Human effector/memory CD4 T cell subsets: deep TCR profiling.

Clonal fate of helper T cells is governed by early costimulatory signals but may also depend on the mode of TCR interaction with peptide-MHC on APCs. We investigate TCR repertoires of eight effector/memory CD4+ T-cell subsets (Th1, Th2, nonclassical Th2 (Th2a), Th17, Th1-17, Tfh, Treg, Th22), revealing subset-specific physicochemical and recombinational features reproducible across donors. At a threshold of 3 reads per UMI, the number of obtained UMI-labeled cDNA molecules per repertoire per sample ranged from 5,300 to 303,500, and the number of CDR3 clonotype variants at the nucleotide level per repertoire per sample ranged from 1,200 to 83,200. Deep unbiased TCR profiling allowed us to assess the natural level of in vivo CD4+ subsets plasticity. We observed a major clonal exchange between Th17/Th22/Th2/Th2a and the high stability of Treg and Tfh subsets. The latter two subsets also show higher repertoire publicity across donors. Tfh repertoire features reflect those of mature antibodies and indicate stringent selection of highly antigen-specific, low cross-reactive TCRs. We conclude that functional subsets are marked with non-random universal for donors and specific features of passed selection. In future TCR sequencing applications, subset-specific profiling could provide better insights of normal and pathological states of adaptive immunity compared to the classical approach when TCR profiling is performed on bulk T cells or after rough division into CD4 and CD8-enriched populations. Dataset consists of 86 samples: T cell receptor clonesets from 5 healthy donors. For each of the donors, 8 functional CD4 T cell subsets were sorted and for each subset alpha and beta TCR libraries were prepared for NGS. Deep TCR profiling was achieved with UMI libraries barcoding according to Milaboratory protocol. Additionally, for 3 samples from donor 4 there are biological replicates: 3 replicate TCR alpha and 3 TCR beta libraries.

辅助性T细胞的克隆命运受早期共刺激信号调控，同时也可能取决于T细胞受体（T cell receptor, TCR）与抗原呈递细胞（antigen-presenting cell, APC）表面肽-主要组织相容性复合体（peptide-MHC）的相互作用模式。本研究对8种效应/记忆性CD4阳性T细胞亚群（Th1、Th2、非经典Th2（Th2a）、Th17、Th1-17、滤泡辅助性T细胞（T follicular helper, Tfh）、调节性T细胞（regulatory T cell, Treg）、Th22）的T细胞受体库进行分析，揭示了在不同供体间可重复的亚群特异性理化特征与重组特征。在每个唯一分子标识符（unique molecular identifier, UMI）对应3条测序读段的阈值下，每个样本的每个受体库中获得的UMI标记互补DNA（cDNA）分子数范围为5300至303500，而每个样本的每个受体库在核苷酸水平上的互补决定区3（complementarity-determining region 3, CDR3）克隆型变体数范围为1200至83200。深层无偏倚T细胞受体谱型分析使我们能够评估体内CD4阳性T细胞亚群的天然可塑性水平。我们观察到Th17、Th22、Th2与Th2a亚群间存在显著的克隆型交换，而Treg与Tfh亚群则具有较高的稳定性；后两个亚群的受体库在不同供体间共享的克隆型比例更高。Tfh受体库的特征与成熟抗体的特征相符，提示其经历了对抗原特异性强、交叉反应性低的T细胞受体的严格筛选。本研究得出结论：功能性T细胞亚群均带有供体间通用的非随机特征，以及经历过选择过程的特异性特征。在未来的T细胞受体测序应用中，与将T细胞受体谱型分析应用于整体T细胞群或粗略分为CD4富集、CD8富集群的经典方法相比，亚群特异性谱型分析能够更深入地解析适应性免疫的正常与病理状态。本数据集共包含86份样本：来自5名健康供体的T细胞受体克隆型数据。每名供体的8种功能性CD4阳性T细胞亚群均经过分选，且针对每个亚群均构建了α链与β链的T细胞受体文库，用于下一代测序（next-generation sequencing, NGS）。本研究采用基于Milaboratory实验流程的UMI文库条形码标记技术，实现了深层T细胞受体谱型分析。此外，来自供体4的3份样本设有生物学重复：包含3份T细胞受体α链重复文库与3份T细胞受体β链重复文库。