Evidence map›Paper›PMID 39985112›Full record

ArticleJournal of translational medicine2025

Function and structure of broadly neutralizing antibodies against SARS-CoV-2 Omicron variants isolated from prototype strain infected convalescents.

Dan Li, Caiqin Hu, Junwei Su, Shuo Du, Ying Zhang, Wanqi Ni, Li Ren, Yanling Hao, Yi Feng, Changzhong Jin and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

16 authors.

Dan Li *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Caiqin Hu *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Junwei Su *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Shuo Du *Changping Laboratory, Beijing, 102206, China.
Ying Zhang *State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100091, China.
Wanqi NiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Li RenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yanling HaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yi FengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Changzhong JinState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
Shuo WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Xinxian DaiNational Vaccine and Serum Institute, Beijing, 101111, China.
Zheng WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. wangzheng@chinaaids.cn.ORCID 0000-0001-8020-9768
Biao ZhuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China. zhubiao1207@zju.edu.cn.
Junyu XiaoChangping Laboratory, Beijing, 102206, China. junyuxiao@pku.edu.cn.
Yiming ShaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/ STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. yshao@bjmu.edu.cn.

Funding

National Natural Science Foundation of China 92369103National Natural Science Foundation of China U20A20362
6 · The paper itself

Abstract

backgroundThe ongoing emergence of evolving SARS-CoV-2 variants poses great threaten to the efficacy of authorized monoclonal antibody-based passive immunization or treatments. Developing potent broadly neutralizing antibodies (bNabs) against SARS-CoV-2 and elucidating their potential evolutionary pathways are essential for battling the coronavirus disease 2019 (COVID-19) pandemic.

methodsBroadly neutralizing antibodies were isolated using single cell sorting from three COVID-19 convalescents infected with prototype SARS-CoV-2 strain. Their neutralizing activity against diverse SARS-CoV-2 strains were tested in vitro and in vivo, respectively. The structures of antibody-antigen complexes were resolved using crystallization or Cryo-EM method. Antibodyomics analyses were performed using the non-bias deep sequencing results of BCR repertoires.

resultsWe obtained a series of RBD-specific monoclonal antibodies with highly neutralizing potency against a variety of pseudotyped and live SARS-CoV-2 variants, including five global VOCs and some Omicron subtypes such as BA.1, BA.2, BA.4/5, BF.7, and XBB. 2YYQH9 and LQLD6HL antibody cocktail also displayed good therapeutic and prophylactic efficacy in an XBB.1.16 infected hamster animal model. Cryo-EM and crystal structural analyses revealed that broadly neutralizing antibodies directly blocked the binding of ACE2 by almost covering the entire receptor binding motif (RBM) and largely avoided mutated RBD residues in the VOCs, demonstrating their broad and potent neutralizing activity. In addition, antibodyomics assays indicate that the germline frequencies of RBD-specific antibodies increase after an inactivated vaccine immunization. Moreover, the CDR3 frequencies of V

conclusionsThese data suggest that current identified broadly neutralizing antibodies could serve as promising drug candidates for COVID-19 and can be used for reverse vaccine design against future pandemics.

Indexed as

Antibodies, NeutralizingAntibodies, ViralBroadly Neutralizing AntibodiesCOVID-19SARS-CoV-2AnimalsAntibodies, MonoclonalCryoelectron MicroscopyHumansNeutralization TestsSpike Glycoprotein, CoronavirusAntibodies, MonoclonalAntibodies, NeutralizingAntibodies, ViralBroadly Neutralizing AntibodiesSpike Glycoprotein, CoronavirusAntibodyomics assayBroad neutralizationCryo-electron microscopyHamster modelMonoclonal antibodiesSARS-CoV-2

Identifiers

PMID39985112
PMCPMC11844185

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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.