Evidence map›Paper›PMID 37996617›Full record

ArticleNature biomedical engineering2024

High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2.

Charles W F Chan, Bei Wang, Lang Nan, Xiner Huang, Tianjiao Mao, Hoi Yee Chu, Cuiting Luo, Hin Chu, Gigi C G Choi, Ho Cheung Shum and 1 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Nature biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. A Machine Vision Perspective on Droplet-Based Microfluidics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Screening for drivers of SARS-CoV-2 uptake.Nature biomedical engineering · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Charles W F Chan *Laboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.ORCID 0009-0004-2751-6565
Bei Wang *Laboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Lang Nan *Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.ORCID 0000-0002-1978-2482
Xiner Huang *State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.ORCID 0000-0002-0154-8372
Tianjiao MaoDepartment of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Hoi Yee ChuLaboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Cuiting LuoState Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
Hin ChuState Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China. hinchu@hku.hk.ORCID 0000-0003-2855-9837
Gigi C G ChoiLaboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China. gigichoi@hku.hk.ORCID 0000-0003-2774-9188
Ho Cheung ShumDepartment of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China. ashum@hku.hk.
Alan S L WongLaboratory of Combinatorial Genetics and Synthetic Biology, School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China. aslw@hku.hk.ORCID 0000-0003-1790-3233
Hong Kong Science and Technology Parks Corporation · HKNano and Advanced Materials Institute · CNUniversity of Hong Kong · HK

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32022089Research Grants Council, University Grants Committee (RGC, UGC) C7103-22G
6 · The paper itself

Abstract

Mapping mutations and discovering cellular determinants that cause the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce infected cells to form syncytia would facilitate the development of strategies for blocking the formation of such cell-cell fusion. Here we describe high-throughput screening methods based on droplet microfluidics and the size-exclusion selection of syncytia, coupled with large-scale mutagenesis and genome-wide knockout screening via clustered regularly interspaced short palindromic repeats (CRISPR), for the large-scale identification of determinants of cell-cell fusion. We used the methods to perform deep mutational scans in spike-presenting cells to pinpoint mutable syncytium-enhancing substitutions in two regions of the spike protein (the fusion peptide proximal region and the furin-cleavage site). We also used a genome-wide CRISPR screen in cells expressing the receptor angiotensin-converting enzyme 2 to identify inhibitors of clathrin-mediated endocytosis that impede syncytium formation, which we validated in hamsters infected with SARS-CoV-2. Finding genetic and cellular determinants of the formation of syncytia may reveal insights into the physiological and pathological consequences of cell-cell fusion.

Indexed as

COVID-19SARS-CoV-2Giant CellsHigh-Throughput Screening AssaysHumansSpike Glycoprotein, CoronavirusSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID37996617
PMCPMC10963270
OpenAlexW4388939058

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.