IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-38103-6.html
   My bibliography  Save this article

Dynamic changes of the Prf/Pto tomato resistance complex following effector recognition

Author

Listed:
  • Arsheed H. Sheikh

    (University of Warwick
    King Abdullah University of Science and Technology)

  • Iosif Zacharia

    (University of Warwick)

  • Alonso J. Pardal

    (University of Warwick)

  • Ana Dominguez-Ferreras

    (University of Warwick)

  • Daniela J. Sueldo

    (University of Warwick
    Norwegian University of Science and Technology)

  • Jung-Gun Kim

    (Stanford University)

  • Alexi Balmuth

    (J.R. Simplot Company
    Norwich Research Park)

  • Jose R. Gutierrez

    (Norwich Research Park)

  • Brendon F. Conlan

    (The Australian National University)

  • Najeeb Ullah

    (University of Warwick)

  • Olivia M. Nippe

    (University of Warwick)

  • Anil M. Girija

    (Tel-Aviv University)

  • Chih-Hang Wu

    (Norwich Research Park)

  • Guido Sessa

    (Tel-Aviv University)

  • Alexandra M. E. Jones

    (University of Warwick)

  • Murray R. Grant

    (University of Warwick)

  • Miriam L. Gifford

    (University of Warwick
    University of Warwick)

  • Mary Beth Mudgett

    (Stanford University)

  • John P. Rathjen

    (The Australian National University)

  • Vardis Ntoukakis

    (University of Warwick
    University of Warwick)

Abstract

In both plants and animals, nucleotide-binding leucine-rich repeat (NLR) immune receptors play critical roles in pathogen recognition and activation of innate immunity. In plants, NLRs recognise pathogen-derived effector proteins and initiate effector-triggered immunity (ETI). However, the molecular mechanisms that link NLR-mediated effector recognition and downstream signalling are not fully understood. By exploiting the well-characterised tomato Prf/Pto NLR resistance complex, we identified the 14-3-3 proteins TFT1 and TFT3 as interacting partners of both the NLR complex and the protein kinase MAPKKKα. Moreover, we identified the helper NRC proteins (NLR-required for cell death) as integral components of the Prf /Pto NLR recognition complex. Notably our studies revealed that TFTs and NRCs interact with distinct modules of the NLR complex and, following effector recognition, dissociate facilitating downstream signalling. Thus, our data provide a mechanistic link between activation of immune receptors and initiation of downstream signalling cascades.

Suggested Citation

  • Arsheed H. Sheikh & Iosif Zacharia & Alonso J. Pardal & Ana Dominguez-Ferreras & Daniela J. Sueldo & Jung-Gun Kim & Alexi Balmuth & Jose R. Gutierrez & Brendon F. Conlan & Najeeb Ullah & Olivia M. Nip, 2023. "Dynamic changes of the Prf/Pto tomato resistance complex following effector recognition," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38103-6
    DOI: 10.1038/s41467-023-38103-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-38103-6
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-38103-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jonathan D. G. Jones & Jeffery L. Dangl, 2006. "The plant immune system," Nature, Nature, vol. 444(7117), pages 323-329, November.
    2. Simon B. Saucet & Yan Ma & Panagiotis F. Sarris & Oliver J. Furzer & Kee Hoon Sohn & Jonathan D.G. Jones, 2015. "Two linked pairs of Arabidopsis TNL resistance genes independently confer recognition of bacterial effector AvrRps4," Nature Communications, Nature, vol. 6(1), pages 1-12, May.
    3. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Deepak D. Bhandari & Dae Kwan Ko & Sang-Jin Kim & Kinya Nomura & Sheng Yang He & Federica Brandizzi, 2023. "Defense against phytopathogens relies on efficient antimicrobial protein secretion mediated by the microtubule-binding protein TGNap1," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Aaron C Ericsson & J Wade Davis & William Spollen & Nathan Bivens & Scott Givan & Catherine E Hagan & Mark McIntosh & Craig L Franklin, 2015. "Effects of Vendor and Genetic Background on the Composition of the Fecal Microbiota of Inbred Mice," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-19, February.
    3. Hossain, Ahmed & Beyene, Joseph & Willan, Andrew R. & Hu, Pingzhao, 2009. "A flexible approximate likelihood ratio test for detecting differential expression in microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3685-3695, August.
    4. Sheng Yang & Weiwei Cai & Ruijie Wu & Yu Huang & Qiaoling Lu & Hui Wang & Xueying Huang & Yapeng Zhang & Qing Wu & Xingge Cheng & Meiyun Wan & Jingang Lv & Qian Liu & Xiang Zheng & Shaoliang Mou & Dey, 2023. "Differential CaKAN3-CaHSF8 associations underlie distinct immune and heat responses under high temperature and high humidity conditions," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    5. Xiaohong Li & Guy N Brock & Eric C Rouchka & Nigel G F Cooper & Dongfeng Wu & Timothy E O’Toole & Ryan S Gill & Abdallah M Eteleeb & Liz O’Brien & Shesh N Rai, 2017. "A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-22, May.
    6. Jiahui Liu & Xiaoyun Wu & Yue Fang & Ye Liu & Esther Oreofe Bello & Yong Li & Ruyi Xiong & Yinzi Li & Zheng Qing Fu & Aiming Wang & Xiaofei Cheng, 2023. "A plant RNA virus inhibits NPR1 sumoylation and subverts NPR1-mediated plant immunity," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    7. Kerr Kathleen F., 2012. "Optimality Criteria for the Design of 2-Color Microarray Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-9, January.
    8. Paul Vincelli, 2016. "Genetic Engineering and Sustainable Crop Disease Management: Opportunities for Case-by-Case Decision-Making," Sustainability, MDPI, vol. 8(5), pages 1-22, May.
    9. Ambroise Jérôme & Bearzatto Bertrand & Robert Annie & Macq Benoit & Gala Jean-Luc, 2012. "Combining Multiple Laser Scans of Spotted Microarrays by Means of a Two-Way ANOVA Model," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-20, February.
    10. J. McClatchy & R. Strogantsev & E. Wolfe & H. Y. Lin & M. Mohammadhosseini & B. A. Davis & C. Eden & D. Goldman & W. H. Fleming & P. Conley & G. Wu & L. Cimmino & H. Mohammed & A. Agarwal, 2023. "Clonal hematopoiesis related TET2 loss-of-function impedes IL1β-mediated epigenetic reprogramming in hematopoietic stem and progenitor cells," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    11. Alexandra Gyurdieva & Stefan Zajic & Ya-Fang Chang & E. Andres Houseman & Shan Zhong & Jaegil Kim & Michael Nathenson & Thomas Faitg & Mary Woessner & David C. Turner & Aisha N. Hasan & John Glod & Ro, 2022. "Biomarker correlates with response to NY-ESO-1 TCR T cells in patients with synovial sarcoma," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    12. Sora Yoon & Seon-Young Kim & Dougu Nam, 2016. "Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    13. Yu Lianbo & Gulati Parul & Fernandez Soledad & Pennell Michael & Kirschner Lawrence & Jarjoura David, 2011. "Fully Moderated T-statistic for Small Sample Size Gene Expression Arrays," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-22, September.
    14. Norliza Abu-Bakar & Nor Mustaiqazah Juri & Ros Azrinawati Hana Abu-Bakar & Mohd Zulfadli Sohaime & Rafidah Badrun & Johari Sarip & Mohd Azhar Hassan & Khairulmazmi Ahmad, 2021. "Recombinant Protein Foliar Application Activates Systemic Acquired Resistance and Increases Tolerance against Papaya Dieback Disease," Asian Journal of Agriculture and rural Development, Asian Economic and Social Society, vol. 11(1), pages 1-9, March.
    15. Chaofeng Yuan & Wensheng Zhu & Xuming He & Jianhua Guo, 2019. "A mixture factor model with applications to microarray data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 60-76, March.
    16. Nan Li & Matthew N. McCall & Zhijin Wu, 2017. "Establishing Informative Prior for Gene Expression Variance from Public Databases," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 160-177, June.
    17. Brian Caffo & Liu Dongmei & Giovanni Parmigiani, 2004. "Power Conjugate Multilevel Models with Applications to Genomics," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1062, Berkeley Electronic Press.
    18. Nott, David J. & Yu, Zeming & Chan, Eva & Cotsapas, Chris & Cowley, Mark J. & Pulvers, Jeremy & Williams, Rohan & Little, Peter, 2007. "Hierarchical Bayes variable selection and microarray experiments," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 852-872, April.
    19. Xin Tong & Jia-Jia Zhao & Ya-Lan Feng & Jing-Ze Zou & Jian Ye & Junfeng Liu & Chenggui Han & Dawei Li & Xian-Bing Wang, 2023. "A selective autophagy receptor VISP1 induces symptom recovery by targeting viral silencing suppressors," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    20. Santu Ghosh & Alan M. Polansky, 2022. "Large-Scale Simultaneous Testing Using Kernel Density Estimation," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 808-843, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38103-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.