OMIP-112: 42参数(40色)光谱流式细胞仪面板,用于人外周血白细胞的综合免疫表型。

IF 2.5 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Laurien A. Waaijer, Bram van Cranenbroek, Hans J. P. M. Koenen
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引用次数: 0

摘要

分析人体免疫系统对于了解其在疾病中的作用至关重要,但这需要先进的新技术。光谱流式细胞术(SFM)能够在单细胞水平上进行深度分析。它能够在一次测量中检测到许多荧光参数;因此,当病人的材料有限时,它是非常有用的。然而,设计和分析这些高维数据集仍然很复杂。我们优化了42个参数面板(40个市售荧光染料,一个堆叠荧光染料和一个自动荧光(AF)参数),能够识别先天和适应性免疫细胞组成。这是第一个针对外周全血进行优化的42个参数面板,就复杂性而言,它优于其他已发布的40种颜色的omip。通过这个面板,我们能够识别中性粒细胞、嗜碱性粒细胞、嗜酸性粒细胞、单核细胞、树突状细胞、CD4 T细胞、CD8 T细胞、调节性T细胞、粘膜相关不变T (MAIT)细胞、γδ T细胞、B细胞、NK细胞、树突状细胞和先天淋巴样细胞(ILCs)。此外,利用共刺激、检查点、激活、归巢和成熟标记,该面板可以实现更深层次的表型分型。在一次测量中,FlowSOM识别了80多个不同的免疫细胞亚群,并手工注释。总之,通过这种高维SFM面板,我们的目标是生成免疫图谱,以了解疾病和监测治疗反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

OMIP-112: 42-Parameter (40-Color) Spectral Flow Cytometry Panel for Comprehensive Immunophenotyping of Human Peripheral Blood Leukocytes

OMIP-112: 42-Parameter (40-Color) Spectral Flow Cytometry Panel for Comprehensive Immunophenotyping of Human Peripheral Blood Leukocytes

Profiling the human immune system is essential to understanding its role in disease, but it requires advanced and novel technologies. Spectral flow cytometry (SFM) enables deep profiling at the single-cell level. It is able to detect many fluorescent parameters within one measurement; therefore, it is vastly useful when patient material is limited. However, designing and analyzing these high-dimensional datasets remains complex. We optimized a 42-parameter panel (40 commercially available fluorochromes, one stacked fluorochrome and an autofluorescent (AF) parameter) that enables the identification of innate and adaptive immune cell composition. It is the first 42-parameter panel that is optimized on peripheral whole blood, and it outperforms other published OMIPs of 40 colors in terms of complexity. With this panel, we are able to identify neutrophils, basophils, eosinophils, monocytes, dendritic cells, CD4 T cells, CD8 T cells, regulatory T cells, mucosal-associated invariant T (MAIT) cells, γδ T cells, B cells, NK cells, dendritic cells, and innate lymphoid cells (ILCs). Furthermore, with the utilization of co-stimulatory, checkpoint, activation, homing, and maturation markers, this panel enables deeper phenotyping. Within one measurement, more than 80 distinct immune cell subsets were identified by FlowSOM and annotated manually. In conclusion, with this high-dimensional SFM panel, we aim to generate immune profiles to understand disease and monitor therapy response.

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来源期刊
Cytometry Part A
Cytometry Part A 生物-生化研究方法
CiteScore
8.10
自引率
13.50%
发文量
183
审稿时长
4-8 weeks
期刊介绍: Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques. The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome: Biomedical Instrumentation Engineering Biophotonics Bioinformatics Cell Biology Computational Biology Data Science Immunology Parasitology Microbiology Neuroscience Cancer Stem Cells Tissue Regeneration.
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