High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification
Torsten Kroll, David Schmidt, Georg Schwanitz, Mubashir Ahmad, Jana Hamann, Corinne Schlosser, Yu-Chieh Lin, Konrad J. Böhm, Jan Tuckermann, Aspasia Ploubidou
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引用次数: 7
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Abstract
High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc.
亚细胞结构的高含量显微分析:检测发展及其在黏附定量中的应用
高含量分析(High-content analysis, HCA)通过对相关信息内容的自动提取、多参数分析和分类,将原始光学显微镜图像转换为定量数据。与自动化高通量图像采集相结合,应用于化学物质或rnai试剂筛选的HCA被称为高含量筛选(HCS)。它在定量细胞表型方面的能力使HCA也适用于常规显微镜。然而,开发有效的HCA和生物信息学分析管道来获取HCS中具有生物学意义的数据是具有挑战性的。在这里,逐步发展的HCA测定方案和HCS生物信息学分析管道被描述。使用已发表的RNAi筛选的主要数据,该协议的功能通过应用于病灶粘附(FA)检测,多个FA特征的定量分析以及调节FA大小的信号通路的功能注释得到了证明。该分析和潜在策略的目标是研究人员在小规模或大型HCS实验中对亚细胞特征进行基于显微镜的定量分析。©2016 by John Wiley &儿子,Inc。
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