Evidence map›Paper›PMID 31801862›Full record

ArticleJournal of virology2020

Impact of Suboptimal APOBEC3G Neutralization on the Emergence of HIV Drug Resistance in Humanized Mice.

Matthew M Hernandez, Audrey Fahrny, Anitha Jayaprakash, Gustavo Gers-Huber, Marsha Dillon-White, Annette Audigé, Lubbertus C F Mulder, Ravi Sachidanandam, Roberto F Speck, Viviana Simon

Open access · greenAbstract read
In one paragraph

Article in Journal of virology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Matthew M Hernandez *The Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Audrey Fahrny *Division of Infectious Diseases and Hospital Epidemiology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland.
Anitha JayaprakashDepartment of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Gustavo Gers-HuberDivision of Infectious Diseases and Hospital Epidemiology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland.
Marsha Dillon-WhiteDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Annette AudigéDivision of Infectious Diseases and Hospital Epidemiology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland.
Lubbertus C F MulderDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Ravi Sachidanandam *Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Roberto F Speck *Division of Infectious Diseases and Hospital Epidemiology, University Hospital of Zurich, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-8453-1137
Viviana Simon *Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA viviana.simon@mssm.edu.
Icahn School of Medicine at Mount Sinai · USUniversity of Zurich · CHThe Graduate Center, CUNY · US

Funding

MOUNT SINAI MEDICAL SCIENTIST TRAINING PROGRAMT32GM007280 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI BARON, MARGARET H · 1985 to 2021
$22.8M
TRAINING PROGRAM: MECHANISMS OF VIRUS-HOST INTERACTIONST32AI007647 · NIAID · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI Domenico Tortorella · 2000 to 2026
$11.5M
HIV Evolution Driven by Intracellular DefensesR01AI064001 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SIMON, VIVIANA A · 2005 to 2015
$3.8M
HIV restriction by APOBEC3AR01AI120998 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SIMON, VIVIANA A · 2016 to 2020
$2.4M
Impact of HERV-K expression on HIV-1 life cycleR01GM113886 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MULDER, LUBBERTUS C · 2014 to 2018
$1.8M
NIAID NIH HHS R01 AI064001NIAID NIH HHS R01 AI120998NIAID NIH HHS T32 AI007647NIGMS NIH HHS R01 GM113886NIGMS NIH HHS T32 GM007280
6 · The paper itself

Abstract

HIV diversification facilitates immune escape and complicates antiretroviral therapy. In this study, we take advantage of a humanized-mouse model to probe the contribution of APOBEC3 mutagenesis to viral evolution. Humanized mice were infected with isogenic HIV molecular clones (HIV-WT, HIV-45G, and HIV-ΔSLQ) that differ in their abilities to counteract APOBEC3G (A3G). Infected mice remained naive or were treated with the reverse transcriptase (RT) inhibitor lamivudine (3TC). Viremia, emergence of drug-resistant variants, and quasispecies diversification in the plasma compartment were determined throughout infection. While both HIV-WT and HIV-45G achieved robust infection, over time, HIV-45G replication was significantly reduced compared to that of HIV-WT in the absence of 3TC treatment. In contrast, treatment responses differed significantly between HIV-45G- and HIV-WT-infected mice. Antiretroviral treatment failed in 91% of HIV-45G-infected mice, while only 36% of HIV-WT-infected mice displayed a similar negative outcome. Emergence of 3TC-resistant variants and nucleotide diversity were determined by analyzing 155,462 single HIV reverse transcriptase gene (

Indexed as

AnimalsAnti-HIV AgentsAPOBEC-3G DeaminaseDisease Models, AnimalDrug Resistance, ViralGenetic VariationHEK293 CellsHIV-1HIV InfectionsHumansLamivudineMiceVirus ReplicationAnti-HIV AgentsAPOBEC-3G DeaminaseAPOBEC3G protein, mouseLamivudineAPOBEC3HIV diversificationHIV drug resistanceHIV Vifhuman immunodeficiency virushumanized micevirus-host interactions

Identifiers

PMID31801862
PMCPMC7022346
OpenAlexW2992592289

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.