title: A method for characterizing phenotypic changes in highly variable cell populations and its application to high content screening of Arabidopsis thaliana protoplasts.
abstract: Quantitative image analysis procedures are necessary for the automated discovery of effects of drug treatment in large collections of fluorescent micrographs. When compared to their mammalian counterparts, the effects of drug conditions on protein localization in plant species are poorly understood and underexplored. To investigate this relationship, we generated a large collection of images of single plant cells after various drug treatments. For this, protoplasts were isolated from six transgenic lines of A. thaliana expressing fluorescently tagged proteins. Eight drugs at three concentrations were applied to protoplast cultures followed by automated image acquisition. For image analysis, we developed a cell segmentation protocol for detecting drug effects using a Hough transform-based region of interest detector and a novel cross-channel texture feature descriptor. In order to determine treatment effects, we summarized differences between treated and untreated experiments with an L1Cramér-von Mises statistic. The distribution of these statistics across all pairs of treated and untreated replicates was compared to the variation within control replicates to determine the statistical significance of observed effects. Using this pipeline, we report the dose dependent drug effects in the first high-content Arabidopsis thaliana drug screen of its kind. These results can function as a baseline for comparison to other protein organization modeling approaches in plant cells. © 2017 International Society for Advancement of Cytometry.
authors.affiliation: Computational Biology Department, Carnegie Mellon University, Pittsburgh.
authors.forename: Gregory R
authors.initials: GR
authors.lastname: Johnson
authors.affiliation: Computational Biology Department, Carnegie Mellon University, Pittsburgh.
authors.forename: Joshua D
authors.initials: JD
authors.lastname: Kangas
authors.affiliation: Institute for Biology II/Molecular Plant Physiology, Faculty of Biology, Albert Ludwig University of Freiburg, Freiburg, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Dovzhenko
authors.affiliation: Centre for Biological Systems Analysis (ZBSA), Albert Ludwig University of Freiburg, Freiburg, Germany.
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Trojok
authors.affiliation: Institute for Biology II/Molecular Plant Physiology, Faculty of Biology, Albert Ludwig University of Freiburg, Freiburg, Germany.
authors.forename: Karsten
authors.initials: K
authors.lastname: Voigt
authors.affiliation: Computational Biology Department, Carnegie Mellon University, Pittsburgh.
authors.forename: Timothy D
authors.initials: TD
authors.lastname: Majarian
authors.affiliation: Institute for Biology II/Molecular Plant Physiology, Faculty of Biology, Albert Ludwig University of Freiburg, Freiburg, Germany.|Freiburg Institute for Advanced Studies (FRIAS), Albert Ludwig University of Freiburg, Freiburg, Germany.
authors.forename: Klaus
authors.initials: K
authors.lastname: Palme
authors.affiliation: Computational Biology Department, Carnegie Mellon University, Pittsburgh.|Freiburg Institute for Advanced Studies (FRIAS), Albert Ludwig University of Freiburg, Freiburg, Germany.|Departments of Biological Sciences, Biomedical Engineering and Machine Learning, Carnegie Mellon University, Pittsburgh.
authors.forename: Robert F
authors.initials: RF
authors.lastname: Murphy
mesh_terms: D017360:Arabidopsis / Q000187:drug effects; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010641:Phenotype; D030821:Plants, Genetically Modified; D011523:Protoplasts / Q000187:drug effects
keywords: cellular heterogeneity; fluorescence microscopy; high content screening; subcellular location