An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data

<p>Abstract</p> <p>Background</p> <p>Entry of human immunodeficiency virus type 1 (HIV-1) into the host cell involves interactions between the viral envelope glycoproteins (Env) and the cellular receptor CD4 as well as a coreceptor molecule (most importantly CCR5 or CXC...

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Main Authors: Bozek Katarzyna, Eckhardt Manon, Sierra Saleta, Anders Maria, Kaiser Rolf, Kräusslich Hans-Georg, Müller Barbara, Lengauer Thomas
Format: Article
Language:English
Published: BMC 2012-07-01
Series:Retrovirology
Online Access:http://www.retrovirology.com/content/9/1/60
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author Bozek Katarzyna
Eckhardt Manon
Sierra Saleta
Anders Maria
Kaiser Rolf
Kräusslich Hans-Georg
Müller Barbara
Lengauer Thomas
author_facet Bozek Katarzyna
Eckhardt Manon
Sierra Saleta
Anders Maria
Kaiser Rolf
Kräusslich Hans-Georg
Müller Barbara
Lengauer Thomas
author_sort Bozek Katarzyna
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Entry of human immunodeficiency virus type 1 (HIV-1) into the host cell involves interactions between the viral envelope glycoproteins (Env) and the cellular receptor CD4 as well as a coreceptor molecule (most importantly CCR5 or CXCR4). Viral preference for a specific coreceptor (tropism) is in particular determined by the third variable loop (V3) of the Env glycoprotein gp120. The approval and use of a coreceptor antagonist for antiretroviral therapy make detailed understanding of tropism and its accurate prediction from patient derived virus isolates essential. The aim of the present study is the development of an extended description of the HIV entry phenotype reflecting its co-dependence on several key determinants as the basis for a more accurate prediction of HIV-1 entry phenotype from genotypic data.</p> <p>Results</p> <p>Here, we established a new protocol of quantitation and computational analysis of the dependence of HIV entry efficiency on receptor and coreceptor cell surface levels as well as viral V3 loop sequence and the presence of two prototypic coreceptor antagonists in varying concentrations. Based on data collected at the single-cell level, we constructed regression models of the HIV-1 entry phenotype integrating the measured determinants. We developed a multivariate phenotype descriptor, termed phenotype vector, which facilitates a more detailed characterization of HIV entry phenotypes than currently used binary tropism classifications. For some of the tested virus variants, the multivariant phenotype vector revealed substantial divergences from existing tropism predictions. We also developed methods for computational prediction of the entry phenotypes based on the V3 sequence and performed an extrapolating calculation of the effectiveness of this computational procedure.</p> <p>Conclusions</p> <p>Our study of the HIV cell entry phenotype and the novel multivariate representation developed here contributes to a more detailed understanding of this phenotype and offers potential for future application in the effective administration of entry inhibitors in antiretroviral therapies.</p>
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spelling doaj.art-048a1d4290aa45b5ada15ca682f089452022-12-21T21:18:00ZengBMCRetrovirology1742-46902012-07-01916010.1186/1742-4690-9-60An expanded model of HIV cell entry phenotype based on multi-parameter single-cell dataBozek KatarzynaEckhardt ManonSierra SaletaAnders MariaKaiser RolfKräusslich Hans-GeorgMüller BarbaraLengauer Thomas<p>Abstract</p> <p>Background</p> <p>Entry of human immunodeficiency virus type 1 (HIV-1) into the host cell involves interactions between the viral envelope glycoproteins (Env) and the cellular receptor CD4 as well as a coreceptor molecule (most importantly CCR5 or CXCR4). Viral preference for a specific coreceptor (tropism) is in particular determined by the third variable loop (V3) of the Env glycoprotein gp120. The approval and use of a coreceptor antagonist for antiretroviral therapy make detailed understanding of tropism and its accurate prediction from patient derived virus isolates essential. The aim of the present study is the development of an extended description of the HIV entry phenotype reflecting its co-dependence on several key determinants as the basis for a more accurate prediction of HIV-1 entry phenotype from genotypic data.</p> <p>Results</p> <p>Here, we established a new protocol of quantitation and computational analysis of the dependence of HIV entry efficiency on receptor and coreceptor cell surface levels as well as viral V3 loop sequence and the presence of two prototypic coreceptor antagonists in varying concentrations. Based on data collected at the single-cell level, we constructed regression models of the HIV-1 entry phenotype integrating the measured determinants. We developed a multivariate phenotype descriptor, termed phenotype vector, which facilitates a more detailed characterization of HIV entry phenotypes than currently used binary tropism classifications. For some of the tested virus variants, the multivariant phenotype vector revealed substantial divergences from existing tropism predictions. We also developed methods for computational prediction of the entry phenotypes based on the V3 sequence and performed an extrapolating calculation of the effectiveness of this computational procedure.</p> <p>Conclusions</p> <p>Our study of the HIV cell entry phenotype and the novel multivariate representation developed here contributes to a more detailed understanding of this phenotype and offers potential for future application in the effective administration of entry inhibitors in antiretroviral therapies.</p>http://www.retrovirology.com/content/9/1/60
spellingShingle Bozek Katarzyna
Eckhardt Manon
Sierra Saleta
Anders Maria
Kaiser Rolf
Kräusslich Hans-Georg
Müller Barbara
Lengauer Thomas
An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
Retrovirology
title An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
title_full An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
title_fullStr An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
title_full_unstemmed An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
title_short An expanded model of HIV cell entry phenotype based on multi-parameter single-cell data
title_sort expanded model of hiv cell entry phenotype based on multi parameter single cell data
url http://www.retrovirology.com/content/9/1/60
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