深度突变扫描鉴定出目前可用的快速抗原检测的 SARS-CoV-2 核衣壳逃逸突变。

Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests.

机构信息

Department of Biochemistry, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; The Atlanta Center for Microsystems-Engineered Point-of-Care Technologies, Atlanta, GA 30322, USA.

出版信息

Cell. 2022 Sep 15;185(19):3603-3616.e13. doi: 10.1016/j.cell.2022.08.010. Epub 2022 Aug 29.

DOI:10.1016/j.cell.2022.08.010

PMID:36084631

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9420710/

Abstract

The effects of mutations in continuously emerging variants of SARS-CoV-2 are a major concern for the performance of rapid antigen tests. To evaluate the impact of mutations on 17 antibodies used in 11 commercially available antigen tests with emergency use authorization, we measured antibody binding for all possible Nucleocapsid point mutations using a mammalian surface-display platform and deep mutational scanning. The results provide a complete map of the antibodies' epitopes and their susceptibility to mutational escape. Our data predict no vulnerabilities for detection of mutations found in variants of concern. We confirm this using the commercial tests and sequence-confirmed COVID-19 patient samples. The antibody escape mutational 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.

摘要

不断出现的 SARS-CoV-2 变体中的突变的影响是快速抗原检测性能的主要关注点。为了评估突变对 11 种获得紧急使用授权的商业抗原检测中使用的 17 种抗体的影响，我们使用哺乳动物表面展示平台和深度突变扫描测量了所有可能的核衣壳点突变的抗体结合。结果提供了抗体表位及其对突变逃逸易感性的完整图谱。我们的数据预测，针对关注变体中发现的突变进行检测不会存在漏洞。我们使用商业检测和经过序列确认的 COVID-19 患者样本对此进行了确认。这里生成的抗体逃逸突变特征可作为预测快速抗原检测针对过去、现在以及任何可能的未来 SARS-CoV-2 变体性能的有价值资源，为我们的系统建立了直接的临床和公共卫生效用。