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

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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; Asgari, Ehsaneddin; Beutling, Ulrike; Dahlke, Christine; Fathi, Anahita; Khan, Fawad; Lütgehetmann, Marc; Ballmann, Rico; Gerstner, Andreas; Tegge, Werner; Cicin-Sain, Luka; Bilitewski, Ursula; McHardy, Alice C; Brönstrup, Mark.

In: EMERG MICROBES INFEC, Vol. 11, No. 1, 12.2022, p. 1037-1048.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

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, AC & Brönstrup, M 2022, 'Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2', EMERG MICROBES INFEC, vol. 11, no. 1, pp. 1037-1048. https://doi.org/10.1080/22221751.2022.2057874

APA

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. EMERG MICROBES INFEC, 11(1), 1037-1048. https://doi.org/10.1080/22221751.2022.2057874

Vancouver

Hotop S-K, 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. EMERG MICROBES INFEC. 2022 Dec;11(1):1037-1048. https://doi.org/10.1080/22221751.2022.2057874

Bibtex

@article{ca7dcc9617c045f2a2264ec31ffee226,
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 = "Antibodies, Neutralizing, Antibodies, Viral, Antibody Formation, COVID-19, Epitopes, Humans, Machine Learning, Peptides, SARS-CoV-2, Spike Glycoprotein, Coronavirus",
author = "Sven-Kevin Hotop 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",
year = "2022",
month = dec,
doi = "10.1080/22221751.2022.2057874",
language = "English",
volume = "11",
pages = "1037--1048",
journal = "EMERG MICROBES INFEC",
issn = "2222-1751",
publisher = "NATURE PUBLISHING GROUP",
number = "1",

}

RIS

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

PY - 2022/12

Y1 - 2022/12

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.

AB - 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.

KW - Antibodies, Neutralizing

KW - Antibodies, Viral

KW - Antibody Formation

KW - COVID-19

KW - Epitopes

KW - Humans

KW - Machine Learning

KW - Peptides

KW - SARS-CoV-2

KW - Spike Glycoprotein, Coronavirus

U2 - 10.1080/22221751.2022.2057874

DO - 10.1080/22221751.2022.2057874

M3 - SCORING: Journal article

C2 - 35320064

VL - 11

SP - 1037

EP - 1048

JO - EMERG MICROBES INFEC

JF - EMERG MICROBES INFEC

SN - 2222-1751

IS - 1

ER -