Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.

At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rat...

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Autores principales:	Art F Y Poon, Luke C Swenson, Evelien M Bunnik, Diana Edo-Matas, Hanneke Schuitemaker, Angélique B van 't Wout, P Richard Harrigan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/67f567acd2e642d6b7c2cbf1aac1c063
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spelling	oai:doaj.org-article:67f567acd2e642d6b7c2cbf1aac1c0632021-11-18T05:52:44ZReconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.1553-734X1553-735810.1371/journal.pcbi.1002753https://doaj.org/article/67f567acd2e642d6b7c2cbf1aac1c0632012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23133358/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rate of progression to AIDS. The presence of a 'fitness valley' separating CCR5- and CXCR4-using genotypes is postulated to be a biological determinant of whether the HIV coreceptor switch occurs. Using phylogenetic methods to reconstruct the evolutionary dynamics of HIV within hosts enables us to discriminate between competing models of this process. We have developed a phylogenetic pipeline for the molecular clock analysis, ancestral reconstruction, and visualization of deep sequence data. These data were generated by next-generation sequencing of HIV RNA extracted from longitudinal serum samples (median 7 time points) from 8 untreated subjects with chronic HIV infections (Amsterdam Cohort Studies on HIV-1 infection and AIDS). We used the known dates of sampling to directly estimate rates of evolution and to map ancestral mutations to a reconstructed timeline in units of days. HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. We determined that the first mutations contributing to CXCR4 use emerged about 16 (per subject range 4 to 30) months before the earliest predicted CXCR4-using ancestor, which preceded the first positive cell-based assay of CXCR4 usage by 10 (range 5 to 25) months. CXCR4 usage arose in multiple lineages within 5 of 8 subjects, and ancestral lineages following alternate mutational pathways before going extinct were common. We observed highly patient-specific distributions and time-scales of mutation accumulation, implying that the role of a fitness valley is contingent on the genotype of the transmitted variant.Art F Y PoonLuke C SwensonEvelien M BunnikDiana Edo-MatasHanneke SchuitemakerAngélique B van 't WoutP Richard HarriganPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 8, Iss 11, p e1002753 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Art F Y Poon Luke C Swenson Evelien M Bunnik Diana Edo-Matas Hanneke Schuitemaker Angélique B van 't Wout P Richard Harrigan Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
description	At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rate of progression to AIDS. The presence of a 'fitness valley' separating CCR5- and CXCR4-using genotypes is postulated to be a biological determinant of whether the HIV coreceptor switch occurs. Using phylogenetic methods to reconstruct the evolutionary dynamics of HIV within hosts enables us to discriminate between competing models of this process. We have developed a phylogenetic pipeline for the molecular clock analysis, ancestral reconstruction, and visualization of deep sequence data. These data were generated by next-generation sequencing of HIV RNA extracted from longitudinal serum samples (median 7 time points) from 8 untreated subjects with chronic HIV infections (Amsterdam Cohort Studies on HIV-1 infection and AIDS). We used the known dates of sampling to directly estimate rates of evolution and to map ancestral mutations to a reconstructed timeline in units of days. HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. We determined that the first mutations contributing to CXCR4 use emerged about 16 (per subject range 4 to 30) months before the earliest predicted CXCR4-using ancestor, which preceded the first positive cell-based assay of CXCR4 usage by 10 (range 5 to 25) months. CXCR4 usage arose in multiple lineages within 5 of 8 subjects, and ancestral lineages following alternate mutational pathways before going extinct were common. We observed highly patient-specific distributions and time-scales of mutation accumulation, implying that the role of a fitness valley is contingent on the genotype of the transmitted variant.
format	article
author	Art F Y Poon Luke C Swenson Evelien M Bunnik Diana Edo-Matas Hanneke Schuitemaker Angélique B van 't Wout P Richard Harrigan
author_facet	Art F Y Poon Luke C Swenson Evelien M Bunnik Diana Edo-Matas Hanneke Schuitemaker Angélique B van 't Wout P Richard Harrigan
author_sort	Art F Y Poon
title	Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
title_short	Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
title_full	Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
title_fullStr	Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
title_full_unstemmed	Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.
title_sort	reconstructing the dynamics of hiv evolution within hosts from serial deep sequence data.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/67f567acd2e642d6b7c2cbf1aac1c063
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Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data.

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