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

  • 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*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

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.

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

Keywords

  • COVID-19
  • SARS CoV-2
  • immunoassays
  • machine learning
  • neutralizing antibodies
  • peptide arrays
  • serology

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