Background: There is an unmet medical need to develop a vaccine targeting endemic coronaviruses. Antigen-specific monoclonal antibodies (mAbs) are crucial for many assays to support vaccine development. Objective: In this study, we used the HuCal Fab phage display library with a diversity of 4.5 × 1010 to identify antibodies specific to the spike proteins of the four endemic coronaviruses: OC43, NL63, 229E, and HKU1. Methods: As proof of concept, we established a newly designed platform using a long-read NGS workflow for antibody discovery and compared the results against the traditional workflow using Sanger sequencing consisting of lengthy and laborious benchwork. Results: The long-read NGS workflow identified most of the antibodies seen from the Sanger sequencing workflow, and many more additional antigen-specific antibodies against the endemic coronaviruses. Overall efficiency improved up to three times, comparing the traditional workflow with the NGS workflow. Of the 113 NGS-derived mAbs isolated to bind the four endemic coronavirus spike proteins, 107/113 (94.7%) had potent ELISA binding affinities (EC50 < 150 ng/mL, or <1 nM), and 61/113 (54%) had extremely potent ELISA binding affinities (EC50 of <15 ng/mL, or <0.1 nM). Conclusions: We successfully developed and incorporated the long-read NGS workflow to generate target-specific antibodies with many antibodies at sub-nanomolar affinities that are likely missed by a traditional workflow. We identified strong neutralizing antibodies, proving that our endemic spike proteins are capable of generating antibodies that could offer protection against the endemic HCoVs.
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