Kroll Torsten, Schmidt David, Schwanitz Georg, Ahmad Mubashir, Hamann Jana, Schlosser Corinne, Lin Yu-Chieh, Böhm Konrad J, Tuckermann Jan, Ploubidou Aspasia
Leibniz Institute on Aging-Fritz Lipmann Institute, Jena, Germany.
These authors contributed equally to this work.
Curr Protoc Cytom. 2016 Jul 1;77:12.43.1-12.43.44. doi: 10.1002/cpcy.7.
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.
高内涵分析(HCA)通过对相关信息内容进行自动提取、多参数分析和分类,将原始光学显微镜图像转化为定量数据。与自动高通量图像采集相结合,应用于化学物质或RNA干扰试剂筛选的HCA被称为高内涵筛选(HCS)。HCA在量化细胞表型方面的强大功能使其也适用于常规显微镜检查。然而,开发有效的HCA和生物信息学分析流程以在HCS中获取具有生物学意义的数据具有挑战性。在此,描述了HCA检测方案和HCS生物信息学分析流程的逐步开发过程。通过应用已发表的RNA干扰筛选的原始数据,将该方案应用于粘着斑(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,证明了该方案的强大功能。该检测方法和基础策略针对的是在小规模或大型HCS实验中对亚细胞特征进行基于显微镜的定量分析的研究人员。© 2016约翰威立国际出版公司