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面板设计与全光谱流式细胞术的优化。

Panel Design and Optimization for Full Spectrum Flow Cytometry.

机构信息

Hugh Green Cytometry Centre, Malaghan Institute of Medical Research, Wellington, New Zealand.

Malaghan Institute of Medical Research, Wellington, New Zealand.

出版信息

Methods Mol Biol. 2024;2779:99-124. doi: 10.1007/978-1-0716-3738-8_6.

DOI:10.1007/978-1-0716-3738-8_6
PMID:38526784
Abstract

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, which measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks, is now routinely used in laboratories around the world, and the demand for this technology is rapidly increasing. With the ability to use larger and more complex staining panels, optimized protocols are vital for achieving the best panel design, panel optimization, and high-dimensional data analysis outcomes. In addition, a better understanding of how to fully characterize the autofluorescence of the sample, coupled with an intelligent panel design approach, allows improved marker resolution on highly autofluorescent tissues or cells. Here, we provide optimized step-by-step protocols for full spectrum flow cytometry, covering panel design and optimization, autofluorescence evaluation and strategy selection, and methods for performing longitudinal studies.

摘要

荧光流式细胞术的技术进步和对免疫系统复杂性的不断深入理解,导致了大型流式细胞术面板的发展,在单细胞水平上达到了多达 40 个标记物。全光谱流式细胞术现在在世界各地的实验室中得到了常规应用,它可以测量面板中所有荧光染料的全发射范围,而不仅仅是发射峰,对这种技术的需求正在迅速增加。随着使用更大和更复杂的染色面板的能力的提高,优化的方案对于实现最佳的面板设计、面板优化和高维数据分析结果至关重要。此外,更好地理解如何充分描述样本的自发荧光,加上智能的面板设计方法,可以提高对高度自发荧光组织或细胞的标记物分辨率。在这里,我们提供了全光谱流式细胞术的优化分步方案,涵盖了面板设计和优化、自发荧光评估和策略选择,以及进行纵向研究的方法。

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本文引用的文献

1
Ensuring Full Spectrum Flow Cytometry Data Quality for High-Dimensional Data Analysis.确保用于高维数据分析的全谱流式细胞术数据质量。
Curr Protoc. 2023 Feb;3(2):e657. doi: 10.1002/cpz1.657.
2
A comparison of spectral unmixing to conventional compensation for the calculation of fluorochrome abundances from flow cytometric data.流式细胞术数据中荧光染料含量计算的光谱解混与传统补偿方法的比较。
Cytometry A. 2022 Nov;101(11):885-891. doi: 10.1002/cyto.a.24669. Epub 2022 Jul 15.
3
Full spectrum cytometry improves the resolution of highly autofluorescent biological samples: Identification of myeloid cells in regenerating skeletal muscles.
人外周血多形核白细胞激活与吞噬作用的高维光谱流式细胞术
J Leukoc Biol. 2025 Apr 23;117(4). doi: 10.1093/jleuko/qiaf025.
4
High-dimensional spectral flow cytometry of activation and phagocytosis by peripheral human polymorphonuclear leukocytes.人外周多形核白细胞激活和吞噬作用的高维光谱流式细胞术
bioRxiv. 2024 Dec 5:2024.12.01.626241. doi: 10.1101/2024.12.01.626241.
全光谱流式细胞术提高了高自发荧光生物样本的分辨率:再生骨骼肌中髓样细胞的鉴定。
Cytometry A. 2022 Oct;101(10):862-876. doi: 10.1002/cyto.a.24568. Epub 2022 May 24.
4
Identification of fetal liver stroma in spectral cytometry using the parameter autofluorescence.使用参数自发荧光对光谱细胞术中小鼠胎肝基质细胞的鉴定。
Cytometry A. 2022 Nov;101(11):960-969. doi: 10.1002/cyto.a.24567. Epub 2022 May 14.
5
cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies.cyCombine 支持在技术内和跨技术对单细胞细胞仪数据集进行强大的整合。
Nat Commun. 2022 Mar 31;13(1):1698. doi: 10.1038/s41467-022-29383-5.
6
Unlocking autofluorescence in the era of full spectrum analysis: Implications for immunophenotype discovery projects.解锁全光谱分析时代的自发荧光:对免疫表型发现项目的影响。
Cytometry A. 2022 Nov;101(11):922-941. doi: 10.1002/cyto.a.24555. Epub 2022 Apr 12.
7
OMIP 083: A 21-marker 18-color flow cytometry panel for in-depth phenotyping of human peripheral monocytes.OMIP 083:用于人类外周血单核细胞深度表型分析的21标记18色流式细胞术检测板
Cytometry A. 2022 May;101(5):374-379. doi: 10.1002/cyto.a.24545. Epub 2022 Mar 10.
8
Panel Optimization for High-Dimensional Immunophenotyping Assays Using Full-Spectrum Flow Cytometry.采用全光谱流式细胞术的高维免疫表型分析检测面板优化。
Curr Protoc. 2021 Sep;1(9):e222. doi: 10.1002/cpz1.222.
9
Integration, exploration, and analysis of high-dimensional single-cell cytometry data using Spectre.使用Spectre对高维单细胞细胞计数数据进行整合、探索和分析。
Cytometry A. 2022 Mar;101(3):237-253. doi: 10.1002/cyto.a.24350. Epub 2021 Apr 26.
10
Multibatch Cytometry Data Integration for Optimal Immunophenotyping.用于优化免疫表型分析的多批次细胞计数数据整合
J Immunol. 2021 Jan 1;206(1):206-213. doi: 10.4049/jimmunol.2000854. Epub 2020 Nov 23.