Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115.
Proc Natl Acad Sci U S A. 2013 Nov 19;110(47):19030-5. doi: 10.1073/pnas.1318322110. Epub 2013 Nov 4.
Defining and characterizing pathologies of the immune system requires precise and accurate quantification of abundances and functions of cellular subsets via cytometric studies. At this time, data analysis relies on manual gating, which is a major source of variability in large-scale studies. We devised an automated, user-guided method, X-Cyt, which specializes in rapidly and robustly identifying targeted populations of interest in large data sets. We first applied X-Cyt to quantify CD4(+) effector and central memory T cells in 236 samples, demonstrating high concordance with manual analysis (r = 0.91 and 0.95, respectively) and superior performance to other available methods. We then quantified the rare mucosal associated invariant T cell population in 35 samples, achieving manual concordance of 0.98. Finally we characterized the population dynamics of invariant natural killer T (iNKT) cells, a particularly rare peripheral lymphocyte, in 110 individuals by assaying 19 markers. We demonstrated that although iNKT cell numbers and marker expression are highly variable in the population, iNKT abundance correlates with sex and age, and the expression of phenotypic and functional markers correlates closely with CD4 expression.
定义和描述免疫系统的病理学需要通过细胞计量学研究来精确和准确地量化细胞亚群的丰度和功能。此时,数据分析依赖于手动门控,这是大规模研究中变异性的主要来源。我们设计了一种自动化、用户引导的方法 X-Cyt,该方法专门用于快速和稳健地识别大数据集中目标感兴趣的群体。我们首先应用 X-Cyt 来量化 236 个样本中的 CD4(+)效应器和中央记忆 T 细胞,与手动分析高度一致(分别为 r = 0.91 和 0.95),并且优于其他可用方法。然后,我们在 35 个样本中量化了罕见的粘膜相关不变 T 细胞群体,实现了手动一致性为 0.98。最后,我们通过检测 19 个标志物来描述 110 个人中不变自然杀伤 T(iNKT)细胞的群体动力学。我们证明,尽管 iNKT 细胞数量和标记物表达在人群中高度可变,但 iNKT 丰度与性别和年龄相关,表型和功能标记物的表达与 CD4 表达密切相关。