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 Faculty of Science > The Sainsbury Laboratory
UEA Research Groups:	Faculty of Science > Research Groups > Plant Sciences
Depositing User:	Pure Connector
Date Deposited:	10 Aug 2017 05:06
Last Modified:	21 Mar 2024 02:04
URI:	https://ueaeprints.uea.ac.uk/id/eprint/64461
DOI:	10.1111/tra.12505

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