Department of Immunology, Harvard Medical School, and Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA.
Department of Immunology, Harvard Medical School, and Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA.
Curr Opin Immunol. 2020 Apr;63:61-67. doi: 10.1016/j.coi.2020.02.004. Epub 2020 Apr 4.
Single-cell transcriptomics (scRNAseq) holds the promise to generate definitive atlases of cell types. We review scRNAseq studies of conventional CD4 αβ T cells performed in a variety of challenged contexts (infection, tumor, allergy) that aimed to parse the complexity and representativity of previously defined CD4 T cell types, lineages, and cosmologies. With a few years' experience, the field has realized the difficulties and pitfalls of scRNAseq. With the very high-dimensionality of scRNAseq data, subset definitions based on low-dimensionality marker combinations tend to fade or blur: cell types prove more complex than expected; transcripts of key defining transcripts (cytokines, chemokines) are distributed as broad and partially overlapping continua; boundaries with innate lymphocytes are blurred. Tissue location and activation, either cytokine-driven or TCR-driven, determine Teff heterogeneity in sometimes unexpected ways. Emerging techniques for lineage and trajectory tracing, and RNA-protein connections, will further help define the space of differentiated CD4 T cell heterogeneity.
单细胞转录组学 (scRNAseq) 有望生成细胞类型的明确图谱。我们回顾了在各种挑战性环境（感染、肿瘤、过敏）中进行的常规 CD4 αβ T 细胞的 scRNAseq 研究，旨在解析先前定义的 CD4 T 细胞类型、谱系和宇宙的复杂性和代表性。经过几年的经验，该领域已经意识到 scRNAseq 的困难和陷阱。由于 scRNAseq 数据的高维性，基于低维标志物组合的子集定义往往会消失或模糊：细胞类型比预期的更复杂；关键定义转录物（细胞因子、趋化因子）的转录本呈广泛且部分重叠的连续分布；与先天淋巴细胞的边界模糊。组织位置和激活，无论是细胞因子驱动还是 TCR 驱动，都以有时出人意料的方式决定 Teff 的异质性。用于谱系和轨迹追踪以及 RNA-蛋白连接的新兴技术将进一步帮助定义分化的 CD4 T 细胞异质性空间。
