BACKGROUND. The 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. METHODS. Using 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. RESULTS. We identified linear epitopes from the Spike (S) and Nucleocapsid (N) protein and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. 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 of concern B.1.1.7 altered the specificity of the corresponding epitopes. CONCLUSIONS. Epitope-resolved antibody testing not only affords 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 potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern (VOC) in both the peptide array and latex agglutination formats. FUNDING. Ontario 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.
Courtney Voss, Sally Esmail, Xuguang Liu, Michael J. Knauer, Suzanne Ackloo, Tomonori Kaneko, Lori E. Lowes, Peter J. Stogios, Almagul Seitova, Ashley Hutchinson, Farhad Yusifov, Tatiana Skarina, Elena Evdokimova, Peter Loppnau, Pegah Ghiabi, Taraneh Hajian, Shanshan Zhong, Husam Abdoh, Benjamin D. Hedley, Vipin Bhayana, Claudio M. Martin, Marat Slessarev, Benjamin Chin-Yee, Douglas D. Fraser, Ian Chin-Yee, Shawn S.C. Li