Article
Extensive signal integration by the phytohormone protein network https://doi.org/10.1038/s41586-020-2460-0 Received: 6 June 2019 Accepted: 14 April 2020 Published online: xx xx xxxx Check for updates
Melina Altmann1,12, Stefan Altmann1,12, Patricia A. Rodriguez1, Benjamin Weller1, Lena Elorduy Vergara1, Julius Palme1,10, Nora Marín-de la Rosa1, Mayra Sauer1, Marion Wenig2, José Antonio Villaécija-Aguilar3, Jennifer Sales2, Chung-Wen Lin1, Ramakrishnan Pandiarajan1, Veronika Young1, Alexandra Strobel1, Lisa Gross4, Samy Carbonnel5, Karl G. Kugler6, Antoni Garcia-Molina1,11, George W. Bassel7, Claudia Falter1, Klaus F. X. Mayer6,8, Caroline Gutjahr3,5, A. Corina Vlot2, Erwin Grill4 & Pascal Falter-Braun1,9 ✉
Plant hormones coordinate responses to environmental cues with developmental programs1, and are fundamental for stress resilience and agronomic yield2. The core signalling pathways underlying the effects of phytohormones have been elucidated by genetic screens and hypothesis-driven approaches, and extended by interactome studies of select pathways3. However, fundamental questions remain about how information from different pathways is integrated. Genetically, most phenotypes seem to be regulated by several hormones, but transcriptional profiling suggests that hormones trigger largely exclusive transcriptional programs4. We hypothesized that protein–protein interactions have an important role in phytohormone signal integration. Here, we experimentally generated a systems-level map of the Arabidopsis phytohormone signalling network, consisting of more than 2,000 binary protein–protein interactions. In the highly interconnected network, we identify pathway communities and hundreds of previously unknown pathway contacts that represent potential points of crosstalk. Functional validation of candidates in seven hormone pathways reveals new functions for 74% of tested proteins in 84% of candidate interactions, and indicates that a large majority of signalling proteins function pleiotropically in several pathways. Moreover, we identify several hundred largely small-molecule-dependent interactions of hormone receptors. Comparison with previous reports suggests that noncanonical and nontranscription-mediated receptor signalling is more common than hitherto appreciated. To examine phytohormone signal integration by the plant protein network, we first identified 1,252 genes with probable or genetically demonstrated functions in phytohormone signalling (Fig. 1a and Supplementary Table 1). The corresponding network of literature curated binary interactions (LCIs) from the IntAct database5 (LCIIntA) shows extensive intrapathway but sparse interpathway connectivity (Extended Data Fig. 1), which could reflect an insulated organization of hormone signalling, or could be an artefact of inspection biases6. We therefore experimentally generated a systematic (unbiased design) map of the phytohormone signalling network. After cloning open reading frames (ORFs) for 1,226 (98%) of the selected genes (PhyHormORFeome), fivefold investigation of the pairwise matrix using a high-quality yeast two-hybrid (Y2H)-based mapping pipeline7 yielded the phytohormone interactome main (PhIMAIN) network. To find links
into the broader Arabidopsis network, we screened PhyHormORFeome against roughly 13,000 Arabidopsis ORFs8, resulting in an asymmetric PhIEXT data set. We also conducted focused screens for interactions of pathway-specific repressors with transcription factors9(PhIRep-TF), and for hormone-dependent interaction partners of phytohormone receptor proteins (PhIHORM). In the stringent final step of the common Y2H pipeline, all candidate pairs were fourfold-verified (Fig. 1b). The combined PhI network contains 2,072 interactions, of which 1,572 were previously unknown (Fig. 1c, Extended Data Fig. 1 and Supplementary Table 2). The interaction density in the symmetrically investigated PhIMAIN (0.4‰) is higher than in the proteome-scale Arabidopsis Interactome-1 (AI-1, 0.1‰)10, but lower than in the abscisic-acid (ABA)-focused interactome (7.5‰)3. It is likely that the increasing focus on functionally coherent proteins underlies this trend, but system
1 Institute of Network Biology (INET), Helmholtz Center Munich, German Research Center for Environmental Health, Munich-Neuherberg, Germany. 2Inducible Resistance Signaling Group, Institute of Biochemical Plant Pathology (BIOP), Helmholtz Center Munich, German Research Center for Environmental Health, Munich-Neuherberg, Germany. 3Plant Genetics, TUM School of Life Sciences, Technical University of Munich (TUM), Freising, Germany. 4Botany, TUM School of Life Sciences, Technical University of Munich (TUM), Freising, Germany. 5Genetics, Faculty of Biology, Ludwig-Maximilians-Universität (LMU) München, Planegg-Martinsried, Germany. 6Plant Genome and Systems Biology (PGSB), Helmholtz Center Munich, German Research Center for Environmental Health, Munich-Neuherberg, Germany. 7School of Biosciences, University of Birmingham, Birmingham, UK. 8TUM School of Life Sciences, Technical University of Munich (TUM), Freising, Germany. 9Microbe-Host Interactions, Faculty of Biology, Ludwig-Maximilians-Universität (LMU) München, Planegg-Martinsried, Germany. 10Present address: Department of Genetics, Harvard Medical School, Boston, MA, USA. 11Present address: Plant Molecular Biology, Faculty of Biology, Ludwig-Maximilians-Universität (LMU) München, Planegg-Martinsried, Germany. 12 These authors contributed equally: Melina Altmann, Stefan Altmann. ✉e-mail: pascal.falter-braun@helmholtz-muenchen.de
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