Development and characterization of three novel mouse monoclonal antibodies targeting spike protein S1 subunit of Middle East respiratory syndrome corona virus

Abstract

BACKGROUND: Middle East Respiratory Syndrome Coronavirus is a highly pathogenic virus that poses a significant threat to public health. OBJECTIVE: The purpose of this study is to develop and characterize novel mouse monoclonal antibodies targeting the spike protein S1 subunit of the Middle East Respiratory Syndrome Corona Virus (MERS-CoV). METHODS: In this study, three mouse monoclonal antibodies (mAbs) against MERS-CoV were generated and characterized using hybridoma technology. The mAbs were evaluated for their reactivity and neutralization activity. The mAbs were generated through hybridoma technology by the fusion of myeloma cells and spleen cells from MERS-CoV-S1 immunized mice. The resulting hybridomas were screened for antibody production using enzyme-linked immunosorbent assays (ELISA). RESULTS: ELISA results demonstrated that all three mAbs exhibited strong reactivity against the MERS-CoV S1-antigen. Similarly, dot-ELISA revealed their ability to specifically recognize viral components, indicating their potential for diagnostic applications. Under non-denaturing conditions, Western blot showed the mAbs to have robust reactivity against a specific band at 116 KDa, corresponding to a putative MERS-CoV S1-antigen. However, no reactive bands were observed under denaturing conditions, suggesting that the antibodies recognize conformational epitopes. The neutralization assay showed no in vitro reactivity against MERS-CoV. CONCLUSION: This study successfully generated three mouse monoclonal antibodies against MERS-CoV using hybridoma technology. The antibodies exhibited strong reactivity against MERS-CoV antigens using ELISA and dot ELISA assays. Taken together, these findings highlight the significance of these mAbs for potential use as valuable tools for MERS-CoV research and diagnosis (community and field-based surveillance and viral antigen detection).