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

Christine Faulkner, Ji Zhou, Alexandre Evrard, Gildas Bourdais, Dan MacLean, Heidrun Häweker, Peter Eckes, Silke Robatzek

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
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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.

Original languageEnglish
Pages (from-to)683–693
Number of pages11
Issue number10
Early online date26 Jul 2017
Publication statusPublished - Oct 2017


  • Confocal microscopy
  • bioimage informatics
  • microtubules
  • MAP4
  • TUB6
  • endomembrane compartments
  • Arabidopsis
  • herbicides

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