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一个泛疾病和人口一级的单细胞TCRαβ谱的参考谱

Ziwei Xue^1,2, Lize Wu³, Bing Gao¹

¹Department of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.

|October 14, 2025

概括

这项研究从200多万个细胞中建立了一个大型T细胞受体 (TCR) 参考,揭示了与常见病毒和疾病相关的公共TCR. 一个新的工具,TCR-DeepInsight,有助于识别与疾病相关的TCR集群.

科学领域:

免疫学免疫学免疫学
基因组学就是基因组学.
计算生物学计算生物学

背景情况:

单细胞技术现在可以同时捕获T细胞受体 (TCR) 序列和基因表达 (GEX).
在人口层面上,将TCR谱与T细胞表型的疾病关联联系起来是一个显著的差距.

研究的目的:

构建对联单细胞RNA/TCR测序 (scRNA/TCR-seq) 数据的大规模参考.
揭示TCR-主要基因相容综合体 (MHC) 限制的内在特征,并确定公共的TCR.
开发一个计算框架来识别与疾病相关的TCR集群.

主要方法:

汇集了来自70项研究的200万个T细胞的参考数据集,包括scRNA/TCR-seq,全长配对TCR和HLA基因型.
分析了TCR-MHC限制,公共TCR患病率,克隆扩张以及与病毒表位体 (EBV,CMV,IAV) 的关联.
开发了TCR-DeepInsight,这是一个基于序列,GEX和HLA共享的TCR集群的计算框架.

主要成果:

在CD4+/CD8+ T细胞中揭示了生殖系编码的TCR-MHC限制.
观察到与高克隆扩张和共享HLA等位基因相关的广泛公共TCRs,可能针对共同的病毒表位.
证明了TCR-DeepInsight识别HLA共享和与疾病相关的TCR集群的能力.

结论:

这项研究提出了全面的scTCRαβ参考和用于TCR分析的新计算方法.
确定与病毒感染和潜在疾病联系相关的公共TCR.
TCR-DeepInsight有助于对功能性TCR及其疾病关联的表征.

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