Evidence map›Paper›PMID 39339949›Full record

ArticleViruses2024

Multiplex Microscopy Assay for Assessment of Therapeutic and Serum Antibodies against Emerging Pathogens.

Nuno Sartingen, Vanessa Stürmer, Matthias Kaltenböck, Thorsten G Müller, Paul Schnitzler, Anna Kreshuk, Hans-Georg Kräusslich, Uta Merle, Frauke Mücksch, Barbara Müller and 2 more

Abstract read
In one paragraph

Article in Viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nuno SartingenDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.
Vanessa StürmerDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.
Matthias KaltenböckDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.
Thorsten G MüllerDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.ORCID 0000-0002-4197-6224
Paul SchnitzlerDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.
Anna KreshukEuropean Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Hans-Georg KräusslichDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.ORCID 0000-0002-8756-329X
Uta MerleDepartment of Internal Medicine IV, University Hospital Heidelberg, 69120 Heidelberg, Germany.ORCID 0000-0003-1386-3350
Frauke MückschDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.ORCID 0000-0002-0132-5101
Barbara MüllerDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.ORCID 0000-0001-5726-5585
Constantin PapeInstitute of Computer Science, Göttingen University, 37073 Göttingen, Germany.ORCID 0000-0001-6562-7187
Vibor LaketaDepartment of Infectious Diseases, Virology, Medical Faculty Heidelberg, Heidelberg University, 69120 Heidelberg, Germany.ORCID 0000-0002-9472-2738

Funding

Deutsche Forschungsgemeinschaft EXC 2067/1- 390729940German Center for Infection Research TTU 04.710
6 · The paper itself

Abstract

The emergence of novel pathogens, exemplified recently by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the need for rapidly deployable and adaptable diagnostic assays to assess their impact on human health and guide public health responses in future pandemics. In this study, we developed an automated multiplex microscopy assay coupled with machine learning-based analysis for antibody detection. To achieve multiplexing and simultaneous detection of multiple viral antigens, we devised a barcoding strategy utilizing a panel of HeLa-based cell lines. Each cell line expressed a distinct viral antigen, along with a fluorescent protein exhibiting a unique subcellular localization pattern for cell classification. Our robust, cell segmentation and classification algorithm, combined with automated image acquisition, ensured compatibility with a high-throughput approach. As a proof of concept, we successfully applied this approach for quantitation of immunoreactivity against different variants of SARS-CoV-2 spike and nucleocapsid proteins in sera of patients or vaccinees, as well as for the study of selective reactivity of monoclonal antibodies. Importantly, our system can be rapidly adapted to accommodate other SARS-CoV-2 variants as well as any antigen of a newly emerging pathogen, thereby representing an important resource in the context of pandemic preparedness.

Indexed as

Antibodies, ViralCOVID-19SARS-CoV-2Spike Glycoprotein, CoronavirusAntigens, ViralCoronavirus Nucleocapsid ProteinsHeLa CellsHumansMachine LearningMicroscopyPhosphoproteinsAntibodies, ViralAntigens, ViralCoronavirus Nucleocapsid Proteinsnucleocapsid phosphoprotein, SARS-CoV-2PhosphoproteinsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2emerging pathogensmachine learningmonoclonal antibodiesmultiplex microscopySARS-CoV-2serology

Identifiers

PMID39339949
PMCPMC11437451

What OpenQuestion holds

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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.