Evidence map›Paper›PMID 26138068›Full record

ArticleIntegrative biology : quantitative biosciences from nano to macro2015

A passive-flow microfluidic device for imaging latent HIV activation dynamics in single T cells.

Ramesh Ramji, Victor C Wong, Arvind K Chavali, Larisa M Gearhart, Kathryn Miller-Jensen

Open access · bronzeAbstract read
In one paragraph

Article in Integrative biology : quantitative biosciences from nano to macro, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  10. Quantitative profiling of innate immune activation by viral infection in single cells.Integrative biology : quantitative biosciences from nano to macro · 2017
    Article
  11. Article
  12. Single-cell resolution of intracellular T cell CaIntegrative biology : quantitative biosciences from nano to macro · 2017
    Article
  13. Review
  14. Article
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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

5 authors at 2 institutions in 1 country.

Ramesh Ramji *Department of Biomedical Engineering, Yale University, New Haven, CT 06511.
Victor C Wong *Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06511.
Arvind K Chavali *Department of Biomedical Engineering, Yale University, New Haven, CT 06511.
Larisa M GearhartDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511.
Kathryn Miller-JensenDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511.
Yale University · USMills College · US

Funding

PREDOCTORAL TRAINING PROGRAM IN GENETICST32GM007499 · NIGMS · YALE UNIVERSITY · PI CARLSON, JOHN R, REINKE, VALERIE J · 1985 to 2022
$13.9M
NIGMS NIH HHS 2T32GM007499-36NIGMS NIH HHS 5T32GM007499-34NIGMS NIH HHS 5T32GM007499-35NIGMS NIH HHS T32 GM007499
6 · The paper itself

Abstract

Quantifying cell-to-cell variability in drug response dynamics is important when evaluating therapeutic efficacy. For example, optimizing latency reversing agents (LRAs) for use in a clinical "activate-and-kill" strategy to purge the latent HIV reservoir in patients requires minimizing heterogeneous viral activation dynamics. To evaluate how heterogeneity in latent HIV activation varies across a range of LRAs, we tracked drug-induced response dynamics in single cells via live-cell imaging using a latent HIV-GFP reporter virus in a clonal Jurkat T cell line. To enable these studies in suspension cells, we designed a simple method to capture an array of single Jurkat T cells using a passive-flow microfluidic device. Our device, which does not require external pumps or tubing, can trap hundreds of cells within minutes with a high retention rate over 12 hours of imaging. Using this device, we quantified heterogeneity in viral activation stimulated by transcription factor (TF) activators and histone deacetylase (HDAC) inhibitors. Generally, TF activators resulted in both faster onset of viral activation and faster rates of production, while HDAC inhibitors resulted in more uniform onset times, but more heterogeneous rates of production. Finally, we demonstrated that while onset time of viral gene expression and rate of viral production together predict total HIV activation, rate and onset time were not correlated within the same individual cell, suggesting that these features are regulated independently. Overall, our results reveal drug-specific patterns of noisy HIV activation dynamics not previously identified in static single-cell assays, which may require consideration for the most effective activate-and-kill regime.

Indexed as

Lab-On-A-Chip DevicesBiological AssayCell SeparationEquipment DesignEquipment Failure AnalysisFlow Injection AnalysisHistone Deacetylase InhibitorsHIVHumansJurkat CellsMicroscopy, FluorescenceTissue Array AnalysisVirus ActivationVirus LatencyHistone Deacetylase Inhibitors

Identifiers

PMID26138068
PMCPMC4558391
OpenAlexW2117599920

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

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.