Suppr超能文献

由开源软件支持的、用于从通用显微镜数据中对荧光标记物进行高内涵、单细胞定量分析的工作流程。

Workflow for high-content, individual cell quantification of fluorescent markers from universal microscope data, supported by open source software.

作者信息

Stockwell Simon R, Mittnacht Sibylle

机构信息

Cancer Biology, UCL Cancer Institute;

Cancer Biology, UCL Cancer Institute.

出版信息

J Vis Exp. 2014 Dec 16(94):51882. doi: 10.3791/51882.

Abstract

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators. Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software(1) to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

摘要

在理解贴壁哺乳动物组织培养模型中细胞行为的控制机制方面取得的进展越来越依赖于单细胞分析模式。那些提供反映细胞群体生物标志物平均值的综合数据的方法,有可能丢失反映所研究生物系统异质性的亚群动态信息。与此相符的是,传统方法正被更复杂的细胞分析形式所取代,或得到其支持,这些分析形式是为通过高内涵显微镜进行评估而开发的。这些分析可能会生成大量荧光生物标志物的图像,借助配套的专有软件包,可对每个细胞进行多参数测量。然而,这些设备中许多相对较高的资金成本和过度专业化使得许多研究人员无法使用。本文描述了一种普遍适用的工作流程,用于从单个细胞的特定亚细胞区域量化多种荧光标记强度,适用于与大多数荧光显微镜拍摄的图像配合使用。该工作流程的关键是使用免费的Cell Profiler软件(1)来区分这些图像中的单个细胞,将它们分割成定义好的亚细胞区域,并提供这些区域特有的荧光标记强度值。从图像数据中提取单个细胞强度值是该工作流程的核心目的,将通过对贴壁人类细胞中G1检查点调节因子的siRNA筛选的对照数据进行分析来说明。然而,这里介绍的工作流程可应用于分析来自其他细胞扰动方式(如化合物筛选)的数据以及其他基于荧光的细胞标记形式,因此应该对广泛的实验室有用。

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