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

Research output: Contribution to journalArticleResearchpeer review

Authors

  • 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

External Research Organisations

  • 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
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Details

Original languageEnglish
Pages (from-to)1037-1048
Number of pages12
JournalEmerging Microbes and Infections
Volume11
Issue number1
Publication statusPublished - 2022

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

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2. / Hotop, Sven Kevin; Reimering, Susanne; Shekhar, Aditya et al.
In: Emerging Microbes and Infections, Vol. 11, No. 1, 2022, p. 1037-1048.

Research output: Contribution to journalArticleResearchpeer review

Hotop, SK, Reimering, S, Shekhar, A, Asgari, E, Beutling, U, Dahlke, C, Fathi, A, Khan, F, Lütgehetmann, M, Ballmann, R, Gerstner, A, Tegge, W, Cicin-Sain, L, Bilitewski, U, McHardy, AC & Brönstrup, M 2022, 'Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2', Emerging Microbes and Infections, vol. 11, no. 1, pp. 1037-1048. https://doi.org/10.1080/22221751.2022.2057874
Hotop, S. K., Reimering, S., Shekhar, A., Asgari, E., Beutling, U., Dahlke, C., Fathi, A., Khan, F., Lütgehetmann, M., Ballmann, R., Gerstner, A., Tegge, W., Cicin-Sain, L., Bilitewski, U., McHardy, A. C., & Brönstrup, M. (2022). Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2. Emerging Microbes and Infections, 11(1), 1037-1048. https://doi.org/10.1080/22221751.2022.2057874
Hotop SK, Reimering S, Shekhar A, Asgari E, Beutling U, Dahlke C et al. Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2. Emerging Microbes and Infections. 2022;11(1):1037-1048. doi: 10.1080/22221751.2022.2057874
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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.",
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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. ",
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Download

TY - JOUR

T1 - Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2

AU - Hotop, Sven Kevin

AU - Reimering, Susanne

AU - Shekhar, Aditya

AU - Asgari, Ehsaneddin

AU - Beutling, Ulrike

AU - Dahlke, Christine

AU - Fathi, Anahita

AU - Khan, Fawad

AU - Lütgehetmann, Marc

AU - Ballmann, Rico

AU - Gerstner, Andreas

AU - Tegge, Werner

AU - Cicin-Sain, Luka

AU - Bilitewski, Ursula

AU - McHardy, Alice C.

AU - Brönstrup, Mark

N1 - 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.

PY - 2022

Y1 - 2022

N2 - 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.

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KW - machine learning

KW - neutralizing antibodies

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