Evidence map›Paper›PMID 40742736›Full record

ReviewCurrent opinion in HIV and AIDS2025

Using single cell technologies to understand HIV latency models.

Julia S Huff, Edward P Browne

Abstract readReview
In one paragraph

Review in Current opinion in HIV and AIDS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Julia S HuffDepartment of Microbiology and Immunology.
Edward P BrowneDepartment of Microbiology and Immunology.

Funding

Collaboratory of AIDS Researchers for Eradication (CARE)UM1AI164567 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2021 to 2026
$31.6M
Defining the impact of cannabinoids on the latent HIV reservoir through multi-omic analysisR61DA053599 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROWNE, EDWARD P · 2021 to 2023
$2.0M
Regulation of HIV Latency by Host Cell Transcriptional and Epigenetic NetworksR01AI143381 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROWNE, EDWARD P · 2019 to 2022
$1.6M
Defining the impact of cannabinoids on the latent HIV reservoir through multi-omic analysisR33DA053599 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROWNE, EDWARD P · 2024 to 2025
$1.5M
Understanding HIV reservoir formation by profiling transcriptomic and epigenetic changes in CD4 T cells following ART initiationR21AI174898 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROWNE, EDWARD P · 2023 to 2024
$428k
Regulation of HIV Latency by Host Cell Transcriptional and Epigenetic NetworksR56AI143381 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BROWNE, EDWARD P · 2024 to 2024
$415k
NIAID NIH HHS R01 AI143381NIAID NIH HHS R21 AI174898NIAID NIH HHS R56 AI143381NIAID NIH HHS UM1 AI164567NIDA NIH HHS R33 DA053599NIDA NIH HHS R61 DA053599
6 · The paper itself

Abstract

purpose of reviewThis review outlines current model systems of HIV latency and their analysis with single-cell omics technologies. Previous studies have used bulk analyses of infected cell cultures to determine mechanisms of HIV transcription and to identify targets associated with HIV latency in vitro . However, heterogeneity in cell populations creates a barrier to the effectiveness of latency reversing agents. Single cell approaches promise to accelerate our understanding of how the host cell environment regulates complex behaviors of the HIV provirus. RECENT

findingsSeveral recent papers have applied cutting edge single cell omics methods to model systems of HIV latency, including scRNAseq and scATACseq, as well as multiomic methods such as DOGMAseq and ECCITEseq. These papers have revealed complex heterogeneity in latently infected cells but have also led to the identification of several new host cell genes that regulate HIV latency. SUMMARY: Single-cell technologies provide sensitive detection of cellular subpopulations that contribute to proviral reactivation and latency, making them advantageous to apply to widely used cell line and primary cell models of HIV latency. These studies have increased our understanding of HIV latency model systems and generated novel hypotheses which can be tested in clinical samples from people with HIV.

Indexed as

HIV-1HIV InfectionsSingle-Cell AnalysisVirus LatencyHumanscell linesHIV reservoirlatencyprimary cellssingle cell multiomics

Identifiers

PMID40742736
PMCPMC12321199

What OpenQuestion holds

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Registered trials

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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.