Evidence map›Paper›PMID 25340797›Full record

ArticlePLoS computational biology2014

Quantifying the turnover of transcriptional subclasses of HIV-1-infected cells.

Christian L Althaus, Beda Joos, Alan S Perelson, Huldrych F Günthard

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Persistent HIV-1 transcription in CD4Journal of virus eradication · 2021
    Article
  5. Phylogenetic approach to recover integration dates of latent HIV sequences within-host.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  6. Observational
  7. Article
  8. Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Dynamic models of viral replication and latency.Current opinion in HIV and AIDS · 2015
    Review
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

4 authors.

Christian L AlthausInstitute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Beda JoosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.
Alan S PerelsonTheoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Huldrych F GünthardDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.

Funding

Viral Sequencing CoreU19AI067854 · NIAID · DUKE UNIVERSITY · PI LETVIN, NORMAN L · 2006 to 2011
$290.5M
Virus biology scientific research support componentUM1AI100645 · NIAID · DUKE UNIVERSITY · PI MCMICHAEL, ANDREW JAMES · 2012 to 2018
$204.7M
Viral and Host Determinants of HIV-1 TransmissionU01AI067854 · NIAID · DUKE UNIVERSITY · PI HAYNES, BARTON F · 2005 to 2005
$14.9M
Modeling Viral and T Lymphocyte DynamicsR01OD011095 · OD · TRIAD NATIONAL SECURITY, LLC · PI PERELSON, ALAN S · 2012 to 2024
$5.0M
Immune System Modeling/HIVR01AI028433 · NIAID · UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB · PI PERELSON, ALAN S · 1990 to 2021
$3.7M
Immune System Modeling/HIVR37AI028433 · NIAID · UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB · PI PERELSON, ALAN S · 2002 to 2011
$2.4M
NIAID NIH HHS AI028433NIAID NIH HHS AI067854NIAID NIH HHS AI100645NIAID NIH HHS R01 AI028433NIAID NIH HHS R37 AI028433NIAID NIH HHS U01 AI067854NIAID NIH HHS U19 AI067854NIAID NIH HHS UM1 AI100645NIH HHS OD011095NIH HHS R01 OD011095
6 · The paper itself

Abstract

HIV-1-infected cells in peripheral blood can be grouped into different transcriptional subclasses. Quantifying the turnover of these cellular subclasses can provide important insights into the viral life cycle and the generation and maintenance of latently infected cells. We used previously published data from five patients chronically infected with HIV-1 that initiated combination antiretroviral therapy (cART). Patient-matched PCR for unspliced and multiply spliced viral RNAs combined with limiting dilution analysis provided measurements of transcriptional profiles at the single cell level. Furthermore, measurement of intracellular transcripts and extracellular virion-enclosed HIV-1 RNA allowed us to distinguish productive from non-productive cells. We developed a mathematical model describing the dynamics of plasma virus and the transcriptional subclasses of HIV-1-infected cells. Fitting the model to the data allowed us to better understand the phenotype of different transcriptional subclasses and their contribution to the overall turnover of HIV-1 before and during cART. The average number of virus-producing cells in peripheral blood is small during chronic infection. We find that a substantial fraction of cells can become defectively infected. Assuming that the infection is homogenous throughout the body, we estimate an average in vivo viral burst size on the order of 104 virions per cell. Our study provides novel quantitative insights into the turnover and development of different subclasses of HIV-1-infected cells, and indicates that cells containing solely unspliced viral RNA are a good marker for viral latency. The model illustrates how the pool of latently infected cells becomes rapidly established during the first months of acute infection and continues to increase slowly during the first years of chronic infection. Having a detailed understanding of this process will be useful for the evaluation of viral eradication strategies that aim to deplete the latent reservoir of HIV-1.

Indexed as

Models, GeneticAnti-Retroviral AgentsComputational BiologyDrug Therapy, CombinationHIV-1HIV InfectionsHumansLeukocytes, MononuclearRNA, ViralAnti-Retroviral AgentsRNA, Viral

Identifiers

PMID25340797
PMCPMC4207463

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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.