Evidence map›Paper›PMID 30468747›Full record

ArticleJournal of virological methods2019

A high-throughput inhibition assay to study MERS-CoV antibody interactions using image cytometry.

Osnat Rosen, Leo Li-Ying Chan, Olubukola M Abiona, Portia Gough, Lingshu Wang, Wei Shi, Yi Zhang, Nianshuang Wang, Wing-Pui Kong, Jason S McLellan and 2 more

Abstract read
In one paragraph

Article in Journal of virological methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. Article
  6. A high-throughput chemotaxis detection method for CCR4Journal of immunological methods · 2020
    Article
  7. Machine Learning, COVID-19 (2019-nCoV), and multi-OMICS.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2020
    Article
  8. Article
  9. Article
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

12 authors at 3 institutions in 1 country.

Osnat RosenVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Leo Li-Ying ChanDepartment of Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA 01843, United States.
Olubukola M AbionaVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Portia GoughDepartment of Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA 01843, United States.
Lingshu WangVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Wei ShiVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Yi ZhangVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Nianshuang WangMolecular Biosciences Department, University of Texas at Austin, Austin, TX 03755, United States.
Wing-Pui KongVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States.
Jason S McLellanMolecular Biosciences Department, University of Texas at Austin, Austin, TX 03755, United States.
Barney S GrahamVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States. Electronic address: bgraham@nih.gov.
Kizzmekia S CorbettVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, United States. Electronic address: kizzmekia.corbett@nih.gov.
National Institutes of Health · USNational Institute of Allergy and Infectious Diseases · USThe University of Texas at Austin · US

Funding

Pre-clinical Vaccine Development for Emerging and Re-emerging Infectious DiseasesZICAI005134 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI KONG, WING PUI · 2019 to 2024
$17.6M
Coronavirus vaccine developmentZIAAI005125 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI GRAHAM, BARNEY · 2014 to 2021
$5.8M
Structure, Function and Antigenicity of Coronavirus Spike ProteinsR01AI127521 · NIAID · UNIVERSITY OF TEXAS AT AUSTIN · PI MCLELLAN, JASON SCOTT, WARD, ANDREW BARRETT · 2017 to 2021
$3.1M
Intramural NIH HHS ZIA AI005125NIAID NIH HHS R01 AI127521
6 · The paper itself

Abstract

The emergence of new pathogens, such as Middle East respiratory syndrome coronavirus (MERS-CoV), poses serious challenges to global public health and highlights the urgent need for methods to rapidly identify and characterize potential therapeutic or prevention options, such as neutralizing antibodies. Spike (S) proteins are present on the surface of MERS-CoV virions and mediate viral entry. S is the primary target for MERS-CoV vaccine and antibody development, and it has become increasingly important to understand MERS-CoV antibody binding specificity and function. Commonly used serological methods like ELISA, biolayer interferometry, and flow cytometry are informative, but limited. Here, we demonstrate a high-throughput protein binding inhibition assay using image cytometry. The image cytometry-based high-throughput screening method was developed by selecting a cell type with high DPP4 expression and defining optimal seeding density and protein binding conditions. The ability of monoclonal antibodies to inhibit MERS-CoV S binding was then tested. Binding inhibition results were comparable with those described in previous literature for MERS-CoV spike monomer and showed similar patterns as neutralization results. The coefficient of variation (CV) of our cell-based assay was <10%. The proposed image cytometry method provides an efficient approach for characterizing potential therapeutic antibodies for combating MERS-CoV that compares favorably with current methods. The ability to rapidly determine direct antibody binding to host cells in a high-throughput manner can be applied to study other pathogen-antibody interactions and thus can impact future research on viral pathogens.

Indexed as

AnimalsAntibodies, ViralCell LineHigh-Throughput Screening AssaysHumansImage CytometryMiddle East Respiratory Syndrome CoronavirusProtein BindingReproducibility of ResultsSensitivity and SpecificitySpike Glycoprotein, CoronavirusAntibodies, ViralSpike Glycoprotein, CoronavirusAntibody bindingAntibody neutralizationCeligoImage cytometryInhibition assayMERS-CoV

Identifiers

PMID30468747
PMCPMC6357230
OpenAlexW2901055207

What OpenQuestion holds

Textmetadata
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.