Please use this identifier to cite or link to this item:
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Within-epitope interactions can bias CTL escape estimation in early HIV infection
Authors: Garcia, Victor
Feldman, Marcus W.
DOI: 10.21256/zhaw-3857
Published in: Frontiers in Immunology
Volume(Issue): 8
Issue: 423
Issue Date: 1-May-2017
Publisher / Ed. Institution: Frontiers Research Foundation
ISSN: 1664-3224
Language: English
Subjects: Cytotoxic T lymphocytes (CTL); Escape; Genetic interference; Human immunodeficiency virus (HIV); Population genetics
Subject (DDC): 571: Physiology and related subjects
Abstract: As human immunodeficiency virus (HIV) begins to replicate within hosts, immune responses are elicited against it. Escape mutations in viral epitopes-immunogenic peptide parts presented on the surface of infected cells-allow HIV to partially evade these responses, and thus rapidly go to fixation. The faster they go to fixation, i.e., the higher their escape rate, the larger the selective pressure exerted by the immune system is assumed to be. This relation underpins the rationale for using escapes to assess the strength of immune responses. However, escape rate estimates are often obtained by employing an aggregation procedure, where several mutations that affect the same epitope are aggregated into a single, composite epitope mutation. The aggregation procedure thus rests upon the assumption that all within-epitope mutations have indistinguishable effects on immune recognition. In this study, we investigate how violation of this assumption affects escape rate estimates. To this end, we extend a previously developed simulation model of HIV that accounts for mutation, selection, and recombination to include different distributions of fitness effects (DFEs) and inter-mutational genomic distances. We use this discrete time Wright-Fisher based model to simulate early within-host evolution of HIV for DFEs and apply standard estimation methods to infer the escape rates. We then compare true with estimated escape rate values. We also compare escape rate values obtained by applying the aggregation procedure with values estimated without use of that procedure. We find that across the DFEs analyzed, the aggregation procedure alters the detectability of escape mutations: large-effect mutations are overrepresented while small-effect mutations are concealed. The effect of the aggregation procedure is similar to extracting the largest-effect mutation appearing within an epitope. Furthermore, the more pronounced the over-exponential decay of the DFEs, the more severely true escape rates are underestimated. We conclude that the aggregation procedure has two main consequences. On the one hand, it leads to a misrepresentation of the DFE of fixed mutations. On the other hand, it conceals within-epitope interactions that may generate irregularities in mutation frequency trajectories that are thus left unexplained.
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Applied Simulation (IAS)
Appears in Collections:Publikationen Life Sciences und Facility Management

Files in This Item:
File Description SizeFormat 
fimmu-08-00423.pdfVicGarcia_FrontiersImmunology_Publication3.25 MBAdobe PDFThumbnail

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.