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关注的新型冠状病毒变异株的T细胞表位图谱

The T Cell Epitope Landscape of SARS-CoV-2 Variants of Concern.

作者信息

Tennøe Simen, Gheorghe Marius, Stratford Richard, Clancy Trevor

机构信息

NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo, Norway.

出版信息

Vaccines (Basel). 2022 Jul 14;10(7):1123. doi: 10.3390/vaccines10071123.

Abstract

During the COVID-19 pandemic, several SARS-CoV-2 variants of concern (VOC) emerged, bringing with them varying degrees of health and socioeconomic burdens. In particular, the Omicron VOC displayed distinct features of increased transmissibility accompanied by antigenic drift in the spike protein that partially circumvented the ability of pre-existing antibody responses in the global population to neutralize the virus. However, T cell immunity has remained robust throughout all the different VOC transmission waves and has emerged as a critically important correlate of protection against SARS-CoV-2 and its VOCs, in both vaccinated and infected individuals. Therefore, as SARS-CoV-2 VOCs continue to evolve, it is crucial that we characterize the correlates of protection and the potential for immune escape for both B cell and T cell human immunity in the population. Generating the insights necessary to understand T cell immunity, experimentally, for the global human population is at present a critical but a time consuming, expensive, and laborious process. Further, it is not feasible to generate global or universal insights into T cell immunity in an actionable time frame for potential future emerging VOCs. However, using computational means we can expedite and provide early insights into the correlates of T cell protection. In this study, we generated and revealed insights on the T cell epitope landscape for the five main SARS-CoV-2 VOCs observed to date. We demonstrated using a unique AI prediction platform, a significant conservation of presentable T cell epitopes across all mutated peptides for each VOC. This was modeled using the most frequent HLA alleles in the human population and covers the most common HLA haplotypes in the human population. The AI resource generated through this computational study and associated insights may guide the development of T cell vaccines and diagnostics that are even more robust against current and future VOCs, and their emerging subvariants.

摘要

在新冠疫情期间,出现了几种值得关注的严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变异株(VOC),给健康和社会经济带来了不同程度的负担。特别是,奥密克戎变异株表现出传播性增强的明显特征,同时刺突蛋白发生抗原漂移,部分规避了全球人群中现有抗体反应中和该病毒的能力。然而,在所有不同的VOC传播浪潮中,T细胞免疫一直保持强劲,并已成为疫苗接种者和感染者预防SARS-CoV-2及其VOCs的关键保护相关因素。因此,随着SARS-CoV-2 VOCs不断进化,至关重要的是我们要明确人群中B细胞和T细胞人类免疫的保护相关因素以及免疫逃逸的可能性。通过实验为全球人群了解T细胞免疫产生必要的见解目前是一个关键但耗时、昂贵且费力的过程。此外,在潜在未来出现的VOCs的可操作时间框架内对T细胞免疫产生全球或普遍的见解是不可行的。然而,利用计算手段,我们可以加快速度并提供有关T细胞保护相关因素的早期见解。在这项研究中,我们针对迄今为止观察到的五种主要SARS-CoV-2 VOCs生成并揭示了T细胞表位格局的见解。我们使用一个独特的人工智能预测平台证明,每种VOC的所有突变肽中可呈递的T细胞表位具有显著的保守性。这是使用人群中最常见的HLA等位基因进行建模的,涵盖了人群中最常见的HLA单倍型。通过这项计算研究生成的人工智能资源及相关见解可能会指导T细胞疫苗和诊断方法的开发,使其对当前和未来的VOCs及其新兴亚变体更具抗性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d8/9315645/cd5e94bdd030/vaccines-10-01123-g001.jpg

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