Evidence map›Paper›PMID 36246297›Full record

ArticleFrontiers in microbiology2022

A reporter cell line for the automated quantification of SARS-CoV-2 infection in living cells.

Lowiese Desmarets, Nathalie Callens, Eik Hoffmann, Adeline Danneels, Muriel Lavie, Cyril Couturier, Jean Dubuisson, Sandrine Belouzard, Yves Rouillé

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Luteolin Isolated fromMolecules (Basel, Switzerland) · 2023
    Article
  10. 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

9 authors.

Lowiese DesmaretsCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Nathalie CallensCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Eik HoffmannCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Adeline DanneelsCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Muriel LavieCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Cyril CouturierINSERM U1177-Drugs and Molecules for Living Systems, Institut Pasteur Lille, Université de Lille, Lille, France.
Jean DubuissonCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Sandrine BelouzardCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.
Yves RouilléCNRS UMR 9017, INSERM U1019 Centre d'Infection et Immunité de Lille (CIIL), Institut Pasteur de Lille, Université de Lille, Lille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 pandemic and the urgent need for massive antiviral testing highlighted the lack of a good cell-based assay that allowed for a fast, automated screening of antivirals in high-throughput content with minimal handling requirements in a BSL-3 environment. The present paper describes the construction of a green fluorescent substrate that, upon cleavage by the SARS-CoV-2 main protease, re-localizes from the cytoplasm in non-infected cells to the nucleus in infected cells. The construction was stably expressed, together with a red fluorescent nuclear marker, in a highly susceptible clone derived from Vero-81 cells. With this fluorescent reporter cell line, named F1G-red, SARS-CoV-2 infection can be scored automatically in living cells by comparing the patterns of green and red fluorescence signals acquired by automated confocal microscopy in a 384-well plate format. We show the F1G-red system is sensitive to several SARS-CoV-2 variants of concern and that it can be used to assess antiviral activities of compounds in dose-response experiments. This high-throughput system will provide a reliable tool for antiviral screening against SARS-CoV-2.

Indexed as

3CLproantiviralscoronavirushigh content imagingMpronsp5SARS-CoV-2screening

Identifiers

PMID36246297
PMCPMC9558224

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.