SARS-CoV-2 Proteome Microarray for IgG and IgM Response Profiling

IN PATH non-porous nitrocellulose

Convalescent plasma is a potential therapeutic option for patients with coronavirus disease. The therapy is based on the administration of plasma containing antibodies against SARS-CoV-2 to help patients boost their responses to the coronavirus. Additionally, convalescent plasma can also be used for passive immunization with the potential to prevent viral infection. In both applications, determining the presence and titer of the target antibody is essential. The enzyme-linked immunosorbent assay (ELISA) is the traditional method of accurately quantifying antibodies in patients’ serum. This method can usually “ test a single target protein or antibody in an individual reaction. By contrast, protein microarrays enable proteome-wide characterization of antibody responses in a high-throughput format, providing a more systemic description of these vital antibody responses”. HW Jiang et. al., in a recent publication, constructed a SARS-CoV-2 proteome microarray to analyze the IgG and IgM content of convalescent patients’ sera. 37 SARS-CoV-2 proteins produced using yeast cell-free systems or mammalian cell expression systems were printed in quadruplicate on PATH® Protein Microarray Slides using a Super Marathon printer (Arrayjet, UK).

Predicted ORFs in SARS-CoV-2 genome
Predicted ORFs in SARS-CoV-2 genome

Convalescent serum collected from 29 patients along with negative control from naïve subjects was applied to the proteome microarray and fluorescent-labeled anti-human antibodies used to detect SARS-CoV-2-specific IgG and IgM proteins. This study confirmed that S1 and N proteins are the dominant antigens of SARS-CoV and that SARS-CoV-2 elicits both IgG and IgM antibodies. N proteins induced the strongest immune response, however, some false-negatives were also observed. S1 protein, instead, demonstrated very high specificity, thus suggesting that both proteins should be included in diagnostic immune-assays for increased accuracy.

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