bioRxivImmunologyPreprint
Therapeutic and vaccine-induced cross-reactive antibodies with effector function against emerging Omicron variants
A. Addetia, L. Piccoli, J. B. Case, Y.-J. Park, M. Beltramello, B. Guarino, H. Dang, D. Pinto, S. Scheaffer, K. Sprouse, J. Bassi, C. Silacci-Fregni, F. Muoio, M. Dini, L. Vincenzetti, R. Acosta, D. Johnson, S. Subramanian, C. Saliba, M. Giurdanella, G. Lombardo, G. Leoni, K. Culap, C. McAlister, A. Rajesh, , Fran
Abstract
Currently circulating SARS-CoV-2 variants acquired convergent mutations at receptor-binding domain (RBD) hot spots1. Their impact on viral infection, transmission, and efficacy of vaccines and therapeutics remains poorly understood. Here, we demonstrate that recently emerged BQ.1.1. and XBB.1 variants bind ACE2 with high affinity and promote membrane fusion more efficiently than earlier Omicron variants. Structures of the BQ.1.1 and XBB.1 RBDs bound to human ACE2 and S309 Fab (sotrovimab parent) explain the altered ACE2 recognition and preserved antibody binding through conformational selection. We show that sotrovimab binds avidly to all Omicron variants, promotes Fc-dependent effector functions and protects mice challenged with BQ.1.1, the variant displaying the greatest loss of neutralization. Moreover, in several donors vaccine-elicited plasma antibodies cross-react with and trigger effector functions against Omicron variants despite reduced neutralizing activity. Cross-reactive RBD-directed human memory B cells remained dominant even after two exposures to Omicron spikes, underscoring persistent immune imprinting. Our findings suggest that this previously overlooked class of cross-reactive antibodies, exemplified by S309, may contribute to protection against disease caused by emerging variants through elicitation of effector functions.
- organism: human
- assay: proteomics
- assay: structural biology
- research focus: host-pathogen & immune response
- research focus: cell type annotation
- research focus: cell signaling & trafficking
- approach: experimental assay
- approach: statistical model
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