Serological assays have been widely employed during the coronavirus disease 2019 (COVID-19) pandemic to measure antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to track seroconversion in populations. However, currently available assays do not allow determination of neutralization capacity within the assay protocol. Furthermore, commercial serology assays have a high buy-in cost that is inaccessible for many research groups. We have replicated the serological enzyme-linked immunosorbent assay for the detection of SARS-CoV-2 antibody isotypes, developed at the Icahn School of Medicine at Mount Sinai, New York. Additionally, we have modified the protocol to include a neutralization assay with only a minor modification to this protocol. We used this assay to screen local COVID-19 patient sera ( n = 91) and pre-COVID-19 control sera ( n = 103), and obtained approximate parity with approved commercial anti-nucleoprotein-based assays with these sera. Furthermore, data from our neutralization assay closely aligns with that generated using a spike-based pseudovirus infection model when a subset of patient sera was analyzed.
【저자키워드】 SARS-CoV-2, serology, antibody, neutralization, enzyme-linked immunosorbent assay, pseudovirus infection model, 【초록키워드】 COVID-19, coronavirus disease, Coronavirus disease 2019, coronavirus, pandemic, protocol, Antibody Response, Local, severe acute respiratory syndrome Coronavirus, Medicine, enzyme-linked immunosorbent assay, Antibody responses, Seroconversion, SARS-CoV-2 antibody, Neutralization assay, serological assays, sera, Research, School, respiratory, New York, serological, neutralization capacity, COVID-19 patient, a minor, Mount Sinai, acute respiratory syndrome, acute respiratory syndrome coronavirus, acute respiratory syndrome coronavirus 2, minor, patient sera, pseudovirus infection, Modification, populations, isotypes, enzyme-linked immunosorbent, analyzed, include, approved, replicated, groups, subset, inaccessible, serology assay, 【제목키워드】 RBD, Capacity, Profiling, dynamic,