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利用表观遗传空间标记的高内涵图像分析解析干细胞谱系发育

Parsing Stem Cell Lineage Development Using High Content Image Analysis of Epigenetic Spatial Markers.

作者信息

Kim Joseph J, Moghe Prabhas V

机构信息

Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey.

出版信息

Curr Protoc Stem Cell Biol. 2018 Aug;46(1):e54. doi: 10.1002/cpsc.54. Epub 2018 Jun 14.

Abstract

This unit describes a protocol for acquiring and analyzing high-content super-resolution images of human stem cell nuclei for the characterization and classification of the cell differentiation paths based on distinct patterns of epigenetic mark organization. Here, we describe the cell culture, immunocytochemical labeling, super-resolution imaging parameters, and MATLAB-based quantitative image analysis approaches for monitoring human mesenchymal stem cells (hMSCs) and human induced pluripotent stem cells (hiPSCs) as the cells differentiate towards various lineages. Although this protocol uses specific cell types as examples, this approach could be easily extended to a variety of cell types and nuclear epigenetic and mechanosensitive biomarkers that are relevant to specific cell developmental scenarios. © 2018 by John Wiley & Sons, Inc.

摘要

本单元描述了一种用于获取和分析人类干细胞细胞核的高内涵超分辨率图像的方案,以便基于表观遗传标记组织的不同模式对细胞分化路径进行表征和分类。在此,我们描述了细胞培养、免疫细胞化学标记、超分辨率成像参数以及基于MATLAB的定量图像分析方法,用于监测人类间充质干细胞(hMSCs)和人类诱导多能干细胞(hiPSCs)向各种谱系分化的过程。尽管本方案以特定细胞类型为例,但这种方法可轻松扩展到与特定细胞发育情况相关的多种细胞类型以及核表观遗传和机械敏感生物标志物。© 2018 约翰威立父子公司版权所有。

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