Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.
Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.
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DOI：
10.1016/j.immuni.2016.08.015
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发表时间：
2016-09-20
期刊：
影响因子：
32.4
通讯作者：
Ginhoux F
中科院分区：
文献类型：
--
作者：
Guilliams M;Dutertre CA;Scott CL;McGovern N;Sichien D;Chakarov S;Van Gassen S;Chen J;Poidinger M;De Prijck S;Tavernier SJ;Low I;Irac SE;Mattar CN;Sumatoh HR;Low GHL;Chung TJK;Chan DKH;Tan KK;Hon TLK;Fossum E;Bogen B;Choolani M;Chan JKY;Larbi A;Luche H;Henri S;Saeys Y;Newell EW;Lambrecht BN;Malissen B;Ginhoux F
树突状细胞(DC)是一种专业的抗原提呈细胞，具有很大的治疗潜力。已经描述了多个DC亚群，在没有巨噬细胞污染的情况下，跨组织和物种对它们进行比对以分析它们的功能仍然是具有挑战性的。在这里，我们提供并验证了一个通用的工具箱，用于通过对来自多个小鼠、猕猴和人类组织的常规流式细胞术和质量细胞术数据的非监督分析来自动识别DC。使用一组最小的谱系印迹标记足以将DC细分为不同组织和物种的传统型1(CDC1)、传统型2(CDC2)和浆细胞样树突状细胞(PDC)。通过这种方式，大量额外的标记物仍然可以用来进一步表征DC在组织和炎症过程中的异质性。这一框架代表了对突变小鼠和人类患者的DC群体进行普遍、高通量和标准化分析的前进方向。一种保守的门控策略对小鼠和人类组织中的树突状细胞(DC)进行了比对，对流式细胞术数据的非监督计算分析优于手动分析。质量细胞术揭示了跨小鼠和人类组织的DC亚群的异质性。为树突状细胞的自动鉴定提供通用工具箱。该框架代表了对突变小鼠和患者的树突状细胞进行高通量和标准化分析的前进方向。
Dendritic cells (DCs) are professional antigen-presenting cells that hold great therapeutic potential. Multiple DC subsets have been described, and it remains challenging to align them across tissues and species to analyze their function in the absence of macrophage contamination. Here, we provide and validate a universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues. The use of a minimal set of lineage-imprinted markers was sufficient to subdivide DCs into conventional type 1 (cDC1s), conventional type 2 (cDC2s), and plasmacytoid DCs (pDCs) across tissues and species. This way, a large number of additional markers can still be used to further characterize the heterogeneity of DCs across tissues and during inflammation. This framework represents the way forward to a universal, high-throughput, and standardized analysis of DC populations from mutant mice and human patients. A conserved gating strategy aligns dendritic cells (DCs) in mouse and human tissues Unsupervised computational analysis of flow cytometry data outperforms manual analysis Mass cytometry reveals heterogeneity of DC subsets across mouse and human tissues DC activation upon inflammation tracked by automated analysis of mass cytometry Using unsupervised analysis of flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues, Guilliams et al. provide a universal toolbox for the automated identification of dendritic cells. This framework represents the way forward to high-throughput and standardized analysis of dendritic cells from mutant mice and patients.