Journal
JOURNAL OF VIROLOGY
Volume 84, Issue 12, Pages 6218-6228Publisher
AMER SOC MICROBIOLOGY
DOI: 10.1128/JVI.02271-09
Keywords
-
Categories
Funding
- Human Microbiome Demonstration Project [UH2DK083981]
- NIH [K08 AI077713]
- University of Pennsylvania Department of Medicine Measey Basic Science
- Engineering and Physical Sciences Research Council [EP/H003851/1] Funding Source: researchfish
- NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [K08AI077713] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [UH2DK083981] Funding Source: NIH RePORTER
- EPSRC [EP/H003851/1] Funding Source: UKRI
Ask authors/readers for more resources
Hepatitis C virus (HCV) replication in infected patients produces large and diverse viral populations, which give rise to drug-resistant and immune escape variants. Here, we analyzed HCV populations during transmission and diversification in longitudinal and cross-sectional samples using 454/Roche pyrosequencing, in total analyzing 174,185 sequence reads. To sample diversity, four locations in the HCV genome were analyzed, ranging from high diversity (the envelope hypervariable region 1 [HVR1]) to almost no diversity (the 5' untranslated region [UTR]). For three longitudinal samples for which early time points were available, we found that only 1 to 4 viral variants were present, suggesting that productive infection was initiated by a very small number of HCV particles. Sequence diversity accumulated subsequently, with the 5' UTR showing almost no diversification while the envelope HVR1 showed >100 variants in some subjects. Calculation of the transmission probability for only a single variant, taking into account the measured population structure within patients, confirmed initial infection by one or a few viral particles. These findings provide the most detailed sequence-based analysis of HCV transmission bottlenecks to date. The analytical methods described here are broadly applicable to studies of viral diversity using deep sequencing.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available