High-resolution mapping and characterization of epitopes in COVID-19 patients

Abstract

Fine scale delineation of epitopes recognized by the antibody response to SARS-CoV-2 infection will be critical to understanding disease heterogeneity and informing development of safe and effective vaccines and therapeutics. The Serum Epitope Repertoire Analysis (SERA) platform leverages a high diversity random bacterial display library to identify epitope binding specificities with single amino acid resolution. We applied SERA broadly, across human, viral and viral strain proteomes in multiple cohorts with a wide range of outcomes from SARS-CoV-2 infection. We identify dominant epitope motifs and profiles which effectively classify COVID-19, distinguish mild from severe disease, and relate to neutralization activity. We identify a repertoire of epitopes shared by SARS-CoV-2 and endemic human coronaviruses and determine that a region of amino acid sequence identity shared by the SARS-CoV-2 furin cleavage site and the host protein ENaC-alpha is a potential cross-reactive epitope. Finally, we observe decreased epitope signal for mutant strains which points to reduced antibody response to mutant SARS-CoV-2. Together, these findings indicate that SERA enables high resolution of antibody epitopes that can inform data-driven design and target selection for COVID-19 diagnostics, therapeutics and vaccines.

Impact of B.1.1.7 variant mutations on antibody recognition of linear SARS-CoV-2 epitopes

“…Spike glycoprotein in the B.1.1.7 contains 2 deletions and 6 point mutations. First, we noted that the regions harboring mutations generally had no direct overlap with the epitope hotspots we have previously described 4 [ Figure 1A]. The epitope mutations with the most dramatic reduction in outliers (defined as epitope score > 99 th percentile of the pre-pandemic controls) were del144, N501Y, A570D, and P681H.…”

“…Samples were normalized to a final concentration of 4nM for each pool and run on the Illumina NextSeq500." 4 PIWAS analysis. To identify linear epitope signals, we applied the previously published PIWAS method 5 against the Uniprot reference SARS-CoV-2 proteome (UP000464024) 10 and the B.1.1.7 variant described in Rambaut, et al 1 .…”

“…To identify linear epitope signals, we applied the previously published PIWAS method 5 against the Uniprot reference SARS-CoV-2 proteome (UP000464024) 10 and the B.1.1.7 variant described in Rambaut, et al 1 . The PIWAS analysis was run on the IgG SERA samples described in Haynes, Kamath, Bozekowski, et al 4 : a single sample per COVID-19 patient (for a total of 579 patients) versus 497 discovery pre-pandemic controls, and the 1500 validation controls used as the normalization cohort. Additional parameters include: a smoothing window size of 5 5mers and 5 6mers; z-score normalization of kmer enrichments; maximum peak value; and generation of epitope level tiling data.…”

“…At the antigen level, peak wild-type vs. peak mutant PIWAS values were compared to identify individuals with decreased epitope signal at the antigen level. We included motifs from Haynes, Kamath, Bozekowksi, et al 4 that mapped linearly to the protein sequences to highlight dominant epitopes. We compared PIWAS antigen scores for these same proteins and variants.…”

“…Regions outside of the variant region are tiled against the wild-type protein and are marked as identical (grey). Dominant SARS-CoV-2 epitopes identified in Haynes, Kamath, Bozekowski, et al4 . are shown with red bars.…”