The global COVID-19 pandemic has created an urgent demand for large numbers of inexpensive, accurate, rapid, point-of-care diagnostic tests. Analyte-based assays are suitably rapid and inexpensive and can be rapidly mass-produced, but for sufficiently accurate performance, they require highly optimized antibodies and assay conditions. We used an automated liquid handling system, customized to handle arrays of lateral flow (immuno)assays (LFAs) in a high-throughput screen, to identify anti-nucleocapsid antibodies that will perform optimally in an LFA. We tested 1021 anti-nucleocapsid antibody pairs as LFA capture and detection reagents with the goal of highlighting pairs that have the greatest affinity for the nucleocapsid protein of SARS-CoV-2 within the LFA format. In contrast to traditional antibody screening methods (e.g., ELISA, bio-layer interferometry), the method described here integrates real-time reaction kinetics with transport in, and immobilization directly onto, nitrocellulose. We have identified several candidate antibody pairs that are suitable for further development of an LFA for SARS-CoV-2.

中文翻译：

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用于开发检测 SARS-CoV-2 核衣壳蛋白的侧流测定法的抗核衣壳抗体的抗体筛选结果

全球 COVID-19 大流行催生了对大量廉价、准确、快速、即时诊断测试的迫切需求。基于分析物的检测速度快、成本低，可以快速批量生产，但要获得足够准确的性能，它们需要高度优化的抗体和检测条件。我们使用了自动化液体处理系统，定制用于在高通量筛选中处理横向流动（免疫）测定 (LFA) 阵列，以确定在 LFA 中表现最佳的抗核衣壳抗体。我们测试了 1021 个抗核衣壳抗体对作为 LFA 捕获和检测试剂，目的是突出显示对 LFA 格式中对 SARS-CoV-2 核衣壳蛋白具有最大亲和力的对。与传统的抗体筛选方法（如 ELISA、生物层干涉测量），这里描述的方法将实时反应动力学与传输到硝化纤维素上并直接固定到硝化纤维素上。我们已经确定了几种适合进一步开发 SARS-CoV-2 LFA 的候选抗体对。