An automated quantitative image analysis tool for the identification of microtubule patterns in plants

Faulkner, Christine, Zhou, Ji, Evrard, Alexandre, Bourdais, Gildas, MacLean, Dan, Häweker, Heidrun, Eckes, Peter and Robatzek, Silke (2017) An automated quantitative image analysis tool for the identification of microtubule patterns in plants. Traffic, 18 (10). 683–693. ISSN 1398-9219

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    Abstract

    High throughput confocal imaging poses challenges in the computational image analysis of complex subcellular structures such as the microtubule cytoskeleton. Here, we developed CellArchitect, an automated image analysis tool that quantifies changes to subcellular patterns illustrated by microtubule markers in plants. We screened microtubule-targeted herbicides and demonstrate that high throughput confocal imaging with integrated image analysis by CellArchitect can distinguish effects induced by the known herbicides indaziflam and trifluralin. The same platform was used to examine six other compounds with herbicidal activity, and at least three different effects induced by these compounds were profiled. We further show that CellArchitect can detect subcellular patterns tagged by actin and endoplasmic reticulum markers. Thus, the platform developed here can be used to automate image analysis of complex subcellular patterns for purposes such as herbicide discovery and mode of action characterisation. The capacity to use this tool to quantitatively characterise cellular responses lends itself to application across many areas of biology.

    Item Type: Article
    Additional Information: This article is protected by copyright. All rights reserved.
    Uncontrolled Keywords: confocal microscopy,bioimage informatics,microtubules,map4,tub6,endomembrane compartments,arabidopsis,herbicides
    Faculty \ School: Faculty of Science > School of Biological Sciences
    Faculty of Science > School of Computing Sciences
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    Depositing User: Pure Connector
    Date Deposited: 10 Aug 2017 06:06
    Last Modified: 24 May 2019 14:39
    URI: https://ueaeprints.uea.ac.uk/id/eprint/64461
    DOI: 10.1111/tra.12505

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