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Cited by 596

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Deciphering Human Immunodeficiency Virus Type 1 Transmission and Early Envelope Diversification by Single-Genome Amplification and Sequencing

Open access
Salazar-Gonzalez, Jesus F., Bailes, Elizabeth, Pham, Kimmy T., Salazar, Maria G., Guffey, M. Brad, Keele, Brandon F., Derdeyn, Cynthia A., Farmer, Paul, Hunter, Eric, Allen, Susan, Manigart, Olivier, Mulenga, Joseph, Anderson, Jeffrey A., Swanstrom, Ronald, Haynes, Barton F., Athreya, Gayathri S., Korber, Bette T. M., Sharp, Paul M., Shaw, George M., Hahn, Beatrice H.·2008·Journal of Virology

Abstract

Accurate identification of the transmitted virus and sequences evolving from it could be instrumental in elucidating the transmission of human immunodeficiency virus type 1 (HIV-1) and in developing vaccines, drugs, or microbicides to prevent infection. Here we describe an experimental approach to analyze HIV-1 env genes as intact genetic units amplified from plasma virion RNA by single-genome amplification (SGA), followed by direct sequencing of uncloned DNA amplicons. We show that this strategy precludes in vitro artifacts caused by Taq -induced nucleotide substitutions and template switching, provides an accurate representation of the env quasispecies in vivo, and has an overall error rate (including nucleotide misincorporation, insertion, and deletion) of less than 8 × 10 −5 . Applying this method to the analysis of virus in plasma from 12 Zambian subjects from whom samples were obtained within 3 months of seroconversion, we show that transmitted or early founder viruses can be identified and that molecular pathways and rates of early env diversification can be defined. Specifically, we show that 8 of the 12 subjects were each infected by a single virus, while 4 others acquired more than one virus; that the rate of virus evolution in one subject during an 80-day period spanning seroconversion was 1.7 × 10 −5 substitutions per site per day; and that evidence of strong immunologic selection can be seen in Env and overlapping Rev sequences based on nonrandom accumulation of nonsynonymous mutations. We also compared the results of the SGA approach with those of more-conventional bulk PCR amplification methods performed on the same patient samples and found that the latter is associated with excessive rates of Taq -induced recombination, nucleotide misincorporation, template resampling, and cloning bias. These findings indicate that HIV-1 env genes, other viral genes, and even full-length viral genomes responsible for productive clinical infection can be identified by SGA analysis of plasma virus sampled at intervals typical in large-scale vaccine trials and that pathways of viral diversification and immune escape can be determined accurately.

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Metadata

Authors
Salazar-Gonzalez, J. F., Bailes, E., Pham, K. T., Salazar, M. G., Guffey, M. B., Keele, B. F., Derdeyn, C. A., Farmer, P., Hunter, E., Allen, S., Manigart, O., Mulenga, J., Anderson, J. A., Swanstrom, R., Haynes, B. F., Athreya, G. S., Korber, B. T. M., Sharp, P. M., Shaw, G. M., & Hahn, B. H.
Venue
Journal of Virology
Published
2008-04-15
Volume
82
Issue
8
Pages
3952-3970
ISSN
  • 0022-538X (ISSN-L)
  • 1098-5514
OpenAlex
W2148245437
Cited by
596
References
6
FWCI
17.53
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Deciphering Human Immunodeficiency Virus Type 1 Transmission and Early Envelope Diversification by Single-Genome Amplification and Sequencing. https://app.cochat.ai/papers/10.1128/jvi.02660-07
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Salazar-Gonzalez, J. F., Bailes, E., Pham, K. T., Salazar, M. G., Guffey, M. B., Keele, B. F., Derdeyn, C. A., Farmer, P., Hunter, E., Allen, S., Manigart, O., Mulenga, J., Anderson, J. A., Swanstrom, R., Haynes, B. F., Athreya, G. S., Korber, B. T. M., Sharp, P. M., Shaw, G. M., & Hahn, B. H. (2008). Deciphering Human Immunodeficiency Virus Type 1 Transmission and Early Envelope Diversification by Single-Genome Amplification and Sequencing. Journal of Virology. https://doi.org/10.1128/jvi.02660-07

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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