Deep mutational scanning reveals the antibody escape and infectivity landscape of SARS-CoV-2 Omicron JN.1 and XEC receptor-binding domains.

Authors

Chengwei Shao, Lisa Yang, Chuyao Xiao, Yumei Huang, Xiangxi Wang, Ling Chen, Pan Liu, Si Chen, Mingwei Wei, Siyue Jia, Lunbiao Cui, Yiyue Ge, Ming Xu, Xiaoyan Jia, Jingxin Li

Published in

Emerging microbes & infections. Volume 15. Issue 1. Pages 2686472. Epub Jun 21, 2026.

Abstract

SARS-CoV-2 continuously accumulates mutations in the spike receptor-binding domain (RBD), affecting both viral infectivity and antibody evasion. Systematic characterization of RBD mutations is therefore essential for understanding viral adaptation under immune pressure and predicting evolutionary trajectories. In this study, we employed a two-step, non-replicating pseudovirus deep mutational scanning (DMS) platform to measure the effects of all single amino acid substitutions in the RBD of Omicron variant JN.1 and its descendant lineage XEC within a full-length spike background. To identify representative antibodies for escape profiling, we first evaluated six RBD-targeting monoclonal antibodies against JN.1 and XEC pseudoviruses. Only BD55-1205 and 719-14 sIgA retained substantial neutralizing activity and were selected for subsequent escape mapping. The results showed that most single RBD amino acid mutations did not significantly enhance pseudovirus cellular invasion. Among mutations that are functionally retaining and confer marked escape from either antibody, most high escape substitutions cluster within the receptor-binding motif (RBM) and receptor-binding ridge. Furthermore, BD55-1205 and 719-14 sIgA each exhibited distinct, antibody-specific escape sites, demonstrating that different epitope preferences exert unique selective pressures within the same viral lineage. Overall, this pseudovirus-based DMS analysis elucidates the molecular mechanisms of immune escape and fitness for the JN.1 and XEC lineages. Our findings provide critical insights for forecasting SARS-CoV-2 evolution under population immunity and offer guidance for assessing emerging variants, selecting vaccine strains, and optimizing therapeutic antibodies.

PMID:
42324717
Bibliographic data and abstract were imported from PubMed on 22 Jun 2026.

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