Plant Abiotic Stress Signaling 1071630431, 9781071630433

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Methods in Molecular Biology 2642

Ivan Couée  Editor

Plant Abiotic Stress Signaling

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

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For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Plant Abiotic Stress Signaling Edited by

Ivan Couée UMR 6553 ECOBIO (Ecosystems-Biodiversity-Evolution), Centre National de la Recherche Scientifique (CNRS), University of Rennes, Rennes, France

Editor Ivan Coue´e UMR 6553 ECOBIO (Ecosystems-Biodiversity-Evolution) Centre National de la Recherche Scientifique (CNRS) University of Rennes Rennes, France

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-3043-3 ISBN 978-1-0716-3044-0 (eBook) https://doi.org/10.1007/978-1-0716-3044-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover Caption: Propagation of salt stress-induced calcium waves in a detached Arabidopsis leaf, as described in chapter 4 by Carine Alcon and Tou Cheu Xiong. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface Plants live their sessile lives in environments teeming with a multitude of abiotic (nonliving), chemical and physical, factors. Depending on their fluctuations, their intensities, their more or less frequent occurrences, a number of abiotic factors, such as drought, salinity, extreme temperatures (very low or very high), flooding (submergence), low or high light intensity, deficiency or toxic levels of nutrients, carbon limitation or starvation, energy limitation, aerial toxic compounds, soil toxic compounds, mechanical constraints, wounding, have huge stress impacts on plant population and community dynamics in natural ecosystems, on plant distribution and productivity, on wild or cultivated tree species, on pastures and forage crops, and on the production of crops and vegetables. Tremendous efforts have been made to describe and characterize the molecular, biochemical, and physiological basis of stress tolerance mechanisms that allow plants to tolerate or escape stressful conditions. Characterizing the initial mechanisms of plant sensitivity and reactivity to physico-chemical cues related to abiotic stresses is of utmost importance for understanding plant-environment interactions, adaptations of the sessile lifestyle, and the dynamics of plant species and populations, especially when plants and plant communities are confronted with an environmental context of global change, involving climate changes, widespread pollutions of soils, waters, and atmosphere, and additional anthropogenic impacts on soils, biodiversity, land use, and landscapes. The mechanisms through which plants perceive abiotic stress stimuli, and transduce these signals into physiological responses, constitute the primary line of interaction between the plant and the environment, and therefore between the plant and global changes. Such mechanisms are directly linked to the immediate capacities of plant communities to tolerate or not environmental changes, and are thus important features that must be incorporated as pivotal parameters of ecological modeling of plant dynamics under global change and as potential targets for crop improvement and management under the constraints of global change. In the last 10–20 years, remarkable progress has been made in the field of phytohormone sensing and signal transduction, with the necessary development of the relevant methodology for identification and characterization of ligands, of sensing entities, and of transduction pathways. All of these phytohormones and their signal transduction pathways have been found to present some level of involvement in abiotic stress responses, with some phytohormones, such as ethylene, abscisic acid, jasmonate, or salicylate, showing a high degree of specialization in abiotic stress responses. In parallel, and to a certain extent as a consequence of phytohormone signaling discoveries, major breakthroughs have been achieved in the field of abiotic stress sensing and signaling in plants. Sensors of hypoxic, hyperosmotic, or UV radiation stressors have been discovered. Calcium dynamics, phospholipid dynamics, reactive oxygen species dynamics, phosphorylation cascades, and transcriptional regulations have been analyzed in detail. In parallel, given the involvement of plant hormones in the regulation, modulation, and integration of abiotic stress responses, the characterization of abiotic stress sensing and signaling mechanisms necessarily leads to the characterization of the connections between upstream abiotic stress sensing and signaling and downstream stress-related phytohormone sensing and signaling.

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Preface

As occurred in the molecular studies of other fields of plant science, such as those dealing with vegetative and reproductive developmental processes, progress in the field of abiotic stress sensing and signaling has been greatly facilitated by the development of plant genetics and the diverse array of omics technologies. However, numerous sensing and signaling mechanisms related to abiotic stress situations remain unknown and a great number of potential stress cue sensors remain to be identified or fully characterized. Moreover, given the variety of potential physico-chemical stress cues, whether direct or indirect, given the diversity of potential targets in the plant cell, given the complex effects of stress intensity or variability, and, above all, of stress combinations, such as heat and drought, flooding and salinity, or soil pollution and heat, the ranges of adaptive functioning of known stress signaling pathways remain to be fully investigated. All of this expected and urgently needed progress clearly depends on the relevance of the current methodology and on the development of further methodology, including novel methods that may be better suited for the complexity of abiotic stress signaling in plants. The complexities, the discoveries, and the breakthroughs in the scientific field of abiotic stress sensing and signaling in plants have been addressed in a series of recent reviews either giving a synthetic view of mechanisms or focusing on a specific pathway or a specific group of plants. In line with this timely interest in plant abiotic stress signaling, the contributors of the present book bring together conceptual strategies and methodological know-how over a wide range of examples that take into account the diversity of plant models and the diversity of mechanisms that can be used as a stepping stone to unravel the intricacies of signaling networks. The different contributions mainly focus on upstream mechanisms that interact with abiotic stress stimuli. Interface and crosstalk mechanisms between abiotic stress signaling and hormone signaling or between abiotic stress signaling and developmental signaling would require sui generis developments that are beyond the scope of this book. Such issues are usually addressed in generic books on plant hormones and in specific books on auxins and cytokinins, abscisic acid, brassinosteroids, ethylene signaling, or jasmonate signaling. Moreover, the diversity of plant species and the whole range of stress situations are also beyond the scope of a single book. It is therefore important to emphasize that the understanding of abiotic stress sensing and signaling mechanisms requires a strong integration of methods and concepts and of protocols and interpretative outlooks. This book aims to provide both experienced and new researchers with an overview of achievements and challenges, and a significant set of up-to-date methods, strategies, and outlooks covering the identification of novel processes, validation of hypothetical mechanisms, and further characterization of currently known pathways, in relation with a selection of emblematic case studies. The first section is thus dealing with general topics of questions and approaches in the field of plant abiotic stress signaling. The following section addresses the characterization of abiotic stress signals, from targeted single-signal studies to large-scale analysis (signalomics), in the context of environmental stimuli and in the context of cellular signaling. The third section deals with the identification and characterization of abiotic stress signaling processes. The final section takes into account the tissue-specific, systemic and ecosystemic dimensions of abiotic stress signaling and points out to future directions in plant abiotic stress signaling research. The study of plant abiotic stress signaling deals with fundamental molecular mechanisms that also bear on several areas of application, such as the interactions of abiotic stress and biotic stress signaling in the context of plant pathology, the functional ecology of plant communities and ecosystems, the agronomy of cultivated plants, the improvement of crop management and breeding under the constraints of climate change and human

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demographics, and the predictive science of plant biodiversity dynamics under the evolving conditions of climate change. The importance of these issues will be frequently mentioned in the course of the different chapters, but the methodological analysis of such broad-scale issues remains beyond the scope of the present book. I wish to thank Prof. John Walker, chief editor of the series, as well as Anna Rakovsky, David Casey, and Patrick Marton at Springer Nature Group, for giving us the opportunity, and all the friendly and professional help and encouragement, to share our ideas and methods with a large community of experienced researchers, students, young researchers, and new researchers in this field, and with the larger community of science-conscious citizens of the world. I would also like to emphasize that such a book on the universal issue of plant-stress interactions is bound to be the result of worldwide collaborative work. I therefore wish to thank very warmly all of the contributors for their steadfast involvement, their enduring patience, and their inspiring willingness to adapt their work, their methods, their thoughts, and their perspectives to the format and synergy of a collective book. Finally, I would like to thank Carine Alcon and Tou Cheu Xiong for suggesting and providing the integrative cover illustration. Rennes, France

Ivan Coue´e

Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

QUESTIONS AND APPROACHES

1 Interplay of Methodology and Conceptualization in Plant Abiotic Stress Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ivan Coue´e 2 Complexity of Abiotic Stress Stimuli: Mimicking Hypoxic Conditions Experimentally on the Basis of Naturally Occurring Environments . . . . . . . . . . . . Ailbhe Jane Brazel and Emmanuelle Graciet 3 Iron Availability and Homeostasis in Plants: A Review of Responses, Adaptive Mechanisms, and Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nolenn Kermeur, Mathieu Pe´drot, and Francisco Cabello-Hurtado

PART II

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SIGNALS AND SIGNALOMICS

4 Calcium Live Imaging at Multi-Scales from Cellular to Organ Level in Arabidopsis thaliana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carine Alcon and Tou Cheu Xiong 5 Functions of NO and H2S Signal Molecules Against Plant Abiotic Stress . . . . . . Francisco J. Corpas and Jose´ M. Palma 6 Review of Lipid Biomarkers and Signals of Photooxidative Stress in Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michel Havaux 7 The Plant Metabolic Changes and the Physiological and Signaling Functions in the Responses to Abiotic Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Feng Zhu, Yuming Sun, Sagar Sudam Jadhav, Yunjiang Cheng, Saleh Alseekh, and Alisdair R. Fernie 15 8 N-labelling of Leaves Combined with GC-MS Analysis as a Tool for Monitoring the Dynamics of Nitrogen Incorporation into Amino Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anis M. Limami, Caroline Cukier, and Bertrand Hirel 9 Computational Metabolomics to Elucidate Molecular Signaling and Regulatory Mechanisms Associated with Biostimulant-Mediated Growth Promotion and Abiotic Stress Tolerance in Crop Plants . . . . . . . . . . . . . . Kgalaletso Othibeng, Lerato Nephali, and Fidele Tugizimana 10 Electrical Signaling and Its Functions Under Conditions of Abiotic Stress: A Review of Methodological Approaches and Physiological Implications . . . . . . Jo¨rg Fromm and Silke Lautner

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PART III 11

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Quantitative Measurements of Biochemical and Molecular Markers of Oxidative Stress Signaling and Responses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Graham Noctor, Mathias Cohen, Lug Tre´mulot, Frank Van Breusegem, and Amna Mhamdi Fast Identification of In Vivo Protein Phosphorylation Events Using Transient Expression in Leaf Mesophyll Protoplasts and Phos-tagTM SDS-PAGE . . . . . . . . Ellen Broucke, Filip Rolland, and Nathalie Crepin Analysis of Plant L-Cysteine Desulfhydrase (LCD) Isozymes by Non-denaturing Polyacrylamide Gel Electrophoresis . . . . . . . . . . . . . . . . . . . . . ˜ oz-Vargas, Marta Rodrı´guez-Ruiz, Marı´a A. Mun Salvador Gonza´lez-Gordo, Jose´ M. Palma, and Francisco J. Corpas Metabolite-Based Genome-Wide Association Studies of Large-Scale Metabolome Analysis to Illustrate Alterations in the Metabolite Landscape of Plants upon Responses to Stresses . . . . . . . . . . . . . . . . . . . . . . . . . . . . Feng Zhu, Mustafa Bulut, Yunjiang Cheng, Saleh Alseekh, and Alisdair R. Fernie Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gwenola Gouesbet Multi-omics Data Integration in the Context of Plant Abiotic Stress Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Harold Durufle´ and Se´bastien De´jean Protein–Protein Interactions in Abiotic Stress Signaling: An Overview of Biochemical and Biophysical Methods of Characterization. . . . . . . . . . . . . . . . . Ivan Coue´e and Gwenola Gouesbet Beyond the Primary Structure of Nucleic Acids: Potential Roles of Epigenetics and Noncanonical Structures in the Regulations of Plant Growth and Stress Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adriana Volna´, Martin Bartas, Jakub Nezval, Radomı´r Pech, ˇ ervenˇ Petr Pecˇinka, Vladimı´r Sˇpunda, and Jirˇı´ C

PART IV 19

SIGNALING PROCESSES 197

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SYSTEMIC AND ECOSYSTEMIC SIGNALING

Laser Microdissection: A High-Precision Approach to Isolate Specific Cell Types from Any Plant Species for Downstream Molecular Analyses . . . . . . . . . . . 365 Francisco R. Tadeo, Javier Agustı´, Paz Merelo, and Manuel Tal
on 20 An Experimental Rhizobox System for the Integrative Analysis of Root Development and Abiotic Stress Responses Under WaterDeficit Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Mickae¨l Durand, Ame´lie Morin, Benoıˆt Porcheron, and Nathalie Pourtau

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Live Whole-Plant Detection of Rapidly Accumulating Reactive Oxygen Species Following Applied Stress in Arabidopsis thaliana . . . . . . . . . . . . . . . . . . . . 387 Ronald J. Myers Jr., Sara I. Zandalinas, and Ron Mittler 22 Analysis of Small Non-coding RNAs as Signaling Intermediates of Environmentally Integrated Responses to Abiotic Stress. . . . . . . . . . . . . . . . . . . 403 Christophe Penno, Julien Tremblay, Mary O’Connell Motherway, Virginie Daburon, and Abdelhak El Amrani 23 Perspectives in Plant Abiotic Stress Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 Ivan Coue´e Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors JAVIER AGUSTI´ • Centro de Gen
omica, Instituto Valenciano de Investigaciones Agrarias, Moncada, Valencia, Spain; Instituto de Biologı´a Molecular y Celular de Plantas, Universidad Polite´cnica de Valencia-Consejo Superior de Investigaciones Cientı´ficas, Valencia, Spain CARINE ALCON • IPSiM, Universite´ de Montpellier, CNRS, INRAE, Montpellier, France SALEH ALSEEKH • Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany; Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria MARTIN BARTAS • Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czech Republic AILBHE JANE BRAZEL • Department of Biology, Maynooth University, Maynooth, Ireland ELLEN BROUCKE • Plant Metabolic Signaling Lab, Biology Department, KU Leuven, Heverlee, Leuven, Belgium; KU Leuven Plant Institute (LPI), KU Leuven, Heverlee, Leuven, Belgium MUSTAFA BULUT • Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany FRANCISCO CABELLO-HURTADO • University of Rennes, CNRS, Ecobio, UMR 6553, Rennes, France ˇ ERVENˇ • Department of Biology and Ecology, Faculty of Science, University of Ostrava, JIRˇI´ C Ostrava, Czech Republic YUNJIANG CHENG • National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, China MATHIAS COHEN • Universite´ Paris-Saclay, CNRS, INRAE, Universite´ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France; Universite´ Paris Cite´, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France; Department of Plant Biotechnology and Bioinformatics, VIB, 9052 Ghent, Belgium, Ghent, Belgium; VIB Center of Plant Systems Biology, 9052 Ghent, Belgium, Ghent, Belgium FRANCISCO J. CORPAS • Group of Antioxidants, Free Radicals and Nitric Oxide in Biotechnology, Food and Agriculture. Department of Stress, Development and Signaling in Plants. Estaci
on Experimental del Zaidı´n, Spanish National Research Council (CSIC), Granada, Spain IVAN COUE´E • UMR 6553 ECOBIO (Ecosystems-Biodiversity-Evolution), Centre National de la Recherche Scientifique (CNRS), University of Rennes, Rennes, France; Universite´ de Rennes, CNRS, UMR 6553 ECOBIO (Ecosystems-Biodiversity-Evolution), Rennes, France NATHALIE CREPIN • Plant Metabolic Signaling Lab, Biology Department, KU Leuven, Heverlee, Leuven, Belgium; KU Leuven Plant Institute (LPI), KU Leuven, Heverlee, Leuven, Belgium CAROLINE CUKIER • Univ Angers, INRAE, IRHS, SFR QUASAV, Angers, France VIRGINIE DABURON • ECOBIO, CNRS UMR 6553, Universite´ de Rennes, Campus Beaulieu, Rennes, France SE´BASTIEN DE´JEAN • Institut de Mathe´matiques de Toulouse, Universite´ de Toulouse, CNRS, UPS, UMR 5219, Toulouse, France

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Contributors

´ MICKAE¨L DURAND • Ecologie et Biologie des Interactions (EBI), Universite´ de Poitiers, CNRS, EBI, Poitiers, France; EA2106 “Biomole´cules et Biotechnologies Ve´ge´tales”, Universite´ de Tours, Tours, France HAROLD DURUFLE´ • INRAE, ONF, BioForA, UMR 0588, Orle´ans, France ABDELHAK EL AMRANI • ECOBIO, CNRS UMR 6553, Universite´ de Rennes, Campus Beaulieu, Rennes, France ALISDAIR R. FERNIE • Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany; Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria JO¨RG FROMM • Wood Biology, Institute for Wood Science, Universit€ a t Hamburg, Hamburg, Germany SALVADOR GONZA´LEZ-GORDO • Group of Antioxidants, Free Radicals and Nitric Oxide in Biotechnology, Food and Agriculture. Department of Stress, Development and Signaling in Plants. Estaci
on Experimental del Zaidı´n, Spanish National Research Council (CSIC), Granada, Spain GWENOLA GOUESBET • University of Rennes, CNRS, ECOBIO [(Ecosyste`mes, Biodiversite´, Evolution)] – UMR 6553, Rennes, France; UMR 6553 ECOBIO (Ecosystems-BiodiversityEvolution), CNRS, Universite´ de Rennes, Brittany, France EMMANUELLE GRACIET • Department of Biology, Maynooth University, Maynooth, Ireland MICHEL HAVAUX • Aix-Marseille University, CEA, CNRS, UMR7265, Bioscience and Biotechnology Institute of Aix-Marseille, CEA/Cadarache, Saint-Paul-lez-Durance, France BERTRAND HIREL • INRAE, Institut Jean-Pierre Bourgin, Agro-ParisTech, Universite´ ParisSaclay, Paris, France SAGAR SUDAM JADHAV • Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany NOLENN KERMEUR • University of Rennes, CNRS, Ecobio, UMR 6553, Rennes, France; University of Rennes, CNRS, Ge´osciences Rennes, UMR 6118, Rennes, France SILKE LAUTNER • Applied Wood Biology, Eberswalde University for Sustainable Development, Eberswalde, Germany ANIS M. LIMAMI • Univ Angers, INRAE, IRHS, SFR QUASAV, Angers, France PAZ MERELO • Centro de Gen
omica, Instituto Valenciano de Investigaciones Agrarias, Moncada, Valencia, Spain; Instituto de Biologı´a Molecular y Celular de Plantas, Universidad Polite´cnica de Valencia-Consejo Superior de Investigaciones Cientı´ficas, Valencia, Spain AMNA MHAMDI • Department of Plant Biotechnology and Bioinformatics, VIB, 9052 Ghent, Belgium, Ghent, Belgium; VIB Center of Plant Systems Biology, 9052 Ghent, Belgium, Ghent, Belgium RON MITTLER • Division of Plant Sciences and Technology, College of Agriculture Food and Natural Resources and Interdisciplinary Plant Group, University of Missouri, Columbia, MO, USA AME´LIE MORIN • E´cologie et Biologie des Interactions (EBI), Universite´ de Poitiers, CNRS, EBI, Poitiers, France MARI´A A. MUN˜OZ-VARGAS • Group of Antioxidants, Free Radicals and Nitric Oxide in Biotechnology, Food and Agriculture. Department of Stress, Development and Signaling in Plants. Estaci
on Experimental del Zaidı´n, Spanish National Research Council (CSIC), Granada, Spain

Contributors

xv

RONALD J. MYERS JR. • Division of Plant Sciences and Technology, College of Agriculture Food and Natural Resources and Interdisciplinary Plant Group, University of Missouri, Columbia, MO, USA LERATO NEPHALI • Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa JAKUB NEZVAL • Department of Physics, Faculty of Science, University of Ostrava, Ostrava, Czech Republic GRAHAM NOCTOR • Universite´ Paris-Saclay, CNRS, INRAE, Universite´ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France; Universite´ Paris Cite´, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France; Institut Universitaire de France (IUF), Paris, France MARY O’CONNELL MOTHERWAY • APC Microbiome Ireland, University College Cork, Cork, Ireland KGALALETSO OTHIBENG • Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa JOSE´ M. PALMA • Group of Antioxidants, Free Radicals and Nitric Oxide in Biotechnology, Food and Agriculture. Department of Stress, Development and Signaling in Plants. Estaci
on Experimental del Zaidı´n, Spanish National Research Council (CSIC), Granada, Spain RADOMI´R PECH • Department of Physics, Faculty of Science, University of Ostrava, Ostrava, Czech Republic PETR PECˇINKA • Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czech Republic MATHIEU PE´DROT • University of Rennes, CNRS, Ge´osciences Rennes, UMR 6118, Rennes, France CHRISTOPHE PENNO • ECOBIO, CNRS UMR 6553, Universite´ de Rennes, Campus Beaulieu, Rennes, France BENOIˆT PORCHERON • E´cologie et Biologie des Interactions (EBI), Universite´ de Poitiers, CNRS, EBI, Poitiers, France NATHALIE POURTAU • E´cologie et Biologie des Interactions (EBI), Universite´ de Poitiers, CNRS, EBI, Poitiers, France MARTA RODRI´GUEZ-RUIZ • Group of Antioxidants, Free Radicals and Nitric Oxide in Biotechnology, Food and Agriculture. Department of Stress, Development and Signaling in Plants. Estaci
on Experimental del Zaidı´n, Spanish National Research Council (CSIC), Granada, Spain FILIP ROLLAND • Plant Metabolic Signaling Lab, Biology Department, KU Leuven, Heverlee, Leuven, Belgium; KU Leuven Plant Institute (LPI), KU Leuven, Heverlee, Leuven, Belgium VLADIMI´R SˇPUNDA • Department of Physics, Faculty of Science, University of Ostrava, Ostrava, Czech Republic; Global Change Research Institute, Czech Academy of Sciences, Brno, Czech Republic YUMING SUN • Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany; Jiangsu Key Laboratory for the Research and Utilization of Plant Resources, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, China FRANCISCO R. TADEO • Centro de Gen
omica, Instituto Valenciano de Investigaciones Agrarias, Moncada, Valencia, Spain MANUEL TALO´N • Centro de Gen
omica, Instituto Valenciano de Investigaciones Agrarias, Moncada, Valencia, Spain

xvi

Contributors

JULIEN TREMBLAY • Energy, Mining and Environment, National Research Council Canada, Montre´al, QC, Canada; Institut National de la Recherche Scientifique, Centre ArmandFrappier Sante´ Biotechnologie, Laval, QC, Canada LUG TRE´MULOT • Universite´ Paris-Saclay, CNRS, INRAE, Universite´ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France; Universite´ Paris Cite´, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France FIDELE TUGIZIMANA • Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa; International Research and Development Division, Omnia Group, Ltd., Johannesburg, South Africa FRANK VAN BREUSEGEM • Department of Plant Biotechnology and Bioinformatics, VIB, 9052 Ghent, Belgium, Ghent, Belgium; VIB Center of Plant Systems Biology, 9052 Ghent, Belgium, Ghent, Belgium ADRIANA VOLNA´ • Department of Physics, Faculty of Science, University of Ostrava, Ostrava, Czech Republic TOU CHEU XIONG • IPSiM, Universite´ de Montpellier, CNRS, INRAE, Montpellier, France SARA I. ZANDALINAS • Department of Biology, Biochemistry and Environmental Sciences, University Jaume I, Castell
o de la Plana, Spain FENG ZHU • National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, China; Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany

Part I Questions and Approaches

Chapter 1 Interplay of Methodology and Conceptualization in Plant Abiotic Stress Signaling Ivan Coue´e Abstract Characterizing the mechanisms of plant sensitivity and reactivity to physicochemical cues related to abiotic stresses is of utmost importance for understanding plant-environment interactions, adaptations of the sessile lifestyle, and the evolutionary dynamics of plant species and populations. Moreover, plant communities are confronted with an environmental context of global change, involving climate changes, planetary pollutions of soils, waters and atmosphere, and additional anthropogenic changes. The mechanisms through which plants perceive abiotic stress stimuli and transduce stress perception into physiological responses constitute the primary line of interaction between the plant and the environment, and therefore between the plant and global changes. Understanding how plants perceive complex combinations of abiotic stress signals and transduce the resulting information into coordinated responses of abiotic stress tolerance is therefore essential for devising genetic, agricultural, and agroecological strategies that can ensure climate change resilience, global food security, and environmental protection. Discovery and characterization of sensing and signaling mechanisms of plant cells are usually carried out within the general framework of eukaryotic sensing and signal transduction. However, further progress depends on a close relationship between the conceptualization of sensing and signaling processes with adequate methodologies and techniques that encompass biochemical and biophysical approaches, cell biology, molecular biology, and genetics. The integration of subcellular and cellular analyses as well as the integration of in vitro and in vivo analyses are particularly important to evaluate the efficiency of sensing and signaling mechanisms in planta. Major progress has been made in the last 10–20 years with the caveat that cell-specific processes and in vivo processes still remain difficult to analyze and with the additional caveat that the range of plant models under study remains rather limited relatively to plant biodiversity and to the diversity of stress situations. Key words Climate change, Drought, Extreme temperatures, Food security, Multiple stress, Oxidative stress, Stress responses, Signal transduction, Stress sensors

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Introduction In the context of the sessile lifestyle, evolutionary constraints have led plants to connect their development, growth, and physiology with a myriad of environmental factors, whether biotic or abiotic [1, 2]. The fluctuating nature of these environmental factors entails

Ivan Coue´e (ed.), Plant Abiotic Stress Signaling, Methods in Molecular Biology, vol. 2642, https://doi.org/10.1007/978-1-0716-3044-0_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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STRESS SIGNALS Flooding, hypoxia, anoxia Unfolded Protein stress

Surveillance stress

Threats and dangers

NON-STRESS SIGNALS Circadian clock

RNS

ROS

RES

ER stress

Sugars

pH

Development

Root-derived peptides

Regulators

Photoperiod alteration stress

Phytohormones

Cold, chilling, freezing

Starch

Nutrition

Ions

Photooxidative stress Soil degradation

Light

SIGNALING PROCESSES IN THE PLANT CELL

Starvation

Amino-acids

Growth

Environmental factors and fluctuations Photoreceptors Atmospheric oxygen Atmospheric CO2

Biotic interactions

Long-distance systemic signals

UV light

Mechanical stress

Acidity, alcalinity

Soil resources

Temperature Herbivory

Climate change

Abiotic stressors Heat, drought, salinity, hyperosmotic stress Endogenous stressors Biotic stressors Xenobiotic stresses

Heavy metals Wounding Pollution

Fig. 1 Diversity of environmental and abiotic stress cues potentially interacting with plant cell signaling. ER endoplasmic reticulum, RES reactive electrophilic species, RNS reactive nitrogen species, ROS reactive oxygen species

that plants must be able in a permanent way to sense such fluctuations and adjust the whole of their functioning to the information they perceive [3–6]. When these fluctuations consist of adverse environmental abiotic stresses, such as drought, heat, or cold, that may lead to severe perturbation or death, precise and correct sensing and efficient conversion of information into adaptive responses are essential mechanisms for the maintenance of plant vigor and growth at the different levels of integration (cell, tissue, organ, organism, population, community) [1, 2]. Sensing and signaling of abiotic stressors, with their great diversity of cues, whether exogenous or endogenous, function in parallel with or are superimposed on the complex system of fluctuation sensing and signaling that operates under non-stress conditions (Fig. 1). Abiotic stressors can act as single stressors or single cues [7, 8]. However, single stressors naturally occur under a range of stress intensities, dose-effect relationships, and time courses resulting in mild or acute stresses and in intermittent or chronic stresses [5, 7–9]. Moreover, natural conditions of abiotic stress usually occur as multifactorial combinations, where plant cells are confronted with multiple concomitant cues [10–16], thus implying that concomitant processes of sensing and signaling are activated and must be operated in an integrative and efficient manner.

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The Eukaryotic Stress Signaling Framework The range of abiotic stressors inducing plastic responses in plants is very wide, with a very rich corpus of scientific literature covering a myriad of stress-related keywords as exemplified in Fig. 1 [1–3]. These abiotic stress situations are correlated with or generate a variety of external or internal physicochemical cues, such as fluctuations of mineral ions, changes of conformational dynamics of macromolecules and supramolecular assemblages, changes of chromatin dynamics, reactive oxygen species (ROS), reactive carbonyl species (RCS), reactive nitrogen species (RNS), reactive electrophilic species (RES), carbon monoxide (CO), hydrogen sulfide (H2S), unfolded proteins, oxidized proteins, lipid peroxides, pH, photons, metabolites, or degradation products [1, 2, 17, 18]. This myriad of physicochemical cues can interact, in parallel or in a successive manner, with numerous cellular entities which are distributed across the various cellular compartments (cell wall, plasma membrane, cytosol, chloroplast, mitochondrion, peroxisome, endoplasmic reticulum, nucleus) [1, 2, 19, 20]. However, despite this diversity, most mechanisms of abiotic stress signaling follow simple rules and basic principles which can be described in terms of information science and systems science that may apply to all types of prokaryotic or eukaryotic cells. Stress responses can be analyzed as the modular integration of sensors (such as environmental sensors, ligand-binding entities, and signal transduction processes), regulators (such as transcription factors and phosphorelay enzymes), actuators (such as enzymes and structural proteins that actuate or realize stress responses), and crosstalk entities (global and master regulators that participate in two or more networks) [21]. De Nadal et al. [9] describe the eukaryotic stress signaling framework as a succession of sensing/signal-transduction/effector processes. Finally, in the specific context of plant cell responses to abiotic stresses, Zhu [2] emphasizes the involvement of perturbations/organelle-signaling/integration/regulation cascades, which can also be described as cascades of sensing/ signaling-events/second-messengers/regulatory-entities/ induced-changes [1]. In the context of plant synthetic biology and engineering, Leydon et al. [22] decompose the biological parts of signaling mechanisms as sensing modules, signal processing modules, and output modules. Most studies of abiotic stress signaling (Fig. 2) [1, 2, 9, 23–30] are therefore carried out within the general framework described in Fig. 3. Understanding the adaptive plasticity and acclimation of plants to stressful conditions thus usually requires integrative studies from stress cues to adaptive responses. The field of plant abiotic stress signaling studies is therefore circumscribed by the relative emphasis on upstream versus downstream processes (Fig. 3).

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Ivan Coue´e Screening of stress oversensitive mutant lines in a genetic and genomic plant model

Transcriptomic identification of stress oversensitive mutant lines showing deregulation of expression of stress response gene network

Potential identification of mutant lines affected in a master gene controlling upstream regulation of a stress response network

Cartography of the mutation (genetic mapping, T-DNA tag identification, transposon tag identification)

Structural characterization of the corresponding wild-type genetic locus and gene

Verification of causal gene-phenotype relationship: rescue of mutated phenotype through complementation with wild-type gene

Determination of cellular localization of wild-type protein with Green Fluorescent Protein (GFP)-Protein fusions

Biochemical assays of recombinant protein

Biophysical analyses of recombinant protein (X-ray crystallography and spectroscopies)

Biophysical analyses of recombinant protein-signal interactions

Fig. 2 General scheme of mutant studies workflow leading to characterization of abiotic stress sensors. Such typical workflows that combine mutant identification and molecular biology can be exemplified by the references given in Table 1

On the other hand, the emphasis on cues and signals connects stress signaling studies with information science, computer science, cybernetics, and linguistics [26, 29, 31]. This has led to reliance on numerous terms and concepts from these related fields, such as input, output, messenger, signal shape, signal gating, oscillation, wave, crosstalk, nexus, network, node, or hub [29, 32–35]. This kind of conceptualization is however bound to evolve with the ongoing understanding of novel mechanisms and the mathematic modelling of signaling networks [32].

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Abiotic stress-related cue

Perception and sensing (such as membrane receptors, internal receptors, biochemical and biophysical modifications)

Cellular signal transduction (such as second messengers, protein-kinases, proteinphosphatases, calcium channels)

Protein posttranslational modifications (such as phosphorylations, glycosylations, proteolysis )

Gene expression regulations (such as transcription factors, ribosomes, miRNA, siRNA, chromatin dynamics)

Biochemical and physiological adjustments (such as expression of stress proteins, accumulation of stress metabolites, induction of mechanisms for defence, protection and repair)

Fig. 3 General scheme of abiotic stress sensing and signaling. miRNA: microRNA; siRNA: short-interfering RNA

3

Plant Models for Abiotic Stress Signaling Studies As shown in Table 1, core mechanisms of abiotic stress signaling have been identified and characterized in a very limited number of plant models, primarily in Arabidopsis thaliana, but also in rice (Oryza sativa). The preeminence of Arabidopsis is directly linked to its status as a direct genetics, reverse genetics, and molecular biology model that encompasses all of the genes that are necessary to construct a complete plant in interaction with the environment and its abiotic stressors [1, 2, 12]. The characterization of the interactions and combinations between different abiotic stress signaling pathways is one of the clear-cut advantages of such in-depth analysis of Arabidopsis [11–13, 16, 36–39]. In parallel, rice has also become a major model for the discovery of abiotic stress sensing and signaling mechanisms [33, 40–44], whose characterization can readily be applied to the genetic improvement of rice cultivation and agriculture [45].

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Table 1 Major plant models of abiotic stress signaling discoveries (abbreviations are as described in the text) Abiotic stress

Signaling mechanism

Plant species

References

Chilling

COLD1 regulator

Rice

[88]

2+

Chilling

Ca -dependent protein kinases

Rice

[40]

Drought

G protein Gα subunit

Rice

[44]

+

Electrical

H -ATPase

Arabidopsis

[90]

Energy

SnRK1 integrator

Arabidopsis

[86]

Flooding

N-end rule pathway

Arabidopsis

[42, 73]

Heat

Cyclic nucleotide-gated channels

Arabidopsis

[41]

Heat

Cyclic nucleotide-gated channels

Physcomitrium

[91]

Hyperosmotic

OSCA1 homolog osmosensor

Rice

[33]

Arabidopsis

[89]

2+

Multiple

ROS and Ca

1

Carotenoid oxidation derivatives

Arabidopsis

[27]

Oxidative

Cys-rich receptor-like kinases

Arabidopsis

[23]

Oxidative

HPCA1 H2O2 sensor

Arabidopsis

[80]

Salinity

SOS pathway

Arabidopsis

[83]

Salinity

FERONIA receptor kinase

Arabidopsis

[79]

Salinity

GIPC sphingolipids

Arabidopsis

[84]

Temperature

Phytochrome thermosensors

Arabidopsis

[78]

UV radiation

UVR8 UV-B receptor

Arabidopsis

[76]

O2

waves

This Arabidopsis- and rice-based knowledge generally provides the necessary basis to analyze and interpret sensing and signaling information in other plant species [1, 2, 4, 46]. It is however essential, for agronomical, agroecological, and ecological reasons, to obtain a direct understanding of abiotic stress sensing and signaling mechanisms in cultivated crops [3, 43, 46] and in natural plant communities [3, 4, 47]. For example, in the cases of natural extremophile plants (Table 2) [48–54], of wild or cultivated tree species (Table 3) [48, 55–62], or of major cereal or pseudocereal crops other than rice (Table 4) [46, 63–70], some relationships between adaptive biochemical or physiological responses and signaling processes have been characterized or hypothesized. On the one hand, general schemes of abiotic stress signaling and responses in non-model plant species can be construed from this current knowledge, as exemplified in the case of extremophile plants (Fig. 4). On the other hand, this knowledge remains fragmentary, partial, biased, or overspecialized, whether in

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Table 2 Integration of biochemical responses and signaling processes in extremophile plants (abbreviations are as described in the text) Extreme habitat

Species

Biochemical or physiological response Signaling-related process

Deserts

Phoenix dactylifera

Deserts

Atacama Metabolic adjustments desert plant community

Stomatal closure

References

Nitrate regulation of fast ABA [51] signaling Carotenoid and ROS signaling [49]

Mangroves Heritiera littoralis

Salt exclusion

Mountains Chorispora bungeana

Increase of unsaturated fatty Upregulation of genes related [54] acids in plasma membranes to protein phosphorylation and auto-ubiquitination

Polar and Deschampsia subpolar antarctica

Induction of genes encoding dehydrin and ice recrystallization inhibition protein

Underrepresentation of [48] “response to stress” and “response to stimuli” genes

Induction of genes encoding F-box proteins

Polar and Pohlia nutans Increased flavonoid contents, Induction of ABA- and JAsubpolar antioxidant levels, and pathway-related genes enzyme activities Saline lands and shores

Salicornia europaea

NaCl-facilitated increase of nitrate uptake

[50]

[53]

Involvement of cytosolic Ca2+ [52] and Ca2+ channel activity

extremophile plants (Table 2), in wild or cultivated tree species (Table 3), or in major cereal or pseudocereal crops other than rice (Table 4), thus emphasizing the need to develop wide-ranging projects on a greater variety of plant species. Moreover, as argued by Voesenek et al. [47], original and cryptic mechanisms of abiotic stress sensing and signaling are likely to be found in other plant species than rice and Arabidopsis. Mining the biodiversity of plants is therefore a priority, not only for metabolism and pharmacological exploitation [71, 72] but also for mechanistic studies of signaling and regulatory pathways [47].

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Table 3 Integration of biochemical responses and signaling processes in wild and cultivated tree species (abbreviations are as described in the text) Biochemical or physiological response

Tree species

Signaling-related process

References

Asian white birch

Betula Regulation of stomatal Hierarchical network of ethyleneplatyphylla closure response factor, agamous-like (AGL), and NAC (NAM-ATAFCUC) transcription factors

[58]

Cork oak

Quercus suber

Drought-induced accumulation of compatible solutes

Activation of SnRK2 (Snf1-related protein kinase 2) ABA-signaling network

[60]

Desert poplar

Populus Na+/K+ homeostasis euphratica

Involvement of calcineurin b-like (CBL) calcium sensor and CBL-interacting protein kinases (CIPKs)

[62]

Salt exclusion

Underrepresentation of “response to stress” and “response to stimuli” gene categories

[48]

Temperaturedependent epigenetic memory

Altered transcript abundance of [55] miRNAs and miRNA pathway genes

Mangrove Heritiera tree littoralis Norway spruce

Picea abies

Pear tree

Pyrus Drought tolerance betulifolia

Poplar

Populus tremula

Thigmomorphogenesis Differential expression of genes encoding mechanosensitive channels

Walnut

Juglans regia

Expression of Heat Shock Proteins (HSPs)

Induction of long-distance phloemmediated mobile mRNA signals

[56] [57]

Involvement of GRAS family and Dof [61] family transcription factors

4 The Discovery of Abiotic Stress Sensors and Abiotic Signaling Networks in Plant Cells In a review on the abiotic stress responses of rice, Gao et al. [41] stated that “to date, most of the stress sensors remain unidentified.” After 15 years of further research, the general review on plant abiotic stress responses by Zhang et al. [1] concludes on a note of cautious progress: “there are likely many stress sensors yet to be identified, and most of those that have been reported can only be considered putative sensors.” Indeed, stricto sensu sensing mechanisms, as primary processes of interaction between an abiotic

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Table 4 Integration of biochemical responses and signaling processes in major cereal and pseudocereal crops other than rice (abbreviations are as described in the text) Biochemical or physiological response

Signaling-related process

References

ROS and RNS dynamics under cadmium stress

Strigolactone pathway

[68]

Tartary Fagopyrum N transport adjustment to low buckwheat esculentum nitrogen stress

Small secreted peptide regulation

[66]

NO signaling pathway

[67]

ABA accumulation under high salt Involvement of MYB family transcription factors

[69]

Crop species Barley

Maize

Hordeum vulgare

Zea mays

Foxtail millet Setaria italica

Drought-induced increase of proline levels

Oat

Avena sativa Increased levels of ROS-scavenging enzyme activities at high altitude

Auxin, Gibberellin, and [64] JA signaling pathways

Rye

Secale cereale Aluminum-induced increase of proline levels

N-status signaling

[63]

Sorghum

Sorghum bicolor

Hypersensitivity to ABA under heat stress

Ubiquitination regulation

[65]

Wheat

Triticum aestivum

Enhancement of osmotic adjustment in leaves

ABA signaling pathway

[70]

stress physicochemical cue and a cellular entity, can involve extremely elusive events, such as biochemical, biophysical, phasetransition, conformational, or micromorphological changes affecting microdomains, membranes, proteins, nucleic acids, electron fluxes, or reaction velocities. Nevertheless, in spite of all these difficulties, major actors of plant abiotic stress sensing have been discovered and characterized, such as the group VII ethylene response factors (ERF-VII) [42, 73] and plant cysteine oxidases (PCO) [74] involved as sensors of oxygen levels, the UV-B receptor UVR8 [75–77], the hyperosmolarity-gated calcium channelreduced hyperosmolality-induced [Ca(2+)]i increase 1 (OSCA1) osmosensor [33], phytochrome thermosensors [78], the receptor kinase salinity damage sensor FERONIA [79], and the LeucinRich-Repeat receptor kinase H2O2 sensor hydrogen-peroxideinduced Ca2+ increase 1 (HPCA1) [80]. Moreover, the biophysical dynamics of prion-like domains [81] and prion-like proteins [82] have been shown to be respectively involved in thermosensing and in water stress sensing.

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Extreme environment abiotic stress stimuli

Cell functioning surveillance Carotenoid signalling

Epigenetic regulations

ABA signalling

SOS signalling Catalases

Phospholipid signalling

Ca2+ signalling

ROS signalling

RBOHD

RCS

SnRK1

Proteolysis signalling NDPK2

MAPK cascade

Extremophile adaptive responses

Fig. 4 Abiotic stress signaling in non-model plant species: current state of knowledge of stress signaling loops and interactions associated with plant extremophile adaptations. (Reproduced with modifications from Boulc’h et al. [4] with permission from Oxford University Press). Interactions between exogenous and endogenous stress perturbations (in red), downstream cellular signaling (in green), and transduction into stress responses (in blue) are shown. MAPK mitogen-activated protein kinase, NDPK2 nucleoside-diphosphate kinase 2, RBOHD respiratory burst NADPH oxidase homologue D, RCS reactive carbonyl species, ROS reactive oxygen species, SnRK1 Snf1-related protein kinase 1, SOS salt overly sensitive

Mutant identification and analysis, especially in Arabidopsis and in rice, have played a major role in characterizing the molecular mechanisms of developmental and hormonal regulations in plants. The use of relevant criteria, such as stress oversensitive phenotypes [83], disruption of stress-induced biochemical response [84], or disruption of stress-induced gene expression [85], has led to the successful isolation of abiotic stress signaling mutants. This has been a method of choice for the discovery of stress sensors (Fig. 2), with the subsequent in vitro or in vivo biochemical characterization of sensor proteins (Fig. 2), including heterologous expression using animal cell lines [80] or X-ray crystallographic analysis [76]. The identification and characterization of secondary signaling and transduction entities (Fig. 3) present the same difficulties as those mentioned above for the discovery of sensing processes. Progress on signal transduction processes can be ascribed, with the same success and limitations, to the same methodologies of investigation (Fig. 2) as those dealing with sensing mechanisms [40, 44, 83, 86–91]. This has led, for instance, to the identification and characterization of protein kinases such as SnRK1

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(Snf1-related protein kinase 1) [86], of the SOS (Salt Overly Sensitive) pathway of saline stress response [83], or of cyclic nucleotidegated channels (Table 1) [87]. The combinations of mutant analysis and biochemical characterization will keep on yielding fruitful results in the future, since even the elusive primary events of cell-stress interaction are likely to be linked to upstream or downstream entities, such as structural proteins, enzymes, regulators, or transducers, that are genetically determined. However, besides current state-of-the-art methods, novel developments will be necessary in the short term and in the long term in order to obtain a more complete view of abiotic stress sensors and to characterize the connections between signaling pathways and primary sensors [1]. Thus, a number of the following chapters deal with the identification of novel abiotic stress cues, the improvement of bioinformatics methods in order to reconstruct hierarchies of signaling entities, and the fine dynamics of signal transfers. However, in view of future methodological progress, as novel information, more diverse, more detailed, and more complex, is gained, it is also likely that the conceptual emphasis on sensing and signaling cascades may have to evolve from unilinear models to models of reticulate networks. The regulatory networks involved in abiotic stress sensing and signaling are connected to phytohormone signaling, electrical signaling, and developmental signaling, thus implying the integration of abiotic stress signaling and responses from the level of the cell to the level of the whole plant [1, 2, 15, 16, 92, 93]. All of the plant hormones and their signal transduction pathways have been found to present some level of involvement in the downstream integration of abiotic stress responses, with some of these phytohormones, such as ethylene, abscisic acid (ABA), jasmonate (JA), or salicylate (SA) showing a high degree of specialization in abiotic stress responses [1]. The characterization of abiotic stress sensing and signaling mechanisms thus necessarily leads to the characterization of the connections between upstream abiotic stress sensing and signaling and downstream stress-related phytohormone sensing and signaling. However, given the scope of the present book, the different chapters essentially focus on the upstream mechanisms that interact with or are close to abiotic stress stimuli. The characterization of interface, crosstalk, and modulation mechanisms between abiotic stress signaling and hormone signaling [94–96] or between abiotic stress signaling and developmental signaling [2, 93, 96] involves sui generis experiments and methods of investigation that have already given rise to generic books on plant hormones or specific books on the different classes of plant hormones.

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Abiotic Stress Signaling and the Debate on Plant Sentience and Plant Intelligence Our current knowledge of plant sensing and signaling remains fragmentary [1]. However, the discoveries that plants could sense and interpret their environment with a myriad of complex and sophisticated mechanisms and that they could solve intricate issues of optimal adjustment through computational and algorithmic processes have been so remarkable that some plant biologists have been tempted to hail the revelation of plant sentience and intelligence [97–101]. However, to say the least, such contention has been met with disbelief from other quarters of the plant science community and has led to heated debates [102, 103]. On the one hand, such a debate on plant sentience and intelligence reflects the extent to which the understanding of plant sensing and signaling has brought great novelty and new outlooks in our vision of plants. On the other hand, nearly all of these novel sensing and signaling mechanisms, at least under the present state of knowledge, function at the cellular level and are homologous or analogous to mechanisms that are known to occur in unicellular organisms such as yeast or prokaryotic cells [9, 104], or even in subcellular organelles such as mitochondria and plastids [105]. However, for a number of reasons, some of which may be seen as subjective and paradoxically anthropocentric, the debate on plant intelligence has greatly overshadowed any speculation on yeast intelligence, bacterial intelligence, or organellar intelligence. The general consensus would probably be that the definition of intelligence must be considerably broadened, simplified, or even, as some people would say, slackened or distorted, in order to accommodate processes that encompass organelles, bacteria, yeast, plants, invertebrates, and mammals. Indeed, such broadening of the definition of intelligence has been advocated to cover any kind of information gathering and processing leading to improvement of the probability of survival and to adaptability to changing environments [99]. In such a broad framework, basic molecular processes, such as bacterial chemotaxis and targeted swimming, are deemed to be intelligent [99]. Given that the debate focusses on vocabulary and definitions, one may be tempted to let it be and say “why not ?” or “if you decide so,” as emphasized by Chamovitz [102]. However, one may also wonder how wise it is to re-define in such drastic ways words and concepts that are initially based on deep-rooted human experience, human education and development, and thousands of years of human self-analysis through myths, philosophies, literature, and science [106]. It must be noted that intense debates on the nature and definition of intelligence or on the diversity of intelligence categories (such as narrow intelligence and general intelligence) take place in the field of artificial intelligence [106]. No one in the plant biology community would be

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considering to develop novel concepts of “plant friendship,” “plant love,” or plant politics.” In other words, it seems to be rather reasonable and circumspect to keep distinguishing evolutionary divergent objects and processes, even when they present some level of analogy. Thus, given the complexity of the evolutionary dimension of adaptive processes, the potential confusion arising from the use of terms like “plant intelligence” may lead to some kind of anti- or non-evolutionary framework, as highlighted by Chamovitz [102], and to a vision of biological organisms that does not take into account the different levels of organization [99]. As emphasized by Chamovitz [102], “plants and animals independently evolved signaling networks and mechanisms, based on a common tool-set from our unicellular common ancestor.” Besides these evolutionary differences, the integration of abiotic stress signaling at the cell, tissue, organ, and organism levels of the plant remains poorly known. Understanding the integration of plant abiotic stress responses in the context of plant interactions with surrounding microbiota is also a major challenge [1]. Thus, even if information processing and adaptive plasticity are at the heart of sensing and signaling mechanisms in plants, there are so many plant specificities, so many unknowns and so many unknown unknowns that it may be highly recommended to avoid the use of catchwords that bring about additional confusions of concepts and definitions.

6

Implications for Plant Ecology and Agronomy and for Global Change Biology The abiotic stress constraints that plants encounter in real life do not only involve the physicochemical natures of the environmental stresses and the types of internal cellular stresses that are induced, but also depend on the timing, the intensity, the frequency, and the combination of the stress conditions [5, 7, 9, 15, 16]. In this context, abiotic stress sensing and signaling give plants the ability to develop early perception of and early responses to stress-related cues before the full effects of the stress endanger plant survival and fitness [14, 27, 28, 107]. Moreover, some aspects of abiotic stress sensing and signaling, such as endoplasmic reticulum stress, the unfolded protein response, mitochondrial stress, and chloroplast stress, are related to general mechanisms of cell functional surveillance that maintain and protect cell homeostasis [2, 3, 30, 108]. Abiotic stress sensing and signaling therefore endow plants with the ability to integrate and calculate different parameters and adjust their acclimation responses to the global environment [10, 38, 109]. Abiotic stress sensing and signaling mechanisms are thus at the frontline of plant acclimation responses to climate change and global change [3, 15, 16, 110], which implies for

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instance expected increases of global temperatures between +2.6 and +4.8 °C at the end of the century [111]. Exhaustive knowledge on abiotic stress sensing and signaling mechanisms is necessary to assess their potential efficiency or their potential collapse in plants subjected to increasing stress intensity or to extreme climatic events [3, 4, 15, 16]. It is therefore essential to improve the understanding of abiotic stress sensing and signaling mechanisms in order to evaluate the potential responses of cultivated crops [3, 43, 46, 112, 113] or natural plant communities [3, 4, 47] to global change and to assess the potential impacts for food security [1, 14, 46, 114–116] and for vegetation, ecosystem, and planetary protection [3, 4, 55, 117, 118]. Exhaustive knowledge on abiotic stress sensing and signaling mechanisms will be useful to design biochemical or genetic biomarkers for the risk assessment of climate change impacts on plant communities [110, 115, 118, 119] and to integrate signaling responses in the parameterization of plant-climate and vegetationclimate models [115]. Moreover, the genetic determinants and the genetic resources related to these mechanisms could be harnessed by genetic engineering, genome editing, or marker-assisted breeding for crop genetic improvement and crop management in the context of climatic stress [1, 6, 120, 121]. Beyond the development of novel crop varieties, signaling and regulatory processes can also be the targets of transient reprogramming, which aims to tune crops to adverse environmental fluctuations through spray and delivery of RNA into crop plants [122, 123]. Finally, signaling and regulatory mechanisms should provide essential information for the design and development of abiotic stress hardening treatments [14, 124] and of stress protection biostimulant formulations [125, 126].

7

Conclusion The complexities, the discoveries and the breakthroughs in the field of abiotic stress sensing and signaling have been addressed in a series of recent reviews either giving a synthetic view of mechanisms or focused on a specific pathway or a specific group of plants [1–4, 43, 46, 105]. In line with this timely interest for plant abiotic stress signaling, the contributors of the present book bring together conceptual strategies and methodological know-how over a wide range of examples related to the diversity of plant models and to the diversity of mechanisms that can be used as a stepping stone to unravel the intricacies of signaling networks. Moreover, as described above, the field of plant abiotic stress signaling deals with fundamental molecular mechanisms that bear on several fields of application: (i) the interactions of abiotic stress and biotic stress signaling in the context of plant pathology [127], (ii) the functional

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ecology of plant communities and ecosystems [3, 4, 128, 129], (iii) the agronomy of cultivated plants [46], and (iv) the predictive science of climate change dynamics [115]. The importance of these issues will be frequently mentioned in the course of the different chapters, but the methodological analysis of such broadscale issues remains beyond the scope of the present book. References 1. Zhang H, Zhu J, Gong Z, Zhu JK (2022) Abiotic stress responses in plants. Nat Rev Genet 23:104–119. https://doi.org/10. 1038/s41576-021-00413-0 2. Zhu JK (2016) Abiotic stress signaling and responses in plants. Cell 167:313–324 3. Bigot S, Buges J, Gilly L et al (2018) Pivotal roles of environmental sensing and signaling mechanisms in plant responses to climate change. Glob Chang Biol 24:5573–5589 4. Boulc’h PN, Caullireau E, Faucher E et al (2020) Abiotic stress signalling in extremophile plants. J Exp Bot 71:5771–5785 5. Claeys H, Van Landeghem S, Dubois M et al (2014) What is stress? Dose-response effects in commonly used in vitro stress assays. Plant Physiol 165:519–527. https://doi.org/10. 1104/pp.113.234641 6. Zhang H, Sonnewald U (2017) Differences and commonalities of plant responses to single and combined stresses. Plant J 90:839– 855. https://doi.org/10.1111/tpj.13557 7. Carmody M, Waszczak C, Id€anheimo N et al (2016) ROS signalling in a destabilised world: a molecular understanding of climate change. J Plant Physiol 203:69–83. https://doi.org/ 10.1016/j.jplph.2016.06.008 8. Prerostova S, Dobrev PI, Gaudinova A et al (2017) Hormonal dynamics during salt stress responses of salt-sensitive Arabidopsis thaliana and salt-tolerant Thellungiella salsuginea. Plant Sci 264:188–198. https://doi.org/10. 1016/j.plantsci.2017.07.020 9. De Nadal E, Ammerer G, Posas F (2011) Controlling gene expression in response to stress. Nat Rev Genet 12:833–845 10. Nguyen D, Rieu I, Mariani C, van Dam NM (2016) How plants handle multiple stresses: hormonal interactions underlying responses to abiotic stress and insect herbivory. Plant Mol Biol 91:727–740. https://doi.org/10. 1007/s11103-016-0481-8 11. Pandey P, Ramegowda V, Senthil-Kumar M (2015) Shared and unique responses of plants to multiple individual stresses and stress combinations: physiological and molecular

mechanisms. Front Plant Sci 6:723. https:// doi.org/10.3389/fpls.2015.00723 12. Prasch CM, Sonnewald U (2013) Simultaneous application of heat, drought, and virus to arabidopsis plants reveals significant shifts in signaling networks. Plant Physiol 162: 1849–1866. https://doi.org/10.1104/pp. 113.221044 13. Prasch CM, Sonnewald U (2015) Signaling events in plants: stress factors in combination change the picture. Environ Exp Bot 114:4– 14. https://doi.org/10.1016/j.envexpbot. 2014.06.020 14. Savvides A, Ali S, Tester M, Fotopoulos V (2016) Chemical priming of plants against multiple abiotic stresses: mission possible? Trends Plant Sci 21:329–340. https://doi. org/10.1016/j.tplants.2015.11.003 15. Zandalinas SI, Fritschi FB, Mittler R (2021a) Global warming, climate change and environmental pollution: recipe for a multifactorial stress combination disaster. Trends Plant Sci 26:588–599. https://doi.org/10.1016/j. tplants.2021.02.011 16. Zandalinas SI, Sengupta S, Fristchi FB et al (2021b) The impact of multifactorial stress combination on plant growth and survival. New Phytol 230:1034–1048. https://doi. org/10.1111/nph.17232 17. Mishra V, Singh P, Tripathi DK, Corpas FJ, Singh VP (2021) Nitric oxide and hydrogen sulfide: an indispensable combination for plant functioning. Trends Plant Sci 26: 1270–1285 18. Mishra S, Chowdhary AA, Bhau BS, Srivastava V (2022) Hydrogen sulphide-mediated alleviation and its interplay with other signalling molecules during temperature stress. Plant Biol (Stuttg) 24:569–575. https://doi. org/10.1111/plb.13406 19. Beltra´n J, Wamboldt Y, Sanchez R et al (2018) Specialized plastids trigger tissuespecific signaling for systemic stress response in plants. Plant Physiol 178:672–683 20. Dickinson PJ, Kumar M, Martinho C et al (2017) Chloroplast signaling gates

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Chapter 2 Complexity of Abiotic Stress Stimuli: Mimicking Hypoxic Conditions Experimentally on the Basis of Naturally Occurring Environments Ailbhe Jane Brazel

and Emmanuelle Graciet

Abstract Plants require oxygen to respire and produce energy. Plant cells are exposed to low oxygen levels (hypoxia) in different contexts and have evolved conserved molecular responses to hypoxia. Both environmental and developmental factors can influence intracellular oxygen concentrations. In nature, plants can experience hypoxic conditions when the soil becomes saturated with water following heavy precipitation (i.e., waterlogging). Hypoxia can also arise in specific tissues that have poor gas exchange with atmospheric oxygen. In this case, hypoxic niches that are physiologically and developmentally relevant may form. To dissect the molecular mechanisms underlying the regulation of hypoxia response in plants, a wide range of hypoxiainducing methods have been used in the laboratory setting. Yet, the different characteristics, pros and cons of each of these hypoxia treatments are seldom compared between methods, and with natural forms of hypoxia. In this chapter, we present both environmental and developmental forms of hypoxia that plants encounter in the wild, as well as the different experimental hypoxia treatments used to mimic them in the laboratory setting, with the aim of informing on what experimental approaches might be most appropriate to the questions addressed, including stress signaling and regulation. Key words Environmental hypoxia, Ethylene response factors, Hypoxia treatments, Plant cysteine oxidases, Plant stress responses, Oxygen availability, Submergence, Waterlogging

1

Introduction Respiration is an essential process by which cells convert sugars and other respiratory substrates into ATP, the cellular form of energy. To generate ATP, aerobic respiration uses carbon substrates, while oxygen acts as the final electron acceptor. A constant supply of oxygen is thus required for energy production in the cell. Above the ground, stomata form pores and act as “mouths” that are a few microns in size, allowing gaseous diffusion (including oxygen uptake) and transpiration to occur through the mesophyll. Below the ground, gases form air pockets in the soil, from which oxygen

Ivan Coue´e (ed.), Plant Abiotic Stress Signaling, Methods in Molecular Biology, vol. 2642, https://doi.org/10.1007/978-1-0716-3044-0_2, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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diffuses inside the plant through the root hair cells [1]. Another source of oxygen for the plant is internally generated through photosynthesis, which allows plants to convert carbon dioxide and water into sugars and oxygen in the presence of light. Although photosynthesis is a valuable source of oxygen for the plant, not all plant cells are photosynthetically active, and plants can only photosynthesize during daylight hours. Oxygen diffusion to a plant tissue can be impeded by different factors. Fick’s first law describes how the rate of diffusion of a molecule is directly proportional to a diffusion coefficient and a concentration gradient, so that the molecule diffuses from regions of high concentration to those of lower concentration. In addition, this rate of diffusion is inversely proportional to the thickness of the barrier between two areas. The diffusion coefficient of oxygen is 10,000 times lower in water than in air, so that the rate of oxygen diffusion into plant cells is greatly reduced when plants are, for example, submerged in water. Similarly, even when the plant is under normal oxygen conditions, oxygen availability in deep plant tissues can be reduced [2, 3]. Insufficient oxygen supply can be detrimental to all aerobically respiring organisms, which mount molecular and physiological responses to promote survival and tolerance to this hypoxia stress. In plants, oxygen levels can be sensed via a set of enzymes, PLANT CYSTEINE OXIDASEs (PCOs), whose catalytic activity is oxygen dependent [4]. The transcriptional changes that occur downstream of low-oxygen-sensing conditions are under the control of group VII ETHYLENE RESPONSE FACTOR (ERF-VII) transcription factors, which include HYPOXIA RESPONSIVE ERF 1 and 2 (HRE1 and HRE2) and RELATED TO APETALA2.2, 2.3, and 2.12 (RAP2.2, RAP2.3, and RAP2.12) in Arabidopsis thaliana [5]. The regulation of ERF-VII abundance in the cell is key to the onset of the hypoxia response program. The ubiquitin-dependent N-degron pathway has emerged as an essential mechanism for the regulation of stability of ERF-VIIs and hypoxia response in plants [6, 7]. Briefly, the N-degron pathway targets proteins for degradation based on the identity (or specific post-translational modifications) of the N-terminal amino acid residue of substrate proteins [8]. Notably, ERF-VIIs start with a conserved N-terminal cysteine residue, which is oxidized by the oxygen-dependent PCOs under normoxic conditions. This oxidized N-terminal cysteine residue acts as a degradation signal that triggers sequentially (i) the conjugation of an arginine residue at the N-terminus of the ERF-VIIs, (ii) recognition by an E3 ubiquitin ligase (PROTEOLYSIS6 (PRT6)), and (iii) ubiquitylation and degradation of the ERF-VIIs [6, 7]. In contrast, under hypoxic conditions, the N-terminal cysteine of the ERF-VIIs is not oxidized by PCOs, thus preventing their N-degron-mediated degradation. Hence,

Experimental Mimicking of Natural Hypoxic Conditions

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the N-degron pathway mediates the degradation of the ERF-VIIs under “normoxic” oxygen concentrations (normal atmospheric levels of oxygen; 21%), but it allows their accumulation in “hypoxic” (between 0 and 21% oxygen) or “anoxic” conditions (0% oxygen). In the nucleus, the ERF-VIIs regulate the expression of a set of hypoxia response genes, whose activity and protein products promote survival to low-oxygen stress [5]. As part of hypoxia response, metabolic pathways such as carbohydrate metabolism and fermentation become activated and allow the cells to continue generating reduced amounts of ATP via alternative mechanisms to oxidative phosphorylation [9, 10]. Physiological changes also occur in the plant that increase internal oxygen levels, including (i) the formation of air pockets within the plant tissue (e.g., aerenchyma) to increase internal diffusion rates, (ii) elongation of shoots or leaves to prevent tissue submergence under water, and (iii) reduction in cuticle thickness to facilitate gas exchanges [11]. Excess precipitation can result in waterlogging (i.e., saturation of soil with water) or different levels of plant submergence, both of which result in reduced oxygen availability for plants and are the source of important crop losses in the field [12]. While soil waterlogging and plant partial or full submergence are a common cause of hypoxia stress in plants, these stresses have in fact multiple components and are therefore compound stresses. For example, partial or full submergence of the plant will cause part or all of the aerial organs of the plant to be submerged under water, which indeed creates a hypoxic environment but also results in decreased light availability for efficient photosynthesis, the release of toxic compounds from the soil (e.g., iron), reduced availability of nutrients such as nitrogen, and modifications of the soil microbiome [13]. In addition, submergence will favor the accumulation of certain organic molecules in planta, for example, the phytohormone ethylene, which plays an essential role in plant responses to (partial) submergence, or the highly reactive signaling molecule nitric oxide (NO) [14]. Waterlogging or (partial) submergence can therefore trigger a combination of individual stress responses that can be experimentally deconvoluted or assessed in combination. Over the last decades, a variety of experimental approaches have been used to study hypoxia responses. Each of these experimental approaches has a unique set of characteristics and can mimic different aspects of low oxygen stress or conditions encountered by plants in their natural habitat. In this chapter, we summarize what is known about the characteristics and variations in oxygen content in naturally occurring and artificially induced hypoxic environments, with the aim of informing on what experimental approaches might be most appropriate depending on the questions addressed, including stress signaling and regulation.

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Naturally Occurring Hypoxic Environments Much of the focus in the study of plant responses to hypoxia has been in the context of waterlogging and (partial) submergence. However, hypoxic conditions arise in plants in a wider range of situations. This section describes different physiological or stressinducing conditions that trigger hypoxic environments for plants, with the aim of providing information on the characteristics of natural hypoxic environments. These are important for a comparison with hypoxia treatments used in the laboratory setting.

2.1 Developmental Hypoxic Niches

A

In recent years, it has become increasingly clear that oxygen gradients naturally occur in plant tissues (Fig. 1) and that these variations in oxygen levels can play important developmental roles [15, 16]. Multiple factors could contribute to the formation of developmental hypoxic niches, including poor oxygen diffusion, high levels of cellular respiration that deplete oxygen reserves, or low levels of photosynthesis [15, 16]. Certain tissues may be difficult for oxygen to diffuse across. For example, during budburst in the woody perennial grapevine Vitis vinifera L., outer scales prevent oxygen diffusion to the post-dormant bud core [17]. This creates a hypoxic environment in the core of the bud with oxygen levels as low as 2.5 kPa and results in the induction of hypoxia response genes such as homologues of the ERF-VII transcription factors described in the Introduction [17, 18]. In addition, bulky or thicker tissues often present oxygen gradients. For instance, apple cores or the center of growing potato tubers have levels of oxygen that are as low as 5% [2, 3]. Lower oxygen level conditions also occur naturally in a wide range of fruits, such as in Capsicum annuum L. (pepper) [19], or in siliques of plants belonging to the Brassicaceae family. For example, inside Brassica rapa L. and B. napus siliques exposed to light, oxygen levels are slightly lower (~16-19%) than normal atmospheric levels [20–22]. Internal oxygen measurements of B

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Fig. 1 Naturally occurring hypoxic environments. Hypoxic conditions can naturally occur (a) in certain plant tissues, such as the shoot apical meristem or lateral root primordia, or in fruits such as siliques (hypoxic niches indicated in orange), (b) at sites of plant pathogen infection, or (c) in waterlogged soil (left) or (partially) submerged plants (right)

Experimental Mimicking of Natural Hypoxic Conditions

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Arabidopsis thaliana siliques grown in the light showed lower oxygen levels (~8%) compared to the bulkier B. napus siliques [20]. In addition, seeds and seed coats are often reported to have low oxygen levels [22–24]. Strikingly, internal oxygen in B. napus seeds was just 0.8% [22]. Although some of these deviations in oxygen content compared to atmospheric levels may be quite small, they could be physiologically relevant. For example, seeds from B. napus siliques exposed to 12% oxygen for 2 h show a decrease in lipid, protein, and cell wall synthesis compared to those exposed to normal atmospheric oxygen levels [22]. Hypoxic niches have also been shown to exist in developing maize anthers where the air space around tassels contains ~1.5% oxygen during archesporial fate setting [25]. This hypoxic environment is critical for appropriate germ cell differentiation [26] and is accompanied by increased transcription of genes involved in non-respiratory energy production, such as PYRUVATE DECARBOXYLASE (PDC) and ALCOHOL DEHYDROGENASE (ADH), to prepare the tissue for low oxygen levels [27]. A role for hypoxia in pollen development has also been suggested in Nicotiana tabacum, where the hypoxia response proteins ADH and PDC2 have been shown to be stabilized in pollen [28]. Hypoxia also seems to play a role in pollen tube maturation in certain species, and pollen tubes have been found to grow preferentially toward low-oxygen concentrations when cultured in vitro [29]. More recently, it has been shown that the meristems of certain plant species display low-oxygen concentrations that are critical for the stabilization of specific developmental regulators. The shoot apical meristems of both Arabidopsis thaliana and Solanum lycopersicum (tomato) have an oxygen concentration of 5–10% [30]. This hypoxic environment facilitates the stabilization of transcriptional regulators, including VERNALIZATION2 (VRN2) and LITTLE ZIPPER2 (ZPR2), which have important roles in epigenetic regulation and leaf initiation, respectively [6, 30, 31]. Notably, stabilization of VRN2 and ZPR2 relies on the same mechanism as the accumulation of the ERF-VIIs under hypoxic conditions. Indeed, VRN2 and ZPR2 both start with an N-terminal cysteine residue, whose oxidation by the oxygen-dependent PCOs triggers their degradation via the N-degron pathway. In hypoxic niches, such as those found in meristems, VRN2 and ZPR2 accumulate because they are no longer degraded via the N-degron pathway [6, 30, 31]. Hypoxia-stabilized proteins and transcripts have also been shown to accumulate in lateral root primordia [32, 33], potentially due to a hypoxic environment being created by high levels of respiration within this tissue. In sum, it has become increasingly clear that hypoxia is not simply a stress that plants need to respond to once they encounter it within their natural environment, but it is also an integral part of specific developmental regulatory mechanisms. In the coming

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Ailbhe Jane Brazel and Emmanuelle Graciet

years, it will be interesting to determine how oxygen gradients might be interpreted within the plant and therefore to consider if experimental setups are accurately mimicking developmentally relevant hypoxia niches. 2.2 PathogenInduced Hypoxia

A variety of plant pathogens have been shown to induce hypoxia at the site of infection (Fig. 1b) [15, 34]. The localized formation of hypoxic niches at the site of pathogen infection has been established using a combination of methods that include oxygen measurement, monitoring the up-regulation of typical hypoxia responsive genes (e.g., PCO1, HRE2, PDC1, or ADH1) [35–37] and using hypoxia reporters such as the Arabidopsis line expressing the β-glucuronidase (GUS) reporter under the control of the PCO1 promoter [38]. Using these approaches, it has been shown that pathogen-induced tumors are hypoxic environments. This includes crown galls formed at the site of Agrobacterium tumefaciens infection [36] or clubroot of plants infected with the protist pathogen Plasmodiophora brassicae [39]. More specifically, oxygen levels in crown galls formed after infection of Arabidopsis by A. tumefaciens can drop to less than 5% oxygen [36]. Hypoxic niches also arise in infected plant tissue in the absence of tumor formation. Local oxygen concentrations at the site of infection by the necrotrophic fungus Botrytis cinerea in Arabidopsis leaves can drop to