Multispectral autofluorescence for label free classification of immune cell type and activation/polarization status.

IF 4.1 4区 医学 Q2 IMMUNOLOGY
Abbas Habibalahi, Ayad G Anwer, Aline Knab, Shane T Grey, Ewa M Goldys, Jared M Campbell
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Abstract

Evaluating immune status is a challenging and time-consuming process that involves analysing various biomarkers through numerous assays. The sensitive label-free technique of multispectral imaging of cell autofluorescence involves directly assessing the molecular composition of cells to gather biological information. Cells were cultured in RPMI 1640 modified media supplemented with penicillin-streptomycin and 10% foetal bovine serum at 37°C, with 5% CO2 and 95% humidity. Activation and differentiation was confirmed using immunofluorophores against relevant markers. Multispectral microscopy utilized defined spectral regions, which spanned the excitation (345-476 nm) and emission (414-675 nm) wavelength ranges. In total, 56 distinct spectral channels were applied. These channels cover the spectrum of several fluorophores notably NAD(P)H and flavins, whose concentrations depend on cellular metabolism. We identified distinct spectral signatures for characterizing cells from the Jurkat, Ramos, THP-1, and HL-60 immune cell lines. These signatures correspond to four major immune cell types: T cells (Lymphocytes), B cells (Lymphocytes), monocytes and neutrophils. Moreover, our investigation explored the potential identification of both activated and resting forms of these cells, including the discrimination of M0, M1 and M2 polarized macrophages. Classification accuracy ranged from 92% to 100% based on receiver operator characteristic area under the curve (ROC AUC) assessment. These results indicate that the multispectral evaluation of cell autofluorescence is applicable for characterization of immune status. This includes the assessment of cell types and their activation status, all achievable through a single non-invasive assay.

用于免疫细胞类型和激活/极化状态无标记分类的多光谱自身荧光。
评估免疫状态是一个具有挑战性和耗时的过程,需要通过大量的分析来分析各种生物标志物。灵敏的无标记细胞自身荧光多光谱成像技术涉及直接评估细胞的分子组成,以收集生物信息。细胞在添加青霉素-链霉素和10%胎牛血清的RPMI 1640改良培养基中培养,温度37℃,CO2 5%,湿度95%。利用免疫荧光团对相关标记物进行激活和分化证实。多光谱显微镜利用确定的光谱区域,该光谱区域跨越激发(345-476 nm)和发射(414-675 nm)波长范围。总共应用了56个不同的光谱通道。这些通道覆盖了几种荧光团的光谱,特别是NAD(P)H和黄素,其浓度取决于细胞代谢。我们从Jurkat、Ramos、THP-1和HL-60免疫细胞系中鉴定出不同的光谱特征。这些特征对应于四种主要的免疫细胞类型:T细胞(淋巴细胞)、B细胞(淋巴细胞)、单核细胞和中性粒细胞。此外,我们的研究探索了这些细胞的激活和静止形式的潜在识别,包括M0, M1和M2极化巨噬细胞的识别。基于接收算子曲线下特征面积(ROC AUC)评估的分类准确率为92% ~ 100%。这些结果表明,细胞自身荧光的多光谱评价可用于免疫状态的表征。这包括对细胞类型及其激活状态的评估,所有这些都可以通过单一的非侵入性分析实现。
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来源期刊
CiteScore
7.70
自引率
5.40%
发文量
109
审稿时长
1 months
期刊介绍: This peer-reviewed international journal publishes original articles and reviews on all aspects of basic, translational and clinical immunology. The journal aims to provide high quality service to authors, and high quality articles for readers. The journal accepts for publication material from investigators all over the world, which makes a significant contribution to basic, translational and clinical immunology.
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