Evidence map›Paper›PMID 31692968›Full record

ArticleScience advances2019

More than efficacy revealed by single-cell analysis of antiviral therapeutics.

Wu Liu, Mehmet U Caglar, Zhangming Mao, Andrew Woodman, Jamie J Arnold, Claus O Wilke, Craig E Cameron

Abstract read
In one paragraph

Article in Science advances, 2019. 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
–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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. High-Throughput Single-Cell Analysis of Vaccinia Virus Infection.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  6. Article
  7. Non-lytic spread of poliovirus requires the nonstructural protein 3CD.bioRxiv : the preprint server for biology · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. 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

7 authors.

Wu LiuDepartment of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16801, USA.ORCID 0000-0001-6259-3049
Mehmet U CaglarCenter for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, and Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-4377-3770
Zhangming MaoDepartment of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA.
Andrew WoodmanDepartment of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16801, USA.
Jamie J ArnoldDepartment of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16801, USA.
Claus O WilkeCenter for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, and Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-7470-9261
Craig E CameronDepartment of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16801, USA.ORCID 0000-0002-7564-5642

Funding

Single-Cell VirologyR01AI120560 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI CAMERON, CRAIG E., HUANG, TONY JUN · 2015 to 2017
$1.4M
NIAID NIH HHS R01 AI120560
6 · The paper itself

Abstract

Because many aspects of viral infection dynamics and inhibition are governed by stochastic processes, single-cell analysis should provide more information than approaches using population averaging. We have developed a microfluidic device composed of ~6000 wells, with each well containing a microstructure to capture single, infected cells replicating an enterovirus expressing a fluorescent reporter protein. We have used this system to characterize enterovirus inhibitors with distinct mechanisms of action. Single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates not only reveals efficacy but also facilitates clustering of drugs with the same mechanism of action and provides some indication of the ease with which resistance will develop.

Indexed as

Single-Cell AnalysisAntiviral AgentsDrug Therapy, CombinationHeLa CellsHSP90 Heat-Shock ProteinsHumansMicrofluidicsNucleic Acid Synthesis InhibitorsPoliovirusPrincipal Component AnalysisProtease InhibitorsAntiviral AgentsHSP90 Heat-Shock ProteinsNucleic Acid Synthesis InhibitorsProtease Inhibitors

Identifiers

PMID31692968
PMCPMC6821460

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.