Peptide Microarray Analysis of In-Silico Predicted B-Cell Epitopes in SARS-CoV-2 Sero-Positive Healthcare Workers in Bulawayo, Zimbabwe

Identification of immunogenic peptides mimicking B-cell linear epitopes can improve serological diagnostic tests for emerging diseases. This study reports a general approach for profiling B-cell epitopes derived from SARS-CoV-2 using an in-silico method and peptide microarray immunoassay using SARS-CoV-2 sero-positive sera. SARS-CoV-2 antibody tests were conducted using rapid chromatographic immunoassays. SARS-CoV-2 negative control sera was tested using rapid chromatographic immunoassays and RT-PCR. Immunogenic peptides mimicking B-cell linear epitopes were predicted in-silico using ABCpred. IgG and IgM antibodies against the SARS-CoV-2 spike protein, membrane glycoprotein and nucleocapsid derived peptides were measured in sera using peptide microarray immunoassay. Healthcare workers included in the study were RT-PCR negative for SARS-CoV-2. Using rapid chromatographic immunoassays, 10 were SARS-CoV-2 IgM sero-positive and 6 were SARS-CoV-2 IgG sero-positive. From a total of 10 SARS-CoV-2 peptides contained on the microarray, 5 (QTH34388.1-1-14, QRU89900.1-41-54, QTN64908.1-135-148, QTN64908.1-136-149 and QLL35955.1-22-35) showed reactivity against IgG with at least a single serum. Five peptides (QRU89900.1-41-54, QSM17284.1-76-89, PDB: 7LX5_B-686-701, QTN64908.1-135-148 and QPK73947.1-8-21) also showed reactivity against IgM. The reactive peptides were derived from the membrane glycoprotein and nucleocapsid protein. Although, in-silico bioinformatics tools are being used to predict B-cell epitopes specific to pathogens, which could accelerate the development of new diagnostics for emerging infectious diseases such as COVID-19, none of the ABCpred peptides were singularly detected in more than one of the sero-positive samples tested. None of the peptides discriminated between SARS-CoV-2 sero-positive group and sero-negative group. Therefore, we recommend using at least two in-silico peptide prediction tools to improve the sensitivity and specificity of B-cell epitope prediction.