Evidence map›Paper›PMID 35139078›Full record

ArticlePloS one2022

FluoRNT: A robust, efficient assay for the detection of neutralising antibodies against yellow fever virus 17D.

Magdalena K Scheck, Lisa Lehmann, Magdalena Zaucha, Paul Schwarzlmueller, Kristina Huber, Michael Pritsch, Giovanna Barba-Spaeth, Oliver Thorn-Seshold, Anne B Krug, Stefan Endres and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

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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

12 authors at 4 institutions in 2 countries.

Magdalena K ScheckDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.
Lisa LehmannDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0002-5153-3371
Magdalena ZauchaDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0002-3590-1525
Paul SchwarzlmuellerDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.
Kristina HuberDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Michael PritschDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0001-7383-8750
Giovanna Barba-SpaethStructural Virology Unit and CNRS UMR 3569, Virology Department, Institute Pasteur, Paris, France.
Oliver Thorn-SesholdFaculty of Chemistry and Pharmacy, LMU Munich, Munich, Germany.
Anne B KrugInstitute for Immunology, Biomedical Center, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.
Stefan EndresDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.
Simon RothenfusserDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0003-1151-7614
Julia Thorn-SesholdDivision of Clinical Pharmacology, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0002-4879-4159
LMU Klinikum · DEHelmholtz Zentrum München · DECentre National de la Recherche Scientifique · FRUrologische Klinik München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is an urgent need for better diagnostic and analytical methods for vaccine research and infection control in virology. This has been highlighted by recently emerging viral epidemics and pandemics (Zika, SARS-CoV-2), and recurring viral outbreaks like the yellow fever outbreaks in Angola and the Democratic Republic of Congo (2016) and in Brazil (2016-2018). Current assays to determine neutralising activity against viral infections in sera are costly in time and equipment and suffer from high variability. Therefore, both basic infection research and diagnostic population screenings would benefit from improved methods to determine virus-neutralising activity in patient samples. Here we describe a robust, objective, and scalable Fluorescence Reduction Neutralisation Test (FluoRNT) for yellow fever virus, relying on flow cytometric detection of cells infected with a fluorescent Venus reporter containing variant of the yellow fever vaccine strain 17D (YF-17D-Venus). It accurately measures neutralising antibody titres in human serum samples within as little as 24 h. Samples from 32 vaccinees immunised with YF-17D were tested for neutralising activity by both a conventional focus reduction neutralisation test (FRNT) and FluoRNT. Both types of tests proved to be equally reliable for the detection of neutralising activity, however, FluoRNT is significantly more precise and reproducible with a greater dynamic range than conventional FRNT. The FluoRNT assay protocol is substantially faster, easier to control, and cheaper in per-assay costs. FluoRNT additionally reduces handling time minimising exposure of personnel to patient samples. FluoRNT thus brings a range of desirable features that can accelerate and standardise the measurement of neutralising anti-yellow fever virus antibodies. It could be used in applications ranging from vaccine testing to large cohort studies in systems virology and vaccinology. We also anticipate the potential to translate the methodology and analysis of FluoRNT to other flaviviruses such as West Nile, Dengue and Zika or to RNA viruses more generally.

Indexed as

AnimalsAntibodies, NeutralizingAntibodies, ViralChlorocebus aethiopsFluorescenceHumansNeutralization TestsVero CellsYellow FeverYellow fever virusAntibodies, NeutralizingAntibodies, Viral

Identifiers

PMID35139078
PMCPMC8827462
OpenAlexW4210823042

What OpenQuestion holds

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LicenceCC BY
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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.