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通过拉曼光谱研究胚胎干细胞及其分化后代和 iPS 重编程过程中的细胞状态变化。

Following Embryonic Stem Cells, Their Differentiated Progeny, and Cell-State Changes During iPS Reprogramming by Raman Spectroscopy.

机构信息

RIKEN Biosystems Dynamic Research (BDR), 2-6-3 Furuedai, Suita, Osaka 565-0874, Japan.

Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 2-8 Yamadaoka, Suita, Osaka 565-0871, Japan.

出版信息

Anal Chem. 2020 Nov 17;92(22):14915-14923. doi: 10.1021/acs.analchem.0c01800. Epub 2020 Oct 28.

Abstract

Monitoring cell-state transition in pluripotent cells is invaluable for application and basic research. In this study, we demonstrate the pertinence of noninvasive, label-free Raman spectroscopy to monitor and characterize the cell-state transition of mouse stem cells undergoing reprogramming. Using an isogenic cell line of mouse stem cells, reprogramming from neuronal cells was performed, and we showcase a comparative analysis of living single-cell spectral data of the original stem cells, their neuronal progenitors, and reprogrammed cells. Neural network, regression models, and ratiometric analyses were used to discriminate the cell states and extract several important biomarkers specific to differentiation or reprogramming. Our results indicated that the Raman spectrum allowed us to build a low-dimensional space allowing us to monitor and characterize the dynamics of cell-state transition at a single-cell level, scattered in heterogeneous populations. The ability of monitoring pluripotency by Raman spectroscopy and distinguishing differences between ES and reprogrammed cells is also discussed.

摘要

监测多能细胞的细胞状态转变对于应用和基础研究是非常有价值的。在这项研究中,我们证明了无创、无标记的拉曼光谱在监测和表征经历重编程的小鼠干细胞的细胞状态转变方面的相关性。我们使用一个小鼠干细胞的同源细胞系,进行了神经元细胞的重编程,并展示了对原始干细胞、其神经元前体和重编程细胞的活单细胞光谱数据的比较分析。我们使用神经网络、回归模型和比率分析来区分细胞状态,并提取几个特定于分化或重编程的重要生物标志物。我们的结果表明,拉曼光谱使我们能够构建一个低维空间,允许我们在单细胞水平上监测和表征细胞状态转变的动态,这些细胞在异质群体中分散。我们还讨论了通过拉曼光谱监测多能性和区分 ES 细胞和重编程细胞之间差异的能力。

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