1. Cell Biology
  2. Plant Biology
Download icon

Arabidopsis heterotrimeric G proteins regulate immunity by directly coupling to the FLS2 receptor

  1. Xiangxiu Liang
  2. Pingtao Ding
  3. Kehui Lian
  4. Jinlong Wang
  5. Miaomiao Ma
  6. Lin Li
  7. Lei Li
  8. Meng Li
  9. Xiaojuan Zhang
  10. She Chen
  11. Yuelin Zhang
  12. Jian-Min Zhou  Is a corresponding author
  1. Chinese Academy of Sciences, China
  2. University of British Columbia, Canada
  3. National Institute of Biological Sciences, China
Research Article
  • Cited 110
  • Views 6,764
  • Annotations
Cite this article as: eLife 2016;5:e13568 doi: 10.7554/eLife.13568

Abstract

The Arabidopsis immune receptor FLS2 perceives bacterial flagellin epitope flg22 to activate defenses through the central cytoplasmic kinase BIK1. The heterotrimeric G proteins composed of the non-canonical Gα protein XLG2, the Gβ protein AGB1, and the Gγ proteins AGG1 and AGG2 are required for FLS2-mediated immune responses through an unknown mechanism. Here we show that in the pre-activation state, XLG2 directly interacts with FLS2 and BIK1, and it functions together with AGB1 and AGG1/2 to attenuate proteasome-mediated degradation of BIK1, allowing optimum immune activation. Following the activation by flg22, XLG2 dissociates from AGB1 and is phosphorylated by BIK1 in the N terminus. The phosphorylated XLG2 enhances the production of reactive oxygen species (ROS) likely by modulating the NADPH oxidase RbohD. The study demonstrates that the G proteins are directly coupled to the FLS2 receptor complex and regulate immune signaling through both pre-activation and post-activation mechanisms.

Article and author information

Author details

  1. Xiangxiu Liang

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Pingtao Ding

    Department of Botany, University of British Columbia, Vancouver, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Kehui Lian

    Department of Botany, University of British Columbia, Vancouver, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Jinlong Wang

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Miaomiao Ma

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Lin Li

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Lei Li

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Meng Li

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Xiaojuan Zhang

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  10. She Chen

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  11. Yuelin Zhang

    Department of Botany, University of British Columbia, Vancouver, Canada
    Competing interests
    The authors declare that no competing interests exist.
  12. Jian-Min Zhou

    State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
    For correspondence
    jmzhou@genetics.ac.cn
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Thorsten Nürnberger, University of Tubingen, Germany

Publication history

  1. Received: December 6, 2015
  2. Accepted: April 2, 2016
  3. Accepted Manuscript published: April 4, 2016 (version 1)
  4. Version of Record published: April 26, 2016 (version 2)

Copyright

© 2016, Liang et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 6,764
    Page views
  • 2,381
    Downloads
  • 110
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Cell Biology
    2. Computational and Systems Biology
    Taraneh Zarin et al.
    Research Advance Updated

    In previous work, we showed that intrinsically disordered regions (IDRs) of proteins contain sequence-distributed molecular features that are conserved over evolution, despite little sequence similarity that can be detected in alignments (Zarin et al., 2019). Here, we aim to use these molecular features to predict specific biological functions for individual IDRs and identify the molecular features within them that are associated with these functions. We find that the predictable functions are diverse. Examining the associated molecular features, we note some that are consistent with previous reports and identify others that were previously unknown. We experimentally confirm that elevated isoelectric point and hydrophobicity, features that are positively associated with mitochondrial localization, are necessary for mitochondrial targeting function. Remarkably, increasing isoelectric point in a synthetic IDR restores weak mitochondrial targeting. We believe feature analysis represents a new systematic approach to understand how biological functions of IDRs are specified by their protein sequences.

    1. Cell Biology
    2. Physics of Living Systems
    Harsh Vashistha et al.
    Research Article Updated

    Heterogeneity in physical and functional characteristics of cells (e.g. size, cycle time, growth rate, protein concentration) proliferates within an isogenic population due to stochasticity in intracellular biochemical processes and in the distribution of resources during divisions. Conversely, it is limited in part by the inheritance of cellular components between consecutive generations. Here we introduce a new experimental method for measuring proliferation of heterogeneity in bacterial cell characteristics, based on measuring how two sister cells become different from each other over time. Our measurements provide the inheritance dynamics of different cellular properties, and the ‘inertia’ of cells to maintain these properties along time. We find that inheritance dynamics are property specific and can exhibit long-term memory (∼10 generations) that works to restrain variation among cells. Our results can reveal mechanisms of non-genetic inheritance in bacteria and help understand how cells control their properties and heterogeneity within isogenic cell populations.