School of Molecular Sciences, Arizona State University, Tempe, AZ 85281, USA.
Biodesign Institute, Tempe, AZ 85281, USA.
Cell Rep Med. 2021 Mar 16;2(3):100221. doi: 10.1016/j.xcrm.2021.100221. Epub 2021 Feb 25.
Polymorphisms in MHC-I protein sequences across human populations significantly affect viral peptide binding capacity, and thus alter T cell immunity to infection. In the present study, we assess the relationship between observed SARS-CoV-2 population mortality and the predicted viral binding capacities of 52 common MHC-I alleles. Potential SARS-CoV-2 MHC-I peptides are identified using a consensus MHC-I binding and presentation prediction algorithm called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolve a few hundred highly probable MHC-I peptides. By weighing individual MHC allele-specific SARS-CoV-2 binding capacity with population frequency in 23 countries, we discover a strong inverse correlation between predicted population SARS-CoV-2 peptide binding capacity and mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produce a stronger association with observed mortality rate, highlighting the importance of S, N, M, and E proteins in driving productive immune responses.
人群中 MHC-I 蛋白序列的多态性显著影响病毒肽结合能力，从而改变了对感染的 T 细胞免疫。在本研究中，我们评估了观察到的 SARS-CoV-2 人群死亡率与 52 个常见 MHC-I 等位基因预测的病毒结合能力之间的关系。使用一种称为 EnsembleMHC 的共识 MHC-I 结合和呈递预测算法来鉴定潜在的 SARS-CoV-2 MHC-I 肽。从近 350 万个候选物开始，我们确定了几百个高度可能的 MHC-I 肽。通过在 23 个国家/地区以个体 MHC 等位基因特异性 SARS-CoV-2 结合能力与种群频率为权重，我们发现预测的人群 SARS-CoV-2 肽结合能力与死亡率之间存在很强的负相关关系。我们的计算表明，来自病毒结构蛋白的肽与观察到的死亡率之间存在更强的关联，突出了 S、N、M 和 E 蛋白在驱动有效免疫反应中的重要性。
