Evidence map›Paper›PMID 41277841›Full record

ArticleJournal of virology2025

RNA splicing patterns contribute to burst size variation among HIV-1-infected Jurkat cell clones.

Kamya Gopal, Cleo Burnett, Siarhei Kharytonchyk, Ann Emery, Edmond Atindaana, Ronald Swanstrom, Jeffrey M Kidd, Alice Telesnitsky

Abstract read
In one paragraph

Article in Journal of virology, 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

8 authors.

Kamya GopalDepartment of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA.ORCID 0000-0002-8305-8384
Cleo BurnettDepartment of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Siarhei KharytonchykDepartment of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Ann EmeryLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Edmond AtindaanaDepartment of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Ronald SwanstromLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-7777-0773
Jeffrey M KiddDepartment of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Alice TelesnitskyDepartment of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA.ORCID 0000-0001-9878-5931

Funding

Center for Structural Biology of HIV RNAU54AI170660 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ALICE TELESNITSKY · 2022 to 2026
$32.1M
Cellular and Molecular Biology at MichiganT32GM145470 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI John Chadwick Brenner · 2022 to 2026
$4.1M
High throughput analysis of latency/reactivation with barcoded provirusesR33AI116190 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHANG, CHEONG-HEE, KIDD, JEFFREY M · 2016 to 2018
$1.4M
NIAID NIH HHS R33 AI116190NIAID NIH HHS U54 AI170660NIGMS NIH HHS T32 GM145470
6 · The paper itself

Abstract

Accurately quantifying virus release from HIV-1-infected cells is central to predicting infection outcomes and evaluating treatment strategies. Recent studies suggest that viral shedding can vary strikingly among infected cells. To identify predictors of virus release levels, a previously developed high-throughput molecular barcoding system was used to track the expression properties of individual infected clones within a polyclonal population. Consistent with previous reports, virus release spanned four orders of magnitude among clonal integrants. While reporter gene expression correlated poorly with virus release, intracellular viral RNA levels correlated well, and levels of unspliced HIV-1 RNA correlated most closely. Comparing clones with different virus release levels showed that they varied not only in total intracellular HIV-1 RNA levels but also in levels of viral RNA splicing. Remobilizing proviruses revealed that splicing differences were largely due to cell-intrinsic properties, although splicing differences were due to heritable features of the parent provirus for at least one clone. This clone displayed high levels of reporter gene expression from an HIV-1spliced RNA, but low levels of unspliced viral RNA and virus release. This over-splicing clone, which contained a non-synonymous substitution in IMPORTANCE: Many models of HIV-1 infection rely on the assumption that actively infected cells release similar amounts of virus, despite recent reports that suggest shedding differs drastically among infected cells. In this study, the expression phenotypes of hundreds of integrant clones were analyzed to identify factors contributing to burst size variation. In agreement with previous reports, virus release spanned over four orders of magnitude within the infected pool. Both proviral expression levels and variation in splicing contributed to these burst size differences. While cell-intrinsic factors appeared to be the primary contributors to heterogeneous shedding patterns, viral point mutations were also observed and, in at least one case, contributed to particle release levels. Together, these findings demonstrate that expression variation among proviruses is both large and multifaceted and suggest that clone-specific differences in HIV-1 expression properties may contribute to unpredicted responses to treatment interventions.

Indexed as

HIV-1HIV InfectionsRNA SplicingRNA, ViralVirus ReleaseClone CellsGene Expression Regulation, ViralHumansJurkat CellsProvirusesRNA, ViralHIV-1 expression parametersHIV-1 population dynamicshuman immunodeficiency viruslatency-reversing agentsRNA splicing

Identifiers

PMID41277841
PMCPMC12724336

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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.