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Inferring HIV Escape Rates from Multi-Locus Genotype Data

Kessinger, Taylor A. and Perelson, Alan S. and Neher, Richard A.. (2013) Inferring HIV Escape Rates from Multi-Locus Genotype Data. Frontiers in Immunology, 4. p. 252.

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Abstract

Cytotoxic T-lymphocytes (CTLs) recognize viral protein fragments displayed by major histocompatibility complex molecules on the surface of virally infected cells and generate an anti-viral response that can kill the infected cells. Virus variants whose protein fragments are not efficiently presented on infected cells or whose fragments are presented but not recognized by CTLs therefore have a competitive advantage and spread rapidly through the population. We present a method that allows a more robust estimation of these escape rates from serially sampled sequence data. The proposed method accounts for competition between multiple escapes by explicitly modeling the accumulation of escape mutations and the stochastic effects of rare multiple mutants. Applying our method to serially sampled HIV sequence data, we estimate rates of HIV escape that are substantially larger than those previously reported. The method can be extended to complex escapes that require compensatory mutations. We expect our method to be applicable in other contexts such as cancer evolution where time series data is also available.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Computational Modeling of Biological Processes (Neher)
UniBasel Contributors:Neher, Richard
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Frontiers Media
e-ISSN:1664-3224
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Identification Number:
Last Modified:17 Sep 2019 06:46
Deposited On:03 Oct 2017 09:56

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