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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12

AUTHORS

Katarzyna Bozek, Manon Eckhardt, Saleta Sierra, Maria Anders, Rolf Kaiser, Hans-Georg Kräusslich, Barbara Müller, Thomas Lengauer

ABSTRACT

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. More... »

PAGES

60

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1742-4690-9-60

DOI

http://dx.doi.org/10.1186/1742-4690-9-60

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052217087

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22830600


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