Evidence map›Paper›PMID 34873599›Full record

ArticlebioRxiv : the preprint server for biology2021

A large-scale systematic survey of SARS-CoV-2 antibodies reveals recurring molecular features.

Yiquan Wang, Meng Yuan, Jian Peng, Ian A Wilson, Nicholas C Wu

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2021. 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, 10 citations in OpenAlex.

  1. The germinal centre B cell response to SARS-CoV-2.Nature reviews. Immunology · 2022
    Review
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yiquan WangDepartment of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Meng YuanDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
Jian PengDepartment of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Ian A WilsonDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
Nicholas C WuDepartment of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
University of Illinois Urbana-Champaign · USScripps Research Institute · US

Funding

High-throughput identification of antibody features for sequence-based epitope predictionDP2AT011966 · NCCIH · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI WU, NICHOLAS C. · 2021 to 2024
$2.4M
MECHANISTIC UNDERSTANDING OF INFLUENZA-HOST INTERACTIONS FROM A ZOONOTIC PERSPECTIVER00AI139445 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI WU, NICHOLAS C. · 2020 to 2021
$492k
NCCIH NIH HHS DP2 AT011966NIAID NIH HHS R00 AI139445
6 · The paper itself

Abstract

In the past two years, the global research in combating COVID-19 pandemic has led to isolation and characterization of numerous human antibodies to the SARS-CoV-2 spike. This enormous collection of antibodies provides an unprecedented opportunity to study the antibody response to a single antigen. From mining information derived from 88 research publications and 13 patents, we have assembled a dataset of ∼8,000 human antibodies to the SARS-CoV-2 spike from >200 donors. Analysis of antibody targeting of different domains of the spike protein reveals a number of common (public) responses to SARS-CoV-2, exemplified via recurring IGHV/IGK(L)V pairs, CDR H3 sequences, IGHD usage, and somatic hypermutation. We further present a proof-of-concept for prediction of antigen specificity using deep learning to differentiate sequences of antibodies to SARS-CoV-2 spike and to influenza hemagglutinin. Overall, this study not only provides an informative resource for antibody and vaccine research, but fundamentally advances our molecular understanding of public antibody responses to a viral pathogen.

Identifiers

PMID34873599
PMCPMC8647650
OpenAlexW3217583433

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.