Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST.
HIV
SHIV
evolution
transmission
Journal
mBio
ISSN: 2150-7511
Titre abrégé: mBio
Pays: United States
ID NLM: 101519231
Informations de publication
Date de publication:
24 03 2020
24 03 2020
Historique:
entrez:
27
3
2020
pubmed:
27
3
2020
medline:
13
3
2021
Statut:
epublish
Résumé
Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants' times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST.
Identifiants
pubmed: 32209678
pii: mBio.00324-20
doi: 10.1128/mBio.00324-20
pmc: PMC7157514
pii:
doi:
Substances chimiques
RNA, Viral
0
Types de publication
Comparative Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIAID NIH HHS
ID : P01 AI131251
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI131331
Pays : United States
Organisme : NIAID NIH HHS
ID : R37 AI150590
Pays : United States
Informations de copyright
Copyright © 2020 Giorgi et al.
Références
Viruses. 2019 Jul 03;11(7):
pubmed: 31277299
AIDS. 2003 Sep 5;17(13):1871-9
pubmed: 12960819
J Clin Invest. 2013 Jan;123(1):380-93
pubmed: 23221345
BMC Evol Biol. 2007 Nov 08;7:214
pubmed: 17996036
J Exp Med. 2009 Jun 8;206(6):1253-72
pubmed: 19487423
PLoS Pathog. 2005 Sep;1(1):e6
pubmed: 16201018
Bioinformatics. 2000 Apr;16(4):400-1
pubmed: 10869039
PLoS One. 2010 Aug 20;5(8):e12303
pubmed: 20808830
J Virol. 1995 Aug;69(8):5087-94
pubmed: 7541846
Sci Rep. 2016 Dec 02;6:38130
pubmed: 27909304
Nat Commun. 2018 May 15;9(1):1928
pubmed: 29765018
Proc Natl Acad Sci U S A. 2013 Jan 2;110(1):228-33
pubmed: 23248286
BMC Bioinformatics. 2010 Oct 25;11:532
pubmed: 20973976
Proc Natl Acad Sci U S A. 2016 Jun 14;113(24):E3413-22
pubmed: 27247400
Front Immunol. 2018 Apr 27;9:912
pubmed: 29780384
Genetics. 2000 Jul;155(3):1429-37
pubmed: 10880500
Proc Natl Acad Sci U S A. 2008 May 27;105(21):7552-7
pubmed: 18490657
BMC Infect Dis. 2019 Oct 26;19(1):894
pubmed: 31655566
PLoS Pathog. 2016 May 17;12(5):e1005646
pubmed: 27186986
AIDS. 2011 Oct 23;25(16):2019-26
pubmed: 21832936
Mol Biol Evol. 2005 May;22(5):1185-92
pubmed: 15703244