in the classification of uncommon HCV subtypes while also providing a high-resolution view of viral diversity within infected patients, which may be relevant to the development of therapeutic regimens to minimize drug resistance.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Gastroenterology and Hepatology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2013
Deposited On:22 Feb 2013 10:07
Last Modified:31 Aug 2018 23:20
Publisher:Oxford University Press
ISSN:0022-1899
OA Status:Green
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/infdis/jis679
PubMed ID:23136221

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