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Epitope-resolved serology test differentiates the clinical outcome of COVID-19 and identifies defects in antibody response in SARS-CoV-2 variants
Preprint
em En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-21253716
ABSTRACT
BACKGROUNDThe role of humoral immunity in the coronavirus disease 2019 (COVID-19) is not fully understood owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome. METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution. RESULTSWe identified 54 linear epitopes from the Spike (S) and Nucleocapsid (N) protein and showed that epitopes enabled higher resolution antibody profiling than protein antigens. Specifically, we found that antibody responses to the S(811-825), S(881-895) and N(156-170) epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant B.1.1.7 altered the specificity of the corresponding epitopes. CONCLUSIONSEpitope-resolved antibody testing not only offers a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, it may also be used as predictor of clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants in both the peptide array and latex agglutination formats. FUNDINGOntario Research Fund (ORF)-COVID-19 Rapid Research Fund, the Toronto COVID-19 Action Fund, Western University, the Lawson Health Research Institute, the London Health Sciences Foundation, and the AMOSO Innovation Fund.
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Texto completo:
1
Coleções:
09-preprints
Base de dados:
PREPRINT-MEDRXIV
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Preprint