Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA.
Methods Mol Biol. 2021;2285:49-63. doi: 10.1007/978-1-0716-1311-5_4.
CD4 T cells or helper T cells play various roles in the immune response to pathogens, tumors, as well as in asthma, allergy, and autoimmunity. Consequently, there is great interest in the comprehensive investigation of different T helper cell subsets. Here, we use mass cytometry (CyTOF), which is similar to flow cytometry but uses metal ion-tagged antibodies, which are detected using time-of-flight mass spectrometry. CyTOF allows the simultaneous detection of over 40 different antibodies, allowing us to collect high-dimensional single-cell proteomic data on T helper subsets. We use an extensive staining panel with a large number of lineage markers, cytokines, and other functional markers to identify and characterize CD4 T cell subsets. In this method, human peripheral blood mononuclear cells are stimulated ex vivo with PMA and ionomycin, which activates T cells. The activated CD4 T cells can then be identified as Th1, Th2, or Th17 cells based on their production of IFNγ, IL-4, and IL-17, respectively. Tregs are identified as CD4CD25CD127. Once Th1, Th2, Th17, and Tregs have been identified, they can be characterized in more detail using the large number of phenotypic and functional markers included in the CyTOF staining panel. Finally, automated and unbiased high-dimensional data analysis tools can be employed to comprehensively characterize T helper cells and discover novel features.
CD4 T 细胞或辅助性 T 细胞在病原体、肿瘤、哮喘、过敏和自身免疫的免疫反应中发挥多种作用。因此，人们对全面研究不同的辅助性 T 细胞亚群非常感兴趣。在这里，我们使用质谱流式细胞术（CyTOF），它类似于流式细胞术，但使用金属离子标记的抗体，这些抗体使用飞行时间质谱进行检测。CyTOF 允许同时检测超过 40 种不同的抗体，使我们能够收集辅助性 T 细胞亚群的高维单细胞蛋白质组学数据。我们使用大量的谱系标记物、细胞因子和其他功能标记物的广泛染色面板来识别和表征 CD4 T 细胞亚群。在这种方法中，人外周血单核细胞在体外用 PMA 和离子霉素刺激，这激活了 T 细胞。然后，可以根据 IFNγ、IL-4 和 IL-17 的产生分别将激活的 CD4 T 细胞鉴定为 Th1、Th2 或 Th17 细胞。Treg 被鉴定为 CD4CD25CD127。一旦鉴定出 Th1、Th2、Th17 和 Treg，就可以使用 CyTOF 染色面板中包含的大量表型和功能标记物对其进行更详细的描述。最后，可以使用自动化和无偏的高维数据分析工具全面表征辅助性 T 细胞并发现新的特征。
