抗体
表位
病毒学
免疫分析
分析物
抗原
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
生物
分子生物学
化学
计算生物学
作者
David Cate,Helen Hsieh,Veronika Glukhova,Joshua D Bishop,H Gleda Hermansky,Brianda Barrios-Lopez,Ben D Grant,Caitlin E Anderson,Ethan Spencer,Samantha Kuhn,Ryan Gallagher,Rafael Rivera,Crissa Bennett,Sam A Byrnes,John T Connelly,Puneet K Dewan,David S. Boyle,Bernhard H Weigl,Kevin Paul Flood Nichols
标识
DOI:10.26434/chemrxiv.12709538
摘要
<p></p><p>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 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 immunoassay (LFA) tests 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 unique epitopes of 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.</p><p></p>
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