Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST

ABSTRACT 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 s...

Full description

Bibliographic Details
Main Authors: Elena E. Giorgi, Hui Li, Tanmoy Bhattacharya, George M. Shaw, Bette Korber
Format: Article
Language:English
Published: American Society for Microbiology 2020-04-01
Series:mBio
Subjects:
Online Access:https://journals.asm.org/doi/10.1128/mBio.00324-20
_version_ 1819007153622482944
author Elena E. Giorgi
Hui Li
Tanmoy Bhattacharya
George M. Shaw
Bette Korber
author_facet Elena E. Giorgi
Hui Li
Tanmoy Bhattacharya
George M. Shaw
Bette Korber
author_sort Elena E. Giorgi
collection DOAJ
description ABSTRACT 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. IMPORTANCE The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.
first_indexed 2024-12-21T00:20:03Z
format Article
id doaj.art-30d9bab6c88c43259eb13ceab14d43db
institution Directory Open Access Journal
issn 2150-7511
language English
last_indexed 2024-12-21T00:20:03Z
publishDate 2020-04-01
publisher American Society for Microbiology
record_format Article
series mBio
spelling doaj.art-30d9bab6c88c43259eb13ceab14d43db2022-12-21T19:22:07ZengAmerican Society for MicrobiologymBio2150-75112020-04-0111210.1128/mBio.00324-20Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEASTElena E. Giorgi0Hui Li1Tanmoy Bhattacharya2George M. Shaw3Bette Korber4Los Alamos National Laboratory, Los Alamos, New Mexico, USAPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USALos Alamos National Laboratory, Los Alamos, New Mexico, USAPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USALos Alamos National Laboratory, Los Alamos, New Mexico, USAABSTRACT 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. IMPORTANCE The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.https://journals.asm.org/doi/10.1128/mBio.00324-20evolutionHIVSHIVtransmission
spellingShingle Elena E. Giorgi
Hui Li
Tanmoy Bhattacharya
George M. Shaw
Bette Korber
Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
mBio
evolution
HIV
SHIV
transmission
title Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
title_full Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
title_fullStr Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
title_full_unstemmed Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
title_short Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST
title_sort estimating the timing of early simian human immunodeficiency virus infections a comparison between poisson fitter and beast
topic evolution
HIV
SHIV
transmission
url https://journals.asm.org/doi/10.1128/mBio.00324-20
work_keys_str_mv AT elenaegiorgi estimatingthetimingofearlysimianhumanimmunodeficiencyvirusinfectionsacomparisonbetweenpoissonfitterandbeast
AT huili estimatingthetimingofearlysimianhumanimmunodeficiencyvirusinfectionsacomparisonbetweenpoissonfitterandbeast
AT tanmoybhattacharya estimatingthetimingofearlysimianhumanimmunodeficiencyvirusinfectionsacomparisonbetweenpoissonfitterandbeast
AT georgemshaw estimatingthetimingofearlysimianhumanimmunodeficiencyvirusinfectionsacomparisonbetweenpoissonfitterandbeast
AT bettekorber estimatingthetimingofearlysimianhumanimmunodeficiencyvirusinfectionsacomparisonbetweenpoissonfitterandbeast