High‐Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification. Issue 1 (1st July 2016)

• Record Type: Journal Article
• Authors: Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu‐Chieh; Böhm, Konrad J.; Tuckermann, Jan; Ploubidou, Aspasia
• Editors: Robinson, J. Paul; Darzynkiewicz, Zbigniew; Hoffman, Robert; Nolan, John P.; Rabinovitch, Peter S.; Watkins, Simon
• Is Part Of: Current protocols in cytometry. Volume 77:Issue 1(2016)
• Page Start: 12.43.1
• Page End: 12.43.44
• Publication Date: 2016-07-01
• Subjects: focal adhesions -- high‐content analysis -- high‐content screening -- microscopy automation -- quantitative microscopy -- subcellular organelles; Cytology -- Laboratory manuals; Flow cytometry -- Laboratory manuals; Cell separation -- Laboratory manuals; Molecular biology -- Laboratory manuals; Flow Cytometry -- methods; Image Cytometry -- methods; Cell Separation -- methods; Cytological Techniques; Molecular Biology -- methods; Cell separation; Cytology; Flow cytometry; Molecular biology; Laboratory Manuals; Laboratory manuals; 571.6
• DOI: 10.1002/cpcy.7
• Languages: English
• ISSNs: 1934-9297

Abstract

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.