Abstract：
The SARS-CoV-2 Omicron variant evades most neutralizing vaccine-induced antibodies and is associated with lower antibody titers upon breakthrough infections than previous variants. However, the mechanism remains unclear. Here, we find using a geometric deep-learning model that Omicron\'s extensively mutated receptor binding site (RBS) features reduced antigenicity compared with previous variants. Mice immunization experiments with different recombinant receptor binding domain (RBD) variants confirm that the serological response to Omicron is drastically attenuated and less potent. Analyses of serum cross-reactivity and competitive ELISA reveal a reduction in antibody response across both variable and conserved RBD epitopes. Computational modeling confirms that the RBS has a potential for further antigenicity reduction while retaining efficient receptor binding. Finally, we find a similar trend of antigenicity reduction over decades for hCoV229E, a common cold coronavirus. Thus, our study explains the reduced antibody titers associated with Omicron infection and reveals a possible trajectory of future viral evolution.
摘要：
SARS-CoV-2Omicron变体逃避了大多数中和疫苗诱导的抗体，并且在突破感染时与以前的变体相比具有较低的抗体滴度。然而,机制尚不清楚。这里,我们使用几何深度学习模型发现，与以前的变体相比，Omicron的广泛突变的受体结合位点（RBS）特征降低了抗原性。用不同的重组受体结合结构域(RBD)变体进行的小鼠免疫实验证实,对Omicron的血清学应答急剧减弱且效力较低。血清交叉反应性和竞争性ELISA的分析揭示了跨可变和保守RBD表位的抗体应答的降低。计算模型证实RBS具有进一步降低抗原性同时保持有效受体结合的潜力。最后,我们发现hCoV229E几十年来抗原性降低的趋势相似，一种普通的感冒冠状病毒。因此，我们的研究解释了与Omicron感染相关的抗体滴度降低,并揭示了未来病毒进化的可能轨迹.
