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基于荧光寿命成像显微镜相因子分析的液滴中单细胞无标记代谢分类

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.

机构信息

Biomedical Engineering Department, University of California, Irvine, California.

Department of Biomedical Engineering, Laboratory for Fluorescence Dynamics, University of California, Irvine, California.

出版信息

Cytometry A. 2019 Jan;95(1):93-100. doi: 10.1002/cyto.a.23673. Epub 2018 Dec 11.

Abstract

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry.

摘要

单细胞代谢特征对于理解与健康组织发育和许多疾病进展相关的亚细胞功能和生化变化至关重要。然而,单细胞分析通常需要使用荧光标记和细胞裂解,然后进行基因组分析以鉴定细胞异质性。以非侵入性和无标记的方式识别单个细胞对于检测能量代谢至关重要,因为它可以区分细胞类型,最重要的是对于保持细胞活力以进行进一步分析至关重要。在这里,我们使用液滴微流控技术和荧光寿命成像显微镜的相量方法开发了一种强大的测定法,用于研究白血病细胞系(K-562 和 Jurkat)内和之间的细胞异质性。我们已经将这些技术扩展到了增殖和静止细胞之间代谢差异的特征描述中——这是无标记单细胞休眠研究的关键步骤。结果表明,基于液滴的非侵入性和无标记方法可根据其代谢状态区分单个细胞,可作为与基因组统计数据相关的上游表型平台。 © 2018 国际细胞分析学会。

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