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Differential Signaling and Sugar Exchanges in Response to Avirulent Pathogen- and Symbiont-Derived Molecules in Tobacco Cells

Overview of attention for article published in Frontiers in Microbiology, November 2017
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Title
Differential Signaling and Sugar Exchanges in Response to Avirulent Pathogen- and Symbiont-Derived Molecules in Tobacco Cells
Published in
Frontiers in Microbiology, November 2017
DOI 10.3389/fmicb.2017.02228
Pubmed ID
Authors

Carole Pfister, Stéphane Bourque, Odile Chatagnier, Annick Chiltz, Jérôme Fromentin, Diederik Van Tuinen, Daniel Wipf, Nathalie Leborgne-Castel

Abstract

Plants interact with microbes whose ultimate aim is to exploit plant carbohydrates for their reproduction. Plant-microbe interactions (PMIs) are classified according to the nature of their trophic exchanges: while mutualistic microbes trade nutrients with plants, pathogens unilaterally divert carbohydrates. The early responses following microbe recognition and the subsequent control of plant sugar distribution are still poorly understood. To further decipher PMI functionality, we used tobacco cells treated with microbial molecules mimicking pathogenic or mutualistic PMIs, namely cryptogein, a defense elicitor, and chitotetrasaccharide (CO4), which is secreted by mycorrhizal fungi. CO4 was perceived by tobacco cells and triggered widespread transient signaling components such as a sharp cytosolic Ca2+ elevation, NtrbohD-dependent H2O2 production, and MAP kinase activation. These CO4-induced events differed from those induced by cryptogein, i.e., sustained events leading to cell death. Furthermore, cryptogein treatment inhibited glucose and sucrose uptake but not fructose uptake, and promoted the expression of NtSUT and NtSWEET sugar transporters, whereas CO4 had no effect on sugar uptake and only a slight effect on NtSWEET2B expression. Our results suggest that microbial molecules induce different signaling responses that reflect microbial lifestyle and the subsequent outcome of the interaction.

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Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 26%
Researcher 6 19%
Student > Master 3 10%
Professor 2 6%
Lecturer > Senior Lecturer 1 3%
Other 3 10%
Unknown 8 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 45%
Biochemistry, Genetics and Molecular Biology 2 6%
Chemical Engineering 1 3%
Unspecified 1 3%
Computer Science 1 3%
Other 2 6%
Unknown 10 32%