Abstract
Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N = 80 samples from persons with RT-PCR confirmed SARS-CoV-2 infection), and a specificity of 97.2% (N = 106 control samples).
Highlights
Distributions per protein and length show that over half the predicted epitopes were located on only 4 proteins: S, nsp[3], N and nsp[12] (Fig. 1A) and that over 80% of the epitopes were below 15 residues long (Fig. 1B)
From a subset of 6 COVID-19+ plasma and 5 “negative control” plasma, we compared our panel of recombinant SARS-CoV-2 proteins, including spike-receptor binding domain (S-RBD), nucleoprotein, nsp[9], nsp10/nsp[16] complex, nsp[15], and nsp7/nsp[8] complex (Fig. 5)
Our conservation analysis shows that the predicted dominant epitope nprot_10 on the C-terminal domain is matching at least 22 endemic human coronaviruses (HCoVs) strains from Seattle isolates, dated between 2015 and 2019, with 67% identity, which might explain some of the non-specific responses to full-length N in our samples (Table S6)
Summary
We assessed the level of sequence conservation of each SARS-CoV-2 epitope compared to endemic human coronaviruses (HCoVs) strains HKU1, 229E, OC43 and NL63. The unprecedented speed at which experimental SARS-CoV-2 structures have been solved and deposited in the PDB allowed us to predict epitopes on 13 proteins (Table S3)[9,10,11,12].
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