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Emerg Microbes Infect . Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing

tetano

Editor, Senior Moderator
Emerg Microbes Infect


. 2022 Mar 23;1-37.
doi: 10.1080/22221751.2022.2057874. Online ahead of print.
Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2


Sven-Kevin Hotop[SUP] 1 [/SUP], Susanne Reimering[SUP] 1 2 [/SUP], Aditya Shekhar[SUP] 1 [/SUP], Ehsaneddin Asgari[SUP] 1 2 3 [/SUP], Ulrike Beutling[SUP] 1 [/SUP], Christine Dahlke[SUP] 4 5 6 [/SUP], Anahita Fathi[SUP] 4 5 6 [/SUP], Fawad Khan[SUP] 1 [/SUP], Marc Lütgehetmann[SUP] 6 7 [/SUP], Rico Ballmann[SUP] 8 [/SUP], Andreas Gerstner[SUP] 9 [/SUP], Werner Tegge[SUP] 1 [/SUP], Luka Cicin-Sain[SUP] 1 3 [/SUP], Ursula Bilitewski[SUP] 1 [/SUP], Alice C McHardy[SUP] 1 2 3 [/SUP], Mark Brönstrup[SUP] 1 10 3 [/SUP]



Affiliations

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 unsual viral binding epitopes that might be suited as vaccine candidates.

Keywords: COVID-19; SARS CoV-2; immunoassays; machine learning; neutralizing antibodies; peptide arrays; serology.
 
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