对具有多种自发荧光光谱的细胞进行光谱分析的无偏方法。

IF 2.5 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS Cytometry Part A Pub Date : 2024-06-12 DOI:10.1002/cyto.a.24856
Janna E. G. Roet, Aleksandra M. Mikula, Michael de Kok, Cora H. Chadick, Juan J. Garcia Vallejo, Henk P. Roest, Luc J. W. van der Laan, Charlotte M. de Winde, Reina E. Mebius
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引用次数: 0

摘要

自发荧光是细胞的固有特征,由光激发分子成分自然发光引起,会使流式细胞仪数据分析复杂化。不同类型的细胞具有不同的自发荧光光谱,即使在同一类型的细胞中,自发荧光光谱也可能存在异质性,例如活化状态或新陈代谢变化的结果。通过使用全谱流式细胞仪,一组波长范围内的光检测器可捕捉到荧光色素的发射光谱,从而为该荧光色素创建一个独特的特征。然后,利用这一特征从含有不同荧光分子的多色样本中识别或去除该荧光色素的独特光谱。重要的是,这意味着该技术还可用于识别未染色样本的内在自发荧光信号,从而达到去除混色的目的,并将自发荧光信号与荧光团信号分离开来。不过,这只有在样品具有单一、相对均匀和明亮的自发荧光光谱时才有效。为了分析具有异质自发荧光光谱特征的样本,我们建立了一个无偏的工作流程,以更快地识别样本中存在的不同自发荧光光谱,并将其作为 "自发荧光特征 "纳入全染色样本的解混合过程中。首先,通过对未染色细胞进行无偏降维和聚类,识别出具有相似自发荧光光谱的细胞群。然后,确定独特的自发荧光簇,用于提高全染色样本的解混合精度。这种无偏方法不受自发荧光强度和细胞亚群免疫分型的影响,能识别样本中大多数不同的自发荧光光谱,从而减少自发荧光溢出和扩散到外在表型标记的干扰。此外,这种方法同样适用于不同生物样本的光谱分析,包括组织细胞悬浮液、外周血单核细胞和体外培养(原代)细胞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as “autofluorescence signatures” during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.

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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.
期刊最新文献
OMIP‐108: 22‐color flow cytometry panel for detection and monitoring of chimerism and immune reconstitution in porcine‐to‐baboon models of operational xenotransplant tolerance studies Issue Information - TOC Volume 105A, Number 9, September 2024 Cover Image OMIP‐069 version 2: Update to the 40‐color full Spectrum flow cytometry panel for deep immunophenotyping of major cell subsets in human peripheral blood OMIP‐107: 8‐color whole blood immunophenotyping panel for the characterization and quantification of lymphocyte subsets and monocytes in swine
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