Applications, Cytek Biosciences, Inc, Fremont, California, USA.
Department of Microbiology/Immunology, Stanford University, Stanford, California, USA.
Cytometry A. 2022 Nov;101(11):942-959. doi: 10.1002/cyto.a.24565. Epub 2022 May 20.
High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.
高维单细胞数据已成为揭示免疫系统复杂性及其在稳态和多种病理中的作用的重要工具。随着技术工具的发展，研究人员正在采用这些工具来回答越来越复杂的生物学问题。直到最近，质谱流式细胞术（MC）一直是需要超过 29 个标记物的细胞测定中使用的主要技术。然而，最近随着全光谱流式细胞术（FSFC）的引入，已经有可能打破荧光障碍并超越 29 个荧光参数。在这项研究中，我们与斯坦福人类免疫监测中心（HIMC）合作，使用 HIMC 开发的经过验证的免疫面板，对五个患者样本进行了比较，该面板是在他们的 MC 平台上开发的。使用拆分样本和相同的抗体面板，我们能够使用多种数据分析方法证明两种技术之间的结果高度可比。我们在此报告了使用可识别该面板定义的所有先前描述和预期免疫亚群的 32 标记流式细胞免疫监测面板对两种技术平台（MC 和 FSFC）的直接比较。
