Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2

authored by: Sven Kevin Hotop, Susanne Reimering, Aditya Shekhar, Ehsaneddin Asgari, Ulrike Beutling, Christine Dahlke, Anahita Fathi, Fawad Khan, Marc Lütgehetmann, Rico Ballmann, Andreas Gerstner, Werner Tegge, Luka Cicin-Sain, Ursula Bilitewski, Alice C. McHardy, Mark Brönstrup
Abstract: The coronavirus SARS-CoV-2 is the causative agent for the disease COVID-19. To capture the IgA, IgG, and IgM antibody response of patients infected with SARS-CoV-2 at individual epitope resolution, we constructed planar microarrays of 648 overlapping peptides that cover the four major structural proteins S(pike), N(ucleocapsid), M(embrane), and E(nvelope). The arrays were incubated with sera of 67 SARS-CoV-2 positive and 22 negative control samples. Specific responses to SARS-CoV-2 were detectable, and nine peptides were associated with a more severe course of the disease. A random forest model disclosed that antibody binding to 21 peptides, mostly localized in the S protein, was associated with higher neutralization values in cellular anti-SARS-CoV-2 assays. For antibodies addressing the N-terminus of M, or peptides close to the fusion region of S, protective effects were proven by antibody depletion and neutralization assays. The study pinpoints unusual viral binding epitopes that might be suited as vaccine candidates.
Organisation(s): Centre of Biomolecular Drug Research (BMWZ)
External Organisation(s): Helmholtz Centre for Infection Research (HZI)
Technische Universität Braunschweig
Universität Hamburg
Bernhard Nocht Institute for Tropical Medicine (BNITM)
German Center for Infection Research (DZIF)
Städtisches Klinikum Braunschweig
Type: Article
Journal: Emerging Microbes and Infections
Volume: 11
Pages: 1037-1048
No. of pages: 12
ISSN: 2222-1751
Publication date: 2022
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Parasitology, Epidemiology, Microbiology, Immunology, Drug Discovery, Virology, Infectious Diseases
Sustainable Development Goals: SDG 3 - Good Health and Well-being
Electronic version(s): https://doi.org/10.1080/22221751.2022.2057874 (Access: Open)

BibTeX

@article{1d6dfc83be544a7f988f21e482469744,
title = "Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2",
abstract = "The coronavirus SARS-CoV-2 is the causative agent for the disease COVID-19. To capture the IgA, IgG, and IgM antibody response of patients infected with SARS-CoV-2 at individual epitope resolution, we constructed planar microarrays of 648 overlapping peptides that cover the four major structural proteins S(pike), N(ucleocapsid), M(embrane), and E(nvelope). The arrays were incubated with sera of 67 SARS-CoV-2 positive and 22 negative control samples. Specific responses to SARS-CoV-2 were detectable, and nine peptides were associated with a more severe course of the disease. A random forest model disclosed that antibody binding to 21 peptides, mostly localized in the S protein, was associated with higher neutralization values in cellular anti-SARS-CoV-2 assays. For antibodies addressing the N-terminus of M, or peptides close to the fusion region of S, protective effects were proven by antibody depletion and neutralization assays. The study pinpoints unusual viral binding epitopes that might be suited as vaccine candidates.",
keywords = "COVID-19, immunoassays, machine learning, neutralizing antibodies, peptide arrays, SARS CoV-2, serology",
author = "Hotop, {Sven Kevin} and Susanne Reimering and Aditya Shekhar and Ehsaneddin Asgari and Ulrike Beutling and Christine Dahlke and Anahita Fathi and Fawad Khan and Marc L{\"u}tgehetmann and Rico Ballmann and Andreas Gerstner and Werner Tegge and Luka Cicin-Sain and Ursula Bilitewski and McHardy, {Alice C.} and Mark Br{\"o}nstrup",
note = "Funding Information: The work was funded by a grant from the Ministry of Science and Culture of Lower Saxony in Germany (project 14-76103-184 Corona 13/20) and by the COVID-19 Research Network of the State of Lower Saxony (COFONI) (14-76403-184). The authors thank Michael Hust for providing the SH2029-G6 monoclonal antibody for assay validation. We also thank the HZI peptide facility, in particular Brigitte Kornak, for its peptide synthesis support. SKH, UBE, RB and WT manufactured chips, performed chip experiments and analyzed the data; CD, AF, ML and AG characterized and provided the serum samples; AS, FK performed SARS-CoV-2 neutralization experiments, UBI, LC conceived and supervised SARS-CoV-2 neutralization experiments, SR, EA and AM analyzed the data. MB conceived the study, analyzed the data and wrote the manuscript. ",
year = "2022",
doi = "10.1080/22221751.2022.2057874",
language = "English",
volume = "11",
pages = "1037--1048",
journal = "Emerging Microbes and Infections",
issn = "2222-1751",
publisher = "Nature Publishing Group",
number = "1",
}