RESUMO
Widespread and frequent testing is critical to prevent the spread of COVID-19, and rapid antigen tests are the diagnostic tool of choice in many settings. With new viral variants continuously emerging and spreading rapidly, the effect of mutations on antigen test performance is a major concern. In response to the spread of variants the National Institutes of Healths Rapid Acceleration of Diagnostics (RADx(R)) initiative created a Variant Task Force to assess the impact of emerging SARS-CoV-2 variants on in vitro diagnostic testing. To evaluate the impact of mutations on rapid antigen tests we developed a lentivirus-mediated mammalian surface-display platform for the SARS-CoV-2 Nucleocapsid protein, the target of the majority of rapid antigen tests. We employed deep mutational scanning (DMS) to directly measure the effect of all possible Nucleocapsid point mutations on antibody binding by 17 diagnostic antibodies used in 11 commercially available antigen tests with FDA emergency use authorization (EUA). The results provide a complete map of the antibodies epitopes and their susceptibility to mutational escape. This approach identifies linear epitopes, conformational epitopes, as well as allosteric escape mutations in any region of the Nucleocapsid protein. All 17 antibodies tested exhibit distinct escape mutation profiles, even among antibodies recognizing the same folded domain. Our data predict no vulnerabilities of rapid antigen tests for detection of mutations found in currently and previously dominant variants of concern and interest. We confirm this using the commercial tests and sequence-confirmed COVID-19 patient samples. The antibody escape mutation profiles generated here serve as a valuable resource for predicting the performance of rapid antigen tests against past, current, as well as any possible future variants of SARS-CoV-2, establishing the direct clinical and public health utility of our system. Further, our mammalian surface-display platform combined with DMS is a generalizable platform for complete mapping of protein-protein interactions.
