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Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays

BACKGROUND: The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the...

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Autores principales: Poon, Art F. Y., Prodger, Jessica L., Lynch, Briana A., Lai, Jun, Reynolds, Steven J., Kasule, Jingo, Capoferri, Adam A., Lamers, Susanna L., Rodriguez, Christopher W., Bruno, Daniel, Porcella, Stephen F., Martens, Craig, Quinn, Thomas C., Redd, Andrew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6034329/
https://www.ncbi.nlm.nih.gov/pubmed/29976219
http://dx.doi.org/10.1186/s12977-018-0426-1
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author Poon, Art F. Y.
Prodger, Jessica L.
Lynch, Briana A.
Lai, Jun
Reynolds, Steven J.
Kasule, Jingo
Capoferri, Adam A.
Lamers, Susanna L.
Rodriguez, Christopher W.
Bruno, Daniel
Porcella, Stephen F.
Martens, Craig
Quinn, Thomas C.
Redd, Andrew D.
author_facet Poon, Art F. Y.
Prodger, Jessica L.
Lynch, Briana A.
Lai, Jun
Reynolds, Steven J.
Kasule, Jingo
Capoferri, Adam A.
Lamers, Susanna L.
Rodriguez, Christopher W.
Bruno, Daniel
Porcella, Stephen F.
Martens, Craig
Quinn, Thomas C.
Redd, Andrew D.
author_sort Poon, Art F. Y.
collection PubMed
description BACKGROUND: The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the replication-competent HIV-1 LVR, measured by the number of infectious units per million (IUPM) cells. QVOAs are time-consuming because they rely on culturing replicate wells to amplify the production of virus antigen or nucleic acid to reproducibly detectable levels. Sequence analysis can reduce the required number of culture wells because the virus genetic diversity within the LVR provides an internal replication and dilution series. Here we develop a Bayesian method to jointly estimate the IUPM and variant frequencies (a measure of clonality) from the sequence diversity of QVOAs. RESULTS: Using simulation experiments, we find our Bayesian approach confers significantly greater accuracy over current methods to estimate the IUPM, particularly for reduced numbers of QVOA replicates and/or increasing actual IUPM. Furthermore, we determine that the improvement in accuracy is greater with increasing genetic diversity in the sample population. We contrast results of these different methods applied to new HIV-1 sequence data derived from QVOAs from two individuals with suppressed viral loads from the Rakai Health Sciences Program in Uganda. CONCLUSIONS: Utilizing sequence variation has the additional benefit of providing information on the contribution of clonality of the LVR, where high clonality (the predominance of a single genetic variant) suggests a role for cell division in the long-term persistence of the reservoir. In addition, our Bayesian approach can be adapted to other limiting dilution assays where positive outcomes can be partitioned by their genetic heterogeneity, such as immune cell populations and other viruses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12977-018-0426-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-60343292018-07-09 Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays Poon, Art F. Y. Prodger, Jessica L. Lynch, Briana A. Lai, Jun Reynolds, Steven J. Kasule, Jingo Capoferri, Adam A. Lamers, Susanna L. Rodriguez, Christopher W. Bruno, Daniel Porcella, Stephen F. Martens, Craig Quinn, Thomas C. Redd, Andrew D. Retrovirology Research BACKGROUND: The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the replication-competent HIV-1 LVR, measured by the number of infectious units per million (IUPM) cells. QVOAs are time-consuming because they rely on culturing replicate wells to amplify the production of virus antigen or nucleic acid to reproducibly detectable levels. Sequence analysis can reduce the required number of culture wells because the virus genetic diversity within the LVR provides an internal replication and dilution series. Here we develop a Bayesian method to jointly estimate the IUPM and variant frequencies (a measure of clonality) from the sequence diversity of QVOAs. RESULTS: Using simulation experiments, we find our Bayesian approach confers significantly greater accuracy over current methods to estimate the IUPM, particularly for reduced numbers of QVOA replicates and/or increasing actual IUPM. Furthermore, we determine that the improvement in accuracy is greater with increasing genetic diversity in the sample population. We contrast results of these different methods applied to new HIV-1 sequence data derived from QVOAs from two individuals with suppressed viral loads from the Rakai Health Sciences Program in Uganda. CONCLUSIONS: Utilizing sequence variation has the additional benefit of providing information on the contribution of clonality of the LVR, where high clonality (the predominance of a single genetic variant) suggests a role for cell division in the long-term persistence of the reservoir. In addition, our Bayesian approach can be adapted to other limiting dilution assays where positive outcomes can be partitioned by their genetic heterogeneity, such as immune cell populations and other viruses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12977-018-0426-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-05 /pmc/articles/PMC6034329/ /pubmed/29976219 http://dx.doi.org/10.1186/s12977-018-0426-1 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Poon, Art F. Y.
Prodger, Jessica L.
Lynch, Briana A.
Lai, Jun
Reynolds, Steven J.
Kasule, Jingo
Capoferri, Adam A.
Lamers, Susanna L.
Rodriguez, Christopher W.
Bruno, Daniel
Porcella, Stephen F.
Martens, Craig
Quinn, Thomas C.
Redd, Andrew D.
Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title_full Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title_fullStr Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title_full_unstemmed Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title_short Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays
title_sort quantitation of the latent hiv-1 reservoir from the sequence diversity in viral outgrowth assays
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6034329/
https://www.ncbi.nlm.nih.gov/pubmed/29976219
http://dx.doi.org/10.1186/s12977-018-0426-1
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