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The use of quantitative imaging to investigate regulators of membrane trafficking in Arabidopsis stomatal closure.

Authors :
Bourdais, Gildas
McLachlan, Deirdre H.
Rickett, Lydia M.
Zhou, Ji
Siwoszek, Agnieszka
Häweker, Heidrun
Hartley, Matthew
Kuhn, Hannah
Morris, Richard J.
MacLean, Dan
Robatzek, Silke
Source :
Traffic; 2/1/2019, Vol. 20 Issue 2, p168-180, 13p
Publication Year :
2019

Abstract

Expansion of gene families facilitates robustness and evolvability of biological processes but impedes functional genetic dissection of signalling pathways. To address this, quantitative analysis of single cell responses can help characterize the redundancy within gene families. We developed high‐throughput quantitative imaging of stomatal closure, a response of plant guard cells, and performed a reverse genetic screen in a group of Arabidopsis mutants to five stimuli. Focussing on the intersection between guard cell signalling and the endomembrane system, we identified eight clusters based on the mutant stomatal responses. Mutants generally affected in stomatal closure were mostly in genes encoding SNARE and SCAMP membrane regulators. By contrast, mutants in RAB5 GTPase genes played specific roles in stomatal closure to microbial but not drought stress. Together with timed quantitative imaging of endosomes revealing sequential patterns in FLS2 trafficking, our imaging pipeline can resolve non‐redundant functions of the RAB5 GTPase gene family. Finally, we provide a valuable image‐based tool to dissect guard cell responses and outline a genetic framework of stomatal closure. High‐throughput imaging at cellular and subcellular scales enables genetic dissection of plant physiological responses to biotic and abiotic stresses. We developed the software tool StomataMeasurer allowing the identification and measurements of stomatal apertures in an automated fashion. Using Arabidopsis mutant screening, we demonstrate that StomataMeasurer is suitable to analyse stomatal patterning and behaviours in response to five stimuli. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13989219
Volume :
20
Issue :
2
Database :
Complementary Index
Journal :
Traffic
Publication Type :
Academic Journal
Accession number :
134430210
Full Text :
https://doi.org/10.1111/tra.12625