期刊
JOURNAL OF INFECTIOUS DISEASES
卷 208, 期 1, 页码 17-31出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/infdis/jis679
关键词
Hepatitis C virus; pyrosequencing; subtype classification; drug resistance mutations; viral diversity
资金
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services [HHSN272200900018C, HHSN272200900006C, R01-AI067926, U19-AI082630]
- Deutsche Forschungsgemeinschaft [DFG KU2250/1-1]
- BBSRC [BBS/E/D/20241864] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BBS/E/D/20241864] Funding Source: researchfish
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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