Antibody Screening Results for Anti-Nucleocapsid Antibodies Toward the Development of a Lateral Flow Assay to Detect SARS-CoV-2 Nucleocapsid Protein

Abstract

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.

Electrochemical Immunoassay for the Detection of SARS-CoV-2 Nucleocapsid Protein in Nasopharyngeal Samples

“…To screen capture anti-N and detection anti-N-HRP antibodies, we performed the electrochemical immunoassay on our SPCEs using eight different antibody pairs ( Table S1 ). The antibodies tested were selected based on a previous study 39 that identified commercially available antibodies that performed best on immunoassays targeting the SARS-CoV-2 N protein and following commercial supplier recommendations. 40 All antibody pairs from commercial sources (Pairs 2 to 8) were tested against in house-generated antibodies (Pair 1).…”

“…The results show that Δ I is highly variable across the eight antibody pairs tested, which is consistent with results from previous studies. 39 , 41 The difference in the signal observed across antibody pairs can be attributed to multiple factors, including the binding affinity between the antibodies and our target and the way the antibodies bind to the electrode surface. On our electrochemical immunoassay, Pair 5 gave a current output 34% higher than that generated by the affinity-purified rabbit anti-N polyclonal antibodies (Pair 1) and critically demonstrated the most consistent current output, as shown by the lowest standard deviation.…”

Automated liquid handling robot for rapid lateral flow assay development

“…We used the automated liquid handling system to rapidly screen for over a thousand potential pairs of antibodies for spike and nucleocapsid antigen targets combined. More information about this screening effort can be found in the References Section [ 26 , 27 ]. The rapid nature of this work would not have been possible without an automated lateral flow assay development system.…”

“…The integration of an automated liquid handling system with LFA development provides a unique capability previously impossible for traditional LFA development teams. Traditional LFA experiments are often limited in size and scope; consequently, larger optimization and screening efforts using higher throughput methods (e.g., ELISAs) are used for downselection before testing in the LFA format [ 26 , 27 ]. However, conclusions from higher throughput methods do not necessarily translate to performance in an LFA, specifically due to the porous nature of the materials and continuous (but not necessarily homogeneous) flow of reagents [ 1 ].…”

“…Lastly, we demonstrated the comparative benefit of the platform through direct comparison to an ELISA-like platform in a traditional antibody screen. This manuscript moves beyond previous publications and presentations by the inclusion of additional validation, links to all code and CAD files, and a direct comparison to more traditional antibody screening methods [ 26 – 28 ]. These demonstrations suggest this platform has the potential to revolutionize the LFA development process by minimizing hands-on time, maximizing experiment size, increasing reproducibility, and improving the management of experimental complexity.…”