Reactive Oxygen Species in Plants: Methods and Protocols (Methods in Molecular Biology, 2526) 1071624687, 9781071624685

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Methods in Molecular Biology 2526

Amna Mhamdi Editor

Reactive Oxygen Species in Plants Methods and Protocols

METHODS

IN

MOLECULAR BIOLOGY

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

For further volumes: http://www.springer.com/series/7651

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.

Reactive Oxygen Species in Plants Methods and Protocols

Edited by

Amna Mhamdi VIB Center for Plant Systems Biology, Ghent University, Zwijnaarde, Belgium

Editor Amna Mhamdi VIB Center for Plant Systems Biology Ghent University Zwijnaarde, Belgium

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-2468-5 ISBN 978-1-0716-2469-2 (eBook) https://doi.org/10.1007/978-1-0716-2469-2 © Springer Science+Business Media, LLC, part of Springer Nature 2022 This work is subject to copyright. All rights are reserved 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. 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 Reactive oxygen species (ROS) refer to any molecule that is more reactive than oxygen itself. ROS are produced spontaneously by metabolism at different subcellular locations such as chloroplasts, mitochondria, peroxisomes, and the apoplast. In planta, ROS regulate a myriad of processes including development, stress signaling, systemic responses, and cell death. Literature analysis continues to document the tremendous ever-growing interest in research areas related to ROS and redox-related metabolism certainly due to their importance in plant responses to fluctuating environments. I believe that these areas will continue to be relevant to numerous aspects of plant biology and will continue to be of interest to many researchers, even more with the future climate-change context. Advances in these areas would not be possible without a reliable methodology; therefore, this guide is timely and convenient. This book includes detailed information on protocols and methods that can be used to study reactive oxygen species (ROS) in plants and to characterize their roles in development and stress responses and is written by recognized leaders in this field. The aim is to provide a useful collection of protocols that any researcher, and in particular young researchers, can use and reproduce with ease. The book contains 20 chapters and is divided into 4 parts. Part I covers the strategies to induce ROS production. Part II focuses on methods to visualize ROS and detect changes in redox homeostasis. Part III is devoted to small-scale and targeted analyses that allow for investigating the effects of ROS accumulation during stress on plant physiology and metabolism. The final part, Part IV, explores the benefit of using systems biology approaches to understand ROS functions. While the methods described here have been used mostly on our favorite model plant, Arabidopsis thaliana, they can be easily adapted to study ROS in crops and other plant species. This book covers complementary approaches to capture the ROS field from different angles. The Notes section provides the experts’ views on how to handle pitfalls and guides the users to get the best of their data, and for that, I would like to acknowledge all the authors for their valuable contributions. Zwijnaarde, Belgium

Amna Mhamdi

v

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

PART I

STRATEGIES TO INDUCE ROS PRODUCTION

1 Modification of Chloroplast Antioxidant Capacity by Plastid Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shengchun Li, Pan Shen, Bipeng Wang, Xiujie Mu, Mimi Tian, Tao Chen, and Yi Han 2 Analysis of Ascorbate Metabolism in Arabidopsis Under High-Light Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Takanori Maruta and Takahiro Ishikawa 3 Genetic Manipulation of Reactive Oxygen Species (ROS) Homeostasis Utilizing CRISPR/Cas9-Based Gene Editing in Rice. . . . . . . . . . . . Sheng Xu, Tao Chen, Mimi Tian, Marie-Sylviane Rahantaniaina, Linlin Zhang, Ren Wang, Wei Xuan, and Yi Han 4 Studying Plant Stress Reactions In Vivo by PAM Chlorophyll Fluorescence Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alexey Shapiguzov and Jaakko Kangasj€ a rvi

PART II

v xi

3

15

25

43

METHODS TO VISUALIZE ROS AND TO DETECT CHANGES IN REDOX HOMEOSTASIS

5 Live Monitoring of ROS-Induced Cytosolic Redox Changes with roGFP2-Based Sensors in Plants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Jose´ Manuel Ugalde, Lara Fecker, Markus Schwarzl€ a nder, ¨ ller-Schu ¨ ssele, and Andreas J. Meyer Stefanie J. Mu 6 Quantitative Measurement of Ascorbate and Glutathione by Spectrophotometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Graham Noctor and Amna Mhamdi 7 Measurement of NAD(P)H and NADPH-Generating Enzymes . . . . . . . . . . . . . . 97 Amna Mhamdi, Frank Van Breusegem, and Graham Noctor 8 Quantitative Analysis for ROS-Producing Activity and Regulation of Plant NADPH Oxidases in HEK293T Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Sachie Kimura, Hidetaka Kaya, Kenji Hashimoto, Michael Wrzaczek, and Kazuyuki Kuchitsu

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viii

Contents

PART III

SMALL-SCALE TARGETED ANALYSIS OF ROS ACCUMULATION DURING STRESS AND EFFECTS ON PLANT PHYSIOLOGY

9 Estimation of the Level of Abasic Sites in Plant mRNA Using Aldehyde Reactive Probe. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jagna Chmielowska-Ba˛k, Karolina Izbian´ska-Jankowska, and Joanna Deckert 10 A Simplified Method to Assay Protein Carbonylation by Spectrophotometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Corentin Moreau and Emmanuelle Issakidis-Bourguet 11 In Vitro Biochemical Analysis of Recombinant Plant Proteins Under Oxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zeya Chen and Jingjing Huang 12 Methods to Analyze the Redox Reactivity of Plant Proteins . . . . . . . . . . . . . . . . . . Thualfeqar Al-Mohanna, George V. Popescu, and Sorina C. Popescu 13 Determination of ROS-Induced Lipid Peroxidation by HPLC-Based Quantification of Hydroxy Polyunsaturated Fatty Acids . . . . . . . . . . . . . . . . . . . . . Brigitte Ksas and Michel Havaux 14 Detection of Lipid Peroxidation-Derived Free Azelaic Acid, a Biotic Stress Marker and Other Dicarboxylic Acids in Tobacco by Reversed-Phase HPLC-MS Under Non-derivatized Conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . ´ da´m, Gyo¨rgy Ka´tay, Andra´s Ku ¨ nstler, Attila L. A and Lo ra´nt Kira´ly 15 Determination of Reactive Carbonyl Species, Which Mediate Reactive Oxygen Species Signals in Plant Cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jun’ichi Mano, Md. Sanaullah Biswas, Koichi Sugimoto, and Yoshiyuki Murata 16 Measuring Stress-Induced Changes in Defense Phytohormones and Related Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Caroline Lelarge-Trouverie, Amna Mhamdi, Florence Gue´rard, and Graham Noctor

PART IV 17

18

125

135

143 161

181

191

201

215

SYSTEMS BIOLOGY APPROACHES TO UNDERSTAND ROS FUNCTIONS

Targeted Mass Spectrometry Analysis of Protein Phosphorylation by Selected Ion Monitoring Coupled to Parallel Reaction Monitoring (tSIM/PRM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Jesu´s Pascual and Saijaliisa Kangasj€ a rvi Quantitative Analysis of Posttranslational Modifications of Plant Histones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Hana Kucharˇı´kova´, Zuzana Plsˇkova´, Zbyneˇk Zdra´hal, Miloslava Fojtova´, Pavel Kerchev, and Gabriela Lochmanova´

Contents

19

20

ix

Characterization of RBPome in Oxidative Stress Conditions . . . . . . . . . . . . . . . . . 259 Zhicheng Zhang, Evy Timmerman, Francis Impens, and Frank Van Breusegem Analysis of ROS-Triggered Changes in the Transcriptome . . . . . . . . . . . . . . . . . . . 277 Patrick Willems

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

289

Contributors ´ DA´M • Plant Protection Institute, Centre for Agricultural Research, Eo¨tvo¨s ATTILA L. A Lora´nd Research Network (ELKH), Budapest, Hungary THUALFEQAR AL-MOHANNA • Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, MS, USA MD. SANAULLAH BISWAS • Department of Horticulture, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh FRANK VAN BREUSEGEM • Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; VIB-UGent Center for Plant Systems Biology, Ghent, Belgium TAO CHEN • School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China ZEYA CHEN • Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; Center for Plant Systems Biology, VIB, Ghent, Belgium JAGNA CHMIELOWSKA-BA˛K • Department of Plant Ecophysiology, Institute of Experimental Biology, Faculty of Biology, School of Natural Sciences, Adam Mickiewicz University, Poznan, Poland JOANNA DECKERT • Department of Plant Ecophysiology, Institute of Experimental Biology, Faculty of Biology, School of Natural Sciences, Adam Mickiewicz University, Poznan, Poland LARA FECKER • Institute of Crop Science and Resource Conservation (INRES), Rheinische Friedrich-Wilhelms-Universit€ at Bonn, Bonn, Germany ´ MILOSLAVA FOJTOVA • Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology, Masaryk University, Brno, Czech Republic FLORENCE GUE´RARD • Plateforme Me´tabolisme-Me´tabolome, Institut des Sciences des Plantes de Paris-Saclay, Unite´ Mixte de Recherche 8618 Centre National de la Recherche Scientifique, Orsay Cedex, France YI HAN • School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China; National Engineering Laboratory of Crop Stress Resistance Breeding, School of Life Sciences, Anhui Agricultural University, Hefei, China KENJI HASHIMOTO • Department of Applied Biological Science, Tokyo University of Science, Noda, Chiba, Japan MICHEL HAVAUX • Aix-Marseille University, CNRS, CEA, UMR7265, Biosciences and Biotechnologies Institute of Aix-Marseille, CEA/Cadarache, Saint-Paul-lez-Durance, France JINGJING HUANG • Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; Center for Plant Systems Biology, VIB, Ghent, Belgium FRANCIS IMPENS • VIB Center for Medical Biotechnology, Ghent, Belgium; UGent Department of Biomolecular Medicine, Ghent, Belgium; VIB Proteomics Core, Ghent, Belgium TAKAHIRO ISHIKAWA • Department of Life Sciences, Faculty of Life and Environmental Science, Shimane University, Matsue, Shimane, Japan; Institute of Agricultural and Life Sciences, Academic Assembly, Shimane University, Matsue, Shimane, Japan EMMANUELLE ISSAKIDIS-BOURGUET • Universite´ Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Orsay, France

xi

xii

Contributors

KAROLINA IZBIAN´SKA-JANKOWSKA • Department of Plant Ecophysiology, Institute of Experimental Biology, Faculty of Biology, School of Natural Sciences, Adam Mickiewicz University, Poznan, Poland JAAKKO KANGASJA€ RVI • Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, and Viikki Plant Science Center, University of Helsinki, Helsinki, Finland SAIJALIISA KANGASJA€ RVI • Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, FIN-00014 University of Helsinki, Helsinki, Finland; Department of Agricultural Sciences, Faculty of Agriculture and Forestry, FIN-00014 University of Helsinki, Helsinki, Finland GYO¨RGY KA´TAY • Plant Protection Institute, Centre for Agricultural Research, Eo¨tvo¨s Lora´nd Research Network (ELKH), Budapest, Hungary HIDETAKA KAYA • Department of Food Production Science, Ehime University, Matsuyama, Ehime, Japan PAVEL KERCHEV • Phytophthora Research Centre, Department of Molecular Biology and Radiobiology, Faculty of AgriSciences, Mendel University in Brno, Brno, Czech Republic SACHIE KIMURA • Ritsumeikan Global Innovation Research Organization, Ritsumeikan University, Kusatsu, Shiga, Japan LO´RA´NT KIRA´LY • Plant Protection Institute, Centre for Agricultural Research, Eo¨tvo¨s Lora´nd Research Network (ELKH), Budapest, Hungary BRIGITTE KSAS • Aix-Marseille University, CNRS, CEA, UMR7265, Biosciences and Biotechnologies Institute of Aix-Marseille, CEA/Cadarache, Saint-Paul-lez-Durance, France HANA KUCHARˇI´KOVA´ • Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology, Masaryk University, Brno, Czech Republic KAZUYUKI KUCHITSU • Department of Applied Biological Science, Tokyo University of Science, Noda, Chiba, Japan ANDRA´S KU¨NSTLER • Plant Protection Institute, Centre for Agricultural Research, Eo¨tvo¨s Lora´nd Research Network (ELKH), Budapest, Hungary CAROLINE LELARGE-TROUVERIE • Institut des Sciences des Plantes de Paris-Saclay, Unite´ Mixte de Recherche 8618 Centre National de la Recherche Scientifique, Orsay Cedex, France SHENGCHUN LI • State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China GABRIELA LOCHMANOVA´ • Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology, Masaryk University, Brno, Czech Republic JUN’ICHI MANO • Science Research Center, Organization for Research Initiatives, Yamaguchi University, Yamaguchi, Japan TAKANORI MARUTA • Department of Life Sciences, Faculty of Life and Environmental Science, Shimane University, Matsue, Shimane, Japan; Institute of Agricultural and Life Sciences, Academic Assembly, Shimane University, Matsue, Shimane, Japan ANDREAS J. MEYER • Institute of Crop Science and Resource Conservation (INRES), Rheinische Friedrich-Wilhelms-Universit€ at Bonn, Bonn, Germany AMNA MHAMDI • VIB Center for Plant Systems Biology, Ghent University, Zwijnaarde, Belgium CORENTIN MOREAU • Universite´ Paris-Saclay, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Orsay, France

Contributors

xiii

STEFANIE J. MU¨LLER-SCHU¨SSELE • Department of Biology, Molecular Botany, Technische Universit€ at Kaiserslautern, Kaiserslautern, Germany YOSHIYUKI MURATA • Graduate School of Environmental and Life Science, Okayama University, Okayama, Japan XIUJIE MU • School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China GRAHAM NOCTOR • Institut des Sciences des Plantes de Paris-Saclay, Unite´ Mixte de Recherche 8618 Centre National de la Recherche Scientifique, Universite´ de Paris-Sud, Orsay, France; Institut Universitaire de France (IUF), Paris, France JESU´S PASCUAL • Molecular Plant Biology, Department of Biochemistry, University of Turku, Turku, Finland ZUZANA PLSˇKOVA´ • Phytophthora Research Centre, Department of Molecular Biology and Radiobiology, Faculty of AgriSciences, Mendel University in Brno, Brno, Czech Republic GEORGE V. POPESCU • Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, MS, USA; Institute for Genomics, Biocomputing, and Biotechnology, Mississippi State University, Mississippi State, MS, USA SORINA C. POPESCU • Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, MS, USA MARIE-SYLVIANE RAHANTANIAINA • Institute of Ecology and Environmental Sciences of Paris, Molecular Ecophysiology of Stressed plant, Faculte´ des Sciences et Technologie, Universite´ Paris Est Cre´teil, Cre´teil, France MARKUS SCHWARZLA€ NDER • Institute of Plant Biology and Biotechnology, Westf€ alische Wilhelms-Universit€ at Mu¨nster, Mu¨nster, Germany ALEXEY SHAPIGUZOV • Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, and Viikki Plant Science Center, University of Helsinki, Helsinki, Finland; Natural Resources Institute Finland (Luke), Piikkio¨, Finland PAN SHEN • State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China KOICHI SUGIMOTO • Science Research Center, Organization for Research Initiatives, Yamaguchi University, Yamaguchi, Japan; Tsukuba Plant Innovation Research Center, University of Tsukuba, Ibaraki, Japan MIMI TIAN • School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China EVY TIMMERMAN • VIB Center for Medical Biotechnology, Ghent, Belgium; UGent Department of Biomolecular Medicine, Ghent, Belgium; VIB Proteomics Core, Ghent, Belgium JOSE´ MANUEL UGALDE • Institute of Crop Science and Resource Conservation (INRES), Rheinische Friedrich-Wilhelms-Universit€ at Bonn, Bonn, Germany BIPENG WANG • State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China REN WANG • Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, Jiangsu, China PATRICK WILLEMS • Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; Center for Plant Systems Biology, VIB, Ghent, Belgium MICHAEL WRZACZEK • Organismal and Evolutionary Biology Research Programme, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland; Institute of Plant

xiv

Contributors

ˇ eske´ Budeˇjovice, Czech Molecular Biology, Biology Centre, Czech Academy of Sciences, C Republic WEI XUAN • MOA Key Laboratory of Plant Nutrition and Fertilization in Lower-Middle Reaches of the Yangtze River and State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu, China SHENG XU • Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, Jiangsu, China ZBYNEˇK ZDRA´HAL • Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology, Masaryk University, Brno, Czech Republic LINLIN ZHANG • School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China ZHICHENG ZHANG • Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium; VIB-UGent Center for Plant Systems Biology, Ghent, Belgium

Part I Strategies to Induce ROS Production

Chapter 1 Modification of Chloroplast Antioxidant Capacity by Plastid Transformation Shengchun Li, Pan Shen, Bipeng Wang, Xiujie Mu, Mimi Tian, Tao Chen, and Yi Han Abstract As immobile organisms, green plants must be frequently challenged by a broad range of environmental stresses. During these constantly adverse conditions, reactive oxygen species (ROS) levels can rise extremely in plants, leading to cellular dysfunction and cell death presumably due to irreversible protein overoxidation. Once considered merely as deleterious molecules, cells seek to remove them as efficiently as possible. To enhance ROS scavenging capacity, genes encoding antioxidative enzymes can be directly expressed from the genome of plastid (chloroplast), a major compartment for ROS production in photosynthetic organisms. Thus, overexpression of antioxidant enzymes by plastid engineering may provide an alternative to enhance plant’s tolerance to stressful conditions specifically related with chloroplast-derived ROS. Here, we describe basic procedures for expressing glutathione reductase, a vital component of ascorbate-glutathione pathway, in tobacco via plastid transformation technology. Key words ROS, Glutathione reductase, Chloroplast, Plastid transformation, Tobacco

1

Introduction Reactive oxygen species (ROS) are partially reduced or excited forms of atmospheric oxygen. The major forms of ROS in plants are singlet oxygen, hydrogen peroxide, superoxide anion, and hydroxyl radical [1]. ROS were initially recognized as mere toxic by-products of metabolic processes and can result in cellular dysfunction and cell death. ROS are able to cause irreversible modifications to cysteine residues in proteins, leading to their degradation and/or structural alterations [2, 3]. On the other hand, intensive research has demonstrated that ROS play an integral role as signalling molecules in the regulation of numerous biological processes such as growth, development, and responses to a variety of biotic and/or abiotic stimuli in plants [4–7]. To utilize ROS as signalling molecules, non-toxic levels must be maintained in a delicate balance between ROS production and elimination that is achieved via a

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_1, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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Shengchun Li et al.

range of antioxidative systems, including superoxide dismutase, catalase, the ascorbate-glutathione pathway, and numerous antioxidant metabolites [8, 9]. In plants, chloroplast is the key ROS-producing compartment, which mainly produces superoxide anion, primarily by photosystem I acceptors, and singlet oxygen, which is generated in photosystem II [10]. Hence, overexpression of ROS scavenging enzymes in the chloroplast can straightforward modify chloroplastic antioxidant capacity, and improve plant performance under stresses. Asides from targeting recombinant enzyme to the chloroplast with a transit sequence via nuclear transformation, expressing genes encoding ROS-scavenging enzymes directly in the chloroplast via plastid transformation is a promising alternative to protect plants against various oxidative stresses [11–14]. Compared with nuclear genetic engineering, plastid transformation offers several notable advantages, such as highly precise transgene insertion by efficient homologous recombination, the potential for expressing foreign proteins to extraordinarily high levels, the absence of epigenetic and position effects, the possibility of stacking transgenes in synthetic operons, and the excellent biosafety due to exclusion of plastids from pollen transmission in most crops [15, 16]. Therefore, plastid engineering has been extensively applied in biopharmaceuticals and industrial enzyme production and in crop improvement against a variety of environmental stimuli [17–19]. We propose that chloroplast transformants expressing antioxidative genes represent an excellent and challenging tool in which to study the roles of various components of ROS-processing systems in the chloroplasts and their relationship with ROS in response to adverse environmental conditions. The procedure described here is based on the research of Wang et al. [13] with slight modifications. The main steps of the procedure include vector construction, biolistic transformation, selection, regeneration of plastid transformants, and molecular analysis of homoplasmic plants, as well as glutathione reductase (GR) activity and glutathione contents measurement.

2

Materials

2.1 Preparation of Plant Materials

1. Aseptically cultivated tobacco plants (Nicotiana tabacum L. cv Petit Havana). 2. Growth chamber-grown plants of Arabidopsis thaliana (Col-0). 3. Dilute sodium hypochlorite (2% active chlorine). 4. Sterile Milli-Q water. 5. Petri dishes (φ ¼ 90 mm), Magenta boxes.

Antioxidant and Plastid Transformation

2.2 Culture Media Components

5

1. 20 Macro salts for MS medium (1 L): 38.0 g KNO3, 33.0 g NH4 NO3, 8.8 g CaCl2·2 H2O, 7.4 g MgSO4·7H2O, 3.4 g KH2PO4. Store at 4  C. 2. 200 Micro salts for MS medium (1 L): 4.46 g MnSO4·4H2O, 1.72 g ZnSO4·7H2O, 1.24 g H3BO3, 166.0 mg KI, 50.0 mg Na2MoO4·2H2O, 5.0 mg CuSO4·5H2O, 5.0 mg CoCl2·6H2O. Store at 4  C. 3. 200 iron solution for MS (100 mL): 556 mg FeSO4·7H2O and 746.0 mg Na2EDTA. Store at 4  C. 4. 200 vitamins/organic compounds for MS medium (100 mL): 2 g inositol, 2.0 mg thiamine HCl, 10.0 mg pyridoxine HCl, 10.0 mg nicotinic acid, and 40.0 mg glycine. Store at 4  C. 5. Naphthalene acetic acid (NAA), 1 mg/mL (in 0.1 M NaOH). 6. 6-benzylaminopurine (6-BA), 1 mg/mL (in 0.1 M HCl). 7. Spectinomycin, 100 mg/mL. 8. Streptomycin, 100 mg/mL. 9. MS medium for growth of plants in sterile culture (1 L): 20 Macro salts (50 mL), 200 Micro salts (10 mL), 200 iron solution (10 mL), 200 vitamins/organic compounds (10 mL), pH 5.6–5.8 (adjust with 0.2 M KOH). 10. Regeneration medium of plants (RMOP) medium for shoot regeneration: MS medium, 0.1 mg/L NAA, 1.0 mg/L 6-BA, 30 g sucrose, pH 5.7, 8.0 g/L agar. 11. Rooting medium: MS medium, 0.1 mg/L NAA, 30 g sucrose, pH 5.7, 8.0 g/L agar. Shoot regeneration medium or rooting medium is sterilized by autoclaving and cooled to approximately 60  C.

2.3 Vector for Tobacco Plastid Transformation

1. RNA isolation reagent (e.g., TRIzol). 2. Restriction enzymes. 3. PCR Mix (containing Pfu DNA polymerase, dNTPs, and reaction buffer). 4. Milli-Q water. 5. Gene-specific primer pairs (see Note 1). 6. Gel Extraction Kit. 7. Plasmid Extraction Kit. 8. Competent cells of Escherichia coli. 9. Luria-Bertani (LB) solid or liquid medium: 1% tryptone, 0.5% yeast extract, 1% NaCl, with or without 1% agar. 10. Mortar, pestle, liquid nitrogen.

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11. PCR Thermal Cycler. 12. NanoDrop spectrophotometer. 13. Shaking incubator. 14. Tobacco plastid transformation vector: pYY12 [20] (see Note 2). 2.4 DNA-Coated Gold Particles and Biolistic Delivery System

1. Gold particles (0.6 μm). 2. Plasmid Midiprep Kit. 3. 2.5 M CaCl2 solution. 4. 0.1 M spermidine (free base). 5. Ice-cold 100% ethanol. 6. Sterile ultrapure water. 7. PDS-1000/He Biolistic Particle Delivery System. 8. Hepta adaptor, rupture disks (1100 psi), stopping screen, macro-carriers, and macro-carrier holders for biolistic gun. 9. Vacuum pump for biolistic gun. 10. Pressurized helium in tank, 99.999% pure. 11. Laminar flow hood for bombardment.

2.5 Identification of Transplastomic Lines

1. DNA extraction reagent (e.g., cetyltrimethylammonium bromide (CTAB)). 2. Oligonucleotides for hybridization probe: psaB-Fwd, TTAGCCAAAGGTGTAC GTTCATGAG, psaB-Rev: TTGCCCGGCTGGTTAAATGC. 3. Restriction enzyme (Bgl II, see Note 3). 4. Hybridization and detection kit with digoxigenin-labelled probes. 5. Positively charged nylon membranes. 6. UV crosslinker.

2.6 GR Enzyme Activity Measurement

1. Protein extraction buffer (0.1 M NaH2PO4, 1 mM EDTA, pH 7.5). 2. Polyvinylpyrrolidone. 3. 10 mM NADPH. 4. 50 mM oxidized glutathione (GSSG). 5. Bicinchoninic Acid (BCA) Kit. 6. Spectrophotometer.

Antioxidant and Plastid Transformation

3

7

Methods

3.1 Preparation of Tobacco Plant Materials

1. Surface sterilize tobacco seeds in a 1.5 mL microcentrifuge tube with 1 mL of dilute sodium hypochlorite for 8 min. Remove the sodium hypochlorite with a sterile pipette and rinse the seeds with 1 mL of sterile Milli-Q water for 1 min. Repeat rinsing with sterile Milli-Q water three times to remove all traces of sodium hypochlorite. 2. Sprinkle about tobacco 100 seeds on the surface of MS medium containing 3% sucrose in a Petri dish. When seedlings reach 1 cm (about 2 weeks) in size, transfer seedlings to Magenta boxes (one shoot per box) containing MS medium plus 3% sucrose, and let them grow 3–4 weeks (see Note 4). The plants are grown in a growth room in a 16 h photoperiod, 25  C/22  C, and an irradiance of 50–75 μmol m2 s1.

3.2 Construction of Tobacco Plastid Transformation Vector

1. Amplify the coding region (see Note 5) of any gene of interest (for instance, AtGR2, AT3G54660) using gene-specific primers. 2. Digest the pYY12 using the restriction enzymes Nco I and Xba I. 3. Transform the digested pYY12 without GFP gene and targeted gene (e.g., AtGR2) PCR products simultaneously into E. coli competent cells to generate plastid transformation construct pLSC5 via homologous recombination [13, 20, 21] (see Fig. 1a).

3.3 Particle Preparation and DNA Coating

1. Perform the following steps on ice (at 4  C). Sterile ultrapure water and 100% ethanol must be ice-cold. 2. Use 1.5 mg of gold particles (0.6 μm diameter) per seven shots (Hepta Adaptor). 3. Transfer the gold particles to 1.5 mL Eppendorf tube, add 600 μL 100% ice-cold ethanol in tube, and vortex for 1 min at maximum power. 4. Spin down the tube in microcentrifuge at 5000 g. 5. Remove the ethanol completely, and resuspend the gold particles in 600 μL of sterile ultrapure water by vigorous vortex. 6. Spin down the tube in microcentrifuge at 5000 g, and discard the supernatant. 7. Resuspend the gold particles in 175 μL sterile ultrapure water by vortex. 8. Add to the gold preparation in the following order: 20 μg plasmid DNA for transformation (concentration: ~2 μg/μL), 175 μL 2.5 M CaCl2, 35 μL 0.1 M spermidine.

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Fig. 1 Generation of transplastomic tobacco plants. (a) Physical map of plastid genome region (ptDNA) used for integration of transgene and the map of tobacco plastid transformation vector pLSC5. AtGR2 is targeted to the intergenic region between trnfM and trnG. The selectable marker gene aadA is controlled by psbA promoter (CrPpsbA) and fused to rbcL 30 UTR (CrTrbcL) from Chlamydomonas reinhardtii, and the AtGR2 is driven by the tobacco plastid rRNA operon promoter combined with the 50 UTR from gene10 of bacteriophage T7 (NtPrrn: T7g10) and the 30 UTR from the E. coli ribosomal RNA operon rrnB (TrrnB). (b) RFLP analysis of transplastomic tobacco lines (fragment sizes: 3.5 kb in the wild type, Nt-wt; 7.1 kb in Nt-pLSC5). (The figure is from Ref. [13] with modification)

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9. Incubate on ice for 10 min, and vortex for few seconds every minute. 10. Spin down the tube in microcentrifuge at 3500 g, and remove supernatant completely. 11. Add 600 μL of 100% ethanol, and carefully resuspend the particles by pipetting up and down. 12. Spin down the tube in microcentrifuge at 5000 g, and remove supernatant completely. 13. Repeat steps 10 and 11 one more time. 14. Resuspend the particles carefully in 50 μL of 100% ethanol by pipetting up and down. 15. Use 6.5 μL per bombardment shot, and carefully resuspend particles by pipetting immediately before use. 3.4 Bombardment Procedure

1. Place abaxial side of sterile leaf samples (see Note 6) up on a thin layer of RMOP medium without antibiotics in a Petri dish. 2. Sterilize rupture disks (1100 psi) for 1 min, macrocarriers for 5 min, and stopping screens for 10 min by soaking in 100% ethanol, and then air-dry them thoroughly in an open Petri dish in the laminar flow hood. 3. Turn on helium tank and set helium pressure at regulator for 1300–1400 (200–300 psi above rupture disk value). 4. Place the Petri dish holder 9 cm (first shelf from the bottom) below the microcarrier assembly, and close the door. 5. Turn on the vacuum button VAC position, and allow the vacuum pressure to reach 27–28 in. of Hg, switch the vacuum button on HOLD position, and press the FIRE button until the rupture disk is burst. 6. After bombardment, press the VENT switch to release the vacuum. When the vacuum gauge shows zero, open the door and take out the bombarded samples from the chamber. 7. Incubate the bombarded leaves in dark in culture room for 2 days (see Note 7).

3.5 Identification of Transplastomic Lines

1. After 2 days, cut bombarded leaves into 5 mm  5 mm pieces, and place 12 pieces per plate abaxial side up on RMOP medium supplemented with 500 mg/L spectinomycin (see Note 8). The spectinomycin-resistant calli or shoots appear 4–12 weeks after bombardment (see Note 9). 2. Screen plastid transformants by transferring small (5 mm  5 mm) leaf sections of the regenerated shoots onto RMOP medium containing (i) 500 mg/L spectinomycin, and (ii) 500 mg/L each of spectinomycin plus streptomycin (see Note 10).

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3. Verify authentic transplastomic plants via Southern blot (see Note 11) if selected plastid transformant candidates can resist upon above antibiotic treatments. 4. Repeat plant regeneration on the RMOP medium containing 500 mg/L spectinomycin, and confirm uniform transformation of plastid DNA by Southern blot analyses. Plants regenerated twice on selective spectinomycin medium can normally achieve homoplastomic status. 5. Transfer the homoplasmic transplastomic tobacco shoots regenerated on rooting medium in boxes. 6. Once roots have developed, transfer the plants to soil, and grow them to maturity and harvest seeds in the greenhouse. 3.6 GR Enzyme Activity Assay

1. Select nodes 3 and 4 of 6-week-old soil grown plants for measurement of enzyme activity. 2. Grind 100–150 mg leaf tissue in liquid nitrogen, and then add approximately 50 mg insoluble polyvinylpyrrolidone followed by 1.5 mL protein extraction buffer. Continue to grind during thawing until a homogenous suspension is obtained. 3. Centrifuge 10 min at 4  C and 15,000 g, and transfer 1 mL supernatant to a fresh tube. 4. Add 10 μL of 10 mM NADPH and 100 μL of extract 880 μL of assay buffer (the same as extraction buffer) in cuvette at 25  C. 5. Start reaction by addition of 10 μL of 50 mM GSSG, and monitor decrease in A340 (ε340NADPH ¼ 6200 M1cm1) for 2–3 min at 10 s intervals. 6. Determine protein concentration using the commercial BCA kit following the manufacturer’s instructions. 7. Calculate the amount of enzyme in the sample using the following formula (see Note 12): GR activity ðnmol:mg protein  1: min  1Þ ¼

4

sample rate Δ340 = min  blank rate Δ340 = min 6220 M  1cm  1  mg protein in sample

Notes 1. Primers include gene-specific sequence and 20–30 bp extensions homologous to vector ends. The primers harbor (underlined) a short homologous sequence to the vector pYY12 [20]. For instance, oligonucleotides used to amplify coding region of the cDNA of Arabidopsis GR2 as follows: AtGR2Fwd-1,

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TTTAAGAAGGAGATATACCCATGAGTACCGATAATGGAGCTGAATC; AtGR2-Rev-1, GCCTTTCGTTTTATTTG ATTCTAGATTCTACACCCCAGCAGCTGTTTTAG. 2. The plastid transformation vector pYY12 contains a green fluorescent protein (GFP) expression cassette and a selectable spectinomycin resistance gene (aadA) cassette [20]. 3. Apart from Bgl II, alternatively chosen restriction enzyme (s) should cut the DNA creating fragment(s) that consent to clearly distinguish between wild type, heteroplastic, and homoplastic lines. 4. Leaf samples for bombardment can be taken when shoot tip reaches half the height of the Magenta box. 5. Transit peptide sequence is not required for chloroplasttargeted protein. 6. Only the youngest 2–3 leaves are used for bombardment. 7. Incubation allows time for marker gene expression before selection is started. 8. The growth conditions for the whole selection procedure are 16 h light 20–25 μmol m2 s1 at 25  C and 8 h dark at 20  C. 9. The spectinomycin-resistant events are not always true plastid transformants because spontaneous point mutations in the plastid 16S rRNA also confer a similar spectinomycin resistance phenotype. 10. Authentic transplastomic clones carrying an aadA gene are resistant to both spectinomycin and streptomycin, whereas spontaneous spectinomycin-resistant mutants are resistant only to spectinomycin. While resistance is manifested as formation of green calli with regenerating shoots, sensitivity is indicated by formation of scanty white callus in the leaves. Resistance to streptomycin and spectinomycin indicates the presence of selectable aadA gene. However, double selection delays shoot formation. Hence, we score the presence of aadA gene by resistance to streptomycin plus spectinomycin, but screen homoplastic transplastomic plants on spectinomycin. 11. Labeling of the probe and hybridization are performed with the commercial kit containing digoxigenin-labelling. Total cellular DNA (5 μg) from leaves of wild type and spectinomycinresistant plants is digested using restriction enzyme (e.g., Bgl II). Separate the digested DNA by electrophoresis in 1% agarose gel, blot it onto a positively charged nylon membranes through semi-dry capillary transfer method, and cross-link it to the membrane by UV light. A 587 bp fragment of the psaB gene amplified with primer pair psaB-Fwd/psaB-Rev is used as a hybridization probe to verify plastid transformants (see Fig. 1b).

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Fig. 2 Glutathione reductase activity and glutathione analysis. (a) GR activity and (b) glutathione content in wild type and transplastomic lines Nt-pLSC5. White bars, reduced forms. Red bars, oxidized forms. Data are means  SE of four independent extracts. Asterisks indicate significant differences from WT at P20 min to relax qE-NPQ; (d) Fv/Fm measurement. The steps (b)–(d) are repeated 10–15 times to obtain the kinetics of Fv/Fm. This kinetics can be plotted against time as shown in Figs. 5 and 6. Inset: dynamics of chlorophyll fluorescence (F) during the first AL cycle in plants treated with MV plus SHAM. Line A has enhanced mitochondrial signalling under standard growth conditions as compared to line B. Treatment with MV plus SHAM leads to increased F during the first hour of light exposure in line A, but not in line B. The two curves are normalized to darkadapted Fo

4. In the “Script” menu at the bottom of the program window, press “Load.” Open the protocol file IMAGING-PAM_light_15x60min.prg. In the line “Set Act. Light ¼ ” (protocol line 25), replace the pre-set number (the fourth of the numbers separated by the commas) with the desired AL intensity obtained in step 3. Save the script and close the “Edit Script” pop-up window. 5. Switch off AL by removing the check mark from the “AL” box at the bottom of the program window. 6. Switch on near-infrared imaging mode by choosing “Live Video” in the “Select” menu of the “Imaging” tab. In this view mode, illumination is provided by near-infrared light that is virtually not absorbed by chlorophylls and, thus, cannot induce qE-NPQ.

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7. Move the plant material on an agar or a multi-well plate inside the IMAGING-PAM chamber. Position the plate and adjust the focusing, and then close the “Live Video” pop-up window, which will return the program to the chlorophyll fluorescence imaging mode. If long illumination with AL has occurred during the transfer of the plate, let the plants re-acclimate to darkness for 10–20 min (see Note 2). 8. Start the IMAGING-PAM_light_15x60min.prg protocol by pressing “Run” in the “Script” menu at the bottom of the program window. The script pop-up window opens and the script starts. After the measurement, the data is automatically saved in the Data_MAXI folder under the name “Photoinhibition.pim.” 9. When the same script is triggered again, this overwrites the originally saved file in the Data_MAXI folder. Thus, the data files must be renamed or moved to a different folder every time the script is triggered to avoid overwriting the original file. 10. For working with the saved files, the software needs to be switched to the analysis mode. This is done by removing the check mark from the box “Measure” at the bottom of the program window. 11. Open the saved “*.pim” file. 12. To extract the numeric data from the images, select the areas of interest (AOIs). This is done by using the “AOI” menu in the “Image” tab of the program window. Add circular, rectangular, or polygonal selections over the regions from which the data is to be extracted. This can be either individual seedlings/leaf discs or groups of seedlings/leaf discs of the same treatment and genotype. 13. Alternatively, when working with multi-well plates, AOIs can be assigned automatically. For this, in the top menu select “Options > Define AOI array geometry.” In the pop-up window define the number of rows and columns in the imaged plate. Then set AOI type to circle and press “Add.” Adjust the diameter of the selection by pressing “-” and “+” keys on the keyboard. Add the first circular selection at the top left well and the second circular selection at the bottom right well of the multi-well plate image. In the top menu select “Options > Create AOI array.” 14. When all the AOIs have been assigned, select the “Report” tab. On the right side of the program window, select the data to be exported. In this menu, “F” indicates all fluorescence kinetics except the measurements performed under SPs. “Fm’” indicates all fluorescence kinetics plus the measurements performed under SPs. “Y(II)” indicates measurements of φPSII

Alexey Shapiguzov and Jaakko Kangasja¨rvi

performed at every SP. Check-mark only “Y(II)” and “Fm’” and export the data as a “*.csv” file by pressing “Export selected recording as csv-file” (the button with the red arrow). 15. The rows of the exported “*.csv” file correspond to sequential frames of the executed protocol; the columns correspond to individual AOIs. Every time the SP has been triggered, a calculated φPSII value will be presented in the “Y(II)” columns. Since in the described protocol the φPSII measurement is preceded by dark acclimation, these values are assumed equal to Fv/Fm. 16. Plot Fv/Fm over time as shown in Figs. 5 and 6 (see Note 14). 17. To visualize dynamics of F, plot the “Fm’” datasets against time, as shown in Fig. 4. If several curves are presented in the same plot, normalize them to Fo obtained in the beginning of the protocol.

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Fig. 5 Measuring kinetics of Fv/Fm in MV-treated Arabidopsis leaf discs. (Left panel) plotting Fv/Fm against time (expressed as the number of the one-hour AL cycles) allows to assess dynamics of PSII photoinhibition. This approach is advantageous over measuring only the endpoint Fv/Fm values, because extended treatments may lead to either complete recovery of PSII photochemistry (as in lines A and B), or to its complete loss (as in lines D and E). In both cases, the endpoint measurement of Fv/Fm does not allow to differentiate between the different types of response. For this data set, 8 leaf discs from 4 independent plant rosettes have been assayed. The standard deviations are indicated. (Right panel) a sample false-color image of Fv/Fm obtained in the course of the above experiment. A fragment of the 96-well plate is shown. Each row contains leaf discs from one line

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Fig. 6 Measuring kinetics of Fv/Fm in MV-treated Arabidopsis seedlings in absence or presence of AA. The lines A and B have similar tolerance to MV-induced PSII photoinhibition (left panel). When pre-treated with AA, both lines demonstrate increased tolerance to MV (compare left panel to middle panel). Note that the protective effect of AA is higher in line A than in line B. This may indicate differences in transcriptional reprogramming associated with mitochondrial signalling. For this dataset, fifteen seedlings of each line have been assayed. The standard deviations are indicated. (Right panel) a sample false-color image of Fv/Fm obtained in the course of the above experiment. A fragment of the agar plate is shown. The seedlings of lines A and B are sown in two separate groups 3.4 Chlorophyll Fluorescence Imaging Using the FluorCam

1. Download the imaging protocol file FluorCam_light_60min. txt (Electronic Supplemental File 2). This protocol is comprised of the following elements: (a) Dark acclimation period of 5 min. (b) Measurement of φPSII (here referred to as QY_max). (c) One-hour period of AL to induce the Mehler reaction, during which F is followed with MPs. (d) Dark acclimation period of 20 min. When executed several times in a row (as specified below), the protocol results in repetitive one-hour periods of AL. Each AL period is followed by a 25-min dark acclimation and the Fv/Fm (QY_max) measurement, essentially as shown in Fig. 4. 2. To use the protocol file as the script program file, change the extension from “*.txt” to “*.p” and copy the file to an empty folder. 3. Start FluorCam software. The latest version can be downloaded from the manufacturer’s website (https://psi.cz/). Turn on actinic light by check-marking the box “Act1” or “Act2” in the “Live” tab. Use the slider bars “Act1” / “Act2” to set the desired AL intensity for the assays (e.g., 80–100 μmol photons m2 s1). External light meter can be

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used to verify the light intensity. Note the Act1/Act2 values (in %) corresponding to this AL intensity. 4. Use the slider bars “Act1”/“Act2” and “Sensitivity” to reach the minimal AL intensity that allows to clearly see the plant material. 5. Move the plant material on an agar or a multi-well plate inside the FluorCam imaging chamber. Position the plate and adjust the focusing, then switch AL off. At this step, use as short light exposure as possible to minimize generation of qE-NPQ. If long illumination with AL cannot be avoided, let the plants re-acclimate to darkness for 10–20 min (see Note 2). 6. In FluorCam software, select the “Protocols” tab. Open the protocol file FluorCam_light_60min.p. In lines “Act1¼. . .” and “Act2¼. . .” in the header of the protocol, replace the predefined numbers with the Act1 and Act2 values obtained in step 3. Save the updated protocol. 7. In the upper program panel, press the button “Start Script Experiment” (a double red lightning). If this button is inactive, contact Photon Systems Instruments to obtain the predefined script “Advanced Multiple Function for FluorCam Software.” 8. Select a destination folder containing the downloaded protocol. This folder is also used for data storage. Select the number of times the protocol needs to be executed (e.g., 10–15) and the delay between two measurements (e.g., 30 s). Start the script. 9. In the course of the measurement, the resulting “*.tar” files are sequentially saved in the destination folder. 10. To extract the numeric data from the images, open the first of the result files in FluoCam software, and select the “PreProcessing” tab. 11. In the “Selections” menu, press “Manual,” then use rectangular, elliptic, polygonal, or sector selection tools to define the regions of interest from which the data is to be extracted. This can be either individual seedlings/leaf discs or groups of seedlings/leaf discs of the same treatment and genotype. Using the “Selections” menu, save the selection as an “*.xsel” file. 12. Press “Background exclusion” to perform thresholding of plant material within the selected regions of interest. 13. Press “Analyse” to integrate the signal in the selected regions of interest. 14. In the top menu of the “Result” tab, select “Experiment > Export > Numeric > Frames Numeric” to export the Fv/Fm (QY_max) data for individual regions of interest. 15. Repeat steps 10–14 for all the files in the destination folder.

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16. Plot Fv/Fm over time as shown in Figs. 5 and 6. 17. To visualize dynamics of F, extract kinetic data from the regions of interest. For this, in the top menu of the “Result” tab, select “Experiment > Export > Kinetic > All Data” and save the kinetics as a “*.txt” file. Plot the values against time. If several curves are presented in the same plot, normalize them to Fo obtained in the beginning of the protocol (see example in Fig. 4 inset).

4

Notes 1. In related literature, the same chlorophyll fluorescence parameter may be described by several alternative names. Chlorophyll fluorescence under light F can be referred to as Ft (fluorescence at time t), or Fs (fluorescence in light-adapted steady state) [18, 31]. Dark-adapted φPSII may be called QYmax (maximal quantum yield of PSII) and is calculated as Fv/Fm [18]. 2. In most plants including Arabidopsis, dark adaptation time required to relax qE-NPQ is 20–30 min [13]. 3. Pharmacological studies are prone to artefacts related to undesirable off-target effects of the described chemicals. In nonphotosynthetic organisms, activities of MV have been associated with mitochondria, but in plants, such extra-chloroplast activities of MV are poorly understood [32]. In the described assays, the specificity of MV towards PSI is supported by little or no MV-dependent damage to PSII during overnight dark incubation. In addition to its inhibitory activity on mitochondrial complex III, AA (but not myx) inhibits one of the cyclic electron transfer pathways around PSI [33]. The concentration of AA needed to inhibit the chloroplast electron flow in planta is higher than the concentration of AA required to inhibit mitochondrial complex III: in Arabidopsis leaf discs, the effect of AA on cyclic electron transfer is still observable under 20 μM AA, but negligible under 2 μM AA [34]. If high concentrations of AA are used, the specificity of the treatment can be verified by using more expensive myx instead of AA. In addition to inhibiting AOX activity, SHAM has been proposed to affect peroxidase activities acting either as their catalyst or as their inhibitor, depending on the concentration [35]. Thus, care must be taken when interpreting the results obtained with this inhibitor. 4. In Arabidopsis plants with enhanced mitochondrial signalling, treatment with SHAM plus MV leads to transient elevation of F within the first hour of illumination. This effect has been suggested to be caused by over-reduction of the PQ pool

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because of the inhibited AOX activity, although the mechanistic details remain unclear [22]. The imaging protocols described in Subheadings 3.3 and 3.4 include measurements of F that allow for testing whether this phenomenon is present in the plants of interest (see Fig. 4 inset). 5. Avoid using Parafilm, because the deficit of air circulation may lead to CO2 depletion inside the plates [36]. 6. Slight variations in growth light have a cumulative effect on leaf physiology and photosynthesis, including MV tolerance. Thus, it is essential to keep light intensity as uniform as possible across the experiment. It is especially important to consider the edges of shelves in growth chambers or growth rooms. Typically, the light sources are placed in the middle, which means that plants at the edges receive less light. Uniform illumination of seedlings on agar plates can be additionally ensured by occasional rotation of the Petri dishes. 7. The stock solutions of the chemicals can be stored at 20  C for several months. 8. Tween-20 is added to facilitate the uptake of chemicals. Store diluted Tween-20 at room temperature for no more than 7 days. 9. Susceptibility of plants to photoinhibition directly depends on the concentration of MV and on the intensity of AL during the assay. It is likely that these parameters may need to be optimized for every new lab and new type of plant material, because MV tolerance varies significantly in different species, accessions, or mutants and depends on many growth parameters including plant age, growth light intensity, and soil composition. The aim of such optimization is to find the concentration of MV (and/or the intensity of AL) at which Fv/Fm of the reference genotype (e.g., the wild type) gradually decays from its original maximal value before the first AL period (usually ~0.6–0.85) to about a zero after the last AL period (see Figs. 5 and 6). In our laboratory, wild-type Arabidopsis seedlings of accession Col-0 grown on Petri dishes require treatment with 3–10 μM MV and 15 one-hour pulses of AL of intensity 80–100 μmol photons m2 s1 for such a gradual decay to occur (see Fig. 6). Sensitivity of leaf discs cut from soil-grown wild type Col-0 rosettes is lower than that of seedlings and requires ~ 0.2–0.5 μM MV for the same number of cycles and AL intensity [22]. 10. The concentrations of AA and myx are likely to require optimization. In our laboratory, in the wild-type Arabidopsis (accession Col-0) a clear response has been achieved by co-application of 10 μM AA with 3 μM MV to seedlings grown on plates (see Fig. 6); or of 2.5 μM AA (or myx) with

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0.25 μM MV to leaf discs excised from soil-grown rosettes [22]. Variations in soil composition may affect reproducibility of the assay. If such irreproducibility occurs, consider performing the assay in seedlings on Petri dishes. Transcriptional reprogramming induced with AA/myx can be controlled biochemically by harvesting the overnight-treated plant material, isolating total protein and immunoblotting with an anti-AOX antibody as described in [22]. 11. In the SHAM stock solution, precipitate may be formed. Resuspend it by vortexing just before preparing the assay solution. 12. To simultaneously assess several chemical/control treatments in seedlings on agar plates, several plates need to be used, each treated with its own assay solution. Choose the size and the shape of the plates so that they fit the visual field of the imaging PAM fluorometer. Alternatively, seedlings can be sown and treated in 6-well or 12-well plates. 13. Transparent plastic lids are permeable to both the excitation light and chlorophyll fluorescence. However, using them during the assay often leads to condensation of water on the lid, which distorts the fluorescence image. 14. For very low Fv/Fm values, the software may not calculate “Y (II).” In this case the corresponding values in the “*.csv” file are set to zero. If this occurs, Fv/Fm can be calculated manually by extracting raw Fm and Fo from the “Fm’” columns of the “*.csv” file. Fm measurements are performed in frames 12, 46, 80, 114, 148, 182, 216, 250, 284, 318, 352, 386, 420, 454, 488, and 522 of the described protocol. Fo is measured in three frames preceding each Fm measurement. The three Fo measurements can be averaged. Fv/Fm is calculated as (Fm – Fo)/Fm.

Acknowledgments We thank Dr. Fuqiang Cui for his assistance in developing the leaf disc assays. We are grateful to Dr. Zuzana Benedikty for optimizing the FluorCam protocol and for revising the manuscript and to Dr. Erhard Pfu¨ndel, Dr. Mikael Brosche´, and Tuomas Puukko for their helpful comments on the manuscript. References 1. Shapiguzov A, Vainonen JP, Wrzaczek M, Kangasja¨rvi J (2012) ROS-talk – how the apoplast, the chloroplast, and the nucleus get the message through. Front Plant Sci 3:292

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˚ (2018) The 3. Crawford T, Lehotai N, Strand A role of retrograde signals during plant stress responses. J Exp Bot 69:2783–2795 4. Littlejohn GR, Breen S, Smirnoff N, Grant M (2020) Chloroplast immunity illuminated. New Phytol. https://doi.org/10.1111/nph. 17076 5. Yamori W, Shikanai T (2016) Physiological functions of cyclic electron transport around photosystem I in sustaining photosynthesis and plant growth. Annu Rev Plant Biol 67: 81–106 6. Stirbet A, Lazár D, Guo Y, Govindjee G (2020) Photosynthesis: basics, history and modelling. Ann Bot 126:511–537 7. Ruban AV (2016) Nonphotochemical chlorophyll fluorescence quenching: mechanism and effectiveness in protecting plants from photodamage. Plant Physiol 170:1903–1916 8. Rochaix JD (2014) Regulation and dynamics of the light-harvesting system. Annu Rev Plant Biol 65:287–309 9. Rochaix JD, Lemeille S, Shapiguzov A, Samol I, Fucile G, Willig A, GoldschmidtClermont M (2012) Protein kinases and phosphatases involved in the acclimation of the photosynthetic apparatus to a changing light environment. Philos Trans R Soc Lond Ser B Biol Sci 367:3466–3474 10. Go¨hre V, Jones AM, Sklenárˇ J, Robatzek S, Weber AP (2012) Molecular crosstalk between PAMP-triggered immunity and photosynthesis. Mol Plant-Microbe Interact 25:1083–1092 11. Tikkanen M, Gollan PJ, Mekala NR, Isoja¨rvi J, Aro EM (2014) Light-harvesting mutants show differential gene expression upon shift to high light as a consequence of photosynthetic redox and reactive oxygen species metabolism. Philos Trans R Soc Lond Ser B Biol Sci 369:20130229 12. Baker NR (2008) Chlorophyll fluorescence: a probe of photosynthesis in vivo. Annu Rev Plant Biol 59:89–113 13. Murchie EH, Lawson T (2013) Chlorophyll fluorescence analysis: a guide to good practice and understanding some new applications. J Exp Bot 64:3983–3998 14. Kalaji HM, Schansker G, Ladle RJ, Goltsev V, Bosa K, Allakhverdiev SI, Brestic M, Bussotti F, Calatayud A, Da˛browski P, Elsheery NI, Ferroni L, Guidi L, Hogewoning SW, Jajoo A, Misra AN, Nebauer SG, Pancaldi S, Penella C, Poli D, Pollastrini M, RomanowskaDuda ZB, Rutkowska B, Seroˆdio J, Suresh K, Szulc W, Tambussi E, Yanniccari M, Zivcak M (2014) Frequently asked questions about

in vivo chlorophyll fluorescence: practical issues. Photosynth Res 122:121–158 15. Kalaji HM, Schansker G, Brestic M, Bussotti F, Calatayud A, Ferroni L, Goltsev V, Guidi L, Jajoo A, Li P, Losciale P, Mishra VK, Misra AN, Nebauer SG, Pancaldi S, Penella C, Pollastrini M, Suresh K, Tambussi E, Yanniccari M, Zivcak M, Cetner MD, Samborska IA, Stirbet A, Olsovska K, Kunderlikova K, Shelonzek H, Rusinowski S, Ba˛ba W (2017) Frequently asked questions about chlorophyll fluorescence, the sequel. Photosynth Res 132:13–66 16. Schreiber U, Schliwa U, Bilger W (1986) Continuous recording of photochemical and non-photochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosynth Res 10:51–62 17. Nedbal L, Soukupová J, Kaftan D, Whitmarsh J, Trtı´lek M (2000) Kinetic imaging of chlorophyll fluorescence using modulated light. Photosynth Res 66:3–12 18. Maxwell K, Johnson GN (2000) Chlorophyll fluorescence – a practical guide. J Exp Bot 51: 659–668 19. Waszczak C, Carmody M, Kangasja¨rvi J (2018) Reactive oxygen species in plant signaling. Annu Rev Plant Biol 69:209–236 20. Exposito-Rodriguez M, Laissue PP, YvonDurocher G, Smirnoff N, Mullineaux PM (2017) Photosynthesis-dependent H2O2 transfer from chloroplasts to nuclei provides a high-light signalling mechanism. Nat Commun 8:49 21. Murata N, Allakhverdiev SI, Nishiyama Y (2012) The mechanism of photoinhibition in vivo: re-evaluation of the roles of catalase, α-tocopherol, non-photochemical quenching, and electron transport. Biochim Biophys Acta 1817:1127–1133 22. Shapiguzov A, Vainonen JP, Hunter K, Tossavainen H, Tiwari A, Ja¨rvi S, Hellman M, Aarabi F, Alseekh S, Wybouw B, Van Der Kelen K, Nikkanen L, Krasensky-Wrzaczek J, Sipari N, Keina¨nen M, Tyystja¨rvi E, Rintama¨ki E, De Rybel B, Saloja¨rvi J, Van Breusegem F, Fernie AR, Brosche´ M, Permi P, Aro EM, Wrzaczek M, Kangasja¨rvi J (2019) Arabidopsis RCD1 coordinates chloroplast and mitochondrial functions through interaction with ANAC transcription factors. elife 8:e43284 23. De Clercq I, Vermeirssen V, Van Aken O, Vandepoele K, Murcha MW, Law SR, Inze´ A, Ng S, Ivanova A, Rombaut D, van de Cotte B, Jaspers P, Van de Peer Y, Kangasja¨rvi J, Whelan J, Van Breusegem F (2013) The membrane-bound NAC transcription factor

PAM Fluorometry in Plant Stress Studies ANAC013 functions in mitochondrial retrograde regulation of the oxidative stress response in Arabidopsis. Plant Cell 25:3472– 3490 24. Ng S, Ivanova A, Duncan O, Law SR, Van Aken O, De Clercq I, Wang Y, Carrie C, Xu L, Kmiec B, Walker H, Van Breusegem F, Whelan J, Giraud E (2013) A membranebound NAC transcription factor, ANAC017, mediates mitochondrial retrograde signaling in Arabidopsis. Plant Cell 25:3450–3471 25. Pfannschmidt T, Terry MJ, Van Aken O, Quiros PM (2020) Retrograde signals from endosymbiotic organelles: a common control principle in eukaryotic cells. Philos Trans R Soc Lond Ser B Biol Sci 375:20190396 26. Shapiguzov A, Nikkanen L, Fitzpatrick D, Vainonen JP, Gossens R, Alseekh S, Aarabi F, Tiwari A, Blokhina O, Panzarová K, Benedikty Z, Tyystja¨rvi E, Fernie AR, Trtı´lek M, Aro EM, Rintama¨ki E, Kangasja¨rvi J (2020) Dissecting the interaction of photosynthetic electron transfer with mitochondrial signalling and hypoxic response in the Arabidopsis rcd1 mutant. Philos Trans R Soc Lond Ser B Biol Sci 375:20190413 27. Jacques CN, Hulbert AK, Westenskow S, Neff MM (2020) Production location of the gelling agent Phytagel has a significant impact on Arabidopsis thaliana seedling phenotypic analysis. PLoS One 15:e0228515 28. Weigel D, Glazebrook J (2006) Kanamycin selection of transformed arabidopsis. Cold Spring Harb Prot 2006:pdb.prot4669-pdb. prot4669 29. Lindsey BE 3rd, Rivero L, Calhoun CS, Grotewold E, Brkljacic J (2017) Standardized

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Part II Methods to Visualize ROS and to Detect Changes in Redox Homeostasis

Chapter 5 Live Monitoring of ROS-Induced Cytosolic Redox Changes with roGFP2-Based Sensors in Plants Jose´ Manuel Ugalde, Lara Fecker, Markus Schwarzla¨nder, Stefanie J. Mu¨ller-Schu¨ssele, and Andreas J. Meyer Abstract Plant cells produce reactive oxygen species (ROS) as by-products of oxygen metabolism and for signal transduction. Depending on their concentration and their site of production, ROS can cause oxidative damage within the cell and must be effectively scavenged. Detoxification of the most stable ROS, hydrogen peroxide (H2O2), via the glutathione-ascorbate pathway may transiently alter the glutathione redox potential (EGSH). Changes in EGSH can thus be considered as an indicator of the oxidative load in the cell. Genetically encoded probes based on roGFP2 enable extended opportunities for in vivo monitoring of H2O2 and EGSH dynamics. Here, we provide detailed protocols for live monitoring of both parameters in the cytosol with the probes Grx1-roGFP2 for EGSH and roGFP2-Orp1 for H2O2, respectively. The protocols have been adapted for live cell imaging with high lateral resolution on a confocal microscope and for multi-parallel measurements in whole organs or intact seedlings in a fluorescence microplate reader. Elicitor-induced ROS generation is used for illustration of the opportunities for dynamic ROS measurements that can be transferred to other research questions and model systems. Key words Grx1-roGFP2, roGFP2-Orp1, ROS, Plate reader, CLSM, Glutathione disulfide reductase, NADPH oxidase, flg22

1

Introduction Reactive oxygen species (ROS) are formed ubiquitously in cells exposed to molecular oxygen. Superoxide (O2
) is generated as a by-product of oxygenic photosynthesis, by the mitochondrial electron transport chain and extracellularly by plasma membranelocalized NADPH oxidases (in plants RBOH) [1, 2]. Due to its extremely high reactivity with itself, other radicals, and transition metals in aqueous medium, O2
 has an estimated half-life of only few μs in a cellular environment. It is usually rapidly converted to hydrogen peroxide (H2O2), which has an estimated half-life in the low ms range in the cell [3]. Cellular superoxide dismutases (SODs)

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_5, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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mediate this conversion speeding up the reaction by 104 orders of magnitude compared to spontaneous conversion [4, 5]. In plants, increased production of ROS has been observed under several stress situations [6] as well as during developmental processes, such as polarized growth in root hairs and pollen tubes [7, 8] or the transition from proliferation to differentiation in root tips [9]. While still being reactive and potentially damaging, H2O2 also acts as a signaling molecule that induces posttranslational modifications on proteins with redox-reactive cysteine residues. These modifications may alter the structural properties and activities of proteins [10, 11]. Indirect H2O2-dependent signaling may also occur via the cellular glutathione redox buffer if significant fluxes of H2O2 are detoxified via the glutathione-ascorbate pathway, which can lead to a transient change in the glutathione redox potential (EGSH) [12, 13]. The signaling function of H2O2 implies dynamic changes in H2O2 fluxes to ensure that activation or inactivation of downstream target proteins is only transient. Most assays for H2O2 based on chemical dyes such as 20 ,70 -dichlorodihydrofluorescein diacetate or dihydrorhodamine 123 can, however, only monitor ROS accumulation but fail to report any dynamics. Limitations in the dynamic monitoring of ROS have been partially overcome with the development of a whole series of genetically encoded redox biosensors [14]. Redox-sensitive GFP (roGFP) in conjunction with glutaredoxin (Grx) as a thiol-disulfide switch operator equilibrates with the local EGSH in a reversible manner and provides dynamic information about the EGSH in its direct vicinity, i.e., typically a specific cell compartment [15, 16]. roGFP probes have two excitation peaks with maxima at 395 nm for the protonated neutral form of the chromophore (A-band) and at 490 nm for the de-protonated anionic form (B-band) (see Fig. 1) [17]. The two excitation peaks show opposite redox-dependent changes in fluorescence intensity and are separated by the redox-indifferent isosbestic point. With these spectral characteristics, roGFP-probes are bona fide ratiometric sensors. The H2O2 sensors of the HyPer family contain the redox-active domain from the bacterial oxidation-sensitive transcription factor OxyR as redox-reactive specificity unit, which has been separated into two parts and fused to the N- and C-terminal ends of circularly permuted YFP (cpYFP). Oxidation of the reactive Cys residues of the OxyR domain by H2O2 triggers a conformational change that modifies the structural environment of the chromophore. As a result, the HyPer probes can report changes in H2O2 concentrations [18–21]. The ratiometric redox response of all these reporters enable normalized measurements that are independent of the amount of sensor protein present in cells or subcellular compartments. To respond dynamically, the sensors require re-reduction. Electrons must be provided by endogenous redox systems of the

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Fig. 1 Spectral properties of purified roGFP2-Orp1. (a) Fluorescence excitation spectra recorded for fully reduced (light gray) or fully oxidized (dark gray) probes. Superposition of excitation spectra for reduced and oxidized sensors reveals the redox-indifferent isosbestic point at 422 nm. The two spectral areas left and right of the isosbestic point are labeled as A-band and B-band. (b) Relative redox-dependent changes in fluorescence intensities along the entire excitation spectrum. Fold changes in fluorescence were calculated for each wavelength from intensities in panel (A) as Imax(λ)/Imin(λ), which is IH2O2/IDTT for the A-band (light grey triangles) and IDTT/IH2O2 for the B-band (dark gray squares). Note that for the total spectral dynamic range of the sensor, the relative changes at the chosen excitation wavelengths of the A- and the B-band need to be multiplied. Data are means of 4 replicates and are taken from an experimental dataset previously reported in [23], Fig. 2a

local cell compartment, such as the glutathione system or thioredoxins (TRXs), depending on the sensor [22, 23]. Most HyPer probes are extremely pH-sensitive and thus require careful pH control or parallel recording of pH [22]. This persisting drawback has been overcome only recently with the introduction of HyPer7 [20, 21]. Another possibility for pH-independent sensing of H2O2 levels inside cells has been reported with roGFP2-based probes that use the yeast glutathione peroxidase Orp1 (also named Gpx3) or a single-cysteine variant of the peroxiredoxin Tsa2 as redox-reactive specificity domains [16, 24]. The dynamic responses of both HyPer family proteins and roGFP2-Orp1 depend on the relative rates of oxidation by H2O2 versus the rate of reduction by the interacting endogenous thiol system. Consequently, calibrations to determine absolute H2O2 levels do not carry any meaning; instead the sensors are well suited to monitor physiologically meaningful relative redox changes in time and space. Visualization of sensor redox status can be achieved by confocal laser scanning microscopy (CLSM) [25]. If a focus on a specific tissue area is not required or even unfavorable (e.g., due to heterogeneity), it is also possible to record the dynamic response of the respective sensors for EGSH and H2O2 in plant cells, leaf samples, or even whole seedlings using a fluorescence microplate reader. Importantly, genetic targeting of the sensors maintains subcellular specificity of the measurements across the measured tissues, even

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though the structures are not individually resolved. This approach is particularly well suited for measurements over several hours, can cover high numbers of samples, replicates and/or controls in parallel, and can be expanded towards in situ biosensor multiplexing [23, 26, 27]. Here, we provide protocols on how to use the Grx1-roGFP2 and roGFP2-Orp1 probes in both CLSM- and plate reader-based experiments for live monitoring of ROS-dependent redox changes in the cytosol. All approaches described here can be extended to measurements in other subcellular compartments assuming lines with appropriate sensor targeting are available.

2

Materials

2.1 Plant Material and Growth Conditions

1. Seeds of Arabidopsis lines constitutively expressing Grx1roGFP2 or roGFP2-Orp1 in the cytosol. 2. Media plates for growing young seedlings: Agar plates with 0.5x Murashige and Skoog growth medium, 0.1% (w/v) sucrose, 0.05% (w/v) MES (pH ¼ 5.8, KOH), and 0.8% (w/v) phytoagar (see Note 1). 3. Pots for growing plants in soil to rosette stage: Jiffy-7®-pellets (Jiffygroup, Oslo, Norway) (see Note 1). 4. Growth chamber capable of maintaining controlled conditions with a long day regime (16 h light, 100–120 μmol photons m2 s1, 19  C; 8 h dark, 17  C) with a relative humidity of 50%.

2.2 Assay Media and Stock Solutions

1. Imaging buffer: 10 mM MES, 10 mM MgCl2, 10 mM CaCl2, 5 mM KCl, pH ¼ 5.8 (KOH) supplemented with the different compounds for specific experiments. 2. 5–10 mM H2O2 and 5–10 mM DTT (dithiothreitol) dissolved in imaging buffer to achieve full oxidation or reduction of the sensors, respectively. 3. 100 mM luminol (5-amino-2,3-dihydrophthalazine-1,4dione) dissolved in DMSO (dimethyl sulfoxide). 4. 10 mg mL1 horseradish peroxidase (HPR) dissolved in distilled water. 5. 1 mM flg22 peptide dissolved in distilled water.

2.3 Confocal Laser Scanning Microscopy and Perfusion Setup

1. Confocal microscope equipped with laser lines for 405 nm and 488 nm to excite both roGFP2-based sensors and fluorescence detection in the 505 nm to 530 nm band. Here, a Zeiss LSM780 confocal microscope (Carl Zeiss Microscopy GmbH, Jena, Germany) equipped with a 25 mW Ar/MLlaser and a 30 mW 405 nm diode laser was used, but other

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confocal microscopes with laser lines of the same wavelengths are suitable, assuming sequential excitation is possible. 2. A 25x (NA 0.8) objective to image root regions or epidermal tissue areas or a 40x (NA 1.2) for imaging single cells of the cotyledon, leaf, or hypocotyl epidermis (see Note 2). 3. Glass slides and coverslips (typically #1.5; thickness 0.17 mm depending on the exact objective used). 4. Featherweight forceps. 5. Adhesive rubber tape. 6. RC-22 perfusion chamber mounted on a P1 platform (Warner Instruments, Hamden CT) or similar. 7. Steel anchor harp with a 1.5 mm grid mesh to mount the seedling inside a perfusion chamber. The model SHD-22L/ 15 (Warner Instruments) was used for the RC-22 chamber. 8. Open 50 mL syringes connected to a VC-8M valve controller (Warner Instruments). 9. 1.5 mm polyethylene tubes (Warner Instruments). 10. Peristaltic pump (Ismatec, Wertheim, Germany) (see Fig. 2a). 2.4 Plate Reader Setup

1. Plate reader equipped with a monochromator and suitable filters for the two excitation maxima of both roGFP2-based sensors (e.g., 400  5 nm and 480  5 nm) and a 520  5 nm emission filter, and a detector capable of detecting fluorescence and luminescence. Here, a CLARIOstar plate reader (BMG Labtech, Ortenberg, Germany) was used. 2. Polystyrene 96-well microtiter plates (Sarstedt, Nu¨mbrecht, Germany) with transparent flat bottom. 3. Dissecting needle.

2.5 Image and Data Analysis Software

1. Redox Radio Analysis (RRA) software for MATLAB (The MathWorks, Natick, MA) ([28]; https://markfricker.org/). 2. MARS Data Analysis Software (BMG Labtech). 3. MS Excel. 4. Statistical computing software such as R (https://www.rproject.org/) or GraphPad Prism (GraphPad Software, San Diego, CA) (https://www.graphpad.com/scientific-software/ prism/).

3

Methods The methods described below are based on the genetically encoded roGFP2 reporter constructs Grx1-roGFP2 and roGFP2-Orp1. Both sensors have been characterized in vitro and in vivo and

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Fig. 2 Live monitoring of roGFP2-based sensors using a perfusion system. (a) Scheme of the perfusion setup (made in ©BioRender - biorender.com). All treatments are provided in 50 mL syringes and fed into the chamber by gravity. The influx of each treatment solution is set by a central valve controller with a single

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have been frequently used for live monitoring of EGSH and H2O2, respectively. The biochemical and biophysical properties of the sensors are summarized in Table 1 (see Note 3). 3.1

CLSM Methods

3.1.1 Sample Mounting for Steady-State Measurements

1. Prepare a microscope slide with two stripes of standard adhesive rubber tape to create a 180–250 μm spacer that will protect the sample from being squeezed by the coverslip. 2. Screen Arabidopsis seedlings grown on vertically oriented agar plates for fluorescence under a stereo microscope equipped with the excitation/emission filters for GFP. Indicate the positive seedlings on the plate with a marker pen (see Notes 4 and 5). 3. Carefully take a seedling using featherweight forceps, and place it on the microscope slide pre-loaded with a drop of imaging buffer. 4. Place a coverslip over the sample, and secure it with two pieces of adhesive tape. 5. If the slide is not completely filled with imaging buffer, add additional buffer from the edge to fill the space between the slide and the coverslip. 6. Mount the slide on the microscope stage and secure it with stage clips. 7. Select a lens. The 40x lens (NA 1.2) is recommended to image whole epidermal cells, while the 25x (NA 0.8) is recommended to see entire root tips. 8. Illuminate the sample in transmission mode, locate and focus on the tissue to image. 9. Perform the measurements as detailed in Subheadings 3.1.3 or 3.1.4.

3.1.2 Perfusion System Setup

1. Place a 22  40 mm coverslip on the bottom of the perfusion chamber, and secure it with the side clamps (see Fig. 2a). 2. Remove the piston from 50 mL syringe, and fill each syringe with either 5–10 mM H2O2, 5–10 mM DTT, or imaging buffer. It is recommended to fill the syringes up to the same levels to start with the same flow. For this setup the gravity-

ä Fig. 2 (continued) output connected to the perfusion chamber. In the chamber, the plant tissue is held in place by a steel anchor, and all excess media are continuously collected through suction generated by a peristaltic pump and discarded. (b) Calibration of roGFP2 probes in Arabidopsis roots. Root tissues of wild-type plants expressing cytosolic Grx1-roGFP2 or roGFP2-Orp1 were treated as indicated in the plot, and the fluorescence ratio 405 nm/488 nm was recorded over time. (c) False-colored ratio images indicate the redox state of the sensors at different points during the time course

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Table 1 Characteristics of roGFP2-based sensors for the glutathione redox status (EGSH) and hydrogen peroxide (H2O2) Parameter

EGSH

H2O2

Sensor

Grx1-roGFP2

roGFP2-Orp1

Localization

Cytosol (see Note 2)

Promoter (see Note 4)

proUBQ10

pro35S

(from Arabidopsis)

(from CaMV)

Plasmid backbone

pBinCM

pH2GW7

Resistance in plants

Kanamycin

Hygromycin

Fluorescent protein

EGFP

EGFP

Operator/sensor

Human glutaredoxin 1 (hGrx1) Yeast glutathione peroxidase like 3 (Gpx3/Orp1)

Excitation maximum (see Fig. 1)

395 nm, 490 nm

Excitation wavelength (for CLSM)

405 nm, 488 nm

Excitation filter (for plate reader)

400  5 nm, 480  5 nm

Emission maximum

511 nm

Emission bandwidth (for CLSM)

505–530 nm

Emission filter (for plate reader)

520  5 nm

Ratio calculation

Excitation A-band/excitation B-band (see Fig. 1 and Note 6)

Mid-point potential

280 mV

Dynamic range (purified sensor, in vitro)

12 390/480 nm

8 (pH > 6.5) 400/482 nm

Dynamic range (in plants)

5 (CLSM, 405 nm/488 nm) ~3.5 (Plate reader, 400 nm/480 nm)

~6.5 (CLSM, 405 nm/488 nm) ~4.2 (Plate reader, 400 nm/480 nm)

Linear range for measurements

245 to 315 mV

N/A

Key references

[15–17, 25, 32]

[23, 33, 34]

dependent flow rate is 10 mL min1, but may be modified by different tubing or restricting the flow. 3. Prime the tubes connected to the syringes carefully removing all air bubbles using the valve controller.

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4. Place the steel anchor harp on a small petri dish, with the mesh facing upward, on a drop of water. 5. Carefully place a 4–5-day-old Arabidopsis seedling (pre-screened for fluorescence; see Subheading 3.1.1) on top of the mesh using featherweight forceps (see Note 7). Avoid the area of interest to be imaged being too close to the mesh since its material is autofluorescent when illuminated at 405 nm. 6. Put a drop of imaging buffer into the perfusion chamber, and insert the steel anchor harp. The sample should remain between the coverslip and the mesh. 7. Mount the chamber on the microscope stage and secure it with stage clips. 8. Start perfusing imaging buffer into the chamber, and close the top of the chamber with a second coverslip. 9. Connect the suction tube to the suction reservoir, and collect the excess volume with a peristaltic pump. Adjust the aspiration rate to be equal to the flow into the perfusion chamber. 3.1.3 Elicitor-Induced ROS Generation and Sensor Calibration

1. Incubate a 2-week-old Arabidopsis seedling (pre-screened for fluorescence; see Subheading 3.1.1) in a 10 μM flg22 solution for 15 or 30 min. 2. Carefully transfer the seedling to a microscope slide between two stripes of adhesive tape (see Subheading 3.1.1). 3. Carefully place a coverslip on top of the sample, without damaging the seedling. 4. Proceed as described in Subheading 3.1.1, step (5) onwards. 5. To calibrate the sensor on the perfusion system, perfuse for 10 min 5–10 mM H2O2 and 5–10 mM DTT (see Note 8). We recommend perfusing imaging buffer for at least 10 min between treatments (see Fig. 2b, c). To calibrate the sensor on steady-state measurements, incubate the seedlings for 10 min in 5–10 mM H2O2 to fully oxidize or 5–10 mM DTT to fully reduce the sensor (see Note 8). After incubation in either H2O2 or DTT, place the seedlings carefully on a slide with a drop of the selected treatment solution for steady-state measurements (see Fig. 3). Root tips are best for imaging due to their permeability, but treatments on cotyledons or hypocotyl are possible (see Note 8).

3.1.4 CLSM Settings

1. Set up two tracks for imaging roGFP2-based sensors with excitation at 405 nm and 488 nm, respectively. roGFP2 fluorescence is to be recorded in one channel between 508 nm and 530 nm for each track. An extra channel on the 405 nm track is used for detecting sample autofluorescence between

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Fig. 3 Cytosolic Grx1-roGFP2 and roGFP2-Orp1 respond to elicitor-induced oxidation in epidermal cells of A. thaliana leaves. True leaves of 2-week-old Arabidopsis wild-type plants (WT) and the GR1-deficient mutant gr1-1 expressing Grx1-roGFP2 and roGFP2-Orp1 were treated with the bacterial elicitor flg22 (10 μM) for different time periods (15 and 30 min) to visualize the oxidative response. As control, leaves were treated with imaging buffer. For calibration, the samples were fully reduced (red) and fully oxidized (ox) with 10 mM DTT and 10 mM H2O2, respectively. (a) For confocal live cell imaging, both roGFP2-based sensors were excited at 405 nm and 488 nm and fluorescence collected from 508 nm to 530 nm. The upper panels are a merge between images from the 405 nm (red) and 488 nm (green) channels. The false-colored ratio images indicate the redox state of the sample (lower panels). Scale bars ¼ 10 μm. (b) Quantitative analysis of flg22- induced oxidation in Arabidopsis leaves. Box plots indicate the log10 of the fluorescence ratios 405/488 nm of all measured samples expressing Grx1-roGFP2 or roGFP2-Orp1. For statistical analysis, a two-way ANOVA with Tukey’s multiple comparison test and a confidence level of P ¼ 0.05 was conducted. Line ¼ median, whiskers ¼ min to max. n ¼ 5

430 nm and 470 nm, while an extra channel on the 488 nm track can be used to collect chlorophyll autofluorescence in green tissues.

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2. Select line switching as scan mode for the two tracks and an averaging of maximum two scans. Set the pixel dwell time to 1.27 μs/pixel and the frame size to 512  512 pixels with a data depth of 12 bits. These settings will limit the required time for imaging to about 2.46 s per frame, which allows monitoring fast redox changes during perfusion treatments. 3. Adjust the master gain to the same value (within the linear range of the detector at a maximal value of 800) for the channels detecting roGFP2 and autofluorescence excited at 405 nm. For quantitative imaging, it is crucial that neither the laser power, nor the detector gain of these channels is changed during an experiment. For the transmitted light channel and chlorophyll autofluorescence, the gain can be adjusted independently. 4. Start the “live” preview scan of the sample fluorescence with the range indicator lookup table for image display. Adjust the power of the 488 nm laser until a clear and structured fluorescent signal is visible from the sensor. Adjust gain and offset to set the image into the dynamic range: The master gain for the roGFP channels (405 nm and 488 nm excitation) and the autofluorescence channel (405 nm excitation) must be kept identical over the course of the experiment to allow quantitative comparison. Increase the power of the 405 nm to double the power output of the 488 nm laser (e.g., 2% power for 488 nm; 4% power for 405 nm) (see Note 9). 5. After adjustment of the imaging settings, it is crucial to keep them unchanged between samples. Any modification will affect the resulting ratios, and make comparison of fluorescence ratios between samples impossible. 6. Take an image of an analogous tissue region of a wild-type plant with your final settings in order to determine the bleedthrough of autofluorescence excited at 405 nm to your GFP emission channel. 3.1.5 Data Collection and Analysis

1. Steady-state images or time series are recorded by the microscope software as Zeiss LSM files (*.lsm) or other formats. A minimum of 12 images is recommended to compare genotypes or treatments. 2. Either use the MatLab-based Redox Radio Analysis (RRA) software [28] tailored to the analysis of data of genetically encoded biosensors, or other image analysis software such as, e.g., Image J. 3. Subtract the background from each image. 4. Correct the roGFP2 emission channel at 405 nm excitation for bleed-through of autofluorescence excited at 405 nm: Use images taken on wild-type samples (see Subheading 3.1.4,

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step (6)) to determine the factor between the autofluorescence measured between 430 and 470 nm and the bleed-through to the roGFP emission channel. Subtract the autofluorescence measured for each image multiplied by this determined factor from the roGFP emission at 405 nm excitation. More detailed information is available in the RRA handbook (https:// markfricker.org/) (see Note 10). 5. Calculate the ratio between the corrected roGFP2 emission at 405 nm excitation and the roGFP2 emission at 488 nm excitation for each pixel in the image (see Note 11). 6. Generate a ratio image by using the values measured during calibration as minimum (0% sensor oxidation) and maximum (100% sensor oxidation) values of the color scale. 7. Calculate the average 405/488 ratio for each image. 8. Log10-transform ratio values (see Note 12) and do statistical analysis of differences between treatments or genetic backgrounds. 9. Fluorescence ratios may be converted to the degree of oxidation of roGFP2 and/or EGSH in mV. For further details, see [15, 25, 28]. 3.2 Plate Reader Methods

1. Pre-screen the vertically grown seedlings for fluorescence (see Subheading 3.1.1).

3.2.1 Sample Mounting of Whole Seedlings

2. Fill a 10 cm petri dish with 10 mL imaging buffer, and pipette 200 μL imaging buffer in all wells required for the experiment (see Note 13). 3. Use a modified dissecting needle with its tip being bent to form a hook, to carefully pick up a single seedling at the hypocotyl and transfer it into the imaging buffer in the petri dish. This action will discharge the static electricity on the seedlings, which makes it easier to place them in the 96-well plate. Repeat the process to pool 3–4 seedlings per well, and set up at least 4–6 replicates for each treatment (see Notes 14 and 15). 4. Control seedlings from the same genetic background without sensor expression should be nounted on the same well plate to be used for background and autofluorescence subtraction. 5. To calibrate the sensor at the beginning of the experiment, transfer seedlings to four wells filled with either 5–10 mM H2O2 or 5–10 mM DTT in imaging buffer, to fully oxidize or reduce the sensor, respectively. Alternatively, calibrations can be done on each single well at the end of the experiment by replacing the buffer first with 5–10 mM DTT and subsequently with 5–10 mM H2O2. Fluorescence readings need to be taken for samples immersed in DTT and H2O2, respectively.

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1. For leaf discs, 1–2 discs of 8 mm diameter are cut with a cork borer from a fully expanded leaf of 4-week-old plants. Since the cut is made from the adaxial side, it is recommended to use a flat surface as support from the abaxial side of the leaf. For instance, a piece of cardboard may be used. 2. Transfer a maximum of 8 discs per well on a 6 well-plate pre-loaded with 2 mL imaging buffer using a pair of featherweight forceps. Float the discs with the abaxial side down, and incubate them in the dark overnight to minimize sensor oxidation due to the wounding stress. After incubation, discard the buffer and refill with fresh buffer in order to remove any leaked ions after the cut. Transfer each leaf disc to a single well on a 96 well-plate pre-loaded with 200 μL imaging buffer. 3. Push the disc to the bottom of the well using a second pair of forceps. Since the well (7 mm) is slightly smaller than the disc (8 mm), the disc should not move from the bottom (see Note 16). 4. Control discs from the same genetic background without sensor expression should be used for background and autofluorescence subtraction. 5. Calibration of the sensor should be performed as indicated in Subheading 3.2.1, step (5).

3.2.3 Settings for Spectral Measurements

1. Place the 96 well-plate with the seedlings or leaf discs in the plate reader. 2. Define the layout of the samples in the plate reader software. 3. Run an excitation spectrum scan, from 350 to 495 nm while collecting the fluorescence with the 520  5 nm emission filter (see Note 17). 4. Set the gain and focal height. Use 480 nm excitation, since it is close to excitation maximum of roGFP2 yielding a more intense fluorescence signal. Gain and focal height should be measured in at least 6 different wells, and the average value should be used (see Note 18). It is recommended to adjust the gain to reach 50% of the maximum detectable fluorescence in order to avoid saturation of the detector, which would invalidate the measurement. As a reference, use samples incubated in 10 mM DTT. 5. Set a high number of flashes per well (>30). This will create an average value for each excitation wavelength with improved signal-to-noise, which will result in smooth fluorescence spectra. 6. If available, define the recording as “orbital averaging” with flashes exciting the sample along a circle with no less than 3 mm diameter. Averaging the fluorescence of different areas of the

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same sample will increase the reliability of the measurements. This is particularly important when the plant tissue does not cover the full well area, as typically the case for seedlings. 3.2.4 Settings for Ratiometric Time Course Measurements

1. Place the 96 well-plate with the seedlings or leaf discs in the plate reader. 2. Define the layout of the samples in the software. 3. If auto-injection is required, prepare the treatment stock solutions, and prime the injectors within the plate reader. It is recommended to prepare no less than 5 mL since the pump cylinder of the auto-injection pump holds 500 μL. 4. Set the excitation wavelengths for the two channels to 400  5 nm and 480  5 nm, respectively. In both cases, the emission is set to 520  5 nm (see Note 19). 5. Set the gain and focal height as mentioned in Subheading 3.2.3, step (4). Subsequently, follow the same routine to set the gain for excitation at 405 nm on a sample incubated in 5–10 mM H2O2. 6. Adjust the number of flashes per well and orbital averaging depending on the required speed of measurement (see Subheading 3.2.3, steps (5) and (6)). To document fast reactions, a lower number of flashes is recommended. In contrast, measures for the calibration or steady states for roGFP2 fluorescence might benefit from increased averaging, which is achieved by more flashes per well.

3.2.5 Elicitor-Induced ROS Generation

1. Adjust the layout of the experiment on the plate reader software. 2. Prepare an assay solution of 20 μM flg22 from the stock. 3. Transfer the leaf discs from 4-week-old Arabidopsis plants, expressing any of the roGFP2-based sensors to the wells of a 96 well-plate pre-loaded with 50 μL imaging buffer (see Note 20). 4. Add 50 μL of the assay solution to each well, and start the measurement immediately. 5. Record the fluorescence of the channels as described in Subheading 3.2.4 for 2 h (see Fig. 4). 6. To measure extracellular ROS production, prepare the assay solution with 200 μM luminol, 20 μg/ml HRP, and 20 μM flg22 from the respective stock solutions (see Sect. 2.2). 7. Transfer the samples as indicated in steps (3) and (4). 8. Record the luminescence (see Fig. 4).

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Fig. 4 Time-resolved measurement of the extracellular and intracellular oxidative burst after elicitor-treatment of A. thaliana leaf discs. The combined graph shows the extracellular luminescence after reaction of luminol with ROS in the apoplast (open diamonds) and the intracellular response of Grx1-roGFP2 (darkgray circles) and roGFP2-Orp1 (light-gray circles) after the treatment of gr1-1 leaf discs with 10 μM flg22 (arrow). Data indicates the mean value  SD of the log10 of the 400 nm/480 nm fluorescence ratios collected from the entire tissue in the well. All measurements were done on a plate reader. For luminescence, n ¼ 3, for fluorescence, n ¼ 5 3.2.6 Data Collection and Analysis

1. For each comparison (genotype or treatment) a minimum of 8 replicates of seedling pools or leaf discs is recommended. Depending on the layout, these can be measured on the same run side by side. For non-fluorescent control samples, 5 replicates are sufficient. 2. Export the raw data to a spreadsheet using the data analysis software of the plate reader. 3. For processing of the fluorescence data, average the values of the non-fluorescent samples, and subtract the average value from the fluorescence recorded for samples expressing the sensors. Apply this for each condition tested (e.g., control and treatment). For each time point, divide the corrected fluorescence values of channel 1 (400 nm excitation) by the corrected fluorescence values from channel 2 (480 nm excitation) (see Subheading 3.2.3). 4. The dynamic range of the sensor can be estimated as the value obtained from the ratio values for fully oxidized and fully reduced samples.

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Notes 1. The age of Arabidopsis plants to use varies depending on the research question and requires careful individual consideration of technical and biological issues. 2–5-day-old seedlings grown vertically on plates under axenic conditions are particularly suitable for CLSM imaging of roGFP2-based biosensors. The small size at this developmental stage allows placement of whole seedlings in a perfusion chamber and enables whole seedling imaging. However, there may be other points to consider, such as the non-uniform expression pattern of FLS2 coding for the flagellin receptor, which would be critical for observation of ROS production induced by the elicitor flg22 [29, 30]. To obtain 4-week-old plants, it is recommended to grow them on Jiffy-7®-pellets. 2. To image the sensor targeted to subcellular compartments, such as mitochondria, a 40x (NA 1.2) water immersion objective is recommended [31]. Oil immersion lenses with NA 1.4 can provide results at high resolution for tissue layers just below the coverslip. To image whole seedlings, use a 10x and take various images that can be stitched using image editing software like Gimp, Adobe Photoshop, or the ZEN software from Zeiss. Lower magnification lenses help to avoid photodamage. 3. Both sensors have also been targeted to mitochondria by fusion with the transit peptide sequence either from Serine Hydroxymethyltransferase (SHMT; for roGFP2-Grx1; [32]) or from the Nicotiana plumbaginifolia ATP synthase ß-subunit of (for roGFP2-Orp1; [23]), or to plastids by cloning the Transketolase transit peptide (TKTP) to the N-termini of the sensors [13]). All lines expressing these constructs are available upon request. For measurements on mitochondria, see [31]. 4. Screening by fluorescence for transformants using a fluorescence stereomicroscope is particularly useful if resistance markers that are typically used for selection are present in the background already. In addition, screening or control for fluorescent plant materials under a stereomicroscope enables a first evaluation of the expression levels and potential inhomogeneity of the expression. Constitutive expression driven by the CaMV 35S or UBQ10 promoter may lead to silencing of the transgene as apparent from a decrease of fluorescence over generations and patchy expression of the sensor across a seedling. 5. Some reporter lines, like lines with roGFP targeted to mitochondria or roGFP expressed in some mutant backgrounds, can have a lower fluorescence compared to WT plants with cytosolic roGFP2 constructs driven by a strong promoter. This low fluorescence may be difficult to recognize under the

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stereomicroscope, and thus selection of suitable reporter lines requires particular care. 6. The fold change in fluorescence intensities along the entire excitation spectrum is not constant (see Fig. 1b). Therefore, the achievable dynamic range depends on the chosen wavelength combination. For selection of the most suitable wavelength combination, further parameters like absolute fluorescence intensities and the signal-to-noise ratio need to be taken into account. 7. Mount the seedling with the shoot oriented towards the inlet. This will decrease the risk of unintended movement of the root tip. 8. The appropriate concentration of DTT and H2O2 for the calibrations may vary with different tissues and organs and needs to be determined first. If no complete reduction or oxidation is achieved, a 10 min vacuum infiltration is recommended (for calibration purposes only) or increase the concentrations up to 50 mM. For reference values for the dynamic range, see Table 1. 9. If the sample fluorescence is too low, open the pinhole rather than increasing the laser power. This will minimize the risk of photodamage. To check if chosen settings are suitable for quantitative imaging, the in vivo calibration of the sensor in the respective plant material should be done first. Neither in the fully reduced nor the fully oxidized state many pixels should be saturated. After settings are chosen for quantitative imaging, pixel saturation can only be controlled through pinhole adjustment. Initial pinhole size should depend on the size of the imaged object (e.g., plastids vs. whole cells). Changing the pinhole diameter will also change the volume of sampling and therefore the thickness of the cell layer imaged. 10. Load each *.lsm file into the RRA software, and select a probe MatLab file with all the pre-set parameters for the analysis of each sensor. These parameters include, among others, the sensor midpoint redox potential and identification of the different channels. The range values (Rmin/Rmax) for the false-colored images of the 405 nm/488 nm fluorescence ratio need to be set according to the values obtained by the in vivo calibration. Follow the software interface to subtract the autofluorescence, align the channels if needed, and calculate the fluorescence ratio. The software will export the ratio data of all batched samples to an MS Excel file and the false-colored images as TIFF files. Express the dynamic range of the sensor as the value obtained from ratioox/ratiored. 11. With purified recombinant protein the maximum achievable spectroscopic dynamic range with 405 nm and 488 nm

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excitation is about ninefold for free roGFP2 and Grx1-roGFP2 and about sixfold for roGFP2-Orp1 [23, 25]. In live cells, the dynamic range is often slightly lower, typically between threeand sixfold. The exact value largely depends on the quality of the background and autofluorescence correction. Since the spectroscopic dynamic range at a given excitation wavelength combination is characteristic for a given biosensor and independent of instrument settings, it provides a control parameter for in vivo measurements that cannot exceed the corresponding in vitro value of the purified sensor protein. For further details, see [25, 28]. 12. The correlation between the absolute value of the mean and the variance in ratio data implies that higher ratios have bigger standard deviations. The unequal variance can be corrected for by log10 transformation, which will convert the skewed data distribution to a normal distribution. 13. Lower amounts of buffer can be also used, but the minimum recommended is 100 μL, to evenly cover the bottom of the well and to avoid evaporation during the run. 14. For plate reader measurements in 96-well plates, use 7-day-old vertically grown seedlings and a pool of 3–4 seedlings per well to obtain a good signal while limiting the time for sample preparation. To measure the sensor fluorescence in mature leaves, leaf discs or leaf rolls from 4-week-old plants can be used. In all cases, sufficient material is needed to cover the well area. 15. It is recommended to measure at least 4–6 wells, and average the calculated ratios to account for variability between individual wells. Before ratiometric analysis, all datasets should be pre-screened for any obvious technical inconsistencies. These might be fluorescence ratios far outside the plausible and calibrated spectroscopic dynamic range (see Note 11), a pronounced drift of both channels in the same direction during the course of an experiment, or lack of converse changes of the two fluorescence channels. Such problems might be caused by movement of samples in the wells or technical issues of the plate reader detection. To avoid including erroneous datasets, it is important to check that the fluorescence of the individual channels responds in the expected opposing manner and that all other parameters are fulfilled. Replicates that do not meet these criteria should be treated as outliers and not be considered for further analysis. 16. If leaf discs are treated with H2O2 for extended periods, the cells might lose their turgor, and leaf discs will float atop the medium. This will lead to loss of proper focal adjustment and hence affect the fluorescence measurements.

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17. The upper wavelength for the excitation spectrum is defined by the choice of the dichroic mirror and the emission wavelength. If spectra beyond the nominal emission maximum of the fluorophore are to be collected, appropriate dichroic mirrors and longer emission wavelengths need to be used. 18. Leaf discs placed at the bottom of the wells give uniform measurements of focal height while pools of seedlings can give a range of focal heights. In the latter case, it is recommended to measure at least 6 wells and average the height. 19. Many plant tissues show increasing autofluorescence when moving to wavelengths lower than about 400 nm, but autofluorescence can start to increase also above 400 nm. If the signal-to-noise ratio is too low, it is recommended to use a longer wavelength for excitation depending on the available filters, e.g., 410 nm. 20. In order to detect elicitor-induced ROS bursts in the cytosol via the local glutathione redox potential, we recommend using gr1-1 mutants to achieve higher sensitivity and better resolution.

Acknowledgments Support by the Deutsche Forschungsgemeinschaft through the Research Training Group GRK2064 (to AJM, MS and SJM-S) and through the priority program SPP1710 (to AJM and MS) is gratefully acknowledged. We thank our former lab members Thomas Nietzel, Stephan Wagner, and Philippe Fuchs for their seminal work in establishing protocols and analysis routines for live redox imaging and plate reader assays. References 1. Sagi M, Fluhr R (2006) Production of reactive oxygen species by plant NADPH oxidases. Plant Physiol 141:336–340. https://doi.org/ 10.1104/pp.106.078089 2. Qi J, Wang J, Gong Z, Zhou J-M (2017) Apoplastic ROS signaling in plant immunity. Curr Opin Plant Biol 38:92–100. https://doi.org/ 10.1016/j.pbi.2017.04.022 3. Møller IM, Jensen PE, Hansson A (2007) Oxidative modifications to cellular components in plants. Annu Rev Plant Biol 58:459–481. https://doi.org/10.1146/annurev.arplant.58. 032806.103946 4. Kliebenstein DJ, Monde RA, Last RL (1998) Superoxide dismutase in Arabidopsis: an eclectic enzyme family with disparate regulation and

protein localization. Plant Physiol 118:637– 650. https://doi.org/10.1104/pp.118.2.637 5. Wang Y, Branicky R, Noe¨ A, Hekimi S (2018) Superoxide dismutases: dual roles in controlling ROS damage and regulating ROS signaling. J Cell Biol 217:1915–1928. https:// doi.org/10.1083/jcb.201708007 6. Huang H, Ullah F, Zhou D-X et al (2019) Mechanisms of ROS regulation of plant development and stress responses. Front Plant Sci 10. https://doi.org/10.3389/fpls.2019. 00800 7. Foreman J, Demidchik V, Bothwell JHF et al (2003) Reactive oxygen species produced by NADPH oxidase regulate plant cell growth.

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Nature 422:442–446. https://doi.org/10. 1038/nature01485 8. Boisson-Dernier A, Lituiev DS, Nestorova A et al (2013) ANXUR receptor-like kinases coordinate cell wall integrity with growth at the pollen tube tip via NADPH oxidases. PLoS Biol 11:e1001719 9. Tsukagoshi H, Busch W, Benfey PN (2010) Transcriptional regulation of ROS controls transition from proliferation to differentiation in the root. Cell 143:606–616. https://doi. org/10.1016/j.cell.2010.10.020 10. Waszczak C, Carmody M, Kangasja¨rvi J (2018) Reactive oxygen species in plant signaling. Annu Rev Plant Biol 69:209–236. https:// doi.org/10.1146/annurev-arplant042817-040322 11. Smirnoff N, Arnaud D (2019) Hydrogen peroxide metabolism and functions in plants. New Phytol 221:1197–1214. https://doi.org/10. 1111/nph.15488 12. Meyer AJ (2008) The integration of glutathione homeostasis and redox signaling. J Plant Physiol 165:1390–1403. https://doi.org/10. 1016/j.jplph.2007.10.015 13. Ugalde JM, Fuchs P, Nietzel T et al (2021) Chloroplast-derived photo-oxidative stress causes changes in H2O2 and EGSH in other subcellular compartments. Plant Physiol 186: 125–141. https://doi.org/10.1093/plphys/ kiaa095 14. Mu¨ller-Schu¨ssele SJ, Schwarzla¨nder M, Meyer AJ (2021) Live monitoring of plant redox and energy physiology with genetically encoded biosensors. Plant Physiol 186:93–109. https://doi.org/10.1093/plphys/kiab019 15. Meyer AJ, Brach T, Marty L et al (2007) Redox-sensitive GFP in Arabidopsis thaliana is a quantitative biosensor for the redox potential of the cellular glutathione redox buffer. Plant J 52:973–986. https://doi.org/10. 1111/j.1365-313X.2007.03280.x 16. Gutscher M, Pauleau A-L, Marty L et al (2008) Real-time imaging of the intracellular glutathione redox potential. Nat Methods 5:553–559. https://doi.org/10.1038/nmeth.1212 17. Meyer AJ, Dick TP (2010) Fluorescent protein-based redox probes. Antioxid Redox Signal 13:621–650. https://doi.org/10. 1089/ars.2009.2948 18. Belousov VV, Fradkov AF, Lukyanov KA et al (2006) Genetically encoded fluorescent indicator for intracellular hydrogen peroxide. Nat Methods 3:281–286. https://doi.org/10. 1038/nmeth866 19. Ermakova YG, Bilan DS, Matlashov ME et al (2014) Red fluorescent genetically encoded

indicator for intracellular hydrogen peroxide. Nat Commun 5:5222. https://doi.org/10. 1038/ncomms6222 20. Pak VV, Ezerin¸a D, Lyublinskaya OG et al (2020) Ultrasensitive genetically encoded indicator for hydrogen peroxide identifies roles for the oxidant in cell migration and mitochondrial function. Cell Metab 31:642–653.e6. https:// doi.org/10.1016/j.cmet.2020.02.003 21. Ugalde JM, Schlo¨ßer M, Dongois A et al (2021) The latest HyPe(r) in plant H2O2 biosensing. Plant Physiol 187:480–484. https:// doi.org/10.1093/plphys/kiab306 22. Schwarzla¨nder M, Dick TP, Meyer AJ, Morgan B (2016) Dissecting redox biology using fluorescent protein sensors. Antioxid Redox Signal 24:680–712. https://doi.org/10.1089/ars. 2015.6266 23. Nietzel T, Elsa¨sser M, Ruberti C et al (2019) The fluorescent protein sensor roGFP2-Orp1 monitors in vivo H2O2 and thiol redox integration and elucidates intracellular H2O2 dynamics during elicitor-induced oxidative burst in Arabidopsis. New Phytol 221:1649–1664. https://doi.org/10.1111/nph.15550 24. Morgan B, Van Laer K, Owusu TNE et al (2016) Real-time monitoring of basal H2O2 levels with peroxiredoxin-based probes. Nat Chem Biol 12:437–443. https://doi.org/10. 1038/nchembio.2067 25. Schwarzla¨nder M, Fricker MD, Mu¨ller C et al (2008) Confocal imaging of glutathione redox potential in living plant cells. J Microsc 231: 299–316. https://doi.org/10.1111/j. 1365-2818.2008.02030.x 26. Rosenwasser S, Rot I, Meyer AJ et al (2010) A fluorometer-based method for monitoring oxidation of redox-sensitive GFP (roGFP) during development and extended dark stress. Physiol Plant 138:493–502. https://doi.org/10. 1111/j.1399-3054.2009.01334.x 27. Wagner S, Steinbeck J, Fuchs P et al (2019) Multiparametric real-time sensing of cytosolic physiology links hypoxia responses to mitochondrial electron transport. New Phytol 224: 1668–1684. https://doi.org/10.1111/nph. 16093 28. Fricker MD (2016) Quantitative redox imaging software. Antioxid Redox Signal 24:752– 762. https://doi.org/10.1089/ars.2015. 6390 29. Beck M, Wyrsch I, Strutt J et al (2014) Expression patterns of FLAGELLIN SENSING 2 map to bacterial entry sites in plant shoots and roots. J Exp Bot 65:6487–6498. https://doi. org/10.1093/jxb/eru366

Live Monitoring of ROS-Induced Redox Changes 30. Zou Y, Wang S, Zhou Y et al (2018) Transcriptional regulation of the immune receptor FLS2 controls the ontogeny of plant innate immunity. Plant Cell 30:2779–2794. https://doi. org/10.1105/tpc.18.00297 31. Wagner S, Nietzel T, Aller I et al (2015) Analysis of plant mitochondrial function using fluorescent protein sensors. Methods Mol Biol 1305:241–252. https://doi.org/10.1007/ 978-1-4939-2639-8_17 32. Albrecht SC, Sobotta MC, Bausewein D et al (2014) Redesign of genetically encoded biosensors for monitoring mitochondrial redox status in a broad range of model eukaryotes. J

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Biomol Screen 19:379–386. https://doi.org/ 10.1177/1087057113499634 33. Gutscher M, Sobotta MC, Wabnitz GH et al (2009) Proximity-based protein thiol oxidation by H2O2-scavenging peroxidases. J Biol Chem 284:31532–31540. https://doi.org/ 10.1074/jbc.M109.059246 34. Albrecht SC, Barata AG, Großhans J et al (2011) In vivo mapping of hydrogen peroxide and oxidized glutathione reveals chemical and regional specificity of redox homeostasis. Cell Metab 14:819–829. https://doi.org/10. 1016/j.cmet.2011.10.010

Chapter 6 Quantitative Measurement of Ascorbate and Glutathione by Spectrophotometry Graham Noctor and Amna Mhamdi Abstract Ascorbate and glutathione are key chemical antioxidants present at relatively high concentrations in plant cells. They are also reducing cofactors for enzymes that process hydrogen peroxide in the ascorbateglutathione pathway. Due to these two related biochemical functions, the compounds form an interface between reactive oxygen species and sensitive cellular components. Therefore, their status can provide reliable and direct information on cell redox state, signaling, and plant health. While several methods exist for quantification of ascorbate and glutathione, simple enzyme-dependent assays allow them to be measured easily and inexpensively in common extracts. This chapter describes a protocol to measure total contents, as well as the major oxidized and reduced forms, of both compounds in plant tissues. Key words Ascorbate, Glutathione, ROS, H2O2, Antioxidant, Redox state

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Introduction Among the many cell components that can interact with reactive oxygen species (ROS), ascorbate and glutathione are key players in the soluble phase of cells [1]. Both can interact chemically with ROS, and, perhaps even more importantly, they are cycling redox buffers in high-capacity peroxidase-based systems that metabolize H2O2 (see Fig. 1). Measuring ascorbate and glutathione can therefore provide direct assessment of important components of cellular redox states as well as indirect information on ROS levels [2, 3]. Given that ascorbate and glutathione have additional roles in other biochemical pathways and are both required for plant development and stress signaling [4–12], methods able to quantitate them are a useful inclusion in the toolbox of researchers working in areas such as plant responses to environmentally challenging conditions.

Supplementary Information The online version contains supplementary material available at [https://doi.org/ 10.1007/978-1-0716-2469-2_6]. Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_6, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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CAT

H2O2

H2O

ASC

APX

MDHA

NAD(P)H

GR

DHAR

MDHAR

NADP+

GSH

NAD(P)+

DHA

GSSG

NADPH

Fig. 1 The ascorbate-glutathione pathway in H2O2 metabolism. The scheme shows H2O2 removal by catalase (CAT) or ascorbate peroxidase (APX). When APX removes H2O2, ascorbate is converted to its primary oxidation product, MDHA. MDHA can be reduced back to ascorbate by MDHAR or dismutate to ascorbate and a secondary oxidation product, DHA. DHA is reduced to ascorbate by thiols such as GSH, forming GSSG that can be reduced by GR. Note that reactions are not shown stoichiometrically and that other reactions can cause ascorbate or glutathione redox cycling in plants. ASC ascorbate, APX ascorbate peroxidase, CAT catalase, DHA dehydroascorbate, DHAR dehydroascorbate reductase, GR glutathione reductase, GSH reduced glutathione, GSSG glutathione disulfide, MDHA monodehydroascorbate, MDAR monodehydroascorbate reductase

While both ascorbate and glutathione can be measured using techniques such as HPLC and mass spectrometry, simple spectrophotometric methods have been available for many years that can yield precise quantitative information on both total contents and the redox state of these molecules [13–18]. Important features of such quantitative assays are that they involve enzymes that confer high specificity on the measurements and that they can readily be adapted for assays on plate-readers [19]. In this chapter, we detail the protocol that we use in our laboratories to measure the oxidized and reduced forms of ascorbate and glutathione in the same tissue extracts. Glutathione is used here to indicate both oxidized and reduced forms without distinction. GSH and GSSG are used to denote reduced glutathione and glutathione disulfide, respectively.

2

Materials

2.1 Reagents and Solutions

1. 0.2 M HCl 2. 0.2 M NaOH 3. 120 mM NaH2PO4, pH 5.6

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4. 120 mM NaH2PO4, pH 7.5 5. 200 mM NaH2PO4, pH 7.5, 10 mM EDTA 6. 12 mM DTNB, pH 7.5 7. 25 mM dithiothreitol (DTT) 8. 10 mM NADPH 9. 10 mM GSSG 10. 10 mM GSH 11. Ascorbate oxidase (AO), 40 U/mL, in 120 mM NaH2PO4, pH 5.6 12. Glutathione reductase (GR), 20 U/mL in 200 mM NaH2PO4, pH 7.5, 10 mM EDTA 13. 2-vinylpyridine (2-VPD) 2.2

Equipment

1. Variable wavelength UV-visible spectrophotometer or platereader 2. UV-transparent plates, 96 wells 3. 1.5 mL Eppendorf tubes 4. pH indicator paper (pH 4–10), cut lengthwise into four strips 5. Multichannel automatic pipettes

3

Methods The following protocol is based on previously described procedures adapted for analyses by plate-reader [19]. The advantage of the plate-reader compared to a traditional spectrophotometer is higher assay throughput and economies in reagent costs (see Notes 1 and 2). Specificity for ascorbate and glutathione is conferred by the use of ascorbate oxidase (AO) and glutathione reductase (GR), respectively.

3.1

Extraction

1. Grind a known amount (100–150 mg fresh weight) of fresh or pre-frozen plant tissue in liquid nitrogen in a pestle and mortar until a fine powder is obtained (see Note 3). 2. Add 1 mL 0.2 M HCl and continue to grind while the suspension freezes. Allow to thaw on bench, making sure to continue to grind from time to time to ensure homogenization of ground tissue with the acid during thawing (see Note 4 and 5). 3. Transfer the homogenates from the mortar to Eppendorf tubes, vortex thoroughly, and centrifuge 10 000 g at 4
C for 10 min to pellet debris. 4. Remove tubes from centrifuge and transfer 0.5 mL of acid supernatant to a fresh tube (see Note 6).

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Neutralization

1. To 0.5 mL acid supernatant, add 0.1 mL NaH2PO4 buffer (pH 5.6). Bring to pH 5–6 (using pH paper strips) by stepwise addition of 0.2 M NaOH (see Note 7). 2. Keep neutralized extracts on ice for all pre-treatments and assays.

3.3 Treatment of Extract Aliquots to Distinguish Between Oxidized and Reduced Forms 3.3.1 Preparation of the GSSG Assay

The redox state of glutathione is determined by comparing total glutathione (see Subheading 3.4.2) to values obtained in aliquots of the neutralized extract treated with 2-VPD, a molecule that binds tightly to the GSH sulfhydryl group and makes it unreactive in the subsequent assay [16]. If derivatization of GSH in the aliquots is complete, the assay measures only GSSG, which can be compared with the assay of total glutathione (GSH + GSSG) in untreated extracts, to determine the redox state (see Note 8). 1. To prepare the GSSG assay, transfer 0.2 mL of the neutralized extracts to fresh tubes alongside four tubes containing blanks and GSSG standards to run in triplicate. Typically, we use 0, 40, 80, 160 pmoles GSSG in the cuvettes. Add 5 μL 2-VPD to each tube and vortex for 30 s (see Note 9). 2. Incubate at room temperature for 30 min with re-vortexing every 10 min. 3. Centrifuge for 15 min at 10,000 g. 4. Transfer 170 μL of the supernatant to a fresh tube, and centrifuge again for 15 min at 10,000 g (see Note 10). Set aside centrifuged tubes for the assay of GSSG (see Subheading 3.4.4).

3.3.2 Reduction of Dehydroascorbate (DHA) for Assay of Total Ascorbate

The ascorbate assay is specific for the reduced form. To measure the stable oxidized form, DHA, aliquots are treated with a reductant able to convert DHA to ascorbate, enabling both forms to be measured without distinction (total ascorbate). The redox state is calculated by comparing values for ascorbate with those for total ascorbate (ascorbate + DHA). 1. Transfer 100 μL neutralized extract to a fresh tube containing 140 μL 120 mM NaH2PO4 buffer (pH 7.5), then add 10 μL 25 mM DTT, and incubate at room temperature for 30 min (see Note 11).

3.4

Assays

In total, four assays are performed on the extracts. We do them in the following order: ascorbate; total glutathione; total ascorbate; GSSG. Standards are used to determine total glutathione and GSSG while ascorbate contents are calculated according to known extinction coefficients (see Note 12). We begin the ascorbate assays immediately after performing the preparation of the sample aliquots for measurement of GSSG and total ascorbate (see Note

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13). All four assays are performed in triplicate for extracts and, for glutathione, standard solutions. 3.4.1 Ascorbate

Ascorbate is assayed in aliquots of untreated neutralized extracts as the A265 that can be removed by the addition of AO (see Note 14). Ultimately, AO converts ascorbate to DHA, which has negligible absorbance at this wavelength. Be sure to use UV-transparent plates. 1. Add 100 μL of 0.2 M NaH2PO4 (pH 5.6), 55 μL H2O, and 40 μL of neutralized extract to the plate wells, and mix twice by automated shaking. 2. Measure absorbance at A265. 3. After the first read of the plate add 5 μL AO (40 unit.mL1) to each well using a multichannel pipette, and mix by automated shaking. 4. Monitor A265 for about 5 min, and take final reading after the reaction is complete. 5. Calculate Ascorbate from the difference between A265 before and after addition of AO (see Note 15).

3.4.2 Total Glutathione

The assays of total glutathione and GSSG are based on the same principle: the reduction of 5,50 -dithiobis-(2-nitrobenzoic acid) (DTNB or Ellman’s reagent) mediated by glutathione [14]. The reduced form of glutathione, GSH, produces the reduced form of DTNB, which can be detected by an increase in A412. In reducing DTNB, 2 GSH are oxidized to GSSG which in the assay is re-reduced to 2 GSH by GR in an NADPH-dependent manner. The overall reaction is DTNB reduction by NADPH at a rate that depends on the concentrations of GR and glutathione. Assuming the concentration of GR is constant and glutathione is present at concentrations well below the KMGSSG of GR, the rate of increase in A412 is directly proportional to glutathione, whether present as GSH or GSSG (see Note 16). Note that at equal concentrations, the rate for GSSG should be twice that for GSH. 1. Prepare enough GR solution for the assays of both total glutathione and GSSG. Centrifuge the (NH4)2SO4 suspension at 10,000 g for 2 min, and resuspend pellet in 200 mM NaH2PO4 buffer (pH 7.5), 10 mM EDTA to a concentration of 20 unit. mL1. Keep on ice (see Note 17). 2. Add 10 μL of neutralized untreated extracts (see Subheading 3.2) to plate wells containing 0.1 mL 0.2 M NaH2PO4 (pH 7.5), 10 mM EDTA, 10 μL NADPH, 10 μL 12 mM DTNB, and 60 μL water, and mix by automated shaking. GSH standards should be run in triplicates, depending on the range of values obtained in the extracts. Typically, we use three

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standards of 0.2, 0.4, and 1 nmol GSH, together with a blank containing neither GSH nor extract (see Note 18). 3. Check that A412 values are stable, and then add 10 μL GR (20 unit.mL1) to all wells using a multichannel pipette. 4. Monitor increase in A412 for 5 min (see Note 19). 3.4.3 Total Ascorbate

The procedure is similar to that used for reduced ascorbate (see Subheading 3.4.1), except that here DTT-treated aliquots are used (see Subheading 3.3.2). 1. Add 100 μL of 0.2 M NaH2PO4 (pH 5.6), 55 μL H2O, and 40 μL of DTT-treated extract to the plate wells, and mix twice by automated shaking. 2. Measure absorbance at A265. 3. After the first read of the plate add 5 μL AO (40 unit.ml1) to each well using a multichannel pipette, and mix by automated shaking. 4. Monitor A265 for about 5 min, and take final reading after the reaction is complete.

3.4.4 GSSG

The procedure is similar to that used for total glutathione (see Subheading 3.4.2), except using aliquots treated with 2-VPD (see Subheading 3.3.1). 1. Add 20 μL of the pre-treated extract aliquots and standards (see Subheading 3.3.1) to plate wells containing 0.1 mL 0.2 M NaH2PO4 (pH 7.5), 10 mM EDTA, 10 μL NADPH, 10 μL 12 mM DTNB, and 50 μL water, and mix by automated shaking. 2. Check that A412 values are stable, and then add 10 μL GR to all wells using a multichannel pipette. 3. Monitor increase in A412 for 5 min (see Notes 20 and 21).

3.5

Data Processing

For all assays, the triplicate technical repeats are averaged to obtain a single value that is used to calculate contents and redox states for each extract (see Note 22). 1. Ascorbate is calculated as A265 before addition of AO minus A265 afterwards (ΔA265). Convert to moles ascorbate using ε ¼ 7 mM1 for a path length of 5 mm. 2. Glutathione is calculated according to standard curves. Subtract mean blank value from all rates for standards and extracts, and construct a standard curve from which the relationship between the increase in A412 per unit time and glutathione concentration can be obtained. A typical example of data processing calculations is given in the Excel file in Electronic Supplemental Table 1.

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Notes 1. The oxidized forms of pyridine nucleotides (NAD+, NADP+) can also be measured in the same extracts [3, 19]. By contrast, the reduced forms of these compounds (NADH, NADPH) have to be measured in separate extracts because of their instability in acid. 2. The method also lends itself to ready measurement of glutathione by HPLC-fluorescence in aliquots of the same extracts. This has the advantage of being able to provide additional information on other, typically less abundant non-protein thiols that are commonly found in many biological tissues, such as cysteine, homocysteine, cysteinyl-glycine, and γ-glutamylcysteine [17–19]. 3. A key point in the procedure is avoiding artefactual oxidation of reduced forms of ascorbate and glutathione that can occur at several steps. Use fresh material or tissue stored at 80
C or below. Avoid freezing once the material is extracted, and proceed to the assays as quickly as possible. To allow rapid processing of extracts, it is better to limit the number of samples per series. We recommend no more than six samples per series for beginners. If it is absolutely impossible to assay extracts immediately, it is better to freeze extracts that are still in acid (prior to neutralization). Once neutralized, extracts can undergo significant oxidation during storage, even at 80
C. 4. To minimize artefactual oxidation, the tissue should not be allowed to thaw while not yet in contact with the acid. Acidic conditions counteract oxidation by inhibiting deprotonation of both ascorbate and glutathione redox groups. Avoid visible particles in the homogenate: thawed tissue that is not yet in contact with acid can suffer alterations in redox state compared to the tissue at the moment of sampling. 5. A pestle and mortar is preferable to a ball mill, in which it is difficult to keep the temperature cold enough to avoid oxidation and to achieve the same degree of homogenization. 6. The “neutralization” step (see Subheading 3.2) is performed to bring the extract to a pH compatible with the procedures described in Subheading 3.3 as well as the assays described in Subheading 3.4. 7. To minimize oxidation of reduced forms, care should be taken not to exceed pH 6. This can be achieved by adding NaOH stepwise and vortexing rapidly after each addition to avoid local alkalinization. If the pH after neutralization significantly exceeds 7, we would tend to discard the tube. 8. Perform all procedures with 2-VPD in a fume cupboard.

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9. The pH of the solutions should be high enough to enable the reaction between GSH in the extracts and 2-VPD but low enough to minimize GSH oxidation to GSSG. Although somewhat below the pKa of the GSH thiol group (about pH 8.5), we have found pH values between 5 and 6 to be optimal for 2-VPD derivatization. The efficacity can be checked by 2-VPD treatment of control tubes containing GSH at similar concentrations to the extracts. We strongly recommend treating the GSSG standards the same as the extracts to correct for an effect of 2-VPD that might be carried over into the assay (see Note 20). 10. 2-VPD is not very soluble in aqueous solution, and droplets tend to stick to the sides of the tubes. This is why we vortex regularly and also take care to try and minimize carry-over of 2-VPD into the assay by two centrifugations and by avoiding touching the sides of the tube when pipetting (see Note 20). 11. This procedure was found to be optimal for extracts of Arabidopsis leaves [19]. Different reductants or other concentrations of DTT might be more appropriate for other types of extract. 12. Periodic checks can be performed with ascorbate standards. This can be particularly important to check recovery of known amounts added at the beginning of the extraction procedure, particularly in the application of the method to a new system that might pose specific problems. 13. Preparation of the aliquots for the total ascorbate and GSSG assays takes about 30 and 60 min, respectively. The assays of ascorbate (reduced) and total glutathione can largely be completed before the total ascorbate aliquots are ready. The GSSG assay is done last. 14. Ascorbate oxidase is a relatively unstable enzyme. We dissolve the enzyme in 120 mM NaH2PO4 (pH 5.6) on receipt of the vial and divide into multiple aliquots for storage at 20
C. For each experiment, an aliquot is thawed, kept on ice, and any residual enzyme is discarded at the end of the day. 15. The extinction coefficient of ascorbate at 265 nm is about 14 mM1cm1. We use 7 mM1 to calculate ascorbate as the path length in a typical 96-well plate reader is close to 5 mm. 16. For accurate comparison of samples and standards, each assay needs to be performed at the same GR concentration. We advise against using different preparations of enzyme in the same experiment. 17. We prepare the GR solution freshly each day, prior to the extractions, and keep on ice throughout the experiment. 18. Blank assays have to be performed because NADPH-dependent reduction of DTNB by GR occurs at low rates,

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independent of glutathione. The blank value is subtracted from the rates observed with standards and extracts. 19. Unless glutathione concentrations in the extracts are very low or very high, the increase in A412 should be constant for at least 5 min. 20. Any residual 2-VPD carried over into the cuvette (see Notes 9 and 10) will tend to bind to GSH that is produced within the assay by GR from GSSG, thus competing with DTNB and leading to a progressive inhibitory effect on the rate of increase in A412. Pre-treatment of GSSG standards with 2-VPD alongside extract aliquots is intended to correct for any such effect. Like the total glutathione assay, triplicate blanks are run to determine a glutathione-independent rate that is subtracted from the rates obtained with standards and extracts. 21. We generally monitor the glutathione assays for 5 min, but use the rates over the first 2 min for calculations. 22. For all assays, variability between technical repeats should generally be low. High variability may indicate a problem with one or more of the wells or a general error in the assay.

Acknowledgments Work in the GN laboratory is supported by the French Agence Nationale de la Recherche HIPATH project (ANR-17-CE200025) and by the Institut Universitaire de France (IUF). References 1. Foyer CH, Noctor G (2011) Ascorbate and glutathione: the heart of the redox hub. Plant Physiol 155:2–18 2. Foyer CH, Noctor G (2005) Redox homeostasis and antioxidant signaling: a metabolic interface between stress perception and physiological responses. Plant Cell 17: 1866–1875 3. Noctor G, Mhamdi A, Foyer CH (2016) Oxidative stress and antioxidative systems: recipes for successful data collection and interpretation. Plant Cell Environ 39:1140–1160 4. Vernoux T, Wilson RC, Seeley KA et al (2000) The ROOT MERISTEMLESS1/CADMIUM SENSITIVE2 gene defines a glutathionedependent pathway involved in initiation and maintenance of cell division during postembryonic root development. Plant Cell 12: 97–110 5. Vanacker H, Carver TLW, Foyer CH (2000) Early H2O2 accumulation in mesophyll cells

leads to induction of glutathione during the hypersensitive response in the barley-powdery mildew interaction. Plant Physiol 123: 1289–1300 6. Pastori GM, Kiddle G, Antoniw J et al (2003) Leaf vitamin C contents modulate plant defense transcripts and regulate genes that control development through hormone signalling. Plant Cell 15:939–951 7. Frendo P, Harrison J, Norman C et al (2005) Glutathione and homoglutathione play a critical role in the nodulation process of Medicago truncatula. Mol Plant Microb Interact 18: 254–259 8. Cairns NG, Pasternak M, Wachter A et al (2006) Maturation of Arabidopsis seeds is dependent on glutathione biosynthesis within the embryo. Plant Physiol 141:446–455 9. Dowdle J, Ishikawa T, Gatzek S et al (2007) Two genes in Arabidopsis thaliana encoding GDP-L-galactose phosphorylase are required

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for ascorbate biosynthesis and seedling viability. Plant J 52:673–689 10. Mhamdi A, Hager J, Chaouch S et al (2010) Arabidopsis GLUTATHIONE REDUCTASE 1 is essential for the metabolism of intracellular H2O2 and to enable appropriate gene expression through both salicylic acid and jasmonic acid signaling pathways. Plant Physiol 153: 1144–1160 11. Han Y, Chaouch S, Mhamdi A et al (2013) Functional analysis of Arabidopsis mutants points to novel roles for glutathione in coupling H2O2 to activation of salicylic acid accumulation and signaling. Antioxid Redox Signal 18:2106–2121 12. Rahantaniana MS, Li S, Chatel-Innocenti G et al (2017) Cytosolic and chloroplastic DHARs cooperate in the induction of the salicylic acid pathway by oxidative stress. Plant Physiol 174:956–971 13. Hewitt EJ, Dickes GJ (1961) Spectrophotometric measurements on ascorbic acid and their use for the estimation of ascorbic acid and dehydroascorbic acid in plant tissues. Biochem J 78:384–391 14. Tietze F (1969) Enzymic method for quantitative determination of nanogram amounts of total and oxidised glutathione. Applications to

mammalian blood and other tissues. Anal Biochem 27:502–522 15. Foyer C, Rowell J, Walker D (1983) Measurement of the ascorbate content of spinach leaf protoplasts and chloroplasts during illumination. Planta 157:239–244 16. Griffith OW (1980) Determination of glutathione and glutathione disulfide using glutathione reductase and 2-vinylpyridine. Anal Biochem 106:207–212 17. Strohm M, Jouanin L, Kunert KJ et al (1995) Regulation of glutathione synthesis in leaves of transgenic poplar (Populus tremula  P. alba) overexpressing glutathione synthetase. Plant J 7:141–145 18. Noctor G, Foyer CH (1998) Simultaneous measurement of foliar glutathione, γ-glutamylcysteine, and amino acids by highperformance liquid chromatography: comparison with the two other assay methods for glutathione. Anal Biochem 264:98–110 19. Queval G, Noctor G (2007) A plate-reader method for the measurement of NAD, NADP, glutathione and ascorbate in tissue extracts. Application to redox profiling during Arabidopsis rosette development. Anal Biochem 363:58–69

Chapter 7 Measurement of NAD(P)H and NADPH-Generating Enzymes Amna Mhamdi, Frank Van Breusegem, and Graham Noctor Abstract Pyridine nucleotides (NAD(H) and NADP(H)) are key redox carriers in cells and may also have other functions related to stress. These two molecules are crucial in linking metabolism to electron transport chains in photosynthesis and respiration, but they are also critical for ensuring redox signaling and homeostasis during episodes of stress. This is especially the case for NADPH, which must be generated from its oxidized form, NADP+, by key dehydrogenases. Here, we describe methods that can be used to assay contents and redox states of NAD(H) and NADP(H), as well as simple assays to measure the capacity of two key NADPH-generating enzymes. Key words NADPH, ROS, Isocitrate dehydrogenase, Glucose-6-phophate dehydrogenase, Spectrophotometry

1

Introduction NAD(H) and its phosphorylated derivative NADP(H) are key redox carriers in cells (see Note 1) (see Fig. 1). Both nucleotides are substrates for various enzymes involved in primary and secondary metabolism. For example, NAD(H) is involved in the extraction of energy through catabolic pathways, while NADP(H) is used in biosynthetic pathways such as photosynthesis. However, both play other important roles in plants. Within the context of cytosolic stress signaling, NADH is a source of electrons for nitrate reductase-dependent nitric oxide production [1]. NADPH in particular is a key factor underpinning redox homeostasis and signaling, supplying electrons to such components as plasma membrane NADPH oxidases, the NADPH-dependent thioredoxin system, and, with together NADH, the ascorbate-glutathione pathway [2–5]. NAD(P) redox states can remain quite constant over a wide range of conditions and metabolic states, although differences are observed as a function of high-flux pathways such as photorespira-

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_7, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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Reduced forms e340 = 6200 M-1 cm-1

Oxidized forms

NAD(P)+

H C

O

P

CH2

O

O

HO

H

2 e-, H+

O

P

CH2

O

HO

OH

O NH2 N N

P

NH2

N O

OH

O

O

O C

N

O

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NH2

+

O

NAD(P)H

O

O

CH2

N

N N

2

e-,

H+

N O

O

O HO

NH2

OR

Midpoint redox potenal at pH7 -340 mV

P

O

CH2

N N

O

O HO

OR

Fig. 1 Identity card for NAD(H) and NADP(H): key players in the redox-cycling game of life. Both dinucleotides are composed of an adenosine monophosphate (bottom) and a nicotinamide monophosphate (top). The latter is highlighted green to indicate that it is the site of redox activity. The yellow highlight indicates the difference between NAD(H) and NADP(H): in NAD, R is H whereas in NADP, it is a phosphate group. The reduced forms are an important source of electrons for many processes (see text), while the oxidized forms are equally crucial as their ability to accept electrons is required to maintain key processes such as photosynthesis and glycolysis. The redox potential, which is relatively negative, is an indication of the tendency to reduce or oxidize other redox-active molecules. « Midpoint » means the value obtained when oxidized and reduced forms are present at equal concentrations. For researchers interested in enzyme assays, a key property is that the reduced forms absorb light quite strongly at 340 nm whereas the oxidized forms do not. The extinction coefficient of the reduced forms is indicated. Typical leaf content in plants are between 20 and 80 nmol g
1FW, 10–20% reduced form for NAD(H), and 10–60 nmol g
1FW, 40–60% reduced form for NADP(H).

tion [6, 7]. In the chloroplast, redox states can change transiently during abrupt transitions between light and dark [8]. Total contents of NAD(P) can be modified by targeted manipulation of the biosynthetic pathway or by more indirect alterations in associated pathways such as respiration [9–11]. Changes during conditions requiring additional NADPH for signaling have also been reported [12]. While many enzymes are responsible for NADPH production, some are more highly expressed or more active than others. Among highly expressed cytosolic enzymes, glucose-6-phosphate dehydrogenase (G6PDH) and NADP+-dependent isocitrate dehydrogenase (ICDH) have been implicated in responses to abiotic and biotic stresses [13–15], and changes in their capacities can be readily monitored in protein extracts by in vitro assay of NADPH oxidation that is dependent on their respective substrates. Here, we

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describe classical methods for determining NAD(H) and NADP (H) and, as potentially important NADPH-generating enzymes during stress conditions, G6PDH and ICDH.

2

Materials

2.1 Reagents and Solutions

1. 0.2 M HCl 2. 0.2 M NaOH 3. 200 mM NaH2PO4 (pH 5.6) 4. 100 μL 0.1 M HEPES (pH 7.5), supplemented with 2 mM EDTA 5. Isocitrate dehydrogenase extraction buffer (100 mM NaH2PO4 (pH 7.5), supplemented with 10 mM MgCl2) 6. Glucose-6-phosphate dehydrogenase extraction buffer (0.05 M Tris-HCl pH 8, 10 mM MgCl2, 5 mM EDTA, and 1 mM DTT) 7. 1.2 mM 2,6-dichlorophenolindophenol (DCPIP) 8. 20 mM phenazine methosulfate (PMS) 9. 10 mM G6P 10. 10 mM NADPH 11. 10 mM NAD+ 12. 10 mM NADH 13. 10 mM NADP+ 14. Glucose-6-phosphate dehydrogenase (G6PDH) (see Note 2) 15. Alcohol dehydrogenase (ADH) (see Note 3) 16. Ethanol 17. 2-mercaptoethanol 18. 250 mM isocitrate 19. 100 mM G6P 20. 100 mM MgCl2

2.2

Equipment

1. Refrigerated centrifuge 2. Variable wavelength UV-visible spectrophotometer or a platereader 3. 1.5 and 2 mL Eppendorf tubes 4. UV-transparent plates, 96 wells 5. pH indicator paper (pH 4–10), cut lengthwise into four strips 6. Multichannel automatic pipettes

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Methods

3.1 Quantification of Pyridine Nucleotides

Here we describe protocols that have been optimized and used extensively in the Arabidopsis (Arabidopsis thaliana) Col-0 background as well as T-DNA mutant lines grown in optimal or stress conditions [16]. The method exploits a recycling assay that affords the necessary sensitivity [17], as only the reduced forms of pyridine nucleotides have substantial absorbance and pyridine nucleotides are rarely abundant enough to quantify directly in extracts. Full details of the principles underlying the extraction and assay protocols have been detailed elsewhere [18].

3.1.1 Metabolite Extraction and Neutralization

The reduced and oxidized forms of nucleotides pyridines are quantified in extracts performed in parallel using different extraction media (see Note 4). 1. Grind plant material in liquid nitrogen using a pestle and a mortar until a fine powder is obtained (see Note 5). 2. Add 1 mL of the desired extraction buffer (0.2 M HCl or 0.2 M NaOH), and continue to homogenize while the suspension freezes. Ensure that the sample is immersed in the acid or the base at all times during thawing (see Note 6). 3. Transfer the extract to a new Eppendorf tube, and centrifuge at 10 000 g at 4  C for 10 min. 4. Transfer 0.2 mL of the extract supernatant to a heat-resistant tube, and incubate for 1 min in a water-bath at 95  C (see Note 7). 5. Cool extracts on ice, and then add 50 μL NaH2PO4 buffer (pH 5.6) to the cooled 0.2 mL aliquot. 6. Neutralize the samples to pH 6–7 (using pH paper as indicator) by sequential addition of 0.2 M NaOH to the acid extracts or 0.2 M HCl to the alkaline extracts (see Note 7). 7. Save neutralized samples on ice, and proceed immediately with the assays as described below.

3.1.2 Quantification of NAD+ and NADH

The assay principle is based on ethanol-driven ADH-dependent reduction of DCPIP in which NAD(H) cycles as an intermediate and PMS serves as a catalyst for DCPIP reduction by NADH (see [18] for further details). The rate of reaction is linearly related to NAD(H) concentrations within a certain range which should be checked with standards. Assay NAD+ and NADH in the acid and basic extracts, respectively. 1. Add 100 μL 0.1 M HEPES, 2 mM EDTA (pH 7.5), 20 μL 1.2 mM DCPIP, 10 μL 20 mM PMS, 10 μL ADH, 25 μL H2O,

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and 20 μL of each neutralized extract to a plate well. Assay in triplicates (technical replicates). 2. Introduce the plate into the plate reader and mix twice by automated shaking. 3. Initiate the reaction by adding of 15 μL absolute ethanol in each well. 4. Monitor decrease in A600 for 5 min. 5. Calculate pyridine nucleotide contents in the samples using standard curves generated from solutions of NAD+ or NADH assayed on the same plate (see Notes 8 and 9). 3.1.3 Quantification of NADP and NADPH

The assay principle is based on G6P-driven G6PDH-dependent reduction of DCPIP in which NADP(H) cycles as an intermediate and PMS serves as a catalyst for DCPIP reduction by NADPH (see [18] for further details). The rate of reaction is linearly related to NADP(H) concentrations within a certain range which should be checked with standards. Assay NADP+ and NADPH in the acid and basic extracts, respectively. 1. Add 100 μL 0.1 M HEPES, 2 mM EDTA (pH 7.5), 20 μL 1.2 mM 2,6-DCPIP, 10 μL 20 mM PMS, 10 μL 10 mM G6P, 30 μL water, and 20 μL of each neutralized extract to a plate well. Assay in triplicates (technical replicates). 2. Put the plate in the plate reader and mix twice by automated shaking. 3. Initiate the reaction by adding of 10 μL G6PDH in each well. 4. Monitor decrease in A600 for 5 min. 5. Calculate pyridine nucleotide contents in the samples using standard curves generated from solutions of NADP+ or NADPH assayed on the same plate (see Notes 8 and 9).

3.2 Assays of NADPH-Generating Enzymes

3.2.1 Measurement of NADP+-Dependent Isocitrate Dehydrogenase

Since both G6PDH and ICDH generate NADPH from NADP+ and are relatively active in plants, their activities in protein extracts can be readily assayed by monitoring the substrate-dependent production of NADPH from NADP+ at 340 nm. The assays are performed in standard conditions using substrate and cofactor concentrations that are largely non-limiting. Hence, values are more a measure of capacity rather than activity in planta, where substrate concentrations might be more limiting or regulatory mechanisms that are not detected in the assays could be working. 1. Prepare extraction buffer (100 mM NaH2PO4 (pH 7.5), 10 mM MgCl2, and 14 mM 2-mercaptoethanol). 2. Prepare isocitrate and NADP+ freshly each day.

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3. Harvest 100–200 mg leaf material in 2 mL Eppendorf tube, and grind tissue in liquid nitrogen to a fine powder (see Notes 10 and 11). 4. Add a few mg of insoluble PVP, and mix with the sample powder (about 10% of the sample FW). 5. Add 1 mL of extraction buffer and continue grinding to homogenize the sample. 6. Transfer the extract to 2 mL tubes, and centrifuge for 15 min at 11,000 g and at 4  C. 7. Transfer the supernatant to a fresh tube and keep the extracts on ice at all times. Proceed with the assays immediately. 8. Desalt protein extracts (optional) (see Note 12). 9. Measure protein concentration in each extract. 10. In a disposable plastic cuvette at 25  C, add 830 μL 100 mM NaH2PO4 (pH 7.5), 50 μL 100 mM MgCl2, and 10 μL 25 mM NADP+. 11. Mix well and add 100 μL of the extract. 12. Initiate the reaction by adding isocitrate to a final concentration of 2.5 mM. 13. Monitor the reduction of NADP+ at 340 nm and at 25  C for 5 min. 14. Calculate the total ICDH activity using the formula below (see Notes 13 and 14).
ICDH activity nmol mg
1 protein min
1

¼ Δ340 min
1  106 =6200  ð1=0:1 ½extract volume used in assayÞ  ð1=extract protein concentration ½mg=mLÞ: 3.2.2 Measurement of Glucose-6-Phosphate Dehydrogenase

1. Prepare extraction buffer (0.05 M Tris-HCl buffer pH 8, 10 mM MgCl2, 5 mM EDTA, and 1 mM DTT). 2. Prepare G6P and NADP+ freshly each day. 3. Harvest 100–200 mg leaf material in 2 mL Eppendorf tube, and grind tissue in liquid nitrogen to a fine powder. Add a few mg of insoluble PVP and mix with the sample powder. 4. Add 1 mL of extraction buffer and continue grinding to homogenize the sample. 5. After thawing, clarify the sample by centrifugation at 4  C and 11,000 g for 10 min. 6. Transfer the supernatant to a fresh tube and keep the extracts on ice at all times. Proceed with the assays immediately.

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7. Desalt protein extracts (optional). 8. Measure protein concentrations in the extracts. 9. If desired, inhibit the chloroplastic isoforms of G6PDH (see Note 15). 10. In a disposable plastic cuvette at 25  C, add 808 μL 0.05 M Tris-HCl buffer pH 8, 50 μL 100 mM MgCl2, 12 μL 10 mM NADP+, and 100 μL extract. 11. Start reaction by adding 30 μL of 100 mM G6P, and monitor increase in A340 for 5 min. 12. Monitor the reduction of NADP+ at 340 nm and at 25  C for 5 min. 13. Calculate the total G6PDH activity using the formula below (see Notes 13 and 14).
G6PDH activity nmol mg
1 protein min
1

¼ Δ340 min
1  106 =6200  ð1=0:1 ½extract volume used in assayÞ  ð1=extract protein concentration ½mg=mLÞ:

4

Notes 1. Here, we use NAD(H) and NADP(H) as generic terms to indicate total contents that includes both oxidized and reduced forms. The specific forms are indicated by NAD+, NADH, NADP+, and NADPH. 2. G6PDH is freshly prepared each day by centrifugation of the solution and resuspension of the pellet in 0.1 M HEPES, 2 mM EDTA (pH 7.5) to 200 U.mL
1. 3. ADH is freshly prepared each day by resuspending the powder in 0.1 M HEPES, 2 mM EDTA (pH 7.5) to 2500 U.mL
1. 4. The extraction of pyridine nucleotides (oxidized NAD+ and NADP+ and reduced NADH and NADPH forms) is performed separately, as they are not stable in the same extraction media. To measure NAD+ and NADP+, samples are extracted in acid (related acid-stable redox compounds such as ascorbate and glutathione could also be quantified in these extracts) and neutralized to pH 5–6 using 0.2 M NaOH. To measure NADH and NADPH, parallel samples are extracted in 0.2 M NaOH and neutralized to pH 7–8 using 0.2 M HCl. 5. The exact sample fresh weight should be recorded to enable calculation of tissue contents. Typically, we use around 100 mg tissue, which was found to be optimal for the procedure

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described here. For mature Arabidopsis plants (e.g., grown in soil), several leaves can be mixed to get one sample. However, for younger plants (grown in vitro), samples consist of a pool of few seedlings/rosettes. 6. All extraction steps should be performed at 4  C or below. The samples should always be immersed in the cold extraction buffer to avoid heating and degradation, or artefactual oxidation of the samples during the extraction procedure. 7. The duration of the heating can be critical to achieve efficient removal of the unwanted forms (e.g., NADH, NADPH in acid extracts) while avoiding degradation of the desired forms (e.g., NAD+ and NADP+ in acid extracts). In our hands, 1 min of heating at 95  C is optimal to this end for both acid and alkaline extracts. Care should also be taken not to exceed the pH values as this can lead to artefactual degradation of the target compounds. If developing the protocol, we strongly recommend validating the procedure by recovery experiments using authentic standards, initially in the absence of extract and then in combination with the extract. 8. For Arabidopsis, we use standards of 0, 10, 20, and 40 pmol NAD(P)+ or NAD(P)H in the well. 9. In interpreting the data obtained, it can be useful to bear two points in mind. First, like many other compounds of relatively low molecular mass, both NAD(H) and NADP(H) are found in several compartments, and these pools may have different concentrations and redox states. Hence, as for whole-tissue extracts of many other compounds, analysis of total extractable NAD(H) or NADP(H) produces a composite value. Second, a significant fraction of these molecules can be bound to proteins at any given point in time: many enzymes, some of them rather abundant, depend on them [19]. This means caution should be exercised in extrapolating in vivo information from results of in vitro measurements as the extraction procedure will enable measurement of both protein-bound nucleotides and the free pools, which are often the most biologically relevant. 10. It is important to record the exact amount of FW used if you need to express the enzyme activity relative to the FW. Otherwise, or additionally, the activity can be expressed on a protein basis. 11. We typically use 3 or 4 biological replicates for enzyme activities. 12. In our hands, using Arabidopsis leaves, similar activities for both ICDH and G6PDH are observed between crude and desalted protein extracts.

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13. The extinction coefficient of NADPH at 340 nm is classically taken as 6200 M
1 cm
1. For assays performed in a platereader with a shorter path length, the coefficient should be adjusted as necessary. 14. While activities may be influenced by plant species, tissue type, and growth conditions, values we obtain for NADP+-dependent ICDH and G6PDH in protein extracts from Arabidopsis leaves are typically within the range of 25–100 nmol.mg
1prot. min
1. If values are far removed from this range, we recommend re-checking the calculations. 15. It is important to note that, in plants for which information is available, both ICDH and G6PDH are encoded by several genes. In the case of ICDH, analysis of gene-specific mutants suggests that a gene for the cytosolic isoform encodes most of the leaf activity in Arabidopsis [15]. For G6PDH, most of the activity is probably attributable to cytosolic and chloroplastic isoforms. The latter can be inhibited by disulfide reduction, which allows their contribution to the total activity to be separated from the activities of isoforms in other subcellular compartments. To inhibit chloroplastic G6PDHs, incubate the samples with 20 mM DTT for 30 min, and then measure the activities in treated and untreated samples.

Acknowledgments Work in the GN laboratory is supported by the French Agence Nationale de la Recherche HIPATH project (ANR-17-CE200025) and by the Institut Universitaire de France (IUF). References 1. Astier J, Gross I, Durner J (2018) Nitric oxide production in plants: an update. J Exp Bot 69: 3401–3411 2. Torres MA, Dangl JL, Jones JD (2002) Arabidopsis gp91phox homologues AtrbohD and AtrbohF are required for accumulation of reactive oxygen intermediates in the plant defense response. Proc Natl Acad Sci USA 99:517–522 3. Bashandy T, Guilleminot J, Vernoux T, Caparros-Ruiz D, Ljung K, Meyer Y, Reichheld JP (2010) Interplay between the NADPlinked thioredoxin and glutathione systems in Arabidopsis auxin signaling. Plant Cell 22: 376–391 4. Foyer CH, Noctor G (2011) Ascorbate and glutathione: the heart of the redox hub. Plant Physiol 155:2–18

5. Tuzet A, Rahantaniaina MS, Noctor G (2019) Analyzing the function of catalase and the ascorbate-glutathione pathway in H2O2 processing: insights from an experimentally constrained kinetic model. Antioxid Redox Signal 30:1238–1268 6. Kasimova MR, Grigiene J, Krab K, Hagedorn PH, Flyvbjerg H, Andersen PE, Møller IM (2006) The free NADH concentration is kept constant in plant mitochondria under different metabolic conditions. Plant Cell 18:688–698 7. Igamberdiev AU, Gardestro¨m P (2003) Regulation of NAD- and NADP-dependent isocitrate dehydrogenases by reduction levels of pyridine nucleotides in mitochondria and cytosol of pea leaves. Arch Biochem Biophys 1606: 117–125

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8. Takahama U, Shimizu-Takahama M, Heber U (1981) The redox state of the NADP system in illuminated chloroplasts. Biochim Biophys Acta 637:530–539 9. Noctor G, Hager J, Li S (2011) NAD synthesis and its manipulation in plants. Adv Bot Res 58: 153–201 10. Pe´triacq P, de Bont L, Hager J, Didierlaurent L, Mauve C, Gue´rard F, Noctor G, Pelletier S, Renou JP, Tcherkez G, Gakie`re B (2012) Inducible NAD overproduction in Arabidopsis alters metabolic pools and gene expression correlated with increased salicylate content and resistance to Pst-AvrRpm1. Plant J 70:650–665 11. Dutilleul C, Lelarge C, Prioul JL, De Paepe R, Foyer CH, Noctor G (2005) Mitochondriadriven changes in leaf NAD status exert a crucial influence on the control of nitrate assimilation and the integration of carbon and nitrogen metabolism. Plant Physiol 134:64–78 12. Harding SA, Oh SH, Roberts DM (1997) Transgenic tobacco expressing a foreign calmodulin gene shows an enhanced production of active oxygen species. EMBO J 16: 1137–1144 13. Valderrama R, Corpas FJ, Carreras A, Go´mezRodrı´guez MV, Chaki M, Pedrajas JR, Ferna´n˜ a A, del Rı´o LA, Barroso JB (2006) dez-Ocan The dehydrogenase-mediated recycling of NADPH is a key antioxidant system against

salt-induced oxidative stress in olive plants. Plant Cell Environ 29:1449–1459 14. Hodges M, Flesch V, Galvez S, Bismuth E (2003) Higher plant NADP-dependent isocitrate dehydrogenases, ammonium assimilation and NADPH production. Plant Physiol Biochem 41:577–585 15. Mhamdi A, Mauve C, Gouia H, Saindrenan P, Hodges M, Noctor G (2010) Cytosolic NADP-dependent isocitrate dehydrogenase contributes to redox homeostasis and the regulation of pathogen responses in Arabidopsis leaves. Plant Cell Environ 33:1112–1123 16. Queval G, Noctor G (2007) A plate-reader method for the measurement of NAD, NADP, glutathione and ascorbate in tissue extracts. Application to redox profiling during Arabidopsis rosette development. Anal Biochem 363:58–69 17. Mone´ger R, Vermeesch J, Lechevallier D, Richard C (1977) Micro-analyse du NADP et du NAD re´duits et oxyde´s dans les tissus foliaires et dans les plastes isole´s de Spirode`le et de Ble´. Physiol Ve´g 15:29–62 18. Noctor G, Mhamdi A, Foyer CH (2016) Oxidative stress and antioxidative systems: recipes for successful data collection and interpretation. Plant Cell Environ 39:1140–1160 19. Hagedorn PH, Flyvbjerg H, Møller I (2007) Modelling NADH turnover in plant mitochondria. Physiol Plant 120:370–385

Chapter 8 Quantitative Analysis for ROS-Producing Activity and Regulation of Plant NADPH Oxidases in HEK293T Cells Sachie Kimura, Hidetaka Kaya, Kenji Hashimoto, Michael Wrzaczek, and Kazuyuki Kuchitsu Abstract Reactive oxygen species (ROS) produced by plant NADPH oxidases, respiratory burst oxidase homologs (RBOHs), play key roles in biotic and abiotic stress responses and development in plants. While properly controlled amounts of ROS function as signaling molecules, excessive accumulation of ROS can cause undesirable side effects due to their ability to oxidize DNA, lipids, and proteins. To limit the damaging consequences of unrestricted ROS accumulation, RBOH activity is tightly controlled by post-translational modifications (PTMs) and protein-protein interactions. In order to analyze these elaborate regulatory mechanisms, it is crucial to quantitatively assess the ROS-producing activity of RBOHs. Given the high endogenous ROS generation in plants, however, it can be challenging in plant cells to measure ROS production derived from specific RBOHs and to analyze the contribution of regulatory events for their activation and inactivation. Here we describe human embryonic kidney 293T (HEK293T) cells as a heterologous expression system and a useful tool to quantitatively monitor ROS production by RBOHs. This system permits the reconstitution of regulatory events to dissect the effects of Ca2+, phosphorylation, and protein-protein interactions on RBOH-dependent ROS production. Key words NADPH oxidase, Respiratory oxidase homolog (RBOH), Human embryonic kidney 293T (HEK293T), Luminol

1

Introduction Reactive oxygen species (ROS) play major roles as signaling molecules in numerous processes throughout the plant life cycle. ROS are produced in multiple subcellular compartments, including the chloroplast, mitochondria, peroxisomes, and the apoplast [1]. Apoplastic ROS are produced mainly by plasma membrane-localized NADPH oxidases (NOXs) and cell wall class III peroxidases [2]. Plant NOXs, referred to as respiratory burst oxidase homologs (RBOHs), have been identified as homologs of phagocyte gp91phox/NOX2, which contains six transmembrane helices and cytosolic flavin adenine dinucleotide (FAD)- and nicotinamide

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_8, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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adenine dinucleotide phosphate (NADPH)-binding domains in the C-terminal region [3, 4]. Unlike gp91phox/NOX2, RBOHs contain an additional N-terminal region with Ca2+ binding EF hands, similar to nonphagocytic NOXs, such as NOX5 [5]. RBOHs transfer electrons from cytoplasmic NADPH, through FAD, and across the plasma membrane via two hemes to molecular oxygen to produce superoxide anion radicals (O2• ). O2• can be dismutated to hydrogen peroxide (H2O2) spontaneously, but the existence of plasma membrane/extracellular superoxide dismutases (SODs) has been proposed [6–8]. ROS produced by RBOHs play important biological roles in immunity, abiotic stress tolerance (including salt, hypoxia, heavy metals, drought, wounding, light, and extreme temperature stresses), but also plant growth and development [9, 10]. While the spatio-temporal control of RBOH expression is important for their functions, RBOH activity is also strictly and rapidly controlled at the post-translational level to avoid oxidative damage to cellular components as consequence of unrestricted ROS accumulation. Numerous studies have shown that RBOH activity can be regulated by Ca2+, protein phosphorylation, S-nitrosylation, S-persulfidation, ubiquitination, ROP/RAC small GTPases, and phosphatidic acid [10–14]. More than 150 members of the RBOH protein family have been identified and/or characterized in various plant species, and the genome of the model plant species Arabidopsis thaliana encodes 10 RBOHs. In addition, physiological functions for at least 56 members have been characterized so far [5, 10]. However, information on the enzymatic activity and post-translational regulation is missing for many of the identified RBOHs. ROS accumulation in plant cells has been visualized by diverse tools such as diaminobenzidine (DAB) staining, nitroblue tetrazolium (NBT) staining, fluorescent dyes, genetically encoded ROSsensitive probes, and also ROS-response promoters/proteins as well as electron microscopic cytochemistry [15, 16]. On the other hand, horseradish peroxidase (HRP)-luminol based assays have been used to quantify apoplastic ROS production in plant cells, e.g., microbe-associated molecular patterns (MAMPs)-induced apoplastic ROS production [17]. Recognition of ligands including MAMPs by receptor-like kinases (RLKs) frequently triggers ROS production in the apoplast and intracellular compartments [18, 19]. Lipopolysaccharides (LPS) are MAMPs that have been reported to induce a biphasic ROS production, consisting of early apoplastic ROS production and late chloroplastic ROS production [20]. This suggests that plant cells have high endogenous ROS-producing activity which is continually adjusted. Hence measuring specific RBOH-derived ROS production and investigating the regulation of the activity of specific RBOHs in proper time resolution is challenging in plant cells.

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ROS measurement by HRP-luminol based assays in human embryonic kidney 293T (HEK293T) cells has been used to study human NOXs [21–23]. HEK293T cells produce minimal amounts of extracellular ROS due to a lack of expression of endogenous gp91phox/NOX2 and NOX5 [21, 24]. Moreover, HEK293T cells are easy to grow in culture and can be efficiently co-transfected with two or three different expression constructs for protein production. These factors contribute to a high reproducibility of results obtained using the HEK293T cell system. Therefore, we used heterologous co-expression of plant RBOHs and their regulators in HEK293T cells to assess the regulation of RBOH-dependent ROS production. Subsequently, RBOH-mediated extracellular ROS production was measured by a HRP-luminol-based assay. Using this approach, we were able to show that ionomycin, a Ca2+ ionophore that increases cytosolic Ca2+ levels, and calyculin A, a protein phosphatase inhibitor that enhanced protein phosphorylation of RBOH in HEK293T cells, induced ROS production in HEK293T cells transfected with Arabidopsis thaliana or rice RBOHs [25–30]. The results suggest that RBOH is activated by Ca2+ and protein phosphorylation. Furthermore, co-transfection with regulatory proteins altered RBOH-derived ROS production in HEK293T cells [12, 31–36]. The ROS-producing activity of various site-directed mutant RBOHs showed strong correlation with the complementing activity of the phenotype of the mutants in planta [12, 26, 29], suggesting that the ROS-producing activity of RBOHs assayed in HEK293T cells at least partly reflects their activity in vivo and can be used to model regulatory events in the plant cell. In this chapter, we describe the detailed methods including steps to cultivate and maintain HEK293T cell culture, to transfect plant RBOH genes and to measure ROS production in cells transfected with RBOH.

2

Materials

2.1 Media and Buffers

1. Culture medium: Dulbecco’s Modified Eagle Medium Ham’s Nutrient Mixture F-12 (DMEM/F-12 Ham) with 10% (v/v) Fetal Bovine Serum (FBS) (see Note 1). 2. Opti-MEM® I Reduced-Serum Medium (see Note 2). 3. BAMBANKER® Serum-Free Cell Freezing Medium. 4. PBS (Phosphate-buffered saline), autoclave. 5. Hanks’ Balanced Salt Solution (HBSS), calcium chloride, magnesium chloride, no phenol red (see Note 3).

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Solutions

1. 0.05% trypsin-EDTA (pH 7.4). 2. GeneJuice® Transfection Reagent. 3. Dimethyl sulfoxide (DMSO) (see Note 4). 4. Luminol (sodium salt) stock solution of 0.4 M in dH2O (see Note 5). Make 100 μL aliquots and store at 20  C. 5. ROS assay buffer: 6 units/mL horseradish peroxidase (HRP), 250 μM luminol in HBSS. Cover the tube with aluminum foil (HRP and luminol are light sensitive) (see Note 6). 6. 3 μM ionomycin solution: Prepare a stock solution of 1 mM in DMSO. Make 100 μL aliquots and store at 20  C. To prepare 8 mL of 3 μM ionomycin solution, add 24 μL of 1 mM stock with 8 mL of the ROS assay buffer, and cover the tube with aluminum foil (see Note 7). 7. 0.2 μM calyculin A solution: Prepare a stock solution of 0.1 mM in DMSO. Make 100 μL aliquots and store at 20  C. To prepare 8 mL of 0.2 μM calyculin A solution, add 16 μL of 0.1 mM stock with 8 mL of ROS assay buffer, and cover the tube with aluminum foil (see Note 8). 8. 1SDS sample buffer with 7–10% (v/v) 2-mercaptoethanol (2-ME) and 100–300 mM dithiothreitol (DTT) (see Note 9).

2.3

Equipment

1. Endotoxin-free plasmid DNA purification kit. 2. Tissue cell culture flask with vent cap (75 cm2) (see Note 10). 3. Poly-D-lysine coated 96 well white plate (flat bottom with lid) (see Note 11). 4. Plastic petri dish (90 mm). 5. Tissue culture dish (60 mm). 6. Disposable hemocytometer. 7. Tally counter. 8. 8-channel pipette. 9. Water bath. 10. Inverted microscope. 11. CO2 incubator. 12. Laminar flow hood (clean bench). 13. Microtiter plate reader with injector and temperature control.

3

Methods Methods 3.2, 3.3, 3.7, and 3.8 should be performed in a sterile environment.

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1. Prepare RBOH constructs in pcDNA3.1 vector. Insert Kozak sequence (GCCGCCACC) and epitope tag at the N-terminus of the RBOH coding region (see Fig. 1a) (see Notes 12 and 13). 2. Prepare protein of your interest constructs in pEF1/myc-His vector. Insert Kozak sequence at the N-terminus of the protein coding region. Add an epitope tag at the N- or C-terminus as needed (see Fig. 1b) (see Notes 13 and 14). 3. Purify plasmid DNA from E. coli for transfection using an endotoxin-free plasmid DNA purification kit. After washing the plasmid DNA pellet with 70% ethanol, dissolve the pellet in sterile dH2O under a laminar flow hood (clean bench). The sterile purified plasmid DNA stock should be stored at 4  C as the freeze-thawing cycles will decrease the quality of DNA.

3.2 Subculture of HEK293T Cell and Preparation of 96 Well Plate for ROS Assay

1. Check the cells by microscopy to monitor viability, morphology, growth rates, and confluency (% surface area covered with cell layer) (see Fig. 2a) (see Note 15). 2. Prewarm culture medium and PBS in a 37  C water bath and trypsin-EDTA to room temperature (see Note 16). 3. Place the flask vertically and remove the old culture medium by aspirator or pipette without touching the cell layer (see Fig. 2b) (see Note 17). 4. Add 5 mL of prewarmed PBS to the opposite side of the cell layer, and briefly wash cells with PBS. Place the flask vertically and remove PBS. 5. Add 1 mL of trypsin-EDTA to the flask, and incubate at 37  C, 5% CO2 for 5 min to release cells from the flask. 6. Add 5 mL of prewarmed culture medium, and gently pipette cells up and down 5 times to obtain a single cell suspension, while avoiding frothing of medium. 7. Leave 1.5 mL of aliquot from the 6 mL cell suspension in the flask, and transfer the rest to a sterile 90 mm plastic petri dish (see Note 18). 8. Add 9.5 mL of prewarmed culture medium to the flask. Gently pipette cells up and down 5 times avoiding frothing of medium, and incubate at 37  C, 5% CO2 until the cell layer has become more than 80% confluent. 9. To separate cells gently pipette up and down the cell suspension in the 90 mm plastic petri dish 5 times. If cells are not separated, use a pipette attached with a 200 μL tip (see Fig. 2c). 10. Transfer 2 mL of the cell suspension to a new 90 mm plastic petri dish containing 8 mL of prewarmed new medium, and gently pipette cells up and down 5 times.

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(a)

Nhe I-GCC GCC ACC-(ATG-3×FLAG)-Bam HI-Eco RV-stop-Kpn I PCMV

Kozak 3×FLAG MCS

BGH pA

pcDNA3.1-3×FLAG-MCS Backbone: pcDNA3.1(-) Amp (b)

Bam HI-GCC GCC ACC-(ATG-CRK2)-Not I Kpn I-Bam HI-Not I-3×Myc-stop-Xba I PEF-1α

MCS

3×Myc

Myc-6xHis BGH pA

pEF1/MCS-3×Myc Backbone:pEF1/myc-His (B) Amp

Fig. 1 Examples of the plasmid map. (a) pcDNA3.1-Kozak-3FLAG-RBOHD [12, 30]. (b) pEF1-Kozak-Cysteine-rich receptor-like kinase 2 (CRK2)-3Myc [12]. PCMV Human cytomegalovirus promoter, PEF-1α Human elongation factor 1α-subunit promoter, MCS multiple cloning site, BGH pA Bovine growth hormone polyadenylation signal, Amp Ampicillin resistance gene

11. Take a 10 μL aliquot to count the cell density with a hemocytometer. 12. Adjust the cell density to 1.5  105 cells/mL, in a volume of 20 mL suspension (see Note 19). e.g., to prepare 20 mL of 1.5  105 cells/mL cell suspension from 6.0  105 cells/mL, add 5 mL of 6.0  105 cells/mL cell suspension with 15 mL of new culture medium (see Fig. 2d). 13. Take 10 μL to confirm that the cell density is in the range of 1.0 – 2.0  105 cells/mL. 14. Transfer a 130 μL aliquot to each well of a 96 well plate using an 8-channel pipette. 15. Incubate at 37  C, 5% CO2 for 12–24 h before transfection. 3.3

Transfection

1. Design a transfection experiment for ROS measurement (see Fig. 3). For example, if you plan to perform four measurements with a 96 well plate, transfect a total of 120 ng plasmid DNA to cells in each well of columns 1–12. Background ROS-producing activity of cells in row A and H should be checked before use for transfection. We use columns 1–3 for

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(b)

(c))

Pittette should not touch the cell layer surface. (d) 6.0 x 105 cells/mL

1.5 x 105 cells/mL

5 mL

+ 15 mL culture medium

Fig. 2 (a) Cell culture flask with HEK293T cells. (b) Place the flask vertically, and remove the old culture medium by pipette without touching the cell layer surface. (c) If cells are not separated, use a pipette attached with a 200 μL tip. (d) An example of cell dilution for ROS assay measurement 1st 1

2

2nd 3

4

5

3rd 6

7

8

4th 9

10

11

12

A B

RBOH (120 ng)

C

Empty vector (120 ng)

D

Protein of interest (120 ng)

E

RBOH (100 ng) + Protein of interest (20 ng)

F

RBOH (100 ng) + GFP control (20 ng)

G

Empty vector (100 ng) + Protein of interest (20 ng)

H

Fig. 3 An example of a plate design for transfection. Drawing of transfection design for four measurements with a 96 well plate. Transfect a total of 120 ng plasmid DNA (RBOH, protein of interest and negative controls such as empty vector and GFP) to cells in each well of column 1–12. Depending on the plate reader, row A and H may give a higher background. Therefore, it would be better to compare chemiluminescence from non-transfected cells in row A and H vs. empty vector-transfected cells in the other row before use for transfection

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Table 1 Composition of transfection master mix Components/well of 96 well plate

1 Master mix (μL)

13Master mix (μL)

6.3

81.9

0.36

4.68

100 ng/μL RBOH Plasmid DNA (120 ng)

1.2

15.6

Total volume

7.86

102.18

Opti-MEM GeneJuice

®

®

Table 2 Composition of cotransfection master mix Components/well of 96 well plate

1 Master mix (μL)

13Master mix (μL)

Opti-MEM®

6.3

81.9

0.36

4.68

100 ng/μL RBOH Plasmid DNA (60–100 ng)

0.6–1

7.8–13

100 ng/μL Regulator Plasmid DNA (20–60 ng)

0.2–0.6

2.5–7.8

Total volume

7.86

102.18

GeneJuice

®

The total amount of plasmid DNA should not exceed 120 ng, e.g., pcDNA3.1-3FLAG-AtRBOHD (100 ng) and pEF1CRK2-3Myc (20 ng) or pEF1-3Myc-GFP (20 ng) were co-transfected [12]

the first measurement, columns 4–6 for the second, columns 7–9 for the third, and columns 10–12 are for the fourth measurement. 2. Calculate the required amounts of serum-free medium, transfection regent, and plasmid DNA (see Tables 1 and 2). 3. Dilute the endotoxin-free plasmid DNA stock to a concentration of 100 ng/μL with sterile dH2O (see Note 20). 4. Place Opti-MEM® I Reduced-Serum Medium into a sterile 1.5 mL tube. Add Genejuice® Transfection Reagent directly to the serum-free medium. 5. Mix thoroughly by vortexing and spin down. 6. Incubate at room temperature for 5 min. 7. Add plasmid DNA to GeneJuice®/Opti-MEM® mixture. Mix by gentle pipetting. Do not vortex. 8. Incubate at room temperature for 5 min. 9. Add 7.86 μL of GeneJuice®/Opti-MEM®/DNA mixture drop-wise to cells in 96 well plate. Distribute drops over the entire surface of well. Make a drop on the tip of a pipette above the well, and gently touch the surface of the medium in the 96 well plate.

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10. Gently rock dish to ensure even distribution. Do not swirl plate, as doing so will concentrate transfection mixture in center of plate. 11. Incubate at 37  C, 5% CO2 for 48 h. 3.4 ROS Measurement

1. Prepare the ROS assay buffer, 3 μM ionomycin solution, and/or 0.2 μM calyculin A solution. 2. Prime the injector with 3 μM ionomycin solution and/or 0.2 μM calyculin A solution. Set measurement program of the microplate reader (see Note 21). 3. Carefully remove the old medium from each well to be measured using an 8-channel pipette and avoid scratching the cell surface. 4. Gently add 130 μL of HBSS to wash the cells using an 8-channel pipette but avoid scratching the cell surface (let HBSS run down along the internal surface of the well). 5. Carefully remove the HBSS and gently add 50–100 μL of the ROS assay buffer using an 8-channel pipette while avoiding scratching of the cell surface (let buffer run down along the internal surface of the well) (see Note 22). 6. Place the 96 well plate in the microplate reader and start monitoring luminescence. Before the addition of ionomycin or calyculin A, the background level has to be measured for about 5–30 min. Interrupt the background measurement by addition of ionomycin or calyculin A, and continue the measurement for 20–25 min.

3.5 Representative Data

3.6 Protein Extraction for Western Blot Analysis

Monitored ROS production is presented in RLU (relative light units). Since RLU can vary by plate reader, it is difficult to compare the results obtained from different machines. The measurement of ROS production over time results in a kinetics curve as it is shown in the example graph (see Fig. 4). Values should be represented as mean  SEM of n ≧ 3. While ionomycin frequently induces transient ROS production in RBOH-transfected cells, calyculin A typically induces sustained ROS production (see Fig. 4a, b). Calyculin A and ionomycin synergistically quite often activate ROS-producing activity of RBOH in HEK293T cells (see Fig. 4c). 1. Prepare fresh 1SDS sample buffer. 2. Choose 3 wells of each transfected line, and remove the ROS assay buffer (typically the wells measured last are suitable). 3. Add 75 μL of the 1SDS sample buffer. 4. Collect the lysates into 1.5 mL tube (attention: high viscosity), and incubate for 10–60 min at room temperature (see Note 23).

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(a)

(b)

ROS production (RLU/s)

Ionomycin

Ionomycin-induced ROS

Negative control 0

5

10

15 20 Time (min)

25

ROS production (RLU/s)

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Calyculin A

Negative control 0

30

Calyculin A-induced ROS

5

10

15 20 Time (min)

25

30

(c) ROS production (RLU/s)

Ionomycin

Calyculin A + Ionomycin-induced ROS

Calyculin A-induced ROS Calyculin A

Iomomycin-induced ROS 0

5

10

15

20 25 Time (min)

30

35

40

Fig. 4 Typical patterns of ROS production of RBOH-transfected HEK293T cells. (a) Ionomycin-induced transient ROS production suggesting that RBOH is activated by Ca2+ influx into cells. (b) Calyculin A-induced sustained ROS production suggesting that RBOH is activated by protein phosphorylation. (c) Synergistic activation of RBOH by calyculin A and ionomycin

5. Store at

20  C.

6. Fragment the genomic DNA to reduce viscosity by sonication or pipetting the sample up and down using a sterile 1 mL syringe with a narrow needle (e.g., 25G  16 mm) 5–10 times. 7. Subject 10–50 μL of the protein sample to SDS-PAGE and subsequent Western blot analysis (see Note 24). 3.7 Starting Cell Culture from Frozen HEK293T Cells Stock

1. Thaw a frozen stock of HEK293T in a 37  C water bath. 2. Pipette once very gently, and slowly transfer into 15 mL conical tube containing 5 mL of prewarmed culture medium. 3. Centrifuge at 100g for 5 min at room temperature to pellet cells, and remove the supernatant carefully by aspirator or pipette without disturbing the pellet. 4. Add 5 mL of prewarmed culture medium, and very gently suspend by pipetting cells up and down.

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HEK293T frozen stock (a) If you do not make frozen stocks

(b) If you make frozen stocks

60 mm culture dish

60 mm culture dish × 4

T75 flask

Mix together from three dishes

90 mm plastic petri dish Start periodical subculture

100×g, 5 min

Aliquot 1mL into cryotubes and store at -80°C

Resuspend cells in BAMBANKER® at 1.0 - 2.0×106 cells/mL

50 mL conical tube

Fig. 5 (a) Schematic diagram of experiments starting cell culture from frozen stock (see Method 3.7). (b) Schematic diagram of experiments preparing new frozen stocks from frozen stock (see Method 3.8)

5. Transfer cell suspension to a 60 mm culture dish. 6. Incubate at 37  C, 5% CO2 until the cell layer has become more than 80% confluent (see Note 25). 7. When the cells are approximately 80% confluent, remove the old culture medium, and briefly wash the cells with 1 mL of prewarmed PBS while avoiding damage of the cell layer. 8. Remove PBS and add 400 μL of trypsin-EDTA. 9. Incubate at 37  C for 5 min for cells to release from the dish. 10. Add 5 mL of prewarmed culture medium, and gently pipette cells up and down 5 times. 11. Transfer all of the cell suspension into a new T75 flask containing 6 mL of prewarmed culture medium, and gently pipette cells up and down 5 times (see Fig. 5a). 12. Incubate at 37  C, 5% CO2 and start periodical subculture (see Note 26).

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3.8 Freezing Cells for New Frozen Stocks

1. Steps 1–9 are identical to the starting cell culture from frozen HEK293T cells stock. 2. During the 5 min incubation period, prepare 4 new 60 mm dishes containing 5 mL of prewarmed culture medium (see Fig. 5b). 3. Add 5 mL of prewarmed culture medium to the trypsin-treated cells, and gently pipette up and down 5 times. 4. Aliquot 1 mL of the cell suspension to each of the 60 mm dishes, and gently pipette cells up and down 5 times. 5. Incubate at 37  C, 5% CO2. 6. When the cells are approximately 80% confluent, take one 60 mm dish from the CO2 incubator. Repeat the starting cell culture from frozen HEK293T cells stock steps 7–12 with the dish. 7. Take the rest of three dishes from CO2 incubator, and repeat the starting cell culture from frozen HEK293T cells stock steps 7–10 with each of the three dishes. 8. Combine the suspension from the three dishes to a new 90 mm plastic petri dish. 9. Count the cell density and calculate the volume (X mL) to be processed. HEK293T cells should be frozen and stored at 1.0 2.0  106 cells/mL (see Note 27). 10. Take X mL of the suspension in a clean 50 mL conical tube, and centrifuge at 100g for 5 min at room temperature. 11. Remove the supernatant and resuspend in appropriate amount of BAMBANKER® and aliquot 1 mL into cryotubes. 12. Store at

4

80  C (see Note 28).

Notes 1. We have tested DMEM/F-12 Ham, FBS (qualified/characterized grade). Heat-inactivated FBS is not necessary for this protocol. Prepare 28–28.5 mL aliquots of FBS and store at 20  C. To prepare DMEM/F-12 Ham with 10% FBS, add 56 mL of FBS (two aliquots) into 500 mL DMEM/F-12 Ham bottle. While HEK293T cells are resistant to neomycin, considering potential effects of neomycin on the ROS assay, we do not routinely use neomycin for subculture. 2. We change the Opti-MEM® for a fresh bottle every 6 months after the opening. 3. HBSS (no calcium chloride, no magnesium chloride, no phenol red) is used according to the intended application. 4. DMSO for cell culture.

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5. L-012 stock solution of 62.4 mM in dH2O. 6. Prepare 30 mL of ROS assay buffer for 1 plate (45 mL for 2 plates). (1) Take 30 mL HBSS into 50 mL tube. (2) Place 2.0 mg of HRP (100 units/mL) into 1.5 mL tube. (3) Add 100 μL of HBSS from the 30 mL of HBSS to HRP. Mix by vortexing. You have 20 mg/mL HRP/HBSS in the 1.5 mL tube. (4) Add 90 μL of 20 mg/mL HRP/HBSS into the 30 mL of HBSS in 50 mL tube. (5) Add 18.8 μL of 0.4 M luminol stock (or 200 μL of 62.4 mM L-012 stock). 7. Prepare 8 mL of 3 μM ionomycin solution for 1 plate (13 mL for 2 plates). 8. Prepare 8 mL of 0.2 μM calyculin A solution for 1 plate (13 mL for 2 plates). 9. 1SDS sample buffer should be prepared fresh every time. Prepare 2stock solution of 156 mM Tris-HCl (pH6.8), 5% (w/v) SDS, 12.5% (w/v) sucrose, 0.01% (w/v) bromophenol blue (BPB) in dH2O. Store at room temperature. To prepare 2 mL of 1SDS sample buffer with 7–10% (v/v) 2-ME and 100–300 mM DTT, add 1 mL of 2SDS sample buffer, 140–200 μL of 2-ME, 0.03–0.09 g of DTT with dH2O. 10. Poly-D-lysine coating is not necessary. 11. We use Bio Coat PDL 96 well white plate (sterile, poly-Dlysine coated, flat bottom with rid). 12. Kozak sequence will increase transcription efficiency. Epitope tags fused to the C-terminus can disrupt the activity of RBOHs. 13. In case the protein expression level of your RBOH or other protein of interest is low, codon-optimization of coding sequence could increase the expression. 14. As a negative control for cotransfection, we use green fluorescent protein (GFP). 15. Media in the flask should be pink/orange in color. A pale-yellow color of media indicates acidity and decrease of pH which is often associated with contamination or unhealthy cells. When the cells are approximately 80% confluent, cells will require sub-culturing. It is not recommended to allow cells to become over confluent as this may negatively affect gene expression. 16. Do not warm Trypsin-EDTA to 37  C to avoid self-digestion. 17. HEK293T cells detach easily from the flask bottom surface; therefore handle the cells gently. 18. This means cells are passaged in a ratio of 1:4 (1.5:6). A 1:4 split should be 80% confluent in 2 days. 1:10 split should be 80% confluent in 3 days. If you do not prepare the plate for ROS measurement, you can discard the rest of cell suspension instead of transferring to a 90 mm plastic petri dish.

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19. Prepare 20 mL of cell suspension for 1 plate (30 mL for 2 plates). 20. 100 ng/μL of plasmid DNA stock can be stored at 4  C for 1 month. Plasmid quality is critical for transfection efficiency. 21. Select 3 wells (at least) of each transfected line. Set injection volume to 50 μL and chemiluminescence measurement each well for 1 s in a 1-minute interval. Repetitions of measurement cycle/total time should be set to appropriately monitor chemiluminescence for 30–60 min. Set the temperature of microplate reader to 37  C 22. Amount of ROS assay buffer. (a) 1 μM ionomycin application: ROS assay buffer 100 μL + 3 μM ionomycin solution 50 μL. (b) 0.1 μM calyculin A application: ROS assay buffer 50 μL + 0.2 μM calyculin A solution 50 μL. (c) Both 0.1 μM calyculin A and 1 μM ionomycin application: ROS assay buffer 50 μL + 0.2 μM calyculin A solution 50 μL +3 μM ionomycin solution 50 μL (see Fig. 4). Option: If you would like to test Diphenyleneiodonium (DPI), a flavoenzyme inhibitor which is broadly used as NOX inhibitor, prepare ROS assay buffer containing DPI. 23. Given heat denaturation can lead to RBOH protein aggregation, 1SDS buffer contains a high concentration of 2-ME and DTT as an alternative to heat denaturation. 24. To evaluate ROS production in RBOH-transfected cells properly, its protein expression level should be confirmed by Western blotting. We used anti-FLAG antibody and anti-Myc antibody to check the protein expression level of 3FLAGRBOHD, CRK2-3Myc, and 3Myc-GFP [12] (see Note 13). Sometimes a transfected gene can have a negative effect on HEK293T cell viability. Thus, you should check its effect by using antibodies against housekeeping proteins, for example, cytoskeletal proteins such as anti-β-Actin. 25. After a thawing, cultures usually contain a large fraction of floating dead cells or debris. Option: Gently replace medium after 24–48 h with 5 mL of prewarmed culture medium, and continue to incubate at 37  C, 5% CO2. 26. Subculture cells at least 3 times (~1 week) before using them in the ROS measurement. One month later, it is recommended to thaw a new frozen stock and start a new culture. 27. For example: To prepare 2  106 cells/mL stock from 14 mL of 1  106 cells/mL suspension, centrifuge the cell suspension, and resuspend the cells pellet in 7 mL of BAMBANKER®. 28. BAMBANKER® does not require flash freezing with liquid nitrogen.

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Part III Small-Scale Targeted Analysis of ROS Accumulation During Stress and Effects on Plant Physiology

Chapter 9 Estimation of the Level of Abasic Sites in Plant mRNA Using Aldehyde Reactive Probe Jagna Chmielowska-Ba˛k, Karolina Izbian´ska-Jankowska, and Joanna Deckert Abstract Oxidation of RNA is associated with the development of numerous disorders including Alzheimer’s and Parkinson’s diseases, amyotrophic lateral sclerosis (ALS), cancer, and diabetes. Additionally, a correlation has been found between increase in RNA oxidation and the process of aging. In plants, elevated level of oxidatively modified transcripts has been detected during alleviation of seeds dormancy and stress response. Increasing interest on the topic of RNA oxidative modifications requires elaboration of new laboratory techniques. So far, the most common method used for the assessment of RNA oxidation is quantification of 8-hydroxyguanine (8-OHG). However, reactive oxygen species (ROS) induce also numerous other changes in nucleic acids, including formation of abasic sites (AP-sites). Recently, the level of AP-sites in RNA has been measured with the use Aldehyde Reactive Probe (ARP). In the present chapter, we describe application of this technique for the evaluation of the level of AP-sites in plant transcripts. Key words Ribonucleic acid, Oxidation, Abasic sites, Reactive oxygen species, Oxidative stress, Aldehyde Reactive Probe

Abbreviations AP-sites ARP ROS

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abasic sites Aldehyde Reactive Probe reactive oxygen species

Introduction Reactive oxygen species (ROS) are called double-faced molecules. On one hand they are involved in plants physiological processes such as signalling, cell differentiation, and regulation of gene expression. On the other hand, their over-accumulation leads to oxidative stress [1]. The consequences of ROS-dependent

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_9, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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oxidation of biomolecules is ambiguous. ROS action might damage lipids, proteins, and nucleic acids alerting their optimal functioning. However, it has been proposed that some molecules derived from ROS-dependent oxidation can act as signalling and gene regulatory elements [2, 3]. Recently an increasing attention has been paid to the role of oxidative modifications in transcripts. It has been evidenced in animal models that intensified RNA oxidation is related to the process of aging and development of numerous disorders such as Alzheimer’s and Parkinson’s diseases, amyotrophic lateral sclerosis (ALS), hemochromatosis, cancer, and diabetes [reviewed in 4 and 5]. In plants, increased levels of RNA oxidative modifications have been demonstrated in the processes of the breakage of seed dormancy and response to abiotic and biotic stress factors [6– 10]. Interestingly it has been evidenced that at least some oxidative modifications of transcripts are formed in a selective manner and provoke inhibition of the translation of specific proteins [6, 7, 11, 12]. The emerging role of RNA oxidative modifications in physiological and pathological processes in animals and plants gains increasing interest. Thus, new methods for the assessment of RNA oxidation are required. The most common oxidative modification of RNA is 8-hydroxyguanosine (8-OHG, 8-oxoG). The level of this modification can be quantified, for example, by the means of competitive ELISA kits or high-performance liquid chromatography (HPLC). The level of 8-OHG has been measured in various animal and plant samples including human urine samples, human and mouse brain tissues, sunflower and wheat seeds, maize and soybean seedlings, and Arabidopsis plants [6–13]. Reactive oxygen species (ROS) induce, beside 8-OHG, also other changes in nucleic acids [3]. One of the results of DNA damage and/or action of repairs systems is loss of bases and resultant formation of abasic sites, referred also as apurinic/apyrimidinic sites (AP-sites) [14]. Elevated levels of AP-sites in animal DNA are associated with exposure to toxic agents. Bank voles inhabiting polluted sites were characterized by elevated levels of AP-sites in DNA related to higher metal content in liver and/or kidneys [15]. Similarly, AP-sites in DNA were induced by iron in rats’ brain tissue and exposure to chemotherapeutical drug, nitrogen mustard (NM), in mice liver [16, 17]. The frequency of AP-sites is assessed by the means of Aldehyde Reactive Probe (ARP). Initially this method has been developed for the quantification of AP-sites in DNA [18]. In subsequent years it has been successfully applied to quantify AP-sited in DNA derived from various models including HeLa cells, human pancreatic carcinoma cells, human leukocytes, rat kidney cells, and calf thymus [19–23]. In 2011, the ARP method has been adopted by Tanaka and colleagues for the detection of the AP-sites in RNA [24]. In the

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Fig. 1 Scheme presenting specific steps of the procedure applied for quantification of AP-sites in mRNA derived from plant tissues. ARP Aldehyde Reactive Probe, HRP horseradish peroxidase

present chapter, we describe in details the application of this method for the evaluation of the level of AP-sites in mRNA isolated from plant tissues. The procedure has been originally used for the estimation of the level of mRNA oxidation in the roots of soybean seedlings exposed to cadmium stress [7]. The first methodological section of the present chapter describes exemplary cultivation, treatment, and sampling procedures. The second section presents the procedure of total RNA isolation from plant samples by the means of commonly used reagents based on method reported by Chomczynski and Sacchi [25]. Subsequent sections describe in detail the ARP method used for assessment of AP-sites in purified mRNA. The first step of the procedure comprises binding of aminooxy groups of aminooxymethylcarbonylhydrazino D-biotin to the abasic sites in transcripts. The subsequent step consists in detection of the AP-sites using streptavidin-horseradish peroxidase and their visualization by the means of chemiluminescence. The level of the AP-sites is reflected by the intensity of black spots developed on the membrane. The specific steps of the procedure are presented on Fig. 1.

2

Materials

2.1 Buffers and Solutions

1. 100% and 75% ethanol 2. 1% sodium hypochlorite solution (e.g., diluted bleach) 3. Reagent for RNA isolation (e.g., TriReagent, Trizol, Extrazol [25]) 4. Chloroform 5. Isopropanol

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6. Kit dedicated for mRNA purification 7. Blocking solution (e.g., 1% casein blocking buffer, 1 g of casein dissolved in 100 ml of distilled water) 8. ECL solution; (e.g., Clarity Western ECL Substrate consisting of luminol/enhancer solution and peroxide solution mixed in equal volumes immediately prior to use) 9. Phosphate saline buffer (PBS) 10. RNase free water 11. 3 M sodium acetate pH ¼ 5.2 12. 10 mM Tris-EDTA buffer, pH ¼ 8.0 13. TWEEN® 20 14. 50 mM formaldehyde 15. Hybond N+ membranes (e.g., Zeta-Probe® GT Membrane) 16. N0 - aminooxymethylcarbonylhydrazino D-biotin (ARP) 17. Streptavidin-Horseradish peroxidase 2.2

Equipment

1. Fume hood 2. Centrifuge capable of centrifugation by 16 000 g at 4  C 3. Heating block 4. Spectrophotometer or NanoDrop for mRNA quantification 5. Gel/membrane imaging system for chemiluminescence 6. UV crosslinker 7. Orbital shaker 8. Software for Densitometric Analysis (e.g., Image Lab Software: Densitometric Analysis of Gels and Western Blots, BioRad)

3

Methods

3.1 Plant Cultivation and Treatment

1. Sterilize soybean seeds by submerging for 5 min in 75% ethanol and thereafter for 10 min in solution containing 1% sodium hypochlorite (e.g., diluted bleach). 2. Wash the seeds for 30 min under running water. 3. Soak the seeds for 3–4 h in tap water. 4. Place the seeds in sterilized Petri dishes of 300 mm of diameter lined with two layers of blotting paper and one layer of lignin. 5. Water the seeds with 30 ml of tap water, and leave for germination for 48 h in growing chamber set for 21–22  C in the dark. 6. Transfer the seedlings selected based on similar roots length to previously sterilized Petri dished of 100 mm of diameter with

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Fig. 2 Visualization of the proposed placement of the seedlings on Petri dishes before treatment with appropriate solutions

two layers of lignin with 10 cut out holes in the upper layer. Place the roots of the seedlings in the cut out holes to locate them between the two lignin layers (as shown in Fig. 2). 7. Treat the seedlings with 5 ml of appropriate solutions (e.g., distilled water in the case of control, metal solutions). 8. After defined treatment time, cut the roots off on ice, transfer to Eppendorf tubes, freeze immediately in liquid nitrogen, and store in 80  C. 3.2 Isolation of Total RNA

1. Add 1 mL of reagent dedicated for RNA isolation to the Eppendorf tubes containing frozen samples (e.g., TRI Reagents, Extrazol, Trizol) (see Notes 1 and 2). 2. Homogenize the samples and incubate 15 min at room temperature. 3. Add 200 μL of chloroform, mix thoroughly, and incubate 20 min at room temperature. 4. Centrifuge 15 min at 4  C by 13 500 g, and thereafter transfer the aqueous phase to new Eppendorf tube (see Note 3). 5. Add 500 μL of isopropanol, mix thoroughly, and incubate 10 min at room temperature. 6. Centrifuge 10 min at 4  C by 14 500 g and discard the supernatant. 7. Wash the precipitate with 1 mL of 75% sterile frozen ethanol.

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8. Centrifuge 5 min at 4  C by 5 500 g; remove the ethanol. 9. Dissolve the RNA in 30 μl of sterile RNase free water. 3.3 Binding of ARP with mRNA Abasic Sites

1. Purify mRNA from the total RNA using dedicated kits according to manufacturer’s instructions (see Note 4). 2. Prepare 5 μg of mRNA in 50 μL of RNase free water (see Note 5). 3. Add 50 μL of 2 mM N0 - aminooxymethylcarbonylhydrazino D-biotin (ARP) dissolved in 10 mM Tris-EDTA. 4. Incubate 1 h at 37  C. 5. Add 50 μL of 50 mM formaldehyde to terminate the reaction (under fume hood). 6. Precipitate the RNA in 15 μL of 3 M sodium acetate and 450 μL of ice-cold ethanol in 20  C during the night. 7. Centrifuge 20 min at 4  C by 13 500 g. 8. Wash with 500 μL of 75% ice-cold ethanol. 9. Centrifuge 20 min at 4  C by 13 500 g. 10. Dissolve the sediment in 10 μL of Tris-EDTA. 11. Quantify the amount of mRNA using NanoDrop, NanoCell, or other equipment predestined for nucleic acids quantification in small sample volume (see Note 6). 12. Prepare samples comprising 300–1000 ng of mRNA dissolved in Tris-EDTA (see Notes 7 and 8).

3.4 Detection and Quantification of Abasic Sites in mRNA

1. Soak the Hybond N+ membrane in Tris-EDTA. 2. Air dry the membrane for around 10 min at room temperature (see Note 9). 3. Pipette the samples on the membrane (step 12 in Subheading 3.3) (see Note 10). 4. Air dry the membrane for around 10 min. 5. Irradiate the membrane with UV (λ ¼ 254 nm) light for 15 min. 6. Incubate the membrane for 30 min in blocking solution at room temperature with gentle shaking (see Note 11). 7. Incubate 1 h with streptavidin-horseradish peroxidase dissolved at 1:20 000 proportion in blocking solution at room temperatures with gentle shaking (see Note 12). 8. Wash 6 times for 4 min in PBS with 0.05% Tween on an orbital shaker. 9. Incubate in ECL solution for 5 min with gentle shaking. 10. Capture the chemiluminescence during 5–30 min of exposure time (see Note 13).

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Notes 1. The isolation of RNA from 5 to 20 samples takes around 3–4 h. 2. Due to the toxicity of the used reagents, the procedure should be performed under the fume hood. The surfaces should be cleaned with tissues/sprays containing RNase inhibitors. All used small laboratory equipment (e.g., Eppendorf tubes, pipette endings) should be sterilized prior to use. 3. Caution should be paid not to mix the phases. Usually it is possible to transfer 300–450 μl of the aqueous phase. 4. To avoid loss of RNA, it is recommended to carry out the mRNA purification directly after total RNA isolation. The procedure takes approx. 2 h. 5. The total time required for the procedure is 8–9 h, divided into 2 days as presented in Table 1. 6. Obtaining proper quantity of mRNA was a crucial step in the method. In order to preserve as much mRNA as possible, its quantity has been measured in 1 μl using highly sensitive equipment for nucleic acids quantification. Simultaneously, the purity of mRNA has been estimated on the basis of OD260/OD280 ¼ 2.0. 7. The images were of the best quality when 1 μg of mRNA has been dissolved in 3.5 μl of 10 mM Tris-EDTA and then transferred with automatic pipette on the membrane. The proposed concentration was valid for mRNA. However, in the case of total RNA, no images were obtained using same procedure and same concentrations indicating higher mRNA susceptibility for the formation of abasic sites. Most likely in the case of total RNA higher quantities (e.g., 5–10 μg) should be used to evaluate the level of abasic sites using described method.

Table 1 The estimation of time needed for the assessment of the level of AP-sites in isolated mRNA 1st day of the procedure Steps 1–5 in Subheading 3.1 (excluding the time needed for RNA defreezing and quantification)

2–3 h

2nd day of the procedure Steps 6–11 in Subheading 3.1

Approx. 2 h

Steps 1–10 in Subheading 3.2

Approx. 4 h

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Fig. 3 Image of the detection of AP-sites in soybean mRNA using ARP-based method. The mRNA has been isolated from the control plants (control) and plants treated for 6 h with CdCl2 with Cadmium at the concentration of 10 and 25 mg/L (Cd10 and Cd25, respectively). The level of AP-sites is reflected by the intensity of black spots developed on membrane. Current results show that exposure to Cadmium at this time point has limited effect on the level of AP-sites

8. In parallel the negative control has been prepared using ARP dissolved in 10 mM Tris-EDTA buffer, without the RNA. 9. The procedure has been carried out on the cut pieces of membranes of the size 10  7.5 cm. It is also very important to make sure that the membrane is well dried after steps 2 and 4. 10. Attention should be paid to pipette all samples on the porous side of the membrane. Minimize the area that the samples penetrate the membrane (usually 3–4 mm diameter) by applying it slowly. 11. The blocking, incubation with streptavidin-horseradish peroxidase, washing and membrane developing have been performed on a rocking platform. 12. The streptavidin-horseradish peroxidase (1 μg) has been dissolved in 20 mL of blocking solution immediately before use. 13. In our case the chemiluminescence has been captured during 15 min exposure time with images captured every 7 s. A representative image is presented in Fig. 3. Thereafter, the intensity of spots was measured densitometrically using appropriate software (e.g., Lab Software: Densitometric Analysis of Gels and Western Blots). The spots have been outlined and their average optical density has been quantified. The optical density of the background has been subtracted and the result divided by pixel2 according to the formula Q-B/pixel2, where Q is optical density of the spots and B is the optical density of the background.

Acknowledgments The method has been applied in research project number 2014/ 13/D/NZ9/04812 financed by the National Science Center, Poland.

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References 1. Dumanovic´ J, Nepovimova E, Natic´ M, Kucˇa K, Jac´evic´ V (2020) The significance of reactive oxygen species and antioxidant defense system in plants: a concise overview. Front Plant Sci 11:552969. https://doi.org/10. 3389/fpls.2020.552969 2. Mittler R, Vanderauwera S, Suzuki N, Miller G, Tognetti VB, Vandepoele K, Gollery M, Shulaev V, Breusegem FV (2011) ROS signaling: the new wave? Trends Plant Sci 16:300– 309. https://doi.org/10.1016/j.tplants. 2011.03.007 3. Chmielowska-Ba˛k J, Izbian´ska K, Deckert J (2015) Products of lipid, protein and RNA oxidation as signals and regulators of gene expression in plants. Front Plant Sci 6:405. https://doi.org/10.3389/fpls.2015.00405 4. Poulsen HE, Specht E, Broedbaek K, Henriksen T, Ellervik C, Mandrup-Poulsen T, Tonnesen M, Nielsen PE, Andersen HU, Weimann A (2012) RNA modifications by oxidation: a novel disease mechanism? Free Radical Biol Med 52:1353–1361. https://doi.org/10. 1016/j.freeradbiomed.2012.01.009 5. Li Z, Chen X, Liu Z, Ye W, Li L, Qian L, Ding H, Li P, Aung LHH (2020) Recent advances: molecular mechanism of RNA oxidation and its role in various disease. Front Mol Biosci 7:184. https://doi.org/10.3389/ fmolb.2020.00184 6. Bazin J, Langlade N, Vincourt P, Arribat S, Balzergue S, El-Maarouf-Bouteau H, Bailly C (2011) Targeted mRNA oxidation regulates sunflower seed dormancy alleviation during dry after-ripening. Plant Cell 23:2196–2208. https://doi.org/10.1105/tpc.111.086694 7. Gao F, Rampitsch C, Chitnis VR, Humphreys GD, Jordan MC, Ayele BT (2013) Integrated analysis of seed proteome and mRNA oxidation reveals distinct post-transcriptional features regulating dormancy in wheat (Triticum aesativum L.). Plant Biotechnol J 11:921–932. https://doi.org/10.1111/pbi.12083 8. Chmielowska-Ba˛k J, Izbian´ska K, EknerGrzyb A, Bayar M, Deckert J (2018) Cadmium stress leads to rapid increase in RNA oxidative modifications in soybean seedlings. Front Plant Sci 8:2219. https://doi.org/10.3389/fpls. 2017.02219 9. Labudda M, Ro´z˙an´ska E, Czarnocka W, Sobczak M, Dzik JM (2018) Systemic changes in photosynthesis and reactive oxygen species homeostasis in shoots of Arabidopsis thaliana infected with the beet cyst nematode Heterodera schachtii. Mol Plant Pathol 19:1690– 1704. https://doi.org/10.1111/mpp.12652

10. Sytykiewicz H, Łukasik I, Goławska S, Chrzanowski G (2019) Aphid-triggered changes in oxidative damage markers of nucleic acids, proteins, and lipids in maize (Zea mays L.) seedlings. Int J Mol Sci 20:3742. https://doi.org/ 10.3390/ijms20153742 11. Shan X, Tashiro H, Lin CG (2003) The identification and characterization of oxidized RNAs in Alzheimer’s disease. J Neurosci 23:4913– 4 9 2 1 . h t t p s : // d o i . o r g / 1 0 . 1 5 2 3 / JNEUROSCI.23-12-04913.2003 12. Chang Y, Kong Q, Shan X, Tian G, Llieva H, Cleveland DW, Rothstein JD, Borchelt DR, Wong P, Lin CG (2008) Messenger RNA oxidation occurs early in disease pathogenesis and promotes motor neuron degeneration in ALS. PLoS One 3:e2849. https://doi.org/10. 1371/journal.pone.0002849 13. Pappas-Gogos G, Tellis CC, Tepelenis K, Vlachos K, Chrysos E, Tselepis AD, Glantzounis GK (2021) Urine 8-hydroxyguanine (8-OHG) in patients undergoing surgery for colorectal cancer. J Investig Surg 3(8):e2849. https://doi.org/10.1080/08941939.2021. 1904466 14. Berquist BR, Wilson DM III (2012) Pathways of repairing and tolerating the spectrum of oxidative DNA lesions. Cancer Lett 327:61– 72. https://doi.org/10.1016/j.canlet.2012. 02.001 15. Mikowska M, S´wiergosz-Kowalewska R (2018) DNA damage in liver tissues of metal exposed Clethrionomys glareolus. Chemosphere 199:625–629. https://doi.org/10.1016/j. chemosphere.2018.02.053 16. Chen H, Cui Z, Hejazi L, Yao L, Walmsley SJ, Rizzo CJ, Turesky RJ (2020) Kinetics of DNA adducts and abasic site formation in tissue of mice treated with nitrogen mustard. Chem Res Toxicol 33:988–998. https://doi.org/10. 1021/acs.chemrestox.0c00012 17. Nakamura T, Keep RF, Hua Y, Nagao S, Hoff JT, Xi G (2006) Iron-induced oxidative brain injury after experimental intracerebral hemorrhage. Acta Neurochir 96:194–198. https:// doi.org/10.1007/3-211-30714-1_42 18. Kubo K, Ide H, Wallace SS, Kow YW (1992) A novel, sensitive, and specific assay for abasic sites, the most commonly produced DNA lesion. Biochemistry 31:3703–3708. https:// doi.org/10.1021/bi00129a020 19. Asaeda A, Ide H, Tano K, Takamori Y, Kubo K (2006) Repair kinetics of abasic sites in mammalian cells monitored by the aldehyde reactive probe (ARP). Nucleos Nucleot Nucl 17:503–

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5 1 3 . h t t p s : // d o i . o r g / 1 0 . 1 0 8 0 / 07328319808005194 20. Atamna H, Cheung I, Ames BN (2000) A method for detecting abasic sites in living cells: age-dependent changes in base excision repair. Proc Natl Acad Sci 97:686–691. https://doi.org/10.1073/pnas.97.2.686 21. Lin P-H, Nakamura J, Yamaguchi S, Asakura S, Swenberg JA (2003) Aldehydic DNA lesions induced by catechol estrogens in calf thymus DNA. Carcinogenesis 24:1133–1141. https:// doi.org/10.1093/carcin/bgg049 22. McDorman KC, Pachkowski BF, Nakamura J, Wolf DC, Swenberg JA (2005) Oxidative DNA damage from potassium bromate exposure in Long-Evans rats is not enhanced by a mixture of drinking water disinfection by-products.

Chemico-Biol Interact 152:107–117. https:// doi.org/10.1016/j.cbi.2005.02.003 23. Viswesh V, Gates K, Sun D (2010) Characterization of DNA damage induced by natural product antitumor antibiotic leinamycin in human cancer cells. Chem Res Toxicol 23:99– 107. https://doi.org/10.1021/tx900301r 24. Tanaka M, Song H, Ku¨pfer PA, Leuman CJ, Sonntag WE (2011) An assay for RNA oxidation induced abasic sites using the Aldehyde Reactive Probe. Free Radic Res 45:237–247. https://doi.org/10.3109/10715762.2010. 535529 25. Chomczyn´ski P, Sacchi N (1987) Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal Biochem 162:156–159. https://doi. org/10.1006/abio.1987.9999

Chapter 10 A Simplified Method to Assay Protein Carbonylation by Spectrophotometry Corentin Moreau and Emmanuelle Issakidis-Bourguet Abstract Protein carbonylation is an irreversible oxidation process leading to a loss of function of carbonylated proteins. Carbonylation is largely considered as a hallmark of oxidative stress, the level of protein carbonylation being an indicator of the oxidative cellular status. The method described herein represents an adaptation to the commonly used 2,4-dinitrophenylhydrazine (DNPH)-based spectrophotometric method to monitor protein carbonylation level. The classical final sample precipitation was replaced by a gel filtration step avoiding the tedious and repetitive washings of the protein pellet to remove free DNPH while allowing optimal protein recovery. This improved protocol here implemented to assay protein carbonylation in plant leaves can potentially be used with any cellular extract. Key words Protein oxidation, Carbonylation, Spectrophotometry

1

Introduction Carbonylation is the most common protein modification induced by Reactive Oxygen Species (ROS) [1], and carbonylated proteins have been identified in many plant species at different stages of growth and development (reviewed in Ref. [2]). Carbonylation is induced by direct ROS attack of exposed side chains of amino acid residues such as Pro, Arg, Lys, and Thr, but protein carbonylation can also be indirectly induced by ROS through lipid peroxides (for Cys, His, and Lys) and even by glycation/glycoxidation (for Lys) [3]. Because the formation of carbonylated proteins is a major product of protein oxidation and protein carbonylation is considered to be a stable and irreversible modification, it is often used as a marker to evaluate cellular oxidation. In plants, oxidative stress (carbonylation) was shown to accompany senescence/aging in plant leaves as well as in seeds where it is associated to loss of seed viability [2, 4–6]. Extensive carbonyl

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_10, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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formation has been also shown in protein extracts from leaves exposed to abiotic stresses such as low and high temperatures, salinity, or drought [7–11]. It is postulated that carbonylation of proteins induces a loss of their functional properties and/or may serve as a signal for degradation by increasing their susceptibility towards proteolysis by the proteasome and organellar proteolytic systems [12]. Also, it was shown that carbonylated proteins can escape degradation and form high-molecular-weight aggregates that accumulate with age [3]. Protein carbonylation can be detected and quantified at the global level in proteins and protein mixtures using derivatization of carbonyl groups by 2,4-dinitrophenylhydrazine (DNPH) which reacts with the ketone and aldehyde functional groups and produces a stable 2,4-dinitrophenyl (DNP) hydrazone product. The specific UV absorption of DNP-hydrazone at 370 nm allows detection and quantification of carbonyls with a spectrophotometer. Here, we have adapted the DNPH-based spectrophotometric method [13]. It classically includes a final precipitation step of the sample yielding a protein pellet that needs to be carefully washed to ensure reliable and reproducible data. Complete removal of free DNPH is conditional to optimal pellet dispersion. This is achieved by vigorous vortexing (sonication of the pellet is often recommended in commercial kits) to dislodge the pellet and by repeating washing/centrifugation cycles several times (usually 3–5). To overcome this problem, Xia et al. [14] soundly proposed to perform the final step centrifugation at slow speed to form a loose easily dispersible pellet facilitating re-dissolving/washing. But protein loss at washing steps is a major drawback of the DNPH-based method as it results in a relatively low reproducibility and in high standard deviation of the data [15] . We have conveniently modified this commonly used method by replacing the final precipitation by a gel filtration allowing a simple, fast, and efficient removal of free DNPH in a single step combined with optimal protein recovery. Herein, this improved protocol was used to measure protein oxidation in plant extracts, but it can potentially be used with any cellular extract.

2

Materials Prepare all buffers using ultrapure water (double distilled or MilliQ grade). 1. Extraction buffer: 100 mM Tris-HCl pH 6.8. 2. 10% (w/v) streptomycin sulfate prepared in water. 3. Mini clarification spin columns (see Note 1).

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4. Carbonyl labelling solution: 30 mM DNPH prepared in DMSO (see Note 2). 5. 1 mL G-25 spin column prepared in TE (Tris-HCl 100 mM pH 7.9, 1 mM EDTA) buffer at 20% (w/v) (see Notes 3 and 4). 6. Qubit protein assay kit from Invitrogen (protein dye reagent and dedicated fluorometer) (see Note 5).

3

Methods

3.1 Sample Extraction and Clarification

1. Grind around 100 mg of tissue per sample in liquid nitrogen (see Note 6). 2. Add 400 μL of extraction buffer supplemented with a cocktail of protease inhibitors, and homogenize by vigorously vortexing the sample for 5 s (2 times with a 1–2 min stand on ice in the interval) (see Note 7). 3. Centrifuge for 15 min at 4
C and 18,000  g. 4. Further clarify the extract by filtrating the supernatant (380 μL) through a clarification unit (see Note 1). 5. Centrifuge at RT for 2 min at 12,000  g (see Note 8).

3.2 Removal of Nucleic Acids

1. Transfer 360 μL of clarified extract to a new tube, and add 40 μL of 10% streptomycin sulfate to precipitate nucleic acids (see Note 9). 2. Mix by a brief vortexing. 3. Incubate at RT for 20 min with mixing (see Note 10). 4. Centrifuge at RT for 10 min at 12,000  g.

3.3 Derivatization with DNPH

1. Transfer 380 μL of supernatant to a new tube, and add 90 μL of 30 mM DNPH (see Note 11). 2. Mix by a brief vortexing. 3. Incubate at RT, in the dark, for 20 min with mixing (see Note 10).

3.4 Removal of Unincorporated DNPH by Gel Filtration

1. Build up gel filtration column (all steps performed at RT) by adding 1.5 mL of swollen G-25 slurry to a 2 mL centrifuge empty column (see Note 3). 2. Remove twist-off bottom closure and let the column set for 10 min. Place column onto a 15 mL collection tube and centrifuge at 800 x g for 30 s. Check that the resin has packed to a 1 mL volume (graduation on the centrifuge column tube) (see Note 4). 3. Load 210 μL of the sample onto a 1 mL G-25 spin column placed on a new 15 mL collection tube.

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4. Centrifuge at RT for 15 s at 800  g (see Note 12). 5. Transfer the 210 μL eluate into a new tube. Keep the sample on ice. 3.5 Quantification of Carbonyls

1. Determine carbonyl concentration by reading the sample absorbance at 370 nm using TE buffer or the related control sample (without DNPH) as blank (see Note 13). 2. Determine protein concentration using 2–5 μL sample using a protein assay (see Note 5). 3. Calculate carbonyl content using a molar absorption coefficient for aliphatic hydrazones of 22,000 M1 cm1 and expressed in nmol carbonyl mg1 protein, using the following equation: Carbonyl ðMÞ ¼

A 370 22, 000

A 370 22, 000  106 ðnmol=mLÞ=protein concentration ðmg=mLÞ

Carbonyl ðnmol=mg proteinÞ ¼

Using the present method, we quantified carbonyls in Arabidopsis and wheat leaves and found an overall variation of 2–8% of results within experiments. We measured a carbonyl content of 26.46 nmol/mg protein in the leaves of 3-week-old Arabidopsis plants grown on MS medium under short day conditions. We also measured protein oxidation in wheat in the context of heat stress. The results obtained are presented in Fig. 1. Upon heat stress, a marked increase (+ 42–62% in 3 independent experiments) in the carbonyl content of the flag leaf was found, signifying that protein oxidation has massively occurred. An increase in the protein carbonylation level was also found in dehydrated wheat seedlings [10] suggesting a possible link between protein carbonylation and wheat sensitivity to unfavorable environmental conditions. Thus, experimental work points to the idea that protein oxidation level assessed as protein carbonylation may be taken as a biochemical marker for screening stress-tolerant wheat germplasms in breeding programs.

4

Notes 1. We used Proteus Mini Clarification Spin Columns from GENERON. These filter units (hydrophilic PVDF) are designed to remove microorganisms, particles, and precipitates larger than 0.2 μm in size from aqueous solutions. Any equivalent filters may be potentially used. Alternatively, the homogenate can be filtered through Miracloth (cellulosic filtration medium).

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Fig. 1 Effect of heat stress on protein oxidation in wheat. Winter wheat (Triticum aestivum L.) was cultivated under a 16 h photoperiod (120–250 μE/m2/s) at 24
C/18
C day/night temperatures with fertilized watering supplied 3 times per week. Heat stress (30–32
C, under a light of 650–700 μE/m2/s, for 4 h at midday) was conducted during grain filling at the kernel milk stage corresponding to 250–300 degree days after anthesis. Flag leaf samples (2/3 median part of the leaf) were taken at the end of the heat treatment and immediately frozen in liquid N2 and stored at 80
C until analysis. Bars represent the mean  SD (n ¼ 8–12) for 3 independent experiments

2. When preparing the DNPH solution, the actual content of DNPH in the reagent (the powder contains > 30% water) should be taken into account. The DNPH stock solution (protected from light) is stable at RT for several days. 3. We used G-25 gel filtration resin to remove free DNPH from labelled protein samples. Proteins and peptides larger than Mr 5000 are separated from molecules with Mr of less than 1000 (DNPH MW 198.14 g/mol). We found optimal DNPH removal and protein recovery with a minimum sample dilution using Sephadex G-25 superfine resin. We used 2 mL centrifuge empty column tubes from Pierce. 4. The G-25 resin may be cleaned and re-used according to the supplier’s recommendations. Alternatively, pre-packed commercially available columns may be used with protocol adaptation. 5. We used the Qubit protein assay kit from Invitrogen, but alternatively, protein quantitation can be performed using the bicinchoninic acid (BCA) assay [16], or any other protein assay with a suitable range of sensitivity, and a standard spectrophotometer. 6. Freshly harvested tissues or tissues stored at 80
C are suitable. Extraction can be performed using a bead mill or

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manually using a mortar and a pestle. Preliminary cooling is needed to avoid protein degradation. 7. Protease inhibitor cocktails are commercially available and usually provided as ready-to-use 100 times concentrated. We used a protease inhibitor cocktail optimized for plant cell extracts. 8. Filters can be re-used after a careful washing and storage in 20% ethanol. Drain (centrifuge at RT for 2 min at 12,000  g) and rinse the unit with 400 μL water (centrifuge in the same conditions). 9. Nucleic acids also contain carbonyl groups and will react with DNPH. To avoid an erroneously high estimate of protein-bound carbonyls, cellular extracts are treated with 1% streptomycin sulfate to decrease nucleic acid contamination. 1% streptomycin sulfate is usually effective in minimizing interference, but this should be confirmed for specific samples for which higher concentrations of streptomycin sulfate may be required. Interference by nucleic acids can be checked by the ratio of absorbance at 280 nm to that at 260 nm that must be greater than 1. 10. Samples were continuously mixed using a Thermomixer set at 1100 rpm, or alternatively a brief vortex of the samples was performed occasionally during incubation. 11. At this step, a reagent blank can be prepared for each sample by mixing 190 μL of clarified extract with 45 μL DMSO. The carbonyl labelling sample is prepared by mixing 190 μL of clarified extract with 45 μL 30 mM DNPH. We have found that absorbance of reagent blank samples at 370 nm was null using the method described here for Arabidopsis and wheat leaf extracts. 12. We used an Eppendorf 5810R centrifuge equipped with a swinging-bucket rotor for 15 mL conical tubes. 13. Sample preparation (see Note 11) allows performing, for each sample, either a blank or a technical duplicate of the protein carbonyl assay. We used plastic UV-compatible micro cuvettes allowing reads in triplicate with 70 μL of assay samples and a standard spectrophotometer compatible with micro cuvettes.

Acknowledgments This work was financially supported, thanks to the Poc in Labs initiative of the University Paris-Saclay and the Saclay Plant Sciences network, by the program “Investing for the Future” launched by the French State and implemented by the ANR (French National Research Agency). Former undergraduate students of the laboratory, Mai Pham Thy, Albert Kwarteng, and Oscar Freyschlag, are acknowledged for their participation to this work.

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References 1. Levine RL (2002) Carbonyl modified proteins in cellular regulation, aging, and disease. Free Radic Biol Med 32:790–796 2. Ciacka K, Tymin´ski M, Gniazdowska A, Krasuska U (2020) Carbonylation of proteins-an element of plant ageing. Planta 252:12 3. Nystro¨m T (2005) Role of oxidative carbonylation in protein quality control and senescence. EMBO J 24:1311–1317 4. Have´ M, Leitao L, Bagard M, Castell JF, Repellin A (2015) Protein carbonylation during natural leaf senescence in winter wheat, as probed by fluorescein-5-thiosemicarbazide. Plant Biol 17:973–979 5. Rajjou L, Lovigny Y, Groot SP, Belghazi M, Job C, Job D (2008) Proteome-wide characterization of seed aging in Arabidopsis: a comparison between artificial and natural aging protocols. Plant Physiol 148:620–641 6. Yin G, Xin X, Fu S, An M, Wu S, Chen X, Zhang J, He J, Whelan J, Lu X (2017) Proteomic and carbonylation profile analysis at the critical node of seed ageing in Oryza sativa. Sci Rep 7:40611 7. Kingston-Smith AH, Foyer CH (2000) Bundle sheath proteins are more sensitive to oxidative damage than those of the mesophyll in maize leaves exposed to paraquat or low temperatures. J Exp Bot 51:123–130 8. Sundaram S, Rathinasabapathi B (2010) Transgenic expression of fern Pteris vittata glutaredoxin PvGrx5 in Arabidopsis thaliana increases plant tolerance to high temperature stress and reduces oxidative damage to proteins. Planta 231:361–369 9. Mano J, Nagata M, Okamura S, Shiraya T, Mitsui T (2014) Identification of oxidatively

modified proteins in salt-stressed Arabidopsis: a carbonyl-targeted proteomics approach. Plant Cell Physiol 55:1233–1244 10. Gietler M, Nykiel M, Zagdan´ska B (2016) Changes in the reduction state of ascorbate and glutathione, protein oxidation and hydrolysis leading to the development of dehydration intolerance in Triticum aestivum L seedlings. Plant Growth Regul 79:287–297 11. Vanacker H, Guichard M, Bohrer AS, IssakidisBourguet E (2018) Redox regulation of monodehydroascorbate reductase by thioredoxin y in plastids revealed in the context of water Stress. Antioxidants 7:183 12. Dukan S, Farewell A, Ballesteros M, Taddei F, Radman M, Nystro¨m T (2000) Protein oxidation in response to increased transcriptional or translational errors. Proc Natl Acad Sci USA 97:5746–5749 13. Wehr NB, Levine RL (2013) Quantification of protein carbonylation. In: Galluzzi L, Vitale I, Kepp O, Kroemer G (eds) Cell Senescence. Methods in molecular biology (Methods and protocols), vol 965. Humana Press, Totowa 14. Xia Q, El-Maarouf-Bouteau H, Bailly C, Meimoun P (2016) Determination of protein carbonylation and proteasome activity in seeds. Methods Mol Biol 1450:205–212 15. Rogowska-Wrzesinska A, Wojdyla K, Nedic´ O, Baron CP, Griffiths HR (2014) Analysis of protein carbonylation – pitfalls and promise in commonly used methods. Free Radic Res 48: 1145–1162 16. Walker JM (1994) The bicinchoninic acid (BCA) assay for protein quantitation. Methods Mol Biol 32:5–8

Chapter 11 In Vitro Biochemical Analysis of Recombinant Plant Proteins Under Oxidation Zeya Chen and Jingjing Huang Abstract Biochemical analysis is crucial for determining protein functionality changes during various conditions, including oxidative stress conditions. In this chapter, after giving brief guidelines for experimental design, we provide step-by-step instructions to purify recombinant plant proteins from E. coli, to prepare reduced and oxidized proteins for activity assay, and to characterize the protein under reducing and oxidizing conditions, with a focus on thiol-based oxidative modifications, like S-sulfenylation and disulfide formations. Key words Recombinant protein expression, Protein purification, Oxidation and reduction, Posttranslational modifications, S-sulfenylation detection

1

Introduction A variety of (a)biotic stresses can affect plant growth in their lifespan and one of which, oxidative stress is likely to cause the over-accumulation of reactive oxygen species (ROS) in cells [1]. Excessive ROS can attack DNA, proteins, and lipids to cause oxidative damage [2]. To combat oxidative stress, plants have evolved a series of complex mechanisms in different ROS levels, and such redox signaling can be governed at the post-translational level [3–6]. Cysteine residue (Cys) contains a highly reactive sulfur atom that can react with hydrogen peroxide (H2O2), one of the major ROS, and undergo multiple oxidative post-translational modifications (OxiPTMs), thus resulting in different oxidation statuses of the proteins [6]. To understand how oxidation affects the function of a protein, it is important to determine the thiolbased oxidation states of proteins under different oxidation conditions. Reduced Cys in monomer contains a free thiol (–SH) that is highly reactive that can react with H2O2 and form sulfenic acid (– SOH). –SOH is not stable that can easily react with proximal –SHs, either within or from the other proteins, forming intra- or

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_11, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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inter-disulfide bonds (S–S). Formation of -SOH or intra S–S within a protein will not affect protein size significantly. However, the inter S–S formation results in structural alterations of a protein as dimeric, oligomeric forms, or even large aggregates [7], which can be visualized through different migration on SDS-PAGE gels (see Fig. 1). Due to the high complexity of plant growth environment and physiological context, the biochemical analysis using recombinant proteins is rather a more feasible way to determine the oxidation status of proteins, thus evaluating the effects on proteins functionality. The biochemical characterization of recombinant proteins has been used as an essential routine molecular and biological method to study protein functions, as well in the redox field [8, 9]. Here, we describe a brief experimental workflow (see Fig. 2) for the characterization of a plant protein which starts from initial experimental design to protein purification and ends up with the preparation of reduced/oxidized proteins that can be applied for further biochemical analysis depending on individual experiment objectives.

2

Materials

2.1 E. coli Cell Line and Plasmids

1. The host cell line: BL21 (DE3).

2.2 Reagents and Buffers

1. Hydrogen peroxide (H2O2) 2. Sodium dodecyl sulfate (SDS)

2.2.1 Reagents

3. Dithiothreitol (DTT)

2. The expression vectors: pET expression vectors, Gateway Expression Vectors (pDEST) (Vectors sequences can be found at https://www.addgene.org/vector-database/)

4. Isopropyl β-d-1-thiogalactopyranoside (IPTG) 5. Lysogeny broth (LB) base 6. Stain-Free Precast Gels 7. Coomassie Blue Protein Staining 8. Western Lightning Plus ECL 9. NaCl 10. Anti-His-HRP antibody 11. 50 mM Tris-HCl (pH7.5) 12. 120 mM Tris-HCl (pH 6.8) 13. Protease inhibitor 14. KCl 15. Na2HPO4 16. KH2PO4

Characterization of Protein Oxidation

Protein Marker Monomer (WT) (kDa)

(a) Reduced

Monomer (Oxidized)

Dimer

Trimer

Tetramer

Oligomers

145

Large aggregates

(b) Sulfenic acid

protein

(c) Intradisulfides

(d) Interdisulfides

Fig. 1 Protein monomeric, multimeric formations based on inter-disulfide bonds analyzed by SDS-PAGE gel under non-reducing conditions. Cysteine-free thiols (–SHs) (a) in protein monomer are highly reactive that can react with H2O2 and form sulfenic acid (–SOH) (b). –SOH can easily react with proximal –SHs to form intra(c) and inter- (d) disulfide bonds. While the proteins forming –SOH or intra-disulfide usually remain as monomers, the inter-disulfide bonds formations can generate dimer, trimer, or even oligomers, which migration will be changed based on the protein size on the non-reducing SDS-PAGE gels. Large aggregates can also be observed due to cysteine oxidations

17. Tween 20 18. AEBSF hydrochlorid 19. Leupeptin hemisulfat 20. Glycerol 21. Bromophenol blue 22. Dimdone 23. Dimethyl sulfoxide (DMSO)

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Experiment design • • • • •

Literature study Expression vector selection Affinity tag selection Host selection Codon optimization

Recombinant protein expression • Protein expression condition optimization • Large-scale protein expression

Protein purification • Ni-immobilized metal ion affinity chromatography (Ni-IMAC) • Ion exchange chromatography (IEC) • Size exclusion chromatography (SEC)

Preparation of reduced and oxidized protein Characterization of plant protein under oxidation Activity assay • Varies from different proteins

Determine thiol-based oxidation status

S-S based monomer? Dimer? Oligomer? • Analysis by reducing and non-reducing SDS-PAGE gel • SEC analysis

SOH? • Dimedone assay • LC/MS-MS analysis

Fig. 2 Workflow for in vitro biochemical analysis of thiol-based oxidation on recombinant proteins

24. Iodoacetamide (IAM) 25. Skimmed milk powder 2.2.2 Buffers

1. Resuspension buffer: 50 mM Tris-HCl (pH7.5), 150 mM NaCl, 1X Protease inhibitor (freshly prepared), and 5 mM DTT (see Note 1). 2. Phosphate-buffered saline (PBS): 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4, and adjusting pH to 7.4. 3. PBS-T: PBS containing 0.1% (v/v) tween-20. 4. Blocking buffer: 5% skimmed milk in PBS-T. 5. Lysis buffer: 50 mM Tris-HCl (pH 7.5), 200 mM NaCl, 0.1 mg/mL AEBSF hydrochlorid (freshly prepared), 1 μg/ mL Leupeptin hemisulfat (freshly prepared), 1X Protease inhibitor (freshly prepared).

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6. Binding buffer: 50 mM Tris-HCl (pH 7.5) and 200 mM NaCl. 7. Imidazole: dissolved in binding buffer. 8. 2X Laemmli buffer: 120 mM Tris-HCl (pH 6.8), 4% SDS, 20% glycerol, and 0.02% (w/v) bromophenol blue. 9. Dilution buffer: same as binding buffer. 10. 500 mM Dimdone: dissolve in dimethyl sulfoxide (DMSO). 11. 2 mM Iodoacetamide (IAM): dissolved in DMSO. 2.2.3 Equipments

1. Spectrophotometer 2. Centrifuge 3. Sonication machine 4. Ni-NTA resin (e.g., Ni sepharose 6 Fast Flow and HisTrap) 5. Ion exchange resin (e.g., SOURCE 15S and SOURCE 15Q) 6. Size exclusion resin (e.g., Hiload 16/600 Superdex 75 pg) ¨ KTA machine 7. A 8. Desalting columns (e.g., Zeba Spin desalting Column)

3

Methods

3.1 Design Expression Constructs in Escherichia coli (E. coli ) Cell

Here, we list several criteria for designing recombinant expression constructs in E. coli cell (see Note 2).

3.1.1 Select Expression Vector

Both pET and pDEST expression vectors provide C terminal and N terminal-tagged commercial vector that can be selected for E. coli (see Note 3).

3.1.2 Select an Affinity Tag

Different affinity tags can be selected, like histidine (His), glutathione-S-transferase (GST), maltose-binding protein (MBP), hemagglutinin (HA), and streptavidin tags (see Note 4).

3.1.3 Select an Expression Cell Line

BL21(DE3) and some derivatives, such as BL21(DE3)pLysS and Rosetta (DE3), are the most common strains to use (see Note 5).

3.1.4 Delete Transit Peptides

Delete the transit peptide in the target amino acid sequence to avoid possible influence on recombinant protein expression (see Note 6) [10].

3.1.5 Optimize Codon Usage of Your DNA Sequence (Optional) (See Note 7)

Optimize codon of plant protein for expression in E. coli using online tools, for example, https://www.genscript.com/gensmartfree-gene-codon-optimization.html; and https://www.bioline. com/media/calculator/01_11.html.

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3.2 Protein Expression 3.2.1 Test Small-Scale Protein Expression

Here we describe a general method for His-tagged recombinant protein expression in E. coli BL21(DE3) cells. 1. Transform 50 ng plasmids of expression vectors containing the target gene into 50 μL BL21(DE3) chemically competent cells by heat-shock transformation; grow the transformed cells on LB plates with selective antibiotics (LB+ab) at 37  C overnight. 2. Select several colonies randomly from the LB+ab; inoculate them into a 5 mL LB+ab medium separately, which we call the “pre-inoculum” (see Note 8). 3. Inoculate 500 μL from the “pre-inoculum” to 50 mL LB medium with selective antibiotics, according to the ratio of 1: 100 (v:v). The 50 mL inoculated cells are further incubated at 37  C, 200 rpm. The bacteria optical density at a wavelength of 600 nm (OD600) is measured, and the expression is induced by 1 mM IPTG when OD600 reaches between 0.55 and 0.8 (see Note 9). 4. Collect 2  1 mL non-induced cells as control. 5. Incubate the induced cells at 18  C, 28  C, or 37  C with 200 rpm shaking (see Note 10). 6. Collect 2  1 mL induced bacteria at different time points (e.g., 1-h, 3-h, 6-h, and overnight) at different temperatures by centrifugation at 4  C, 10,000 g for 10 min. Keep the cell pellets at 20  C until use.

3.2.2 Prepare Protein Samples for Small-Scale Expression Analysis

1. Resuspend the collected cell pellet from 1 mL cells in 100 μL PBS as total cell protein sample. 2. Resuspend another 1 mL-cell pellet in 100 μL resuspension buffer. Sonicate the resuspended cells in a 4  C water bath for 7 cycles, where each cycle consists of 10-s followed by a 30-s pause (e.g., Bioruput or UCD300, the detailed sonication conditions may vary with the equipment). 3. Centrifuge the sonicated cells at 4  C, 14,000 g for 20 min; separate the supernatant (soluble fraction protein) and the pellet. Resuspend the pellet in 100 μL PBS containing 1% SDS (insoluble fraction). 4. Add Laemmli buffer and 50mM DTT in each sample (see Note 1) and heat the samples at 95  C for 5 min, and then centrifuge them at 10,000 g for 5 min. 5. Collect the supernatant samples for following SDS-PAGE and Western blot analysis (see Subheading 3.2.3). 6. Optimize expression condition by varying concentration of IPTG, temperature, and expression time to induce most of target protein expressing in the soluble fractions (see Note 11).

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In certain cases, the expressed protein with expected molecular size can be visualized on SDS-PAGE after Coomassie blue staining (e.g., InstantBlue® Coomassie Protein Stain). However, for proteins with low expression levels, Western blot using an antibody against the protein affinity tag is required for confirmation. 1. Transfer the protein from the SDS-PAGE gel to a PVDF membrane by a semi-dry transfer protocol (see Note 12). After that, remove the membrane into blocking buffer, and incubate the membrane with gentle shaking overnight at 4  C or 1 h at room temperature. 2. Incubate the membrane with anti-his-HRP antibodies (e.g., Genscript) at the dilution of 1:5000, 1 h at room temperature after blocking. Wash the membrane for 10 min in PBS-T with shaking at room temperature, repeat 3 times. 3. Take out the membrane, and incubate it with Western Lightning Plus ECL (e.g., Perkin Elmer) for 1 min; detect the chemiluminescent signals (e.g., ChemiDoc system).

3.2.4 Upscale Protein Expression

1. Upscale protein expression (e.g., 500 mL or 1 L) using the optimal conditions (see Subheading 3.2.2). 2. Harvest the cell culture by centrifugation at 4  C, 10,000 g for 30 min, and store the pellet at 20  C. At the same time, always remember to collect 2  1 mL non-induced cells (as control) and induced cells for large-scale protein expression analysis (see Note 13). 3. Analyze the protein expression result for large-scale protein induction by SDS-PAGE and Western blot (see Subheading 3.2.3). Further protein purification can proceed when most of your target protein is induced in the soluble fraction.

3.3 Protein Purification

Protein purification can be done by various means based on the properties of the target protein, such as the size, the isoelectric point, and the affinity tag of the recombinant protein [11, 12]. Besides conducting protein purification on bench, ¨ KTA machine can also be used to purify proteins. We summarized A ¨ KTAthe comparison between on-bench experiment and A machine-based experiment; different purification systems are preferred based on the experimental purpose (see Table 1). Here, we describe three commonly used protocols for recombinant protein purification, including the Ni-immobilized metal affinity chromatography (Ni-IMAC) technique to purify His-tagged proteins, ion-exchange chromatography (IEC), and size exclusion ¨ KTA chromatography (SEC), both on bench and using the A machine.

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Table 1 Comparison of protein purification on-bench and with A¨KTA machine

Advantages

On-bench

A¨KTA

-More feasible for small-scale protein -Less effort for machine maintenance -Relatively fast when knowledge on purification conditions already exist

-Suitable for optimizing purification conditions or large-scale protein purification -Purification concentration can be monitored by real-time A280 (and other parameters) -More accurate in gradient elution

Disadvantages -Labor intensive for optimizing purification conditions or large-scale purification -The proteins concentration cannot be monitored in real-time 3.3.1 On-bench Ni-IMAC

-It requires training to learn how to use the Akta system -Regular machine maintenances are needed

1. Take the induced cell pellets from the 20  C freezer and place them on ice. Resuspend the pellet in lysis buffer (3 mL lysis buffer for 1 g cell pellet). 2. Sonicate the resuspended cells on ice at 20% duty strength for 15 cycles, where each cycle consists of 10 s followed by a 10-s pulse (e.g., Branson 450 Digital Sonifier, the detailed sonication conditions may vary with the equipment). 3. Centrifuge the sonicated cell lysate at 4  C, 10,000 g for 30 min; collect the supernatant. 4. Assemble 0.5–1 mL Ni2+ beads in empty disposable columns (see Note 14). Pre-equilibrate the column with binding buffer (at least 10 times of bed volume). 5. Load the protein lysate sample and collect the flow-through, and then elute the column by a gradient of imidazole (e.g., using 20 mM, 40 mM, 80 mM, 150 mM, 250 mM, to 500 mM) (see Note 15). 6. Collect separately the protein samples from each gradient of imidazole. 7. Take a small amount from the flowthrough and each imidazole eluted sample for SDS-PAGE and western blot analysis (see Subheading 3.2.3). Keep the rest of the samples on ice or at 4  C. 8. Analyze the samples by SDS-PAGE and Western blot, and collect the eluted fraction of proteins with the highest purity. 9. Perform the desalting step (see Subheading 3.3.5) to remove the excess imidazole in the Ni-purified protein samples (see Note 16).

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10. Keep the purified sample on ice/4  C for further experiment or store it at -20  C (see Note 17). 3.3.2 Ni-IMAC with A¨KTA

¨ KTA machine should be All the reagents and the samples for A pre-filtrated using a 0.22 μm filter before the experiment. Assemble ¨ KTA machine (see Note 14). The program for HisTrap 5 mL onto A ¨ KTA consists of three processes including equilibration, sample A loading, and elution. 1. Use 5 times the column volume of the binding buffer to equilibrate the column. 2. Load your sample at the speed of 1.5 mL per minute (see Note 18). 3. Wash the column with 40 times column volume of 37.5 mM imidazole (7.5% concentration of the 500 mM imidazole), and then elute the target protein by an increasing gradient concentration of imidazole with 5 times column volume. The elution flowthrough can be fractionated into 1 mL which can be continuously collected in 1.5 mL/2 mL Eppendorf tubes. 4. Collect the different eluted fractions separately (see Note 19). 5. Follow the steps 7–10 in Subheading 3.3.1.

3.3.3 On-bench IEC

IEC can be applied to further purify proteins which are mainly based on differences in the isoelectric point of the protein (PI). At certain pH, the target protein and non-specific proteins may present different charges that can be separated by eluting at different NaCl concentrations (see Fig. 3; see Note 20) [13]. 1. Dilute the protein 10 times with dilution buffer (e.g., PBS) on ice (see Notes 21 and 22). 2. Prepare the ion-exchange beads (e.g., SOURCE 15S) into a 1.5 mL tube. 3. Add 5 times resin volume of water into the tube, and centrifuge at 4  C, 250 g for 1 min. Remove the supernatant and repeat this step 3 times. 4. Add the beads into the diluted protein sample. Incubate beads and the sample with rotation at 4  C for 45 min. 5. Centrifuge the mixture of beads and sample at 4  C, 250 g for 5 min. Remove the supernatant. 6. Add 5 times resin volume of dilution buffer to wash the beads, repeat the step 3 times, and collect the wash at each time. 7. Add 5 times resin volume of dilution buffer containing an increasing concentration of NaCl (e.g., 200 mM, 400 mM, 700 mM, 1 M NaCl) to elute protein from the beads.

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NaCl concentration Cation Column

A B

A

Negative

Na+ Na+

A

Positive

Na+ Na+

A

A

A

Na+

Na+ Na+

A A

Na+

Na+

Na+

At the pH of 7.2

Na+

A

A

Na+

A

Na+

A

Na+

A

Na+

Na+

Na+

Na+

Na+

Na+

Na+

B

A

B

A

B B

ClCl-

A

Na+

A A

Cl-

B

Cl-

B

Cl-

Cl-

Cl-

A

Cl-

A

ClNa+ Cl-

Cl-

Na+

Cl-

Na+ Cl-

Cl-

Na+ Cl-

Na+

Na+ Cl-

Fig. 3 Mechanism of ion (cation) exchange chromatography. At pH 7.2, protein A (pI is at 9) is positively charged while protein B (pI is at 5) is negatively charged. When a mixture of the proteins is loaded into the column, positively charged proteins (protein A) absorb to the column while negatively charged proteins are more likely to be washed. When the increasing concentration of NaCl is loaded, Na+ forms a competence with protein A in the binding column; thus protein A is gradually eluted with the elevated salt, which, ultimately separates protein A and B

8. Collect the fractions from each wash and elution. 9. Follow the step 7–10 in Subheading 3.3.1. 3.3.4 IEC with A¨KTA

¨ KTA is prepacked with cation resin (e.g., The column used for A Omnifit Source S) or anion resin (e.g., Omnifit Source Q). The experiment usually consists of 7 processes which are equilibration, sample loading, elution, wash with water, NaOH, PBS, and 20% ethanol accordingly. The latter 4 stages are usually default set for the recycling use of the column. 1. Dilute the protein according to the step 1 in Subheading 3.3.3. 2. Use 5 times column volume of PBS to remove the original ethanol stored in the column. 3. Start sample loading. The speed of the flow can be set at 1 mL per minute. 4. Elute the sample. Use an increasing gradient concentration of NaCl with 13 times the column volume of the buffer to elute the resin. The elution flowthrough can be fractionated into 1 mL as described in Subheading 3.3.2. Collect the eluted fractions separately. 5. Follow the steps 7–10 in Subheading 3.3.1.

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Dialysis, concentrators, and some commercial columns like Zeba, PD-10, and micro bio-spin can be used for desalting (e.g., removing imidazole). Here we describe a protocol using the Zeba columns. Take out a Zeba spin desalting column (3 kDa), twist off the column’s bottom closure, and loosen the cap. Place the column into a collection tube. Centrifuge column at 4  C, 1000 g for 2 min. The centrifuging settings are the same as below. 1. Pre-equilibrate the column by adding 2 mL binding buffer (see Note 23), and centrifuge. 2. Repeat step 1 three times, discard the flowthrough at each time. 3. Place the column into a new collection tube and load the sample (see Note 24). 4. Centrifuge the column to collect the flowthrough. 5. Conduct SDS-PAGE gel and Western blot analysis for the collected protein (see Subheading 3.2.3). At the same time, protein concentration can be measured (see Note 25). 6. Place the desalted protein on ice for further experiment or aliquot it, and store them at 20  C.

3.3.6 SEC with A¨KTA

Here we use Hiload 16/600 Superdex 75 pg column as an example. The experiment consists of three stages which are equilibration, sample loading, and isocratic elution accordingly. 1. Use double size the column volume of buffer to equilibrate the resin at a speed of 0.7 mL per minute (see Note 26). ¨ KTA machine 2. Inject samples into the injection valve of the A during the equilibration stage (see Note 27). After injection of sample, install the settings for the sample loading program. The flow speed should be at 0.5 mL per minute, and the sample volume settings should be 1.5 or 2 times larger than the actual injected volume of the sample (see Note 28). 3. Collect the elution flowthrough from AKTA. Follow the steps 7–10 in Subheading 3.3.1.

3.4 Reducing and Oxidizing Proteins

1. Equilibrate the micro bio-spin columns with binding buffer (see Note 29). 2. Take purified proteins out from the freezer and keep them on ice; once the protein defrosts, incubate 100 μM purified proteins with 20 mM DTT at room temperature for 1 h. 3. Remove the excess DTT in the protein with equilibrated micro bio-spin columns. 4. Measure the concentration of the reduced protein samples by absorbance at 280 nm, and then keep the samples on ice until use (see Note 25).

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5. Prepare 100 μl oxidation reactions containing 20 μM reduced proteins and different concentrations of H2O2, for instance, 20 μM, 100 μM, 200 μM, 500 μM, 1 mM, and 5 mM (see Note 30). Incubate the samples at room temperature for 30 min, 45 min, or 1 h (see Note 31). 6. Remove the excessive H2O2 by equilibrated micro bio-spin columns; measure the concentration of the oxidized protein sample at A280 nm or by other methods (see Note 32). 7. Keep the reduced and oxidized proteins on ice for further characterization. These samples can be used to investigate the protein activity, oxidative modification, or oligomerization states. 3.5 Non-reducing and Reducing SDSPAGE

1. Take purified protein from the freezer and defrost it on ice. Divide the protein sample equally into 2 Eppendorf tubes. 2. For reducing sample, prepare a 20 μL-reaction containing 100 μM protein, 20 mM DTT, 50 mM Tris buffer (pH 7.5), and 150 mM NaCl; incubate for 10 min at room temperature. For non-reducing sample, prepare a 20 μL-reaction containing 100 μM protein in 50 mM Tris buffer ( pH 7.5), and 150 mM NaCl; incubate for 10 min at room temperature. 3. Add Leammli buffer in the sample and heat the samples at 95  C for 5 min, and then centrifuge at room temperature, 10,000 g for 5 min. 4. Analyze the supernatant on SDS-PAGE gels.

3.6 Detection of Protein S-Sulfenylation by Dimedone

1. Prepare reduced protein as described in Subheading 3.4. 2. Prepare 20 mM dimedone. Dilute 500 mM dimedone in DMSO with 50 mM Tris-HCl (pH 7.5). 3. Prepare a 100 μL reaction for dimedone assay by mixing 20 μM reduced protein with 2 mM dimedone, with or without a gradient of H2O2 (see Note 33). For the negative control, use DTT instead of H2O2 and the DTT must be added before dimedone. 4. Incubate samples at room temperature for 1 h. 5. Remove the excess of dimedone/H2O2/DTT with the equilibrated micro bio-spin column, same as described in Subheading 3.4.3. 6. Treat the samples with 2 mM IAM at room temperature for 30 min in the dark, save an aliquot of the sample for Western blot, and keep the rest of the samples at 20  C for mass spectrometry (MS) analysis (see Note 34). 7. Run SDS-PAGE and Western blot with anti-Cys –SOH antibody.

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Notes 1. DTT should always be prepared freshly throughout the experiment. 2. Escherichia coli (E. coli ) cell is currently the most widely used and well-established economical system to express recombinant protein as it possesses advantages of clear genetic background, high expression of target genes, short cycle, and low-cost media, which increase the feasibility for high-throughput protein production [10, 14, 15]. Besides E. coli, protein expression can also be achieved in yeast, plant, and even in a cell-free system [16, 17]. Though possessing numerous advantages, E. coli is not an ideal choice for expressing disulfide bond-rich proteins that require post-translational modifications; thus other non-bacterial hosts may be preferred. Cell-free protein synthesis system provides new potentials for protein expression which eliminates the reliance on living cells but is more expensive than other methods [18]. If the target protein has been reported and studied previously by recombinant expression in E. coli, similar expression conditions can be considered as an easier way. In case the target proteins have not been studied before, selection of stable vector/host combinations to maintain the plasmid stability as well as obtain the desired yield is necessary. 3. The pET vector is one of the most widely used vectors for expression of recombinant protein in E. coli which is mainly based on the selectively activated T7 polymerase for its promoter [19]. Besides, pDEST vectors, as well as their derivatives, can also be applied for protein expression. While the pET system is based on the traditional cloning strategy using restriction enzyme sites, the pDEST vectors adopt lambda recombination system to transfer heterologous DNA sequences between vectors, terms GATEWAY cloning [20]. 4. Among these tags, the His tag is one of the most widely used affinity tags thanks to its small size and stable binding [21– 24]. The large protein tag, MBP (approximately 42 Da) tag, sometimes is used or combined with His tag, as it can help to increase the solubility of expressed protein [25]. The exact affinity chromatography method that has been used to purify protein is mainly dependent on the specific tag you used. You can use different affinity chromatography beads to purify the target protein based on their tag. For example, His-tagged proteins can be purified by immobilized metal ion affinity chromatography (IMAC) using Ni2+ resins, while MBP-tagged protein can be obtained through amylose beads [26, 27]. When biochemical analysis of the protein is needed,

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the large fusion tag should be removed. To remove the large fusion tag, insert a protease site, such as tobacco etch virus (TEV) or human rhinovirus 3C (HRV3C) between the DNA sequence of the target protein and affinity tag can be considered [28]. 5. BL21 (DE3) is the most commonly used E. coli host cell line for recombinant protein expression not only for its compatibility with the T7 promoter systems but also benefits from the lack of Ion and ompT proteases in the genome that encode to degrade misfolded or extracellular proteins [14]. If the target protein is toxic to the host, strains that contain pLysS and pLysE plasmid can be tried as they can help attenuate the toxic effect of the target protein on the bacteria [25, 29, 30]. 6. The websites that might be useful in predicting transit peptides in amino acid sequence are https://www.psb.ugent.be/ webtools/ptm-viewer/ and http://www.cbs.dtu.dk/services/ ChloroP/). 7. E. coli and plants have different codon usage preferences in translation; the ribosome may pause translation upon encountering an unfavorite codon, thus yielding a low amount of target protein [31]. To solve this problem, either codon optimization or select the host that provides rare tRNA such as Rosetta (DE3) can be considered [25]. 8. In theory, each colony on the plate contains the target plasmid, but false-positive colonies exist. Colony PCR can be conducted to confirm if the plasmid was correctly transformed into the bacteria. 9. Different concentrations of IPTG can be tried. Usually from 0.1 mM to 1 mM. Different constructs may take different hours to reach the range of the OD, the OD600 can be monitored from 1.5 h after induction, and then measure the OD every 20 min. 10. The lower induction temperature usually tends to increase the percentage of soluble fraction protein in total target protein [14]. 11. Purifying protein from insoluble fractions is tricky as it undergoes denaturing and refolding steps in which the protein structure may be changed [32, 33]; that is why in our study, or at least in this chapter, we only focus on soluble protein production and analysis. 12. Protein transfer methods are various and can vary between labs. 13. Upscale can cause the difference in protein expression and solubility; the protein expression should always be checked by SDS-PAGE gel or Western blot whenever a new induction is performed [34].

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14. Generally, 1 mL beads are usually able to bind around 40 mg his-tagged protein (https://www.cytivalifesciences.com/en/ us/shop/chromatography/resins/affinity-tagged-protein/nisepharose-6-fast-flow-histidine-tagged-protein-purificationresin-p-06004); however, this ratio is protein-dependent. 15. The imidazole should be dissolved in the binding buffer instead of water. To reduce the unspecific binding, the binding buffer can contain a low concentration of imidazole like 10–20 mM. Different gradient concentrations of imidazole can be optimized based on different target proteins. 16. As a salt, imidazole may affect further downstream proteins function analysis by mediating polar or charged residues (ionic interactions). Besides, excess imidazole also affects the measurement of protein concentration when using A280 and BCA methods. 17. Purified proteins can be stored at

20  C for several months.

18. The exact speed of the flow may vary from different columns. Usually, increasing the speed of the flow will elevate the pressure within the column; always remember to keep the pressure within the column’s limitation. This rule also applies to other ¨ KTA columns. A ¨ KTA machine is equipped with real-time UV mea19. Since the A surement which displays as a graphical picture, the collected fractions can be chosen based on elution protein peak at A280. 20. The PI of the protein can be checked using online tools, for example, https://web.expasy.org/protparam/. If the pI of the target protein is higher than the pH in the buffer, target proteins are positively charged (an anion); the target protein can be bonded to cation beads and eluted at gradient contraction of NaCl, which is called cation exchange chromatographic protein purification. This principle is vice versa for the pI of target protein lower than the pH of the buffer, where the target protein is negatively charged; in this case, the anion beads will be used. 21. Selection of the dilution buffer with appropriate pH and concentration is important, and this may vary with the different commercial beads you used. According to the PI of the protein, the pH of the dilution buffer is usually at least 1 pH unit above for anion beads, or 1 pH unit below for cation beads. 22. In this step, the dilution of NaCl should be performed stepwise to avoid precipitation of protein. 23. The different volumes of binding buffer should be used according to the different sizes of the column. 24. The volume you should load depends on the size of the column.

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25. BCA assay [35], Bradford assay [36], and UV absorbance at 280 nm [37] can be used to measure the protein concentration. 26. For the SEC column, it is significantly important to set an alarm pressure before starting the program as the SEC column usually stands much less pressure than other columns, which also indicates the flowthrough speed should be slower during the experiment. 27. The injected sample can be automatically processed to the SEC column after the equilibration stage; this means in theory, the sample can be injected at any time before the sample loading program starts. 28. These settings can also be done at the same time as when setting alarm pressure. 29. The buffer can be different based on different proteins; a pre-test for the favorite buffer for the target protein is recommended. 30. Protein residue modification can be significantly affected by different oxidation states that caused by different concentration of H2O2 treatment. For example, cysteine thiolate can react with H2O2 to form sulfenic acid. With the increasing H2O2 concentration, the sulfenic acids are likely to form sulfinic acid and sulfonic acid sequentially. However, not every cysteine from a protein will undergo the same oxidation stage, and this varies from protein to protein. 31. Incubation time and temperature might vary; we usually use temperatures between 20 and 30  C for plant proteins. 32. Protein concentration measurement by UV absorbance at A280 is based on protein extinction coefficient. However, oxidation causes proteins forming multimeric forms that correspond to different extinction coefficients. In this case, other methods will be needed for determining protein concentration. 33. Always add dimedone before adding H2O2. 34. For MS analysis, peptides are analyzed by LC-MS/MS as described [38]. The mass spectrometer was operated in the data-dependent mode and switched automatically between MS, Zoom Scan for charge state determination, and MS/MS for the most abundant ion. The considered dynamic modifications on cysteine residues were +138.0 Da for sulfenic-dimedone, +32.0 Da for sulfinic, +48.0 Da for sulfonic, and +57.0 Da for carbamidomethyl modifications.

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Acknowledgments This work was supported by the Research Foundation-Flanders (FWO) senior postdoctoral fellowship (no.1227020N to J.H.), the China Scholarship Council (CSC, no. 201906300078 to Z.C.). References 1. Huang H, Ullah F, Zhou D-X et al (2019) Mechanisms of ROS regulation of plant development and stress responses. Front Plant Sci 10:800 2. Sharma P, Jha AB, Dubey RS et al (2012) Reactive oxygen species, oxidative damage, and antioxidative defense mechanism in plants under stressful conditions. J Bot 2012:217037 3. Huang J, Willems P, Van Breusegem F et al (2018) Pathways crossing mammalian and plant sulfenomic landscapes. Free Radic Biol Med 122:193–201 4. Jacques S, Ghesquie`re B, Van Breusegem F et al (2013) Plant proteins under oxidative attack. Proteomics 13(6):932–940 5. Sewelam N, Kazan K, Schenk PM (2016) Global plant stress signaling: reactive oxygen species at the cross-road. Front Plant Sci 7:187 6. Willems P, Van Breusegem F, Huang J (2021) Contemporary proteomic strategies for cysteine redoxome profiling. Plant Physiol 186(1): 110–124 7. Kim D, Lim S, Haque MM et al (2015) Identification of disulfide cross-linked tau dimer responsible for tau propagation. Sci Rep 5(1): 1–10 8. Liu XP, Liu XY, Zhang J et al (2006) Molecular and functional characterization of sulfiredoxin homologs from higher plants. Cell Res 16(3): 287–296 9. Yoshida K, Noguchi K, Motohashi K et al (2013) Systematic exploration of thioredoxin target proteins in plant mitochondria. Plant Cell Physiol 54(6):875–892 10. Freudl R (2018) Signal peptides for recombinant protein secretion in bacterial expression systems. Microb Cell Factories 17(1):1–10 11. Kallberg K, Johansson HO, Bulow L (2012) Multimodal chromatography: an efficient tool in downstream processing of proteins. Biotechnol J 7(12):1485–1495 12. Labrou NE (2014) Protein purification: an overview. Protein Downstr Proc:3–10 13. Andersen T, Pepaj M, Trones R et al (2004) Isoelectric point separation of proteins by capillary pH-gradient ion-exchange chromatography. J Chromatogr A 1025(2):217–226

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as a fusion with the Maltose-Binding Protein (MBP) tag. Methods Enzymol 559:17–26 27. Spriestersbach A, Kubicek J, Scha¨fer F et al (2015) Purification of His-tagged proteins. Methods Enzymol 559:1–15 28. Costa S, Almeida A, Castro A et al (2014) Fusion tags for protein solubility, purification and immunogenicity in Escherichia coli: the novel Fh8 system. Front Microbiol 5:63 29. Esposito D, Chatterjee DK (2006) Enhancement of soluble protein expression through the use of fusion tags. Curr Opin Biotechnol 17(4):353–358 30. Studier FW (1991) Use of bacteriophage T7 lysozyme to improve an inducible T7 expression system. J Mol Biol 219(1):37–44 31. Rosano GL, Ceccarelli EA (2009) Rare codon content affects the solubility of recombinant proteins in a codon bias-adjusted Escherichia coli strain. Microb Cell Factories 8(1):1–9 32. Burgess RR (2009) Refolding solubilized inclusion body proteins. Methods Enzymol 463:259–282 33. Wingfield PT, Palmer I, Liang SM (2014) Folding and purification of insoluble (inclusion

body) proteins from Escherichia coli. Curr Protoc Protein Sci 78(1):6.5.1–6.5.30 34. Ukkonen K, Veijola J, Vasala A et al (2013) Effect of culture medium, host strain and oxygen transfer on recombinant Fab antibody fragment yield and leakage to medium in shaken E. coli cultures. Microb Cell Factories 12(1):1–14 35. Smith PE, Krohn RI, Hermanson GT et al (1985) Measurement of protein using bicinchoninic acid. Anal Biochem 150(1):76–85 36. Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72(1-2): 248–254 37. Aitken A, Learmonth MP (2009) Protein determination by UV absorption. In: The protein protocols handbook. Humana Press, Totowa, pp 3–6 38. Huang J, Niazi AK, Young D et al (2017) Selfprotection of cytosolic malate dehydrogenase against oxidative stress in Arabidopsis. J Exp Bot 69(14):3491–3505

Chapter 12 Methods to Analyze the Redox Reactivity of Plant Proteins Thualfeqar Al-Mohanna, George V. Popescu, and Sorina C. Popescu Abstract Proteins can be covalently modified by a broad range of highly reactive chemicals and redox mechanisms. Reversible redox-mediated post-translational modifications of sensitive cysteine thiol groups in proteins impact protein characteristics such as interaction behavior and activity state. Evaluating the response of proteins to redox perturbation or reactive chemical species is critical for understanding the underlying mechanisms involved and their contribution to plant stress physiology. Here we provide a detailed workflow that includes procedures for (i) purification, processing, and analysis of protein samples with redox agents, (ii) determining redox-modulated monomer to oligomer transitions using size exclusion chromatography, and (iii) activity assays for monitoring the impact of redox agents on purified enzymes and in crude extracts from plants subjected to oxidative stress. We exemplified how to apply several of the methods discussed for analyzing redox-sensing metallopeptidases, such as thimet oligopeptidases. We anticipate that these protocols should find broad applications in monitoring biochemical properties of other classes of redox-sensitive plant proteins. Key words Size exclusion chromatography, Redox dimerization, Oxidative activation, Redox potential, In vivo enzymatic assays, Nernst, Peptidase

1

Introduction Cellular redox homeostasis is tightly controlled by continuous signaling for the production and removal of oxidants and reductants. It has been well recognized that reactive oxygen and nitrogen species (ROS/RNS) and diverse antioxidant defense systems (e.g., antioxidant enzymes, protein thiols, glutathione, and other antioxidants) maintain redox homeostasis in plant cells [1–3]. Recent research progress revealed the architecture of the cellular redox physiology organized according to a set of principles denoted as the “Redox Code” [2] and highlighted the underlying dynamic nature of the molecular mechanisms for the maintenance of redox homeostasis [4]. A critical principle of the plant “Redox Code” is that signaling mediated by ROS/RNS supports not only physiological processes but is also regulated by and incorporated into immune and stress response signaling [5–8].

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_12, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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A primary conduit of ROS/RNS-mediated signaling is through post-translational modifications (PTMs) of proteins. Oxidation and other chemical changes may occur at redox-sensitive amino acid residues such as cysteine, methionine, and tyrosine; among these, cysteine thiols have emerged as essential in regulating cellular activities [9–11]. Cysteine residues with low pKa exist as thiolates (S-) sensitive to oxidation by hydrogen peroxide (H2O2) to reversible oxoforms (e.g., S-sulfenylation (SOH), S-nitrosylation (SNO), S-glutathionylation (SSG), and disulfide bridges (S-S)) and irreversible oxoforms (e.g., S-sulfinylation (SO2H) and S-sulfonylation (SO3H)). Reversible thiol oxidation states can function as “redox switches” on protein/enzyme activity, interaction with self or other molecules, intracellular localization. Thus, proteins with redoxsensitive thiols toggle between oxidized and reduced isoforms displaying distinct biochemical characteristics and reactivity [5, 12]. Analogous to signal transmission via phosphorylation [13], redox-sensitive proteins can transmit signals rapidly within signaling networks in response to redox shifts in the intracellular environment. Although thiol-switching has been reported only sporadically for plant proteins, studies published so far emphasize the critical role of redox-sensitive thiols in regulating the selfinteraction and activity level of various types of proteins [5, 14– 17]. Analyses of proteomes of plants undergoing an immune response revealed a significant fraction of the proteome subjected to cysteine thiol oxidation [11, 18, 19]. Thus, since many redox PTMs are known to dynamically modulate the cellular functions of proteins/enzymes, methods aimed at assessing the functional consequences of redox PTMs impact of redox state on a protein’s characteristics are critical. We describe a set of protocols to determine the effect of reducing/oxidation treatments on proteins’ self-interaction and catalytic activity of redox-sensitive enzymes (see Fig. 1). First, a methodology whereby the redox treatment of the protein sample is coupled with Size Exclusion High-Performance Liquid Chromatography (SEC-HPLC) is used to determine and quantify protein polymerization. The high sensitivity of SEC-HPLC [20] ensures the determination of the oligomerization state of a protein of interest with minimal impact on the sample. Next, a method is presented to examine changes in the catalytic activity of proteins in response to reductive and oxidative treatments The procedures detailed here have been optimized for thimet oligopeptidases (AtTOPs), ubiquitous plant metallopeptidases [21] with functions in immune signaling and oxidative stress [14, 22], and recently shown to be subjected to thiol-mediated redox regulation [5]. We anticipate that these procedures and observations provide the necessary information to generalize for other protein and enzyme classes and probing the biological consequences of redox PTMs.

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Fig. 1 Analysis of types of redox regulation of proteins: polymerization through intermolecular disulfide bridges and modulation of enzymatic activity via thiol reduction/oxidation

2

Materials

2.1 Solutions and Reagents

1. Reagents and materials for affinity purification of protein samples, such as His-tag protein purification kits 2. Liquid bacterial culture media (Luria Bertani broth) 3. Bacterial cell lysis reagent, nonionic detergent-based solution 4. Buffer A: 50 mM Tris at pH 8.0 5. Buffer B: 50 mM Tris, 10 0mM Imidazole, and 500 mM NaCl at pH 7.0 6. Material and reagents for SDS-PAGE, immunoblots, and protein staining dyes such as Coomassie Brilliant Dye or analogous protein dyes 7. Protein extraction buffer: 50 mM Tris buffer, 150 mM NaCl, and 06 mM PMSF at pH 8.2 8. Glass or zirconia beads (~2 mm diameter) for disruption of plant tissues

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9. Bradford reagent (Coomassie Brilliant Blue G-250, ethanol, phosphoric acid) 10. Filter paper (e.g., Whatman #1) 11. Liquid nitrogen 12. L-Glutathione reduced (GSH) 13. L-Glutathione oxidized (GSSG) 14. D1, 4-Dithiothreitol (DTTred) 15. Trans-4, 5-dihydroxy-1, 2-dithiane (DTTox) 16. Filters for protein concentration and desalting of the appropriate kD cut-off 17. Tris-HCl 18. Tris-base 19. Phosphate buffer 20. Dialysis membrane tubing 21. Protein Molecular Weight Markers, HPLC 2.2

Equipment

1. HPLC system 2. UV-Visible Spectrophotometer 3. Protein electrophoresis equipment 4. Laboratory shaker benchtop 5. Laboratory shaker with temperature control 6. Centrifuge (refrigerated) 7. Microcentrifuge 8. Vortex 9. Spectrofluorometer (Olis DM 45 or a similar instrument)

3

Methods

3.1 Determine the Impact of the Redox Environment on Proteins Oligomerization 3.1.1 Preparation of Purified Recombinant Protein Samples

Protein samples need to fulfill specific qualitative and quantitative criteria. The choice among available biological systems for producing recombinant proteins is usually based on the compatibility of the production method with the samples, and it involves selecting the method that will interfere least with the native function of the protein tested (see Note 1). 1. Clone the cDNA of the gene of interest into the bacterial expression vector of choice, and transform it into transformation-competent cells of E. coli. We prefer using E. coli strain NiCo21(DE3), suitable for T7 expression with improved purity of target proteins isolated by immobilized metal ion affinity chromatography.

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2. Grow a culture of transformed E. coli cells (500 mL to 1 L) in LB broth and the appropriate selection antibiotic, at 37
C and with continuous shaking. 3. When the E. coli culture OD600nm reaches 05–06, add IPTG (100 mg/L) to induce the recombinant His-tagged protein expression. After 4 h, collect the cells by centrifugation (10,000  g for 30 min at 4
C), flash-freeze the pellet in liquid N, and store it at 80
C. 4. When ready for protein purification, thaw the frozen pellet on ice for 30–40 min, and then lyse the cells using a nonionic detergent-based reagent. For example, we use B-PER Reagent to effectively disrupt cells and solubilize recombinant proteins without denaturation. Add 12 mL B-PER reagent to a pellet obtained from 1 L culture. Incubate with gentle mixing for 15 min at room temperature. 5. Centrifuge the lysed cells at 12,000–14,000 rpm for 30 min at 4
C, and collect the supernatant. 6. While waiting for the centrifugation in step 5, prepare the extraction buffers, Buffer A (50 mM Tris at pH 8.0) and Buffer B (50 mM Tris, 100 mM Imidazole, and 500 mM NaCl at pH 7.0). Keep on ice until ready to use (see step 8). 7. Transfer the supernatant from step 5 to a device for protein concentration and desalting of the appropriate cut-off size for the tested protein(s). We prefer Amicon® Stirred Cell (with a 50 mL container) with Ultrafiltration discs (e.g., Ultracel® regenerated cellulose). 8. Load the concentrated extract onto a Ni-NTA column, and separate protein fractions by running 60 mL of Buffer A and then 50 mL of Buffer B through the column, with a 1 mL/min flow rate. This step should take approximately 2 h. His-TOPs proteins elute with Buffer B. 9. Collect recombinant protein fractions, and concentrate proteins using ultrafiltration units (e.g., Amicon) of the appropriate size-exclusion cut-off. Incubate purified protein samples on ice or transfer for longer-term storage at 4
C or colder (see Note 2). 10. Before storage, it is advisable to determine the concentration of purified protein preparations by directly measuring absorbance at 280 nm. After measuring absorbance (A280) of the protein solution, use the following formula to calculate concentration (C) for a path length of 1 cm (for most spectrometers): C ¼ A280 divided by absorbance coefficient. Concentration is in mg/mL, %, or molarity, depending on which type of coefficient is used. For unit conversion, use these relationships: mg

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protein/mL ¼ % protein divided by 10 ¼ molarity divided by protein molecular weight. 11. Determine the purity of the recombinant protein samples by electrophoresis on SDS-PAGE followed by visualization of protein bands using Coomassie Brilliant Dyes or analogous stains. 12. Determine protein concentration using the Bradford assay, according to the following process: (a) Prepare the Bradford reagent: dissolve 100 mg Coomassie Brilliant Blue G-250 in 50 mL 95% ethanol. Add 100 mL of 85% phosphoric acid while stirring; when Coomassie Brilliant Blue G-250 has dissolved, add sterile distilled water to 1 L. Filter the Bradford solution through filter paper (e.g., Whatman #1) to remove the residual dye. If not used immediately, store at 4
C in a dark bottle. (b) Generate a standard curve using BSA standard solution (01 μg/μL). Prepare a dilution series of your protein sample—mix 10 μL of each standard and sample and 180 μL Bradford reagent. Incubate 10 min at room temperature and measure absorbance at 595 nm. (c) Prepare a calibration curve by plotting absorbance versus protein amount (μg), and determine the amount of protein in your sample using the trend line (see Note 3). 3.1.2 Treatment of Target Proteins with Reducing and Oxidizing Agents

1. Prepare the redox reagents. In our lab, we use stock solutions of 20 mM GSH, 20 mM GSSG, 20 mM DTTred, and 20 mM DTTox. 2. Aliquot to fresh Eppendorf tubes the protein samples (obtained from Subheading 3.1.1, step 9). When testing potential thiol switches, mutants with individual or multiple cysteines mutagenized to redox-insensitive amino acids (e.g., alanine or serine) must be included alongside the wild-type form of the target protein. 3. For the redox treatment of proteins, add a tenfold molar excess of reductant and oxidizing agent to the protein samples. Incubate the samples for 30 min at room temperature with gentle mixing. 4. During the incubation step from step 2, prepare the dialysis buffer: 50 mM sodium phosphate buffer supplemented with 150 mM NaCl at pH 7.00. 5. Dialyze the treated purified protein against the dialysis buffer using dialysis membrane tubing of the appropriate molecular weight cut-off at 4
C overnight (see Note 4). 6. Transfer dialyzed protein samples to fresh Eppendorf tubes.

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7. Filter the dialyzed samples using a syringe-tip filter. Alternatively, centrifuge the sample at 10,000  g for 15 min to enable precipitation of non-soluble aggregates and other large particles (if present). 8. Transfer supernatants to fresh Eppendorf tubes. 9. The samples are now ready for the SEC-HPLC analysis. The protocol can be interrupted at this step, and samples transferred at 4
C or lower temperature for longer-term storage (see Note 2). 3.1.3 Separation and Detection of Monomeric and Multimeric Protein Products Using SEC-HPLC

Several factors need to be considered when selecting a SEC resin for protein separation. Before starting, see Note 5, and consult [20] for recent development in SEC-HPLC methods applied to the analysis of oligomeric protein aggregates. 1. Prepare all necessary HPLC buffers using HPLC grade water and solvents, filtered through 02 μm filters. Make sure all bottles have at least 400 mL buffer/solvent before starting. 2. Equilibrate the column for 30 min with HPLC-grade water (see Note 6). 3. Wash the column with 50 mM sodium phosphate buffer containing 150 mM sodium chloride and 002% sodium azide at pH 7.00 for 30 min. 4. Perform a pilot SEC-HPLC run using a protein standard mix. Slowly inject 100 μL of the standard mix through the injector port of the HPLC instrument. 5. Following the separation of the standard mix, which may vary according to the column type and standard used, determine the retention time taken by each of the protein components. 6. Calculate a regression curve (see Fig. 2b). The retention time of the standards and regression curve will give the time estimates for separation of the target protein samples and allow approximation of the molecular mass of sample peaks (see step 10, below). 7. Proceed with the analysis of the protein samples. Slowly inject 100 uL of the sample through the injector port. More or less material may be injected according to the sample stability and availability. 8. Use the isocratic mode to run the sample for 30 min with phosphate buffer and at a flowrate that allows maximum peak resolution. For example, for the AtTOP samples separated through an XBridge BEH200
A SEC 35 μm 78  300 mm Column, we used a flow rate of 088 μL/min (see Note 7). 9. Determine the protein peak areas on the sample chromatograms using the triangular method. This method equals peak

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A

B

3.0

2

250

3

200

Log Mw kDa

mAU, 280 nm

300

1

150 100

y = -0.3271x + 5.2581 R² = 0.9982

2.5 2.0 1.5

50 1.0

0 5

0

Protein Thyroglobulin IgG BSA Myoglobin

C

Peak 1 2 3 4

Rt 7.5 9.3 10.4 12.4

Rt(min) Area 7977.5 7040 6467.6 8212.5

15

10

Heigth 168.2 241.6 218.8 297.7

Width 0.64 0.41 0.41 0.38

Area% 23.70% 20.90% 19.20% 24.40%

6

8

10

12

14

Rt(min) Protein

Rt

Thyroglobulin IgG BSA Myoglobin

7.5 9.3 10.4 12.4

MW Log MW (kD) (kD) 660 2.82 150 2.18 66.4 1.82 16.7 1.22

3

6 2

5 4 3

2 1

1 0 0 Peak

Rt

1 2 3

8.8 9.3 10.4

10 Degree MW Log MW of (kD) (kD) polymeri zation 239.7 79.89 trimer 152.5 76.27 dimer 71.82 71.82 monomer

Fig. 2 SEC-HPLC to determine the impact of redox treatments on protein polymerization. (a) Separation of a mixture of four purified proteins ranging in molecular weight from 16.7 to 660 kDa. The proteins give peaks of approximately the same intensity for each protein when run on an XBridge BEH200
A SEC 3.5 μm 7.8  300 mm Column with elution buffer 10 mM PBS (140 mM NaCl, 10 mM sodium phosphate, pH 8.0) and monitored at 280 nm. (b) Regression curve for mass calculation of protein markers eluted through the HPLC column. The table on the right contains the information on the protein markers used in A to calculate the regression curve. (c) Representative results showing three self-interaction forms of an Arabidopsis thaliana TOP peptidase, detected following AtTOP treatment with GSSG. AtTOP elutes as a monomer, dimer, and trimer as determined using the regression curve in B. Agilent HPLC software B.04.03 used for data analysis and visualization

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height multiplied by the width at half-height to obtain the relative abundance values for monomers and oligomeric forms (see Fig. 2c) (see Note 8). 10. To obtain the unknown sample peaks’ molecular weight distribution and infer the average degree of sample polymerization under diverse redox conditions, use the calibration curve with protein standards of known molecular weight from step 6. 3.2 Determine the Impact of the Redox Modifications on Enzyme Activity 3.2.1 Redox Treatment of Purified Recombinant Protein Preparations

1. Prepare the redox reagents. In our lab, we use stock solutions of 20 mM GSH, 20 mM GSSG, 20 mM DTTred, and 20 mM DTTox. 2. Mix purified recombinant protein, obtained in Subheading 3.1.3, step 9, with the oxidative (GSSG or DTTox) or reductive (GSH or DTTred) agents added in tenfold molar excess. 3. Incubate at room temperature for 30 min to 2 h, and mix gently by inverting the tube several times (see Note 9). 4. Dialyze the protein preparation against 50 mM Tris-buffer pH 7.0 (or the preferred buffer) using membrane tubing of the appropriate molecular weight cut-off at 4
C overnight. 5. Transfer the sample to fresh Eppendorf tubes. The sample is now ready for further analysis (as described in Subheading 3.2.3). Alternatively, the protocol can be interrupted at this step, and the sample transferred at 4
C or 20
C for longerterm storage (see Note 2).

3.2.2 Analysis of Total Protein Extracts Obtained from Plants Subjected to Oxidative Stress

1. Grow plants and perform the oxidative stress treatment of choice. Include as control tissue samples from un-stressed plants. Flash freeze collected tissues in liquid nitrogen, and store at 80
C until ready to use. 2. Grind tissues in liquid nitrogen to a fine powder, keeping the tissue frozen during processing. For every 100 mg of powdered sample, add 500 μL of protein extraction buffer (e.g., 50 mM Tris/HCl pH 7.5, 5 mm β–mercaptoethanol, and 03% w/v polyvinylpyrrolidone). Add glass or zirconia beads to the sample, and vortex the mixture vigorously for 15 min at room temperature, with incubation on the ice every 5 min (see Note 10). 3. Centrifuge the mixture at 21,300  g for 10 min at 4
C. 4. Collect the supernatant and transfer it to a new tube. Keep on ice. 5. Determine protein concentration using the Bradford assay, according to the process described in Subheading 3.1.1, step 12.

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A Fluorescence (RU)

150,000

DTT

DTT

100,000

50,000

0 5 11 16 22 27 33 38 44 50 55 61 66 72 77 83 88 9 104 0

0

Time (sec)

GSSG

B Fluorescence (RU)

150,000

GSSG

GSSG

100,000

50,000

0 5 11 16 22 27 33 38 44 50 55 61 66 72 77 83 88 9 104 0

0

Time (sec)

C

✱

Rate of reaction

6000

4000

2000

0 DTT

GSSG

Condition

Fig. 3 Oxidative activation of peptidase activity of AtTOP. (a) Representative graphs showing fluorescence values (left) and initial rates (right) plotted against elapsed time (n ¼ 4, 100 s) under the DTTred condition. (b) Representative graphs showing fluorescence values (left) and initial rates (right) plotted against elapsed time (n ¼ 3, 100 s) under the GSSG condition. (c) Bars represent reaction rates for AtTOP following treatments with DTTred and GSSG, with standard deviation over independent replicates (n ¼ 3); enzyme activities were measured at λex ¼ 330 nm and λem ¼ 400 nm, over 100 s. Significance tested with unpaired T-test, two-tailed; pVal < 001 (*). For A-C, the enzymatic activity of purified recombinant AtTOP was tested using the synthetic fluorogenic substrate Mca-PLGPK(DNP)-OH

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6. We recommend immediate use of the protein preparation to determine the specific enzymatic activity (Method, Subheading 3.2.3). 3.2.3 Detection of Peptidase Activity by Fluorometric Assay

To revel substrate specificity of peptidases, many types of assays are available, ranging from the use of synthetic fluorogenic peptides [22, 23], to bacterial or phage display [24, 25], and proteome and mass spectrometry-based methods [21, 26]. Among these, fluorescent methods are more quantitative and can provide highly specific conditions for testing peptidase activity under diverse reaction conditions (see Note 11). 1. Prepare a working solution of a peptide substrate specific for the enzyme tested. Make a stock solution that is at a higher concentration than required for the experimental assay by dissolving the peptide in sterile distilled water, sterile 01% acetic acid, or stronger solvents, where applicable. The stock solution peptide can be diluted further with the assay buffer (see Notes 12 and 13 for guidelines on peptides storage and solubilization, respectively). For thimet oligopeptidases, use the quenched fluorogenic peptide substrate (7-methoxycoumarin-4-acetyl-Arg-Pro-ProGly-Phe-Ser-Ala-Phe-Lys-dinitrophenol) dissolved in 50 mM Tris, pH 7.5. The fluorescence signal appears immediately after peptide hydrolysis. 2. Prepare a no-enzyme control reaction containing only the reaction buffer to assess the background noise of the fluorometer measurements (see Note 14). 3. Prepare for fluorescence measurements by setting the excitation/emission wavelengths of the fluorometric plate reader to the appropriate parameters. For measuring thimet oligopeptidases’ activity on 7-methoxycoumarin-4-acetyl-Arg-Pro-ProGly-Phe-Ser-Ala-Phe-Lys-dinitrophenol, set the fluorometer at 330 nm excitation and 400 nm emission wavelengths (see Note 15). 4. To initiate the enzyme assay using purified recombinant protein, mix the redox-treated protein samples (obtained at step 5 of Subheading 3.2.1) with the fluorogenic substrate at a peptide: protein ratio of 15:1, in 500 μL of 50 mM Tris-buffer pH 8.0. 5. To initiate the enzyme assay using total protein extracts (obtained at step 4 of Subheading 3.2.2), incubate 100 μg of total protein extract in 500 μL of 50 mM Tris-buffer pH 8.0, containing 8 μM of the fluorogenic substrate. 6. Monitor the cleavage of the fluorogenic peptide substrate in treatment and control protein preparations and the no-enzyme

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sample by continuous recording of the fluorescence for 60 to 100 s. See Fig. 3 for an example of a time-dependent plot of fluorescence values measured within the first 100 s of the peptide-substrate reaction. The assays measured the activity of recombinant AtTOP treated with DTTred (see Fig. 3a) and GSSG (see Fig. 3b) on the quenched fluorogenic substrate. For examples of activity assays using crude extracts from plants subjected to biotic stress, see [5]. 3.2.4 Enzyme Activity Analysis

1. In vitro Reactions (a) Estimate the initial reaction rate (μM s1) of enzyme activity from the in vitro reactions (first 100 s time points) using linear or logarithmic methods. (b) Plot the progression curve and assess the best rate estimation method for analysis. (b1) Use a linear method for reactions that progress linearly over the selected time interval (low enzyme concentration). (b2) Use a logarithmic approximation for reactions that progress nonlinearly over the specified time interval. Adjust the time interval to obtain a logarithmic regression R2 value of at least 09 (see Note 16). 2. In vivo Assays (a) Estimate the specific enzyme activity in the samples containing total protein extracts (first 100 s time points) using an integration method. (b) Calculate the normalized total reaction product per time unit, integrated using the Area Under the Curve (AUC) method. We use the GraphPad PRISM v8 (https://www. graphpad.com). (c) Normalize product reaction concentration per microgram of total protein (see Note 17). 3. Test for significant changes in enzyme activity among the diverse redox conditions analyzed using statistical testing methods [27].

3.2.5 Redox Titration Analysis

Use multiple redox couples to assess enzyme activity dependence on redox potential. 1. Select between 8 and 16 redox titration potentials using one or two redox couples (use calculated redox couples shown in Tables 1 and 2) (see Note 18). Sample the redox potential range to generate more measurements in regions where the

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Table 1 Estimated redox potentials obtained by mixing GSH and GSSG solutions Final [GSSG] (mM)

Final volume Ratio R (mL) [GSSG]/[GSH]2

Redox potential Eh (mV)

0.5992

19.4008

250

54035.10867

100

239.03

0.8776

19.1224

250

24828.42492

110

16.02

233.98

1.2816

18.7184

250

11396.29614

120

4

23.27

226.73

1.8616

18.1384

250

5233.909807

130

5

33.56

216.44

2.6848

17.3152

250

2402.16942

140

6

47.86

202.14

3.8288

16.1712

250

1103.105083

150

7

67.18

182.82

5.3744

14.6256

250

506.3533862

160

8

92.13

157.87

7.3704

12.6296

250

232.4917142

170

9

122.29

127.71

9.7832

10.2168

250

106.7463485

180

10

155.36

94.64

12.4288

7.5712

250

49.01243953

190

11

187.03

62.97

14.9624

5.0376

250

22.50200198

200

12

212.63

37.37

17.0104

2.9896

250

10.33199132

210

13

229.94

20.06

18.3952

1.6048

250

4.742549665

220

14

239.97

10.03

19.1976

0.8024

250

2.17719357

230

15

245.19

4.81

19.6152

0.3848

250

1.000114174

240

16

247.75

2.25

19.82

0.18

250

0.458210677

250

17

248.95

1.05

19.916

0.084

250

0.211775176

260

18

249.52

0.48

19.9616

0.0384

250

0.096369704

270

19

249.78

0.22

19.9824

0.0176

250

0.044077542

280

20

249.9

0.1

19.992

0.008

250

0.02001601

290

GSH 20 mM (mL)

GSSG 20 mM (mL)

1

7.49

242.51

2

10.97

3

Sample

Final [GSH] (mM)

enzyme is expected to change its dynamics significantly (see Note 19). 2. Measure enzyme activity at the selected redox potentials as described in Subheading 3.2.3. 3. Calculate the number of electrons exchanged in the target redox reaction; fit the Nernst equation to estimate the Em for the target enzyme. (a) Calculate the oxidation ratio (R) with R ¼ Fox/(Fox + Fred) (Fox and Fred are the fractions of the oxidized and reduced enzyme, respectively) estimated using fluorescent measurements of enzyme activity. Here, we assume that

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Table 2 Estimated redox potentials obtained by mixing DTTox and DTTred solutions Redox potential

Final [DTTox] (mM)

Final volume (mL)

Ratio R [DTTox]/ [DTTred]

0.0104

19.9896

250

1922.076923

230

249.71

0.0232

19.9768

250

861.0689655

240

0.62

249.38

0.0496

19.9504

250

402.2258065

250

4

1.35

248.65

0.108

19.892

250

184.1851852

260

5

2.92

247.08

0.2336

19.7664

250

84.61643836

270

6

6.28

243.72

0.5024

19.4976

250

38.8089172

280

7

13.29

236.71

1.0632

18.9368

250

17.81113619

290

8

27.23

222.77

2.1784

17.8216

250

8.181050312

300

9

52.57

197.43

4.2056

15.7944

250

3.75556401

310

10

91.76

158.24

7.3408

12.6592

250

1.724498692

320

11

139.53

110.47

11.1624

8.8376

250

0.791729377

330

12

183.35

66.65

14.668

5.332

250

0.363512408

340

13

214.24

35.76

17.1392

2.8608

250

0.166915609

350

14

232.21

17.79

18.5768

1.4232

250

0.076611688

360

15

241.5

8.5

19.32

0.68

250

0.035196687

370

16

246.03

3.97

19.6824

0.3176

250

0.016136244

380

17

248.16

1.84

19.8528

0.1472

250

0.007414571

390

18

249.15

0.85

19.932

0.068

250

0.003411599

400

19

249.61

0.39

19.9688

0.0312

250

0.001562437

410

20

249.82

0.18

19.9856

0.0144

250

0.000720519

420

DTTred 20 mM (mL)

DTTox 20 mM (mL)

Final [DTTred] (mM)

1

0.13

249.87

2

0.29

3

Sample

Eh (mV)

measured activity (initial rates) is proportional to the fraction of oxidized enzyme. Another model assumes that the measured activity is proportional to the fraction of reduced enzyme [15]. (b) Use Nernst equation, Eh ¼ Em + (RT/nF)(ln([Fox]/ [Fred]), with RT/F ¼ 25693 mV and n ¼ number of electrons exchanged in the redox reaction. (c) Use the fitting equation (Y ¼ 1/(1 + exp-(XEm)*n/ 25693)); the equation can be implemented using numerical computing software (e.g., GraphPad PRISM or MATLAB) as a nonlinear least square fitting method.

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Fig. 4 Purified recombinant AtTOP1 was incubated in DTTred/DTTox or GSH/GSSG solutions at defined thiol/disulfide ratios. The dots show the oxidation-reduction titration of AtTOP, and the solid line shows the fit of the data to a two-electron Nernst curve. The two titration ranges are shown in light blue (DTTred/DTTox) and light red (GSH/GSSG). The Em value is indicated by the dotted red line. Data were acquired in two independent experiments; one representative is shown

4. Example: Use DTTred/DTTox titration to test AtTOP1 activity at 360, 332, and 322 mV; at these Eh values, over 90% of AtTOP1 was monomeric. Further, titration with GSH/GSSG allowed AtTOP1 testing in oxidative conditions (188, 173, and 100 mV) that promoted AtTOP1 dimerization (~30 to 40% dimers, respectively). We found that under titration with DTTred/DTTox, AtTOP1 activity changes little in the redox range analyzed; comparatively, AtTOP1 activity shows significant changes following GSH/GSSG titration (see Fig. 4).

4

Notes 1. Bacterial expression systems are, in general, suitable for the expression and purification of recombinant plant proteins. Here we briefly describe the steps for the purification of recombinant His-tagged proteins on Ni-NTA columns, with some recommendations for increasing protein yield and purity. 2. In general, for storage up to 24 h, most proteins can be kept at 4
C. For storage times longer than 24 h at 4
C, it may be necessary to filter-sterilize the protein preparation (e.g., 022 μm filter) or add a bacteriostatic agent (e.g., 01% sodium azide) to avoid bacterial growth. For long-term storage (more than a week), it is necessary to freeze the protein preparation. To avoid denaturation, freeze protein samples rapidly using liquid nitrogen or a dry ice/ethanol mixture. Glycerol

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(10–50% (w/v)) and bovine serum albumin (10 mg/mL) can be used as stabilizing agents. For higher volume protein preparations, it is advisable to freeze the preparation in small aliquots to avoid repeated freezing-thawing cycles that may interfere with the biological activity or cause protein denaturation. Storage for longer periods (months to years), protein samples should be stored at 20
C in 50% glycerol or at 80
C in 5–50% glycerol. 3. It is often challenging to select a protein standard complementary to the analyzed protein; instead, it has become scientifically acceptable to use proteins such as bovine serum albumin (BSA) and IgG globulin as standards. However, due to the considerable variation between proteins and yields, the results are estimates of the sample protein concentration. 4. Dialysis is a necessary step to remove redox agents from the protein preparations. DTT, GSH, and GSSG have strong absorbance at 280 nm and may interfere with subsequent SEC-HPLC analysis steps. 5. Resin particle size, chemical composition, flow rate, packing of the column, sample running conditions, and the HPLC system available are several of the factors determining peak resolution in SEC-HPLC. High-performance SEC resins, packed with uniform particles, produce high-resolution peaks. For example, a Superdex 200 Increase SEC column is well suited for separating biomolecules with Mr in the range of 10,000 to 600,000. Running buffers with pH between 60 and 80 are commonly used in SE-HPLC applications since many proteins are stable within this pH range. If resin optimization is required, prioritize the following factors: select a resin with a fractionation range producing optimal peak resolution, select a column size appropriate for the sample volume, and select the highest flow rate that provides the optimal peak resolution. 6. The SEC-HPLC procedure that follows has been optimized to analyze the oligomerization behavior of recombinant AtTOPHis using an XBridge BEH200
A SEC 35 μm 78  300 mm Column connected to an Agilent 1100 series HPLC system. 7. The flow rate affects the resolution between protein peaks, especially for large proteins. Adjust and set a flow rate that allows optimal resolution within the molecular weight range relevant to the proteins tested. For additional information on SEC optimization, please see [28]. 8. Chromatograms can be recorded, then subsequently analyzed and visualized with the data mining software packages available for the HPLC instrument utilized. 9. The optimal incubation time can be determined in preliminary experiments where several protein/redox agent ratios are

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tested. For additional information and protocols used to analyze protein oligomerization using SEC-HPLC, please see [29, 30]. 10. For an example of protein extraction protocol, see [22]. 11. The following protocol steps were optimized for testing the peptidase activity of AtTOP, using purified recombinant protein (Subheading 3.1.1, step 9) or total protein extracts from Arabidopsis leaf tissue (Subheading 3.2.2, step 6). For further information, see [5]. 12. Lyophilized peptides are stable at room temperature for days to weeks. For longer-term storage, lyophilized peptides should be stored at 4
C or colder (20
C), and away from bright light and moisture. Before using the peptide, remove it from the cold and incubate for at least 10 min at room temperature. If the peptide is in solution, freeze/thaw cycles should be avoided by freezing individual aliquots [31]. 13. For acidic peptides, add a small amount of 01 M ammonium bicarbonate to dissolve the peptide, dilute with sterile distilled water to the desired concentration, and adjust the final pH to 7. For basic peptides, use a small amount of 25% acetic acid to dissolve the peptide, add sterile distilled water to the desired concentration, and adjust the final pH to 7 [32]. 14. Background fluorescence determined for the no-enzyme control will be subtracted from each measurement of enzyme activity assays in Subheading 3.2.4. 15. The utility of a particular substrate for an enzyme depends on the substrate’s concentration and amino acid sequence and the pH, temperature, and presence of cofactors in the medium; for measurements using total protein extracts, the suitability of a substrate also depends on its accessibility and stability [33]. 16. Use ICEKAT online tool [34] for rate estimation software implementation. 17. Integrate AUC using numerical computing software (e.g., GraphPad PRISM v8 [35]). 18. The volumes (μL) have been computed from the target Eh values and rounded to 2 decimal points. The maximum absolute error for Eh calculation is 018 mV, and the MSE is 00028 for DTTred/DTTox redox couple, and 0256 mV and 00039, respectively, for GSH/GSSG redox couple. Precise volumes can be obtained by calculating the ratio from the Nernst formula and solving for the redox couple volumes. 19. Calculation of enzyme Eh value is based on the equilibrium midpoint potential values of DTTred/DTTox redox couple (327 mV) and of GSH/GSSG redox couple (240 mV) at pH 7.0 [36].

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Acknowledgments The authors acknowledge funding for this work from NSF-MCB 1714157 to SCP and GVP. References 1. Mock HP, Dietz KJ (2016) Redox proteomics for the assessment of redox-related posttranslational regulation in plants. Biochim Biophys Acta (BBA)-Proteins Proteomics 1864: 967–973 2. Zaffagnini M, Fermani S, Marchand CH, Costa A, Sparla F, Rouhier N, Geigenberger P, Lemaire SD, Trost P (2019) Redox homeostasis in photosynthetic organisms: novel and established thiol-based molecular mechanisms. Antioxid Redox Signal 31: 155–210 3. Wormuth D, Heiber I, Shaikali J, Kandlbinder A, Baier M, Dietz KJ (2007) Redox regulation and antioxidative defence in Arabidopsis leaves viewed from a systems biology perspective. J Biotechnol 129:229–248 4. Sies H (2021) Oxidative eustress: on constant alert for redox homeostasis. Redox Biol 41: 101867. https://doi.org/10.1016/j.redox. 2021.101867 5. Al-Mohanna T, Nejat N, Iannetta AA, Hicks LM, Popescu GV, Popescu SC (2021) Arabidopsis thimet oligopeptidases are redoxsensitive enzymes active in the local and systemic plant immune response. J Biol Chem 100695. https://doi.org/10.1016/j.jbc. 2021.100695 6. Foyer CH, Noctor G (2013) Redox signaling in plants. Antioxid Redox Signal 18: 2087–2090 7. Martins L, Trujillo-Hernandez JA, Reichheld JP (2018) Thiol based redox signaling in plant nucleus. Front Plant Sci 9:705 8. Liebthal M, Maynard D, Dietz KJ (2018) Peroxiredoxins and redox signaling in plants. Antioxid Redox Signal 28:609–624 9. Waszczak C, Akter S, Eeckhout D, Persiau G, Wahni K, Bodra N, Van Molle I, De Smet B, Vertommen D, Gevaert K, De Jaeger G, Van Montagu M, Messens J, Van Breusegem F (2014) Sulfenome mining in Arabidopsis thaliana. Proc Natl Acad Sci 111:11545–11550 10. Akter S, Huang J, Bodra N, De Smet B, Wahni K, Rombaut D, Pauwels J, Gevaert K, Carroll K, Van Breusegem F, Messens J (2015) DYn-2 based identification of Arabidopsis sulfenomes. Mol Cell Proteomics 14:1183–1200

11. McConnell EW, Berg P, Westlake TJ, Wilson KM, Popescu GV, Hicks LM, Popescu SC (2019) Proteome-wide analysis of cysteine reactivity during effector-triggered immunity. Plant Physiol 179:248–1264 12. Leichert LI, Dick TP (2015) Incidence and physiological relevance of protein thiol switches. Biol Chem 396(nd):389–399. https://doi.org/10.1515/hsz-2014-0314 13. Popescu SC, Popescu GV, Bachan S, Zhang Z, Gerstein M, Snyder M, Dinesh-Kumar SP (2009) MAPK target networks in Arabidopsis thaliana revealed using functional protein microarrays. Genes Dev 23. https://doi.org/ 10.1101/gad.1740009 14. Westlake TJ, Ricci WA, Popescu GV, Popescu SC (2015) Dimerization and thiol sensitivity of the salicylic acid binding thimet oligopeptidases TOP1 and TOP2 define their functions in redox-sensitive cellular pathways. Front Plant Sci 6. https://doi.org/10.3389/fpls. 2015.00327 15. Marshall PA, Dyer JM, Quick ME, Goodman JM (1996) Redox-sensitive homodimerization of Pex11p: a proposed mechanism to regulate peroxisomal division. J Cell Biol 135:123–137. https://doi.org/10.1083/jcb.135.1.123 16. Chan KX, Mabbitt PD, Phua SY, Mueller JW, Nisar N, Gigolashvili T, Stroeher E, Grassl J, Arlt W, Estavillo GM (2016) Sensing and signaling of oxidative stress in chloroplasts by inactivation of the SAL1 phosphoadenosine phosphatase. Proc Natl Acad Sci 113: E4567–E4576 17. Dı´az MG, Herna´ndez-Verdeja T, Kremnev D, Crawford T, Dubreuil C, Strand Å (2018) Redox regulation of PEP activity during seedling establishment in Arabidopsis thaliana. Nat Commun 9:50. https://doi.org/10.1038/ s41467-017-02468-2 18. Mhamdi A (2019) The immune redoxome: effector-triggered immunity switches cysteine oxidation profiles. Plant Physiol 179: 1196–1197 19. Bleau JR, Spoel SH (2021) Selective redox signaling shapes plant-pathogen interactions. Plant Physiol 27:53–65 20. Fekete S, Beck A, Veuthey J-L, Guillarme D (2014) Theory and practice of size exclusion

Redox Reactivity of Plant Proteins chromatography for the analysis of protein aggregates. J Pharm Biomed Anal 101: 161–173. https://doi.org/10.1016/j.jpba. 2014.04.011 21. Iannetta AA, Holden TG, Al-Mohanna T, O’Brien JO, Wommack AJ, Popescu SC, Hicks LM (2021) Profiling thimet oligopeptidase-mediated proteolysis in Arabidopsis thaliana. Plant J 106:336–350 22. Moreau M, Westlake T, Zampogna G, Popescu GV, Tian M, Noutsos C, Popescu SC (2013) The Arabidopsis oligopeptidases TOP 1 and TOP 2 are salicylic acid targets that modulate SA-mediated signaling and the immune response. Plant J 76:603–614 23. Harris JL, Backes BJ, Leonetti F, Mahrus S, Ellman JA, Craik CS (2000) Rapid and general profiling of protease specificity by using combinatorial fluorogenic substrate libraries. Proc Natl Acad Sci 97:7754–7759 24. Matthews DJ, Wells JA (1993) Substrate phage: selection of protease substrates by monovalent phage display. Science 260: 1113–1117 25. Packer MS, Rees HA, Liu DR (2017) Phageassisted continuous evolution of proteases with altered substrate specificity. Nat Commun 8: 1–11 26. Lapek JD, Jiang Z, Wozniak JM, Arutyunova E, Wang SC, Lemieux MJ, Gonzalez DJ, O’Donoghue AJ (2019) Quantitative multiplex substrate profiling of peptidases by mass spectrometry. Mol Cell Proteomics 18: 968–981 27. Hothorn T, Everitt BS (2014) A handbook of statistical analyses using R. CRC Press 28. Sˇtulı´k K, Paca´kova´ V, Ticha´ M (2003) Some potentialities and drawbacks of contemporary

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Chapter 13 Determination of ROS-Induced Lipid Peroxidation by HPLC-Based Quantification of Hydroxy Polyunsaturated Fatty Acids Brigitte Ksas and Michel Havaux Abstract Because they are highly unsaturated, plant lipids are sensitive to oxidation and constitute a primary target of reactive oxygen species. Therefore, quantification of lipid peroxidation provides a pertinent approach to evaluating oxidative stress in plants. Here, we describe a simple method to measure upstream products of the peroxidation of the major polyunsaturated fatty acids in plants, namely, linolenic acid (C18:3) and linoleic acid (C18:2). The method uses conventional HPLC with UV detection to measure hydroxy C18:3 and C18:2 after reduction of their respective hydroperoxides. The described experimental approach requires low amounts of plant material (a few hundred milligrams), monitors oxidation of both membrane and free fatty acids, and can discriminate between enzymatic and non-enzymatic lipid peroxidation. Key words Lipid peroxidation, Oxidative stress, Reactive oxygen species, Polyunsaturated fatty acids, Hydroxy fatty acids

1

Introduction Fatty acids are highly unsaturated in plant leaves and are therefore very sensitive to oxidation [1]. Consequently, lipid peroxidation is usually a primary event associated with the production of reactive oxygen species (ROS) and oxidative stress in plants. Actually, the abundancy of polyunsatured fatty acids has been proposed to act as a sink for ROS in the chloroplasts, possibly constituting a protection mechanism against propagation of oxidative stress [2]. The major fatty acids in plant leaves are linolenic acid (C18:3) and linoleic acid (C18:2) containing 3 and 2 double bonds, respectively. In Arabidopsis leaves, C18:3 represents around 50 mol% of the total fatty acid content [3]. Oxidation of the C18:3 fatty acid leads to hydroperoxy octadecatrienoic acid (HPOTE) which can be reduced to form hydroxy octadecatrienoic acid (HOTE). Depending on which double bond is oxidized, six different HOTE stereoisomers can be formed: 9-,

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_13, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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10-, 12-, 13-, 15-, and 16-HOTE. 10- and 15-HOTE are specific to oxidation by singlet oxygen (1O2) [4, 5]. While the latter HOTE isomers do not absorb UV light and require mass spectrometry for detection, the other HOTEs contain conjugated dienes and are accessible to UV detection. 9- and 13-HOTEs can be formed enzymatically under the catalytic action of lipoxygenases [6] whereas 12- and 16-HOTEs are specific markers of ROS-induced lipid peroxidation (1O2 and free radicals) [4, 5]. HPLC analysis of the HOTE profile can thus discriminate between ROS-induced lipid peroxidation and enzymatic oxidation, and, when combined with mass spectrometry, it can also provide information on the type of ROS involved in fatty acid oxidation [5, 7]. As far as linoleic acid C18:2 is concerned, its oxidation leads to HPODE isomers (hydroperoxy octadienoic acid) and their corresponding alcohols, 9-, 10-, 12-, and 13-HODE. Similarly to the HOTEs, two isomers (10- and 12-HODE) are specific to 1O2 oxidation and have non-conjugated dienes. Here, we detail a quantitative method to measure HOTEs and HODEs by high-pressure liquid chromatography (HPLC) coupled with an UV absorption detector. Compared to a previous protocol [7], the method has been optimized to reduce the amounts of plant material and the volumes of the extraction media. This improved protocol also contains helpful tips and provides procedures to specifically derived information on ROS-induced lipid peroxidation. An important step in this method is the stabilization of fatty acid hydroperoxides in the lipid extract by their reduction into the corresponding alcohols using triphenylphosphine. This reductant proved to be more appropriate for this purpose than other reducing agents, such as sodium borohydride which generates unwanted secondary products. This reduction step is important because lipid hydroperoxides and endoperoxides are fairly unstable and can fragment into various secondary products [8]. By the way, the popular TBARS assay (thiobarbituric acid reactive substances) of lipid peroxidation measures malondialdehyde (MDA) which is one such secondary product generated by the decomposition of lipid peroxidation products. Because MDA is not generated exclusively by lipid peroxidation and is not generated by all lipid peroxidation products, MDA determination offers only a partial, indirect, and empirical estimate of the lipid peroxidation which must be taken with caution [9]. Interestingly, some of the decomposition products of lipid peroxides are luminescent, providing an optical means to measure and image lipid peroxide decomposition (proportional to the lipid peroxide concentration) using very sensitive photon detection systems [10]. In general, leaf autoluminescence and biochemically measured HOTE levels are well correlated in plants exposed to oxidative stress (e.g., [11, 12]), hence constituting complementary methods for estimating lipid peroxidation levels.

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In the biochemical method described here, both free and esterified fatty acid peroxides are evaluated together after saponification. The different positional isomers of HOTE and HODE are then separated by HPLC on a straight phase silica column, and the hydroxy fatty acids having conjugated dienes are detected and quantified by UV spectrophotometry. This rather simple biochemical method provides thus a quantitative evaluation of lipid peroxidation as a whole including membrane lipids and free fatty acids. Since polyunsaturated fatty acids are primary targets of ROS in plant tissues and HOTEs are upstream products in this process, quantification of ROS-induced accumulation of HOTE can be considered as a good estimate of oxidative stress in plants.

2

Materials

2.1 Biological Material

2.2 Equipment for the Extraction of Hydroxy Fatty Acids

Biological samples (see Note 1) should not be less than 200 mg and should not exceed 600 mg fresh weight. Once collected and weighted, samples are transferred into 50-ml polypropylene tubes with screw caps. The tubes are frozen in liquid nitrogen and then stored at
20  C before hydroxylipid extraction and HPLC quantification. 1. An ice bath 2. A timer 3. pH indicator paper strips (pH from 1 to 10) 4. A mechanical grinder such as the IKA Ultra-Turrax T25 5. A glass rod for a first manual grinding of the samples 6. 5-mL, 100-μL, and 20-μL pipettes 7. A 10-mL glass syringe with a long stainless steel needle to take the organic phase containing the hydroxy fatty acids 8. Glass tubes of 10 mL with screw caps for the saponification step 9. 1-mL glass tubes with aluminum crimp cap to keep the hydroxy fatty acid samples at
20  C 10. A nitrogen evaporator consisting of a metal block thermostat and a multiplex valve depot for solvent evaporation under nitrogen gaz flux through stainless steel needles

2.3 Solutions for the Extraction of Hydroxy Fatty Acids

1. Extraction solution: 5 mM triphenylphosphine, 1 mM 2-6 Di-ter-butyl-p-cresol (BHT) in methanol/chloroform 50/50 (v/v) 2. 1 M citric acid 3. Ethanol 4. Chloroform

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5. 3.5 N NaOH 6. Solvent mixture of hexane and diethyl ether (50/50, v/v) for the final solution of hydroxy fatty acids (see Note 2) 2.4

HPLC Analysis

1. HPLC glass vials with 300-μL insert. 2. Column: Zorbax rx-SIL 4,6  250 mm, 5 μm particle size. 3. A common HPLC system with a UV detector and a data analysis software. 4. HPLC mobile phase: 70/29.31/0.69 (v/v/v) hexane/diethyl ether/acetic acid. 5. 15-HEDE (15-hydroxy-eicosadienoic acid) is used as internal reference (see Note 3). It is added to the samples at a concentration of 100 nmoles per g of fresh weight.

3

Methods

3.1 Total Lipid Extraction

1. Take the biological samples from the freezer, open the tubes, and add a few mL of liquid nitrogen with a ladle spoon. Grind them manually with a glass rod (for around 30 s). 2. When N2 has vanished (see Note 4), add the Extraction Solution with a ratio of 5 mL of solution per g of fresh weight. Then add 1 M citric acid (2.5 mL per g fresh weight) (see Note 5). 3. Use an Ultra-Turrax T25 mechanical homogenizer or equivalent. Samples must always stay in an ice/water bath. Grind the sample at maximum speed (25,000 rpm) until you get a fine green homogenate (it generally takes about 1 min). 4. Add 15-HEDE, the internal reference, to each sample in order to have a ratio of 100 nmoles per g of fresh weight, and shake it thoroughly with a vortex shaker. 5. Verify the pH of the homogenate which should be between 4 and 5. Acidic pH promotes lipid extraction. However, if the pH is less than 4, it is necessary to quickly readjust the pH with 3.5 N NaOH to avoid loss of extracted lipids in the aqueous phase (see Note 6). 6. At this step you can store your samples at
20  C for a few days or proceed directly with the extraction. 7. Centrifuge at 700 g for 5 min at 4  C using a swinging bucket rotor. Two phases are present in the tubes: the lower organic one (chloroform) and the upper aqueous one. The organic phase (containing free and esterified hydroxy fatty acids) is then taken with the help of a glass syringe equipped with a long (about 7–10 cm long) large-diameter metal needle. In order to go through the aqueous phase and reach the organic one without filling the needle with the aqueous phase, the trick

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is to suck in some air with the syringe before getting through the aqueous phase. Release the air once the needle has reached the organic phase. This will avoid contamination of the organic phase with the aqueous phase. 8. Transfer the organic phase in a glass tube. Rinse the syringe with a few ml of chloroform, and add this to the first collected phase. The remaining aqueous phase in 50-mL tube is then washed with 2.5 mL of chloroform. Shake it thoroughly by vortexing for 30 s, and proceed exactly as previously to get this second organic phase that will be pooled with the first one. 3.2 Evaporation and Saponification

1. Remove the solvent by evaporation at 40 C under nitrogen gas stream with the needle evaporator for 30 min. Monitor evaporation so that residues in the tubes are not too dry. 2. The residue stuck on the glass tube is then carefully solubilized with 1.25 mL of ethanol. Vortex. When the whole residue is dissolved, add 1.25 mL of 3.5 N NaOH (see Note 7). 3. Put the glass tubes in a heating bath, and let the saponification to proceed for 20 min at 80  C. After this treatment, evaporate the excess ethanol under a nitrogen gas stream for 10 min, keeping temperature at 80  C. This step allows the release of the hydroxylipids (see Note 8). 4. Shake manually the tubes; the absence of bubbles ensures that the ethanol is completely evaporated (see Note 9). 5. Let the samples to cool down to room temperature and then transfer them on ice. The samples can be stored for 2–3 h. Adjust the pH to 4–5 with 2.1 mL of 1 M citric acid, and add 1.5 mL of the hexane/diethyl ether solvent mixture (50/50, v/v). Vortex the tubes to properly extract hydroxy fatty acids. Centrifuge them at 700 g for 5 min at 4  C. Take the upper organic phase (yellow color) and transfer it into a storage vial, seal it, and store it at
20  C till HPLC analysis (see Note 10). Alternatively, 100 μL of the solution can be directly injected and analyzed by HPLC.

3.3 Quantification Hydroxy Fatty Acid by HPLC

1. Subject 100 μL of the hydroxy fatty acid solution to the HPLC system. Use an isocratic elution at a flow rate of 1.5 mL.min
1 with the mobile solvent phase (70/29.31/0.69 (v/v/v) hexane/diethyl ether/acetic acid). The running time is 30 min. 2. Detection of the HOTEs/HODEs is done by monitoring their UV absorption at 234 nm. Identification of the HOTE and HODE isomers is shown in Fig. 1a. 3. From the resulting chromatogram, calculate the content of HOTEs and HODEs from the peak area with an appropriate software using the value of the internal reference.

Brigitte Ksas and Michel Havaux

0,60 0,55 0,45

0,25 0,20 0,15 0,10 0,05

16-HOTE - 10,107

0,30

9-HODE - 9,714

0,35

13-HOTE - 8,162

0,40

13-HODE - 7,813

Absorbance at 234 nm

0,50

+11-HHTE

15-HEDE - 7,033

0,65

12-HOTE - 8,388

A

9-HOTE - 10,336

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0,00 -0,05 6,00

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12-HOTE - 15,600

0,35

13-HOTE - 15,150

0,40

13-HODE - 14,583

Absorbance at 234 nm

B

15-HEDE - 12,970

Time (min)

0,00 12,00

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Time (min) Fig. 1 (a) Typical HPLC chromatogram showing the HOTE peaks (9-, 12-, 13-, and 16-HOTE), the HODE peaks (9- and 13-HODE) and 15-HEDE peak (internal reference) with their retention times. The 16-HOTE peak is contaminated with 11-HHTE. This type of chromatogram allows the determination of ROS- and lipoxygenaserelated HOTEs. (b) A modification of the mobile solvent phase and the flow rate allows a better separation of 13-HOTE and 12-HOTE and a more accurate determination of 12-HOTE concentration. This type of chromatogram is useful when only ROS-induced lipid peroxidation has to be measured 3.4 Calculation of Enzymatic and Nonenzymatic Lipid Peroxidation

The method of calculation is based on Ref. [7]. In the chromatogram shown in Fig. 1a, 12-HOTE is the only pure indicator of ROS-induced lipid peroxidation. The peak of the other ROS-specific HOTE, 16-HOTE, is contamined by 11-HHTE (11-hydroxy hexadecatrienoic acid) [7]. 11-HHTE is an oxidation product of C16:3 which can be generated by lipoxygenase [13]. The ratio of the different HOTE isomers generated in planta by ROS attack on C18:3 (9-HOTE, 12-HOTE, 13-HOTE,

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16-HOTE) has been previously established [7]. This ratio was found to be fairly constant between different plant species. 1. Based on the published data, calculate ROS-induced 13-HOTE, 16-HOTE, and 9-HOTE from the measured 12-HOTE value as follows: [12-HOTE] ¼ [ ] measured by HPLC [13-HOTE] ¼ [12-HOTE]  1.68 [16-HOTE] ¼ [12-HOTE]  1.19 [9-HOTE] ¼ [12-HOTE]  1.34 The total concentration of ROS-induced HOTEs is the sum of these four values. 2. Knowing the concentration of 9-HOTE and 13-HOTE produced by ROS, lipoxygenase (LOX)-induced lipid peroxidation can then be estimated: [LOX-induced 9-HOTE] ¼ [9-HOTE] measured by HPLC
[ROS-induced 9-HOTE] calculated as explained in Subheading 3.4. [LOX-induced 13-HOTE] ¼ [13-HOTE] measured by HPLC
[ROS-induced 13-HOTE]. The total lipoxygenase-induced HOTE concentration is the sum of these two values. 3.5 A Variant of the Method

Separation of the 12-HOTE and 13-HOTE peaks is sometimes difficult with our HPLC method, particularly in control samples when lipid peroxidation is low. It is possible to improve substantially the separation of the two peaks by modifying the solvent composition and the flow rate. 1. Use a mobile solvent phase of hexane/diethylether/acetic acid (78/21/1, v/v/v). The flow rate is modified during the run as follows: mL.min
1 for 6 min, then reduced progressively the flow to 1.05 mL.min
1 from time 6 min to time 7 min, and maintain this flow for 10 min (until time 17 min).Then, change again the flow from 1.05 to 1.8 mL.min
1 for 4 min. This flow rate can be kept for 14 min. Total running time: 35 min. 2. The separation of 12-HOTE and 13-HOTE in the resulting chromatogram is improved, allowing a more accurate quantification of both compounds (see Fig. 1b). However, this is achieved with a very poor separation of the HOTE/HODE peaks with retention time above 9 min, hence precluding determination of 9-HOTE and 16-HOTE. So, when information on lipoxygenase-mediated lipid peroxidation is not

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required, this variant of the method can be used for accurate determination of 12-HOTE contents. The 12-HOTE values can directly serve as a specific index of ROS-induced lipid peroxidation or can be used in the calculations detailed in Subheading 3.4 for the ROS-related HOTEs.

4

Notes 1. The method was initially developed with Arabidopsis leaves (Arabidopsis thaliana), but it gives good results with many other species including tobacco (Nicotiana tabacum), tomato (Solanum lycopersicum), or Chlamydomonas reinhardtii. Leaf age does not affect the quality of the analyses. However, in some cases, such as rosemary extracts (Rosmarinus officinalis), we found that additional peaks can perturb quantification of the HOTE peaks. The problem can be overcome by using the alternative method described in Subheading 3.5 to estimate ROS-induced lipid peroxidation through the HOTE-12 content. 2. All solutions prepared for the extraction can be kept at 4  C for a few months. 3. This compound is available commercially from Cayman Chemical (Ann Arbor, USA, product reference: 37,700). 4. Be careful; do not let the samples to defreeze. 5. It is recommended to prepare a list of samples with their weight and the required amounts of extraction solution and citric acid to be added. 6. If pH drops below 4, hydroxy fatty acids will remain in the aqueous phase. Extraction of hydroxy fatty acids in the chloroform phase at step 7 will be compromised. 7. Do not add ethanol and NaOH at the same time. 8. This operation (saponification + evaporation of ethanol) should not last more than 30 min to avoid degradation of the compounds. The use of a N2 gas flux is required for a rapid evaporation of the solvent. 9. Please note that the presence of ethanol in the chromatographic analysis can be problematic. The use of ethanol is not appropriate with the Zorbax rx-SIL column and can alter the chromatogram. 10. The extract is stable and can be kept for months at
20  C.

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Acknowledgments We would like to acknowledge the input from our colleague, the late Christian Triantaphylides, who was very helpful in the optimization of the experimental method described in this article. References 1. Douce R, Joyard J (1980) Plant galactolipids. In: Stumpf PK (ed) The biochemistry of plants, vol 4. Academic, New York, pp 321–362 2. Me`ne-Saffrane´ L, Dubugnon L, Che´telat A et al (2009) Nonenzymatic oxidation of trienoic fatty acids contributes to reative oxygen species management in Arabidopsis. J Biol Chem 284:1702–1708 3. Li-Beisson Y., Shorrosh B, Beisson F et al. (2013) Acyl-lipid metabolism. The Arabidopsis Book 2013, p 11. https://doi.org/10.1199/ tab.0161 4. Stratton SP, Liebler DC (1997) Determination of singlet oxygen-specific versus readicalmefiated lipid peroxidation in photosensitized oxidation of lipid bilayers: effect of β-carotene and α-tocopherol. Biochemistry 36:12911– 12920 5. Triantaphylides C, Krischke M, Hoeberichts FA et al (2008) Singlet oxygen is the major reactive oxygen species involved in photooxidative damage to plants. Plant Physiol 148: 960–968 6. Andreou A, Feussner I (2009) Lipoxygenasesstructure and reaction mechanism. Phytochemistry 70:1504–1510 7. Montillet J-L, Cacas J-L, Garnier L et al (2004) The upstream oxylipin profile of Arabidopsis

thaliana: a tool to scan for oxidative stresses: lipid peroxidation in Arabidopsis. Plant J 40: 439–451 8. Farmer EE, Mueller MJ (2013) ROS-mediated lipid peroxidation and RES-activated signaling. Annu Rev Plant Biol 64:429–450 9. Janero DR (1990) Malondialdehyde and thiobarbituric acid-reactivity as diagnostic indices of lipid peroxidation and peroxidative tissue injury. Free Radic Biol Med 9:515–540 10. Birtic S, Ksas B, Genty B et al (2011) Using spontaneous photon emission to image lipid oxidation patterns in plant tissues. Plant J 67: 1103–1115 11. Shumbe L, Chevalier A, Legeret B et al (2016) Singlet oxygen-induced cell death in Arabidopsis under high-light stress is controlled by OXI1 kinase. Plant Physiol 170:1757–1771 12. Beaugelin I, Chevalier A, D’Alessandro S et al (2019) OXI1 and DAD regulate light-induced cell death antagonistically through jasmonate and salicylate levels. Plant Physiol 180:1691– 1708 13. Osipova EV, Lantsova NV, Chechetkin IR et al (2010) Hexadecanoid pathway in plants: Lipoxygenase dioxygenation of (7Z,10Z,13Z)-hexadecatrienoic acid. Biochem Mosc 75:708–716

Chapter 14 Detection of Lipid Peroxidation-Derived Free Azelaic Acid, a Biotic Stress Marker and Other Dicarboxylic Acids in Tobacco by Reversed-Phase HPLC-MS Under Non-derivatized Conditions Attila L. A´da´m, Gyo¨rgy Ka´tay, Andra´s Ku¨nstler, and Lo´ra´nt Kira´ly Abstract Azelaic acid (AzA, 1,9-nonadienoic acid) is a nine-carbon chain (C9) dicarboxylic acid with multiple and diverse functions in humans and plants. In plants this compound was suggested as a marker for lipid peroxidation under biotic and abiotic stress conditions and an inducer (priming agent) of plant immunity (acquired resistance). Detection methods for AzA in plants include a wide range of methodological approaches. This new and simple reversed-phase HPLC-MS protocol describes the measurement of AzA and other dicarboxylic acids either from tobacco leaf tissue or petiolar exudates (vascular sap) of plants under non-derivatized conditions. Key words Azelaic acid, Dicarboxylic acids, Lipid peroxidation, HPLC-MS, Tobacco, Tobacco mosaic virus (TMV), Biotic stress, Plant immunity

1

Introduction Azelaic acid (AzA, 1,9-nonadienoic acid) is a dicarboxylic acid with many diverse biological activities. In humans AzA has a pharmacological activity against cutaneous disorders [1] and different malignancies [2, 3]. In Arabidopsis thaliana AzA has been considered as a stress marker for lipid peroxidation [4] or an inducer of plant immunity [5–7]. Subsequent studies rather indicated that AzA plays no substantial role in the induction of local and systemic plant resistance mechanisms [8–11], but other products of lipid peroxidation, C18 α-ketocarboxylic acid and C9 aldehydes, have antibacterial and antifungal activity, respectively [8, 12]. However, direct genetic proof for a functional role of AzA in plant defense signaling is still missing [4]. As a new practical application, accumulation of AzA can serve as a pathogen infection biomarker in grapes and olive trees [13, 14].

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_14, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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In plants AzA is produced via two distinct pathways including (i) an enzymatic lipid fragmentation pathway described only in plants that involves lipoxygenase (9-LOX) and hydroperoxide lyase (9-HPL) activities [14] and (ii) a nonenzymatic, radicalcatalyzed oxidative fragmentation pathway (described originally in animals). One of the A. thaliana ecotypes, Columbia (Col-0), however, lacks 9-HPL genes, and the 13-HPL gene has been shown to be mutated and nonfunctional. Since Arabidopsis Col-0 produces fatty acid fragments such as AzA, another yet unknown fragmentation pathway must be operative [5]. More recent in vivo evidence supports this view. Analysis of Arabidopsis mutants defective in 9-lipoxygenases (LOX-1) and 13-lipoxygenase (LOX-2) has showed that chloroplastic galactolipid fragmentation is independent of enzymatic activity of LOXs. It seems that a free radicalcatalyzed galactolipid fragmentation mechanism (outlined in Fig. 1) is responsible for the formation of C7 pimelic acid (PiM, 1,7-pentadienoic acid) as well as of AzA under biotic stress (bacteria-induced hypersensitive response) conditions [4]. Detection methods for AzA measurement in plants cover a wide variety of methodological approaches including UV detection after HPLC separation [13] and GC-MS detection [9]. This HPLC-MS protocol describes the measurement of AzA and other related dicarboxylic acids, suberic acid (1,8-octadienoic acid), and sebacic acid (1,10-decadienoic acid) either from tobacco leaf tissue or petiolar exudates (vascular sap) of plants (see Fig. 2) under non-derivatized conditions [10]. Membrane bilayer bound PUFAs

C18:2, C18:3, C 16:2 and C16:3 fatty acids Radical-mediated oxidation

Lipid hydroperoxide / peroxide dimer formation

Spontaneous fragmentation of C7 and C9 carbon chains

Lipase

Other products:

Free azelaic acid (AzA)

- pimelic acid (PiM) - 7-oxoheptanoic acid (OHA) - 9-oxononanoic acid (ONA)

Fig. 1 Oxidative radical-mediated fragmentation of plant membrane glycerolipid fatty acids and production of azelaic acid and other products (modified after Zoeller et al. [4]). PUFA, polyunsaturated fatty acids (see Note 5)

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Fig. 2 HPLC-MS analysis of suberic acid (SuB), azelaic acid (AzA), and sebacic acid (SeB). (a–c) typical chromatograms of standard compounds of SuB (a, m/z ¼ 173), AzA (b, m/z ¼ 187), and SeB (c, m/z ¼ 201). (d) (AzA), (e) (SuB), and (f) (SeB) depict analysis of dicarboxylic acids in petiolar exudates of control and virus-infected (Tobacco mosaic virus, TMV) leaves (samples taken between 72 and 96 h after inoculation). For quantification of AzA, a linear range calibration curve (100–300 ng mL1; y ¼ 5647.85 + 9482.28 , R2 ¼ 0.9939) was established. Values of limit of detection, LOD ¼ 18 pg, and limit of quantitation, LOQ ¼ 90 pg, were also determined (this figure was modified after Nagy et al. [10])

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Materials For the preparation of solutions, ultrapure UV-sterilized Millipore quality water was used.

2.1 Materials for Preparation of Leaf Tissue Samples

1. Water purification system. 2. Evaporator with metal sample container thermostat and nitrogen flow. 3. High-pressure nitrogen container with pressure regulator. 4. Automatic balance. 5. Liquid nitrogen. 6. Cork borer (approximately 1 cm in diameter). 7. Organic extraction solution; absolute methanol (MeOH, HPLC-MS grade). 8. Pestle and mortar (5 cm in diameter). 9. 2 mL volume Eppendorf tubes (conical version, see Notes 1 and 2). 10. Table centrifuge for Eppendorf tubes (cooling is necessary). 11. Petroleum ether (40–65  C, analytical reagent). 12. 10 mL volume separating funnel. 13. 200 μL and 1000 μL volume automatic pipettes. 14. Ultralow-temperature freezer for sample storage.

2.2 Materials for Preparation of Petiolar Exudates

1. Water purification system. 2. Evaporator with metal sample container thermostat and nitrogen flow. 3. High-pressure nitrogen container with pressure regulator. 4. 200 mL Erlenmeyer flask. 5. Plastic sterile petri dishes. 6. Autoclave or pressure cooker. 7. Scalpel (stainless steel surgical blade). 8. Plastic box with a tight lid. 9. Tap water. 10. Sterile ultrapure water. 11. 100 mL of 0.1 M potassium hydroxide solution. 12. 200 mL of 1 mM K2-EDTA solution in water. Add 80.89 mg of K2-EDTA. 2H2O (EDTA dipotassium salt dihydrate, MW: 404.45 g mol1) to 50 mL of water. After solubilization fill it up to 200 mL volume, and sterilize in an autoclave or pressure cooker. Set the pH of the solution to 7.5 at RT with 0.1 M

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potassium hydroxide solution. (Prepare before use or keep in a refrigerator not longer than a few days.) 13. 2 mL volume Eppendorf tubes (conical version, see Notes 1 and 2). 14. Petroleum ether (40–65  C, analytical reagent). 15. 10 mL volume separating funnel. 2.3 Reversed-Phase HPLC-MS Analysis

1. HPLC-MS analytical system: composed of the liquid-delivery unit, the autosampler, the column thermostat, the photodiode array detector, and the single quadrupole mass spectrometer equipped with an electrospray ionization (ESI) sample pulverization unit. 2. Stationary phase for separation of components of samples: Hypersil C18 (reversed phase) packed column (200 mm  4.6 mm, 5 μm particles) protected by means of a guard cartridge (10 mm  4 mm, 5 μm particles). 3. Water purification system for obtaining ultrapure water. 4. Magnetic stirrer. 5. 200 mL Erlenmeyer flasks, 100 mL graduated cylinder, 500 mL beaker. 6. 10–100 μL and 100–1000 μL micropipettes. 7. 2 mL volume Eppendorf tubes. 8. 1 mL syringe and disposable syringe filters, 0.45 μm. 9. Ultrapure water. 10. HPLC-MS grade acetonitrile (ACN) for preparation of the mobile phase. 11. HPLC-MS grade formic acid for preparation of the mobile phase. 12. For qualitative analysis of plant samples, a methanolic mixture of 730 ng/mL AzA, 100 ng/mL sebacic acid (SeB, 1,10decadienoic acid), and 1100 ng/mL suberic acid (SuB, 1,8-octadienoic acid).

3

Methods Methods for preparation of samples from leaf tissue and petiolar exudates (vascular sap) of tobacco plants are described separately.

3.1

Leaf Tissue

1. Take leaf sample (about 150–200 mg) with cork borer (about four 1 cm diameter disks), and measure exactly the weight. 2. Freeze samples in liquid nitrogen, and store in an ultralowtemperature freezer until further usage.

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3. Homogenize each sample in liquid nitrogen with a mortar and pestle, and then add 0.9 mL of MeOH, and homogenize the sample again. Transfer the liquid into a 2 mL Eppendorf tube. Wash the mortar and pestle with 0.2 mL MeOH and add to the former tube. 4. Incubate for 10 min at RT with vortexing three times (for 10 s each case). 5. Centrifuge at 15,000  g for 12 min at 4  C. 6. Remove supernatant with a 200 μL micropipette into a new tube. 7. Re-extract the former residue with 0.5 mL MeOH by vortexing briefly. 8. Centrifuge as in step 5. 9. Pool supernatants. 10. Extract samples in a separation funnel three times with equal volumes of petroleum ether, combine ether phases, evaporate the ether phase to dryness at RT under nitrogen flow, and redissolve in 150 μL MeOH (see Note 3). 11. Freeze samples in liquid nitrogen until further usage. 3.2

Petiolar Exudates

1. 3–4 uppermost leaves from tobacco (with 5–6 fully expanded leaves), or more in case of plants with smaller leaves, are removed with a scalpel from the stem. In order of the subsequent manipulations, petioles should be kept at their maximum lengths. 2. Wash carefully both sides of the leaf blade and especially the petioles in tap water. 3. Repeat twice the washing in sterile Millipore water. 4. Apply 1 mM EDTA solution to a petri dish (at least 1.0 cm deep, to be able to cover fully the leaf petioles). 5. Insert only the leaf petioles one by one into the EDTA solution, and under the EDTA solution, cut the edge (about a 2-mm-long section and in about a 45 angle) of the petiole to get a new larger surface. A longer section would decrease the petiolar length. 6. Transfer leaves (at least 4 leaves per treatment) quickly into 2 mL Eppendorf tubes (maximum two leaves per tube) filled with approximately 1 mL of a sterile 1 mM EDTA solution. Finally, depending on the size of the petioles, fill the tubes up with EDTA solution (see Note 4). 7. Keep the leaves in tubes with EDTA solution at RT for 1 h to take up EDTA (see Note 4).

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8. Wash quickly the petioles with sterile ultrapure water, and transfer leaves into new tubes filled with ultrapure water. 9. Transfer tubes into a container and place the container into a plastic box for 1-day incubation. To limit transpiration, cover the box with a lid and store in darkness. If necessary, fill the tubes repeatedly with ultrapure water during the incubation period. Check it first after 2 h of incubation. 10. After 24 h of incubation, remove the leaves from the tubes. 11. To concentrate samples before HPLC-MS analysis, waterphase exudates were extracted in a separating funnel three times with equal volumes of petroleum ether, and the combined ether phase was evaporated to dryness at RT under nitrogen flow and finally redissolved in 65 μL of MeOH (see Note 3). 12. Apply samples to HPLC-MS. 3.3 HPLC-MS Analysis

1. Preparation of mobile-phase necessary for gradient elution of sample components: eluent A (98% ultrapure water, 1.9% (v/v) ACN, and 0.1% (v/v) formic acid): mix 490 mL of water and 9.5 mL of ACN in a 500 mL beaker by using graduated cylinders. Add to the liquid mixture 500 μL formic acid. Use the magnetic stirrer for 5 min to homogenize the mixture. Pour eluent A into the corresponding HPLC reservoir. 2. Eluent B (99.9% (v/v) ACN and 0.1% (v/v) formic acid): add 499.5 mL ACN in a 500 mL beaker by using a graduated cylinder. Add to the ACN 500 μL formic acid and homogenize the mixture as before. Pour eluent B into the corresponding HPLC reservoir. The degassing unit of the system ensures the elimination of gas bubbles from eluents during the analysis procedure. 3. Develop the appropriate gradient solvent program for your own HPLC-MS system able for separation of sample components. Table 1 contains the gradient elution profile utilized for determination of AzA, SeB, and SuB by using our analytical HPLC-MS system. 4. Select for ESI-MS measurement of AzA, SeB, and SuB the negative ionization mode (3.5 KV) and m/z values as follows: 178, 201, and 173, respectively. Other recommended conditions: drying gas (N2) flow 15 L min1, nebulizing gas (N2) flow 12 L min1, and the ion source temperature 350  C. For qualitative analysis, the typical chromatograms of chemical standards of SuB (A), AzA (B), and SeB (C) and plant petiolar exudates of control (mock-inoculated) and virus-infected leaves (D, AzA; E, SuB and F, SeB) are depicted in Fig. 2 (see Notes 5, 6 and 7).

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Table 1 Gradient elution scheme for the HPLC-MS analysis method of AzA, SeB, and SuB Column temperature ( C)

Flow rate (mL/min)

0

25

0.8

40

60

25

0.8

16.0

0

100

25

0.8

17.0

0

100

25

0.8

17.2

100

0

25

0.8

24.0

100

0

25

0.8

Time (min)

A (%, v/v)

0.0

100

15.0

B (%, v/v)

A: 0.1% (v/v) formic acid and 1.9% (v/v) acetonitrile (ACN) in ultrapure water; B: 0.1% (v/v) formic acid in ACN

5. For qualitative analysis, prepare four standard samples containing different quantities of AzA, SeB, and SuB usable for construction of calibration curves. The concentration ranges were as follows: AzA, 65–300 ng/mL; SeB, 50–200 ng/mL; and SuB, 500–2150 ng/mL, respectively (see Note 8).

4

Notes 1. Application of conical tubes makes easier the removal of supernatant. 2. The usage of 2 mL tubes can easily accommodate the total sample volume. 3. Evaporation of petroleum ether-containing samples under nitrogen flow does not require heating of samples. This process takes only several minutes. Heating above 35  C can result in the loss of dicarboxylic acids. 4. Incubation of leaves in EDTA solution is an important step to limit callose deposition in the vascular tissue. Callose deposition may block the exudate flow from the petioles. Usually 1 mM EDTA is used [9, 10], but higher concentrations and/or longer exposition times were reported to induce gene expression changes [15]. 5. The HPLC-MS system is suitable for the separation and detection of other dicarboxylic acid products of lipid peroxidation, such as adipic acid (AdA, 1,6-hexadienoic acid), PiM, and a precursor of AzA, 9-oxo-nonanoic acid (ONA). 6. In order to focus the generated molecular ions, an electric lens system is used where potential values have to be selected. The software will establish these values for each component separately.

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7. The negative and positive ionization mode should be selected separately for each molecule of interest. The sensitivity of the method could be improved considerably by choosing the correct ionization mode. 8. In healthy tobacco around 100 ng g1 FW amounts of AzA were detected and double amounts in virus-infected plants. However, in Arabidopsis, wide ranges of AzA concentrations were reported. For example, Zoeller et al. [4] found similar amounts of AzA as in our case in tobacco (around 20 ngg1 FW and 180 ngg1 FW, in healthy and infected plants, respectively, recalculated from [4]). Wang et al. [16] reported much higher concentrations of AzA (around 1500 ngg1 FW and 6000 ng.g1 FW) [16]. The differences in AzA amounts could be related to different extraction procedures and/or detection methods.

Acknowledgments The authors wish to thank the Hungarian National Research, ´ , K112146; Development and Innovation Office for funding (ALA LK, K111995 and K128868; AK, FK131401). References 1. Schulte BC, Wu W, Rosen T (2015) Azelaic acid: evidence-based update on mechanism of action and clinical application. J Drugs Dermatol 14(9):964–968 2. Micheletti G, Calonghi N, Farruggia G, Strocchi E, Palmacci V, Telese D, Bordoni S, Frisco G, Boga C (2020) Synthesis of novel structural hybrids between Aza-heterocycles and azelaic acid moiety with a specific activity on osteosarcoma cells. Molecules 25(2):E404. h t t p s : // d o i . o r g / 1 0 . 3 3 9 0 / molecules25020404 3. Dongdong Z, Jin Y, Yang T, Yang Q, Wu B, Chen Y, Luo Z, Liang L, Liu Y, Xu A, Tong X, Can C, Ding L, Tu H, Tan Y, Jiang H, Liu X, Shen H, Liu L, Pan Y, Wei Y, Zhou F (2019) Antiproliferative and immunoregulatory effects of azelaic acid against acute myeloid leukemia via the activation of Notch signaling pathway. Front Pharmacol 10:1396. https:// doi.org/10.3389/fphar.2019.01396 4. Zoeller M, Stingl N, Krischke M, Fekete A, Waller F, Berger S, Mueller MJ (2012) Lipid profiling of the Arabidopsis hypersensitive response reveals specific lipid peroxidation and fragmentation processes: biogenesis of pimelic and azelaic acid. Plant Physiol 160:

365–378 https://doi.org/10.1104/pp.112. 202846 5. Jung HW, Tschaplinski TJ, Wang L, Glazebrook J, Greenberg JT (2009) Priming in systemic plant immunity. Science 324: 89–91 https://doi.org/10.1126/science. 1170025 6. Yu K, Soares JM, Mandal MK, Wang C, Chanda B, Gifford AN, Fowler JS, Navarre D, Kachroo A, Kachroo P (2013) A feedback regulatory loop between G3P and lipid transfer proteins DIR1 and AZI1 mediates azelaic acid-induced systemic immunity. Cell Rep 3: 1266–1276 https://doi.org/10.1016/j.cel rep.2013.03.030 7. Wittek F, Hoffmann T, Kanawati B, Bichlmeier M, Knappe C, Wenig M, SchmittKopplin P, Parker JE, Schwab W, Vlot AC (2014) Arabidopsis ENHANCED DISEASE SUSCEPTIBILITY1 promotes systemic acquired resistance via azelaic acid and its precursor 9-oxo nonanoic acid. J Exp Bot 65: 5919–5931 https://doi.org/10.1093/jxb/ eru331 8. Vicente J, Casco´n T, Vicedo B, Garcı´aAgustı´n P, Hamberg M, Castresana C (2012) Role of 9-lipoxygenase and α-dioxygenase

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oxylipin pathways as modulators of local and systemic defense. Mol Plant 5: 914–928 https://doi.org/10.1093/mp/ ssr105 9. Na´varova´ H, Bernsdorff F, Do¨ring A-C, Zeier J (2012) Pipecolic acid, an endogenous mediator of defense amplification and priming, is a critical regulator of inducible plant immunity. Plant Cell 24:5123–5141 https://doi.org/10. 1105/tpc.112.103564 ´ , Ka´tay G, Gullner G, Kira´ly L, A ´ da´m 10. Nagy ZA AL (2017) Azelaic acid accumulates in phloem exudates of TMV-infected tobacco leaves, but its application does not induce local or systemic resistance against selected viral and bacterial pathogens. Acta Physiol Plant 39:9. https:// doi.org/10.1007/s11738-016-2303-7 ´ da´m AL, Nagy ZA ´ , Ka´tay G, Mergenthaler E, 11. A Viczia´n O (2018) Signals of systemic immunity in plants: progress and open questions. Int J Mol Sci 19(4):1146. https://doi.org/10. 3390/ijms19041146 12. Matsui K, Minami A, Hornung E, Shibata H, Kishimoto K, Ahnert V, Kindl H, Kajiwara T, Feussner I (2006) Biosynthesis of fatty acid derived aldehydes is induced upon mechanical wounding and its products show fungicidal

activities in cucumber. Phytochemistry 67: 6 49– 657 https://do i.org/10 .101 6/j. phytochem.2006.01.006 13. Bra´s EJS, Fortes AM, Chu V, Fernandes P, Conde JP (2019) Microfluidic device for the point of need detection of a pathogen infection biomarker in grapes. Analyst 144:4871–4879. https://doi.org/10.1039/c9an01002e 14. Nicolı` F, Negro C, Nutricati E, Vergine M, Aprile A, Sabella E, Damiano G, De Bellis L, Luvisi A (2019) Accumulation of azelaic acid in Xylella fastidiosa-infected olive trees: a mobile metabolite for health screening. Phytopathology 109:318–325. https://doi.org/10.1094/ PHYTO-07-18-0236-FI 15. Guelette BS, Benning UF, Hoffmann-Benning S (2012) Identification of lipids and lipidbinding proteins in phloem exudates from Arabidopsis thaliana. J Exp Bot 63: 3603–3613 https://doi.org/10.1093/jxb/ ers028 16. Wang C, Liu R, Lim G-H, Lorenzo L, Yu K, Zhang K, Hunt AG, Kachroo A, Kachroo P (2018) Pipecolic acid confers systemic immunity by regulating free radicals. Sci Adv 4: eaar4509. https://doi.org/10.1126/sciadv. aar4509

Chapter 15 Determination of Reactive Carbonyl Species, Which Mediate Reactive Oxygen Species Signals in Plant Cells Jun’ichi Mano, Md. Sanaullah Biswas, Koichi Sugimoto, and Yoshiyuki Murata Abstract Responses of plant cells to reactive oxygen species (ROS), e.g., reprogramming of defense genes or progression of cell death, should include the ROS signal transmission to target proteins, but the biochemistry of this process is largely unknown. Lipid peroxide-derived α,β-unsaturated aldehydes and ketones (reactive carbonyl species; RCS), downstream products of ROS stimuli, are recently emerging endogenous agents that can mediate ROS signal to proteins via covalent modification. The involvement of RCS in certain ROS signaling in plants (oxidative injury of leaves and roots, ROS-induced programmed cell death, senescence, and abscisic acid and auxin signaling) has been verified by the determination of RCS with the use of conventional HPLC. Because distinct kinds of RCS act differently in the cell and so are metabolized, identification and quantification of each RCS in plant tissues provide central information to decipher biochemical mechanisms of plant responses to ROS. This article illustrates practical methods of plant sample preparation and extraction and analysis of RCS. Key words Abscisic acid, Acrolein, Auxin, 4-Hydroxy-2-nonenal, Lipid peroxidation, Oxidative stress, Programmed cell death, Reactive electrophiles

1

Introduction

1.1 Reactive Carbonyl Species (RCS) Mediate ROS Signaling

Reactive oxygen species (ROS) are ubiquitously formed in plant cells and play critical roles to determine cell fate in various physiological situations. Specifically, ROS act not only as injuring molecules under environmental stress conditions but also as a signal for cell responses such as stomata closure and those for reprogramming cells in response to stressors, infection, and hormonal stimuli [1]. There is keen interest in the biochemical processes of ROS signal transmission in plants, but direct reactions of ROS with putative sensor/receptor proteins have been poorly elucidated. Reactive carbonyl species (RCS), a group of organic compounds derived from lipid peroxides, are emerging as bioactive compounds that can mediate ROS signal to target proteins [2–4]. RCS

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_15, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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Lipid peroxides (LOOH)

ROS

O OH

Fe+2 H

Fenton-type reductive fission

H

Fe+3 O•

R1

alcoxyl radical

R2

Decomposition to carbonyl radicals Reduction by neighboring molecules

various carbonyls

R

a,b-unsaturated carbonyls = reactive carbonyl species (RCS)

formaldehyde

O

acetaldehyde acetone (Z)-3-hexenal etc.

O

O

O

O

OH

OH

acrolein

n-hexanal

=

4-hydroxy-2-nonenal

O

O

malondialdehyde

4-hydroxy-2-hexenal O (E)-2-pentenal O

O

O

4-oxo-2-nonenal O

4-oxo-2-hexenal

O

O

(E)-2-hexenal

methyl vinyl ketone

crotonaldehyde

Fig. 1 Production of RCS from lipids. (Poly)unsaturated fatty acid moiety of a lipid molecule is oxidized by ROS and forms a lipid peroxide, which is subject to a Fenton-type reductive fission to from an alkoxyl radical. Then the radical further decomposes to carbonyl radicals, which abstract electrons from neighboring organic molecules (e.g., lipids in the membrane) to be carbonyls of various structure. RCS comprises the α,β-unsaturated aldehydes and ketones of various carbon chain length

designates the α,β-unsaturated aldehydes and ketones produced from lipid peroxides [2, 3, 5], typically represented by acrolein, 4-hydroxy-(E)-2-nonenal, and malondialdehyde (see Fig. 1). They are also called as “oxylipin reactive electrophile species” [4]. Because of the conjugated double bonds, the β carbon in a RCS molecule has strong electrophilicity and readily forms a Michaeltype adduct with nucleophilic residues such as Cys, Lys, and His on proteins and guanine base in nucleic acids, leading to the alteration of protein functions and mutation [6]. In this way, RCS function as endogenous agents that transmit ROS information to target proteins. Specifically, RCS are messengers downstream of ROS (see Fig. 2). 1.2 Comprehensive Analysis of Carbonyls Providing Key Information to the RCS Functions

The involvement of RCS in ROS-triggered damage or signaling in plants has been demonstrated for various stress/physiological situations (see Table 1), e.g., light stress and ROS stress in leaves [7, 8], aluminum-induced root injury [9], heat-induced leaf injury [10], H2O2- or salt-induced programmed cell death [11, 12], senescence of siliques [13], stomata closure induced by abscisic acid [14] or jasmonic acid [15], and lateral root formation by auxin [16]. The RCS involvement in these cases has been verified on the following

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O2 photosynthesis respiration

photorespiration

NOX (RBOH)

ROS production

Membrane lipids

RCS production

RCS scavenging system

ROS scavenging system

Oxidation of target protein

Modification of target protein

Responses of the cell

Fig. 2 RCS are downstream products of ROS and mediate ROS signal to proteins, in distinct ways from ROS, and evoke corresponding responses of the cell. The RCS levels in each cell and each compartment are strictly regulated by the RCS scavenging system, as are the ROS levels

three experimental criteria. (1) A stimulus that evokes an increase in the tissue ROS level should lead to the enhancement of RCS levels. (2) Suppression of the increase of RCS by scavenging enzymes or chemicals should diminish the ROS-induced response. (3) Addition of RCS to plants should evoke responses similar to those induced by ROS. In these studies, the HPLC-based analysis of carbonyls was employed to verify the correlation of the RCS levels with the cellular responses. Specifically, the carbonyl analysis is critical for testing the first two criteria. In this chapter, we will illustrate a HPLC-based method to determine carbonyls in plant materials. This method has been essential for the validation of the RCS involvement in various physiological aspects as described above. In addition, because a HPLC analysis produces a comprehensive data covering various carbonyl species, it is possible to deduce which carbonyl species correlate with the plant response of your interest. This knowledge is a key to the understanding of biochemical mechanisms of ROS/ RCS signaling. The analytical part of this article is based on our previous articles [16, 17]. We here provide practical details of the preparation of plant samples and extraction of carbonyls from them. In the present protocol, carbonyls are derivatized with 2,4dinitrophenylhydrazine (DNPH) to hydrazone derivatives

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Table 1 Physiological observations where the involvement of RCS has been demonstrated Plant species, tissue

Condition

Carbonyl speciesa

Reference

Nicotiana tabacum, leaf

Strong light stress

Acrolein, (E)-2-pentenal

[7]

A. thaliana, leaf

Methyl viologen + light

Acrolein

[8]

N. tabacum, root Aluminum stress

Acrolein, HNE, HHE, MDA, formaldehyde [9]

Cyclamen persicum, leaf

Heat stress

(E)-2-hexenal, acrolein, methyl vinyl ketone [10]

N. tabacum, cultured cells

H2O2-induced PCD

Acrolein, HNE, MDA, propionaldehyde

[11, 12]

A. thaliana, silique

Senescence

Acrolein, HNE

[13]

N. tabacum, leaf epidermis

ABA-induced stomata closure

Acrolein, HNE, HHE, (E)-2-pentenal, (E)- [14] 2-heptenal

MeJA-induced stomata closure

Acrolein, HNE, HHE, (E)-2-heptenal

[15]

Acrolein, crotonaldehyde, HNE, propionaldehyde, butyraldehyde

[16]

A. thaliana, root Auxin-induced lateral root formation a

Representative carbonyls whose levels were correlated with the extent of the damage or response

immediately after extraction from plant tissues. This is important to minimize unwanted loss of carbonyls in the extract; reactive compounds such as RCS are intrinsically unstable, and it is highly possible that their concentrations in the extract are changed as time advances. This derivatization has another benefit; carbonyls are converted to a form that has a strong absorbance in a 310–380 nm range, which is a specific color of DNP derivatives and allows sensitive detection with a conventional UV detector in the HPLC analysis [18]. We employ an internal standard and an empirically determined “conversion factor” for calculating the content of each carbonyl species in the tissue from the HPLC data [16, 17]. The table of the conversion factors is also updated.

2

Materials

2.1 Plant Growth and Treatment

1. Tobacco (Nicotiana tabacum) Bright Yellow-2 (BY-2) cultured cells. 2. Murashige and Skoog medium supplemented with 0.3% (w/v) sucrose, myo-inositol (100 mg L
1), KH2PO4 (200 mg L
1),

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thiamine HCl (0.5 mg L
1), and 2,4-dichlorophenoxyacetic acid (0.2 mg L
1), pH 5.6. 3. Arabidopsis thaliana seeds. 4. Tobacco seeds. 5. 1 mM H2O2. 6. 5 mM KCl. 7. 50 μM CaCl2. 8. 10 mM MES-Tris, pH 6.15. 9. 10 mM abscisic acid (ABA) in ethanol. 10. 10 mM methyl-jasmonate (Me-JA) in ethanol. 11. 1 mM auxin dissolved in 1 M NaOH. 2.2 Preparation of DNP-Carbonyl Standards

DNP-carbonyls are identified on the retention time, and hence it is necessary to have standard DNP-carbonyls. Some DNP-derivatized aldehydes are commercially available. Commercially unavailable DNP derivatives are synthesized as in Subheading 3.1. 1. DNPH. Commercial DNPH contains ca. 50% water for safety (DNPH may explode when it is dried up). 2. Carbonyl compounds of your interest. Some kinds of carbonyl are available in an acetal form, which is more stable and hence convenient for long storage. Malondialdehyde is available only as its acetal form, such as 1,1,3,3-tetraethoxypropane. To prepare the DNP-carbonyl from the acetal, you need to hydrolyze it first and then mix with DNPH. 3. Formic acid.

2.3 Extraction and Derivatization of Carbonyls

1. Acetonitrile, HPLC grade. 2. 2-Ethylhexanal as an internal standard for HPLC. A stock solution (0.5 mM in acetonitrile, HPLC grade) can be stored at
20  C for a month. 3. Butylated hydroxytoluene (BHT; 2,6-di-t-butyl-4-methylphenol) as antioxidant. 4. Recrystallized DNPH. Since commercial DNPH is usually contaminated with spontaneously formed hydrazone, it is necessary to use recrystallized DNPH preparation for the derivatization of carbonyls extracted from plant tissues. The recrystallization procedure is described in Subheading 3.1. 5. Formic acid, HPLC grade. 6. Saturated NaCl solution. 7. NaHCO3. 8. Deionized, purified water (equivalent to Milli-Q water).

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9. Glass tube with a screw cap. 10. Glass centrifuge tube with a screw cap. 11. Pretreatment cartridge with C18 sorbent (sorbent mass 200 mg). 2.4

HPLC Analysis

1. Wakosil DNPH-II column (4.6  150 mm) (e.g., Fujifilm Wako Pure Chemical Industries, Ltd., Osaka, Japan) (see Note 1). 2. A common HPLC system with a UV detector and a data analysis software. 3. HPLC mobile phases, for example, mobile phase A, Wakosil DNPH-II eluent A (Fujifilm Wako Pure Chemical, Osaka, Japan); mobile phase B, Wakosil DNPH-II eluent B (Fujifilm Wako Pure Chemical); and mobile phase C, acetonitrile. Mobile phase C is used just to facilitate the elution of highly hydrophobic compounds, and hence it can be replaced by B, although a longer time is required for chromatography.

3

Methods

3.1 Recrystallization of DNPH

1. Put acetonitrile (50 mL) in a 100–200 mL flask. 2. Heat the flask at 60  C, and add a spoonful of DNPH. When DNPH are totally dissolved, add another spoon until the solution is saturated, where DNPH solid remains on the bottom. 3. Filtrate the solution while it is warm with a filter paper, and collect clear saturated DNPH solution. 4. Leave the solution still at room temperature. DNPH will be crystallized in several hours (maybe overnight). 5. Filtrate with a glass filter, and wash the crystals once with a small amount of cold acetonitrile (
20  C chilled). 6. Keep the crystals in a brown glass vessel with a small amount of acetonitrile. 7. Dissolve the DNPH crystals in acetonitrile, and adjust the concentration to 20 mM, using an absorption coefficient 14,791 M
1 cm
1 at 350 nm.

3.2 Preparation of Plant Materials

1. Grow tobacco Bright Yellow-2 (BY-2) cell suspensions (L. cv. Bright Yellow) in a 200 mL conical flask containing 50 mL of Murashige and Skoog medium supplemented with 0.3% (w/v) sucrose, myo-inositol (100 mg L
1), KH2PO4 (200 mg L
1), thiamine HCl (0.5 mg L
1), and 2,4-dichlorophenoxyacetic acid (0.2 mg L
1), pH 5.6. Grow the cells in darkness at 25  C with continuous rotation at 120 rpm. Every 7 days, refresh the

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cells by transferring 50 mg of cells to a 50 mL fresh solution. Four-day culture cells were used for PCD treatment. 2. Sterilize the seeds of Arabidopsis thaliana or tobacco on their surface, and spread them on the sterilized nylon membrane that is put on a nutrient agar plate containing 1/2 strength of Murashige and Skoog medium and 1.5% (w/v) sucrose. Seeds can be put densely on the nylon membrane for preparing large number of plants. 3. Grow tobacco and Arabidopsis plants for leaf tissue sampling. Tobacco plants are grown on soil containing 70% (v/v) vermiculite and 30% (v/v) commercial nursery soil in a growth chamber at 21  2  C and 60% relative humidity in a 16-h light/8h dark photoperiod at 80 μmol m
1 s
1 photon flux density with white fluorescent lamps. Apply a commercial nutrient solution (e.g., 0.1% Hyponex; Hyponex, Osaka, Japan) 2–3 times a week. A. thaliana plants are grown on soil at 23  C in a 12-h light/12-h dark photoperiod at 50 μmol m
1 s
1. 3.3 Treatment of Tobacco BY-2 Cells with H2O2

1. Add H2O2 to the flask of a 4-day culture, to 1 mM (concentration in the culture medium), and then return the flask in the incubator with continuous shaking (120 rpm). 2. After a 10-min incubation, collect the cells by filtering on a nylon mesh, and wash them with distilled water. 3. Weigh the fresh cells (ca. 400 mg for one analysis), and record the weight precisely (see Note 2).

3.4 Treatment of Tobacco Leaf Epidermis with ABA and MeJA

1. Prepare a stomatal bioassay buffer solution containing 5 mM KCl, 50 μM CaCl2, and 10 mM MES-Tris, pH 6.15. 2. Excise leaves of 5- to 7-week-old tobacco plants, and blend in 250 mL distilled water for 25 s, which is long enough to disrupt almost all mesophyll cells. The non-green pieces of epidermal tissue should be observed floating on the homogenate. 3. Collect the materials by filtration through a nylon filter (60 μm mesh size), and disperse them on the bioassay solution for 2 h in the light, and then add ABA or MeJA to the solution.

3.5 Treatment of Arabidopsis and Tobacco Roots with Auxin and H2O2

1. Transfer the seedlings on the fifth day after seeding to a fresh agar medium in a square plastic plate (10  10 cm), ca. 50 seedlings per plate in two rows. For treatments with auxin and H2O2, the reagents should be contained in the agar medium. 2. Cut roots with scissors at the base and at 2 mm from the root tip, after growth for 5 days (A. thaliana) or 7 days (tobacco). 3. Use a toothpick to collect the cut roots from two petri plates (100–120 plants).

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4. Rinse the collected roots with sterile water, remove surface moisture on a paper towel, and weigh them precisely, as soon as possible. A fresh weight of ca. 50 mg is expected, which is the minimal amount for one analysis. 3.6 Extraction and DNP-Derivatization of Carbonyls in Plant Tissues

1. Transfer the stress-treated tissue (or cells) to extraction medium immediately after their weight is determined, or freeze the weighed samples immediately with liquid nitrogen, and store them at
80  C. If a sample tissue after stress treatment is left in non-frozen state, carbonyls might be metabolized and their contents changed. For quick handling of samples, extraction medium should be prepared before starting stress treatment of the samples. The following protocol is for the amount of ca. 500 mg fresh tissue (see Note 3). 2. Prepare glass tubes with a screw cap (50 mL size) as many as the samples. Put 5 mL of extraction solution (acetonitrile containing 5 μM 2-ethylhexanal and 0.005% (w/v) BHT) in each tube. 3. Immerse plant tissue in the extraction solution (ca. 500 mg fresh weight, the precise weight has to be recorded). If the tissue sample is thin enough such as leaves and roots of tobacco or Arabidopsis, or cell suspensions, you do not need to homogenize it. When necessary, homogenize the tissue in the extraction solution. Tighten the cap, and incubate the sample in a water bath at 60  C for 30 min. 4. Collect the extract by decantation into a glass centrifuge tube with a screw cap (50 mL size), and add 20 mM DNPH solution (125 μL; final concentration of 0.5 mM) and formic acid (96 μL; final concentration of 0.5 M). Tighten the cap, mix well, and incubate the mixture at 25  C for 60 min. 5. Add 5 ml of saturated NaCl solution and 0.9 g NaHCO3 for neutralizing formic acid. Formation of small bubbles will cease when neutralization is accomplished. Shake at intervals and confirm the neutralization. The mixture is separated into two layers. The upper acetonitrile layer contains DNP derivatives of carbonyls. 6. After centrifugation to facilitate phase separation, collect the upper layer into a glass tube, and dry it up using a vacuum dryer. Dried samples can be kept overnight in a freezer. 7. Add 250 μL acetonitrile, and vortex and collect the solution. This sample solution contains chlorophylls and other pigments that may disturb the detection of DNP derivatives of carbonyls. The contaminants are removed by the following way. 8. Wash a pretreatment C18 cartridge (sorbent mass 200 mg) with 2 mL acetonitrile.

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Table 2 Chromatography conditions 1 ml min
1

Flow rate Gradient program (70 min per run) 0–5 min

100% A

5–20 min

Linear gradient from 100% A to 100% B

20–25 min

100% B

25–45 min

Linear gradient from 100% B to 100% C

45–55 min

100% C

55–60 min

Linear gradient from 100% C to 100% A

60–70 min

100% A

9. Load the sample solution on the cartridge and collect the passthrough. Apply additional acetonitrile (ca. 300 μL) to elute all yellowish fraction, and combine the eluted solution with the pass-through. Store this solution at
20  C in a tightly capped vial until HPLC analysis. Avoid drying up the solution (see Note 4). 3.7 HPLC Analysis and Data Processing

1. Subject the solution to the reverse phase HPLC system. The DNP-carbonyls are separated with the solvent program shown in Table 2. 2. Record a chromatogram at 340 nm (see Note 5). 3. In a chromatogram, extract the peak area of a DNP-carbonyl using an appropriate software. The DNP-carbonyl peaks to be determined are very small compared with the peak of free DNPH eluted around 4 min (see Fig. 3). Because some chromatography analysis software set the full scale of Y-axis of the chromatogram automatically based on the largest peak, you may not see any peaks at a first glance. Expand the Y-scale by 100 or more, until DNP-IS and other DNP-carbonyls appear as peaks. Typical chromatograms are shown in Fig. 3. 4. Correct the carbonyl peak area for the internal standard. 5. Multiply the quote by the carbonyl-specific conversion factor k (see Table 3). This factor is an empirically determined parameter that is a composite of the efficiencies of derivatization of the carbonyl and extinction coefficient of the DNP derivative [16, 17]. The determination of the HNE content in tobacco BY-2 cells is shown as example. Given that the sample fresh weight was 481 mg, the content of HNE in BY-2 cells is determined using the k for acrolein (k ¼ 0.675, Table 3), as follows:

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Absorbance at 340 nm

Free DNPH

auxin-treated untreated control

Acetaldehyde

Internal standard

Crotonaldehyde

(E)-2-Heptenal

Butyraldehyde Propionaldehyde

n-Hexanal HNE

5

10

15

20

25

30

35

Retention time (min)

Fig. 3 Typical chromatograms of carbonyls in Arabidopsis thaliana root. Five-day-grown plants on agar plate were transferred to fresh medium supplemented with auxin (1 μM indoleacetic acid; red) and water as control (black), then incubated for 2 h. Roots excluding the apical 2 mm were collected (60 mg, 120–130 plants). Carbonyls were immediately extracted from the excised root, derivatized with DNPH, and separated by HPLC. The identified aldehydes are labelled at the top of each peak. Inset, internal standard

HNE content ðnmol=g FW Þ ¼ ðAHNE =AIS Þ  0:675  25:0=0:481 where AHNE and AIS represent the HPLC peak area of DNP derivatives of HNE and IS (2-ethylhexanal), respectively, and the numerical value 25.0 is the amount of IS (in nmol) that was added the 481 mg sample (i.e., 5.0 μM IS solution  5.0 mL (see Subheading 3.6)). 3.8 Determination of the Conversion Factor k

In case you cannot find the carbonyl compound of your interest in Table 1, you can determine its conversion factor k in the following way: 1. Prepare a standard 1 mM solution of the test carbonyl in acetonitrile. 2. Prepare 9 glass centrifuge tubes (50 mL size with a screw cap). Put 5.0 mL of extraction solution (acetonitrile containing 5.0 μM 2-ethylhexanal) in each tube. 3. Add 10 μL, 20 μL, or 30 μL of the 1 mM test carbonyl solution to each tube. Make three runs for each concentration. 4. Add 20 mM DNPH solution (125 μL; final concentration of 0.5 mM) and formic acid (96 μL; final concentration of 0.5 M). Tighten the cap, mix well, and incubate the mixture at 25  C for 60 min.

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Table 3 List of relative retention time and conversion factor of typical DNPcarbonyls Cn

Carbonyl

Relative RT

k (340 nm)

1

Formaldehyde

0.188

3.32

2

Acetaldehyde

0.254

0.49

3

Propionaldehyde

0.412

0.56

3

Acrolein

0.375

1.36

3

Acetone

0.347

3.66

3

Malondialdehyde

0.162

3.24

4

n-Butyraldehyde

0.556

0.54

4

Crotonaldehyde

0.497

2.89

4

Methacrolein

0.422

9.03

4

Methyl vinyl ketone

0.626

0.96

5

(E)-2-pentenal

0.617

2.71

6

n-Hexanal

0.804

0.46

6

(Z )-3-hexenal

0.705

0.52

6

(E)-2-hexenal

0.788

2.36

6

4-Hydroxy-(E)-2-hexenal (HHE)

0.266

0.61

7

n-Heptanal

0.92

0.64

8

n-Octanal

1.059

0.89

8

(E)-2-octenal

1.042

–

8

2-Ethylhexanal

1.000

1.00

8

Phenylacetaldehyde

0.601

0.59

9

n-nonanal

1.177

1.53

9

(E)-2-nonenal

1.166

–

9

4-Hydroxy-(E)-2-nonenal (HNE)

0.675

0.60

10

(E)-2-decenal

1.267

3.58

10

1-decanal

1.284

1.10

10

β-Cyclocitral

1.034

2.32

5. After the incubation, follow the same procedure from 5 to 8 in Subheading 3.5, and analyze the sample as described in Subheading 3.6. 6. From the result of each tube, a peak area ratio (DNP-test carbonyl/DNP-IS) is obtained. Confirm that the ratio is

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proportional to the concentration of the test carbonyl, and average the ratio of all tubes. The conversion factor k is obtained as the inverse of the averaged ratio: k ¼ 1=the peak area ratio ðDNP‐test carbonyl=DNP‐ISÞ

4

Notes 1. Instead of the indicated column and eluents, a conventional ODS column with a typical composition of eluents should work, but the elution order of DNP derivatives may be different from that described in this protocol. 2. Because the fresh weight recorded here is used for the calculation of the carbonyl content, a significant figure of three digits is preferred. For weighing a very small sample (less than ca. 50 mg), it is necessary to use a precision balance of 0.1 mg resolution, with a precaution to prevent the sample from drying during the handling. 3. If the sample amount is less than 50 mg, the extracted amounts of carbonyls will be very small as compared with IS and may not be determined precisely. It will be better to use a smaller amount (e.g., 1.00 mL) of the extraction solution. Accordingly, after the DNP derivatives are dried up (from the step 7 in Subheading 3.5), the sample should be dissolved in a smaller volume (e.g., 50 μL) of acetonitrile and purified with a smaller cartridge (e.g., sorbent mass of 30 mg) and obtain smaller amount of the sample (50 μL flow-through and 100 μL wash). 4. The sample solution can be kept at
20  C for up to 1 week after preparation. A longer storage may cause decomposition of DNP derivatives. 5. DNP derivatives of n-alkanals have an absorption peak at around 360 nm, and those of 2-alkenals around 380 nm. In contrast, the DNP-MDA has a peak at 307 nm; its absorption at 360 nm is very low. Choice of the wavelength at 340 nm for the detection is a compromise to determine both MDA and other carbonyls with a single wavelength detector [18]. If a photodiode array detector is available, integration of the absorption from 300 nm to 400 nm will provide selective and sensitive detection of DNP-carbonyls [19].

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References 1. Mittler R (2017) ROS are good. Trends Plant Sci 22:11–19 2. Mano J, Biswas MS, Sugimoto K (2019) Reactive carbonyl species: a missing link in ROS signaling. Plan Theory 8:391 3. Mano J (2012) Reactive carbonyl species: their production from lipid peroxides, action in environmental stress, and the detoxification mechanism. Plant Physiol Biochem 59:90–97 4. Farmer EE, Mueller MJ (2013) ROS-mediated lipid peroxidation and RES-activated signaling. Annu Rev Plant Biol 64:429–450 5. Yalcinkaya T, Uzilday B, Ozgur R et al (2019) Lipid peroxidation-derived reactive carbonyl species (RCS): their interaction with ROS and cellular redox environmental stresses. Environ Exp Bot 165:139–149 6. Esterbauer H, Schauer R, Zollner JH (1991) Chemistry and biochemistry of 4-hydroxynonenal, malondialdehyde and related aldehydes. Free Rad Biol Med 11: 81–128 7. Mano J, Tokushige K, Mizoguchi H et al (2010) Accumulation of lipid peroxidederived, toxic α,β-unsaturated aldehydes (E)2-pentenal, acrolein and (E)-2-hexenal in leaves under photoinhibitory illumination. Plant Biotechnol 27:193–197 8. Yamauchi Y, Hasegawa A, Mizutani M et al (2012) Chloroplastic NADPH-dependent alkenal/one oxidoreductase contributes to the detoxification of reactive carbonyls produced under oxidative stress. FEBS Lett 586: 1208–1213 9. Yin L, Mano J, Wang S et al (2010) The involvement of lipid peroxide-derived aldehydes in aluminum toxicity of tobacco roots. Plant Physiol 152:1406–1417 10. Kai H, Hirashima K, Matsuda O et al (2012) Thermotolerant cyclamen with reduced acrolein and methyl vinyl ketone. J Exp Bot 63: 4143–4150

11. Biswas MS, Mano J (2015) Lipid peroxidederived short-chain carbonyls mediate hydrogen peroxide-induced and salt-induced programmed cell death in plants. Plant Physiol 168:885–898 12. Biswas MS, Mano J (2016) Reactive carbonyl species activate caspase-3-like protease to initiate programmed cell death in plants. Plant Cell Physiol 57:1432–1442 13. Srivastava S, Brychkova G, Yarmolinsky D et al (2017) Aldehyde oxidase 4 plays a critical role in delaying silique senescence by catalyzing aldehyde detoxification. Plant Physiol 173: 1977–1997 14. Islam MM, Ye W, Matsushima D et al (2016) Reactive carbonyl species mediate ABA signaling in guard cells. Plant Cell Physiol 57: 2552–2563 15. Islam MM, Ye W, Akter F et al (2020) Reactive carbonyl species mediate methyl jasmonateinduced stomatal closure. Plant Cell Physiol 61:1788–1797. https://doi.org/10.1093/ pcp/pcaa107 16. Biswas MS, Fukaki H, Mori IC et al (2019) Reactive oxygen species and reactive carbonyl species constitute a feed-forward loop in the auxin signaling for lateral root formation. Plant J 100:536–548 17. Matsui K, Sugimoto K, Kakyumyan P et al (2009) Volatile oxylipins and related compounds formed under stress in plants. In: Armstrong D (ed) Methods in molecular biology ‘lipidomics’. Humana Press, Totowa, pp 17–28 18. Mano J, Biswas MS (2018) Analysis of reactive carbonyl species generated under oxidative stress. In: De Gara L, Locato V (eds) Plant programmed cell death: methods and protocols. Springer, New York, pp 117–124 19. Mano J, Khorobrykh S, Matsui K et al (2014) Acrolein is formed from trienoic fatty acids in chloroplasts: a targeted metabolomics approach. Plant Biotechnol 31:535–544

Chapter 16 Measuring Stress-Induced Changes in Defense Phytohormones and Related Compounds Caroline Lelarge-Trouverie, Amna Mhamdi, Florence Gue´rard, and Graham Noctor Abstract Measuring quantitative changes in plant hormones and derivatives is crucial to understand how reactive oxygen species trigger signaling cascades to regulate stress responses. In this chapter, we describe the liquid chromatography-mass spectrometry procedure that we use to extract and quantify salicylic acid (SA), jasmonic acid (JA), and related compounds in common extracts of Arabidopsis tissue. The method can provide quantitative data on SA, SA glucosides, and JA, as well as information on oxidized and conjugated forms of these compounds and related derivatives of benzoic acid. Key words Salicylic acid, Jasmonic acid, Benzoic acids, LC-MS, Secondary metabolism

1

Introduction Recent work has revealed that redox modifications linked to oxidative stress are tightly integrated with phytohormone functions, forming part of the link between environmental changes and plant responses [1, 2]. While redox states are now known to impact many phytohormone pathways, salicylic acid (SA) in particular interacts closely with reactive oxygen species and associated compounds such as glutathione and thioredoxins [3–5]. Work in our laboratory using catalase-deficient mutants has reported that H2O2-induced changes in glutathione metabolism can strongly modify the expression of genes associated with SA and jasmonic acid (JA), both of which are important players in plant defense [6– 8]. Hence, the ability to quantify SA and JA contents offers an important tool in research aimed at exploring the impact of oxidative stress on plant function. As well as their free forms, plants contain several different conjugates and oxidized forms of both JA and SA [9, 10]. Indeed, in the case of JA, the active form is a conjugate with isoleucine (JA-Ile) [11]. Moreover, benzoic

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_16, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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acid-based compounds other than SA may also play significant roles in stress signaling [12]. Here we describe a protocol based on LC-MS that we have developed to profile SA, JA, and related compounds in plant tissues.

2

Materials

2.1 Reagents and Solvents

1. Jasmonic acid (JA). 2. Salicylic acid (SA). 3. SA-O-glucoside (SAG). 4. SA glucose ester (SEG). 5. Benzoic acid (BA). 6. p-Hydroxybenzoic acid. 7. m-Hydroxybenzoic acid. 8. 2,3-Dihydoxybenzoic acid. 9. 2,4-Dihydroxybenzoic acid. 10. 2,5-Dihydroxybenzoic acid. 11. 2,6-Dihydroxybenzoic acid. 12. 3,4-Dihydroxybenzoic acid. 13. 3,5-Dihydroxybenzoic acid. 14. 2-Hydroxybenzoic acid-[2H4] (d4-SA). 15. Dihydrojasmonic acid (DHJA). 16. Methanol. 17. Acetonitrile. 18. Formic acid. 19. Acetone. 20. Isopropanol. 21. Acetic acid. 22. Deionized Milli-Q water.

2.2 Equipment and Software

1. Solid-phase extraction columns (e.g., EVOLUTE® ABN cartridges (50 mg, 3 cc) or equivalent). 2. Sample concentrator (e.g., TurboVap® LV, Biotage). 3. 2 mL Eppendorf tubes (safe-lock). 4. Glass vials and screw caps. 5. Filters. 6. Balance. 7. Mortars and pestles. 8. Vortex mixer or sample shaker.

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9. Refrigerated microcentrifuge. 10. C18 reversed-phase column. 11. ACQUITY Ultra Performance LC™ System (Waters, SaintQuentin en Yvelines, France). 12. Time of flight mass spectrometer equipped with an electrospray ionization (ESI) source operating in negative mode (Bruker Daltonik GmbH, Germany). 13. Bruker MicrOTOF-Control software. 14. Bruker DataAnalysis software (version 4.0). 15. Bruker QuantAnalysis software (version 2.0).

3

Methods

3.1 Growth Conditions and Sampling

1. Grow Arabidopsis Col-0 and selected mutant genotypes in 16 h days at an irradiance of 200 μmol.m 2.s 1 and 22  C/ 20  C (day/night). 2. Apply stress and control treatments at 21 days (e.g., pathogen infection or wounding) (see Note 1). 3. Sample Arabidopsis rosette leaves (between 200 and 400 mg fresh weight), and immediately freeze in liquid nitrogen, and store at 80  C until analysis (see Notes 2 and 3).

3.2

Extraction

3.2.1 Methanol Extraction and SPE

Below we describe two extraction protocols; the first one involves extraction in methanol followed by solid-phase extraction (SPE), and the second one involves a simpler extraction in acetone. 1. Grind the frozen tissue (400 mg fresh weight) in liquid nitrogen using mortar and pestle. 2. Extract the metabolites by adding 1 mL methanol, homogenize the sample, and add another 1 mL methanol. 3. Transfer the sample to 2 ml Eppendorf tube, and centrifuge at 12,000  g and 4  C for 15 min. 4. Transfer the supernatant to a new Eppendorf tube, and evaporate under air flux using a TurboVap or equivalent machine (see Note 4). 5. Dissolve the dried samples using 1 mL 0.1% acetic acid. 6. Add consecutively 2 mL of methanol and 2 mL 0.1% (v/v) acetic acid to precondition and to equilibrate the SPE columns. 7. Load the 1 mL sample into the SPE column, and then wash with 2 mL 5% (v/v) methanol. 8. Elute using 4 times 500 μL methanol and filtrate (e.g., using Waters filters).

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9. Evaporate fractions under air flux (e.g., TurboVap) (see Notes 5 and 6). 10. Dissolve each sample in 100 μL water and centrifuge at 12,000  g and 4  C for 10 min. The samples are then ready to be injected into the LC system (see Note 7). 3.2.2 Acetone Extraction

Notably, this second method (adapted from [13]) does not involve SPE and therefore allows samples to be injected more directly into the LC-MS system (see Note 8). An overview of the protocol is shown in Fig. 1. 1. Prepare the extraction solution containing acetone/water/ acetic acid (80/19/1, v:v:v), and add the internal standards (d4-SA and DHJA) at a concentration of 4 μM each.

Fig. 1 Overview of extraction and sample preparation method

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2. Grind the frozen tissue (200 mg fresh weight) in liquid nitrogen using mortar and pestle. 3. Extract the metabolites by adding 800 μL extraction buffer containing the internal standards. 4. Shake the sample (vigorously) for 1 min, sonicate for 1 min, and then shake again at 10  C for 10 min. 5. Centrifuge at 12,000  g and 4  C for 15 min. 6. Collect the supernatant into a new Eppendorf tube, and extract the pellet again, twice, using 400 μL of the same extraction solution. 7. Following the three extraction steps, pool the three supernatants, and dry the samples using a TurboVap or equivalent machine. 8. Dissolve the dried samples using 100 μL water, and centrifuge at 12,000  g and 4  C for 10 min. 3.3 Sample Preparation and Liquid Chromatography

1. Prepare (freshly) and filter the mobile phases as water (eluent A) and 0.1% acetic acid (v/v) in acetonitrile (eluent B). 2. Set linear gradients and isocratic flows of eluent B balanced with eluent A as below: isocratic 5% B during 1 min, 5–10% B over 1 min, 10–18% B over 1.5 min, 18–40% B over 3.5 min, 40–95% B over 1 min, isocratic 95% B during 1 min, 95–5% B over 1 min, and isocratic 5% B during 1 min (see Note 9). 3. Prepare standard solutions either separate or in a mix if available (see Note 10). 4. Filter the sample, and transfer into a glass vial with insert and load into the autosampler tray. 5. Inject 5 μL of samples and standards into a reversed-phase LC column (e.g., Kinetex C18, 1.7 U, 100A, 2.1  100 mm, Phenomenex), and set the flow rate to 0.4 mL/min. A typical chromatogram for a mix of standards is shown in Fig. 2 (see Note 11).

3.4 Mass Spectrometry

1. Detect the eluting compounds from m/z 50 to 800 using a mass spectrometer equipped with an electrospray ion source in negative mode (negative ESI). 2. Set the instrument as follows: nebulizer gas, N2, 4 bar; dry gas, N2, 8.5 L/min; capillary voltage, 3700 V; end plate offset (interface voltage), 500 V; acquisition frequency, 2 Hz.

3.5 Data Analysis and Processing

1. Calibrate the samples using the appropriate software, for example, DataAnalysis 4.0.

3.5.1 Identification

2. Generate ion chromatograms and deconvolutions of compound mass spectra.

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Fig. 2 Typical chromatogram of the extracted ion current (EIC) for a mix of compounds for which authentic standards are available. The different colors indicate different fragment ions; for example, 153.0182 represents the M-H ion for the dihydrobenzoic acid isomers. Two internal standards (IS) are also included in the chromatogram

3. Calculate ion elemental composition and isotopic profile. 4. Identify compounds (JA, SA, SAG, SEG, mHBA, pHBA, DHBAs) by comparison of the retention time with standards. Search ions according to the mass spectra of the standards, and confirm identities using a combination of exact mass and isotopic profile. Identify other compounds (for which standards are not available) according to theoretical mass spectra. 3.5.2 Quantification

1. Use QuantAnalysis 2.0 to integrate extracted ion chromatograms of corresponding quantifier ions. 2. Quantify metabolites depending on the availability of the authentic standards (see Note 12). Quantify (absolute quantification) JA, SA, SAG, and SEG by comparison to curves generated from authentic standards and internal standards and express the results as pmol per mg FW (fresh weight). 3. Perform relative quantification for mHBA; pHBA; 2,3-DHBA; 2,4-DHBA; and 2,6-DHBA by comparison with curves generated from authentic standards. 4. Perform semi-quantification for 2,5-DHBA-2-G; 2,5-DHBA5-G; 2,5-DHBA-5-X; 2,3-DHBA-3-X; OH-JA1; OH-JA2; JAG1; OH-JA-Ile; COOH-JA-Ile; 12-SJA; OH-JAG1; OPDA; and pHBAL, and estimate quantities on the basis of the extracted ion chromatogram area. Express the relative and semi-quantification values as in area per mg FW.

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Notes 1. For one experiment, Col-0 was wounded by cutting attached leaves at three different places with a scalpel, and the leaves were sampled 1 h later, together with unwounded Col-0 and cat2. In our hands, this wounding treatment gives an increase in JA content of eightfold (sampling at 1 h after wounding). 2. Wounding can induce changes in plant hormones; hence it is important to freeze the tissues in liquid nitrogen immediately after detaching the tissues from the plants. 3. To get statistically significant results, it is recommended to have at least four biological replicates from each genotype. 4. We have compared several protocols to dry samples, using SpeedVac or TurboVap for variable times. Of these, the use of rapid drying using the TurboVap gave the smallest loss of compounds. 5. Here, samples from the different steps of SPE could be collected to evaluate the recovery of metabolites and their potential loss during the extraction procedure, for example, we take sample from the load, wash, and elute fractions. 6. The temperature used to evaporate the samples can influence the recovery of certain compounds. We use 52  C for the elute fractions and 72  C for the load and wash fractions. 7. If samples are not ready to be injected immediately, then it is better to store them as dried samples at 20  C. During the analysis, dissolved samples are kept in a temperature-controlled autosampler tray at 4  C until injection is complete. 8. Based on our experience using several columns from different suppliers, we have been unable to find an SPE protocol that avoids significant loss of at least some of the target compounds. Therefore, we routinely use this second, simpler sample preparation method. 9. The Phenomenex KNX Calculator Gradient Excel tool is very useful to optimize the chromatographic separation. 10. Standard solutions are first prepared in methanol at a concentration of 200 μM for 2,5-DHBA, 3,5-DHBA, and internal standards, 100 μM for SAG and 10 μM for the others. Then, working concentrations standards are obtained by dilution within a calibration range of 0 to 32 μM for each standard. 11. The UPLC system enables very good elution time repeatability. We typically observe very little variation between injections for both standards and plant extracts. 12. All compounds studied (except JAG) yield an M-H ion as the major fragmentation product in standards, and this is used as

Caroline Lelarge-Trouverie et al.

the quantifier ion. Secondary fragment ions include M-COOH ions and, for glycosylated forms, M-sugar (glucose or xylose) products. For most compounds, highly linear standard curves can be obtained using quantification based on these specific ions or on their sum. Examples of standard curves are shown in Fig. 3 for JA, pHBA, and SAG. However, because fragment ions are sometimes observed at different proportions in samples of plant extracts, absolute quantification is only performed for compounds for which internal standards are available and shown in control experiments to be valid reporters. In our method, these are JA (using DHJA as IS) and SA, SAG, and SEG (using d4-SA as IS).

Peak area

150,000

JA

100,000 M-H R² = 0,9982

50,000 0 0

Peak area

200,000

2

4

6

8

10

pHBA

12

150,000

Total area R² = 0,9999

100,000

M-H R² = 0,9999

50,000

M-COOH R² = 0,9969

0 0

3,000,000

Peak area

222

10

20

30

40

50

60

Total area R² = 0,9945

SAG

2,000,000

M-H R² = 0,9976

1,000,000 M-g R² = 0,9768

0 0

50

100

150

200

250

pmoles compound injected Fig. 3 Representative standard curves for JA, pHBA, and SAG. For JA, only the M-H fragmentation product was found and was used as the quantifier ion. For pHBA, two fragments corresponding to the M-H and M-COOH ions were detected, while for SAG, detected ions were M-H and M-glucose (M-g). As for JA, the majority M-H product was found to be the most robust quantifier ion

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Acknowledgments We thank Gre´gory Mouille (IJPB, INRA Versailles) for discussion. Work in the GN laboratory is supported by the French Agence Nationale de la Recherche HIPATH project (ANR-17-CE200025) and by the Institut Universitaire de France (IUF). References 1. Mhamdi A, Van Breusegem F (2018) Reactive oxygen species in plant development. Development 145 2. Noctor G, Reichheld JP, Foyer CH (2018) ROS-related signaling in plants. Semin Cell Dev Biol 80:3–12 3. Vanacker H, Carver TLW, Foyer CH (2000) Early H2O2 accumulation in mesophyll cells leads to induction of glutathione during the hypersensitive response in the barley-powdery mildew interaction. Plant Physiol 123: 1289–1300 4. Laloi C, Mestres-Ortega MY, Meyer Y, Reichheld JP (2004) The Arabidopsis cytosolic thioredoxin h5 gene induction by oxidative stress and its W-box-mediated response to pathogen elicitor. Plant Physiol 134: 1006–1016 5. Mou Z, Fan WH, Dong XN (2003) Inducers of plant systemic acquired resistance regulate NPR1 function through redox changes. Cell 113:935–944 6. Mhamdi A, Hager J, Chaouch S et al (2010) Arabidopsis GLUTATHIONE REDUCTASE 1 is essential for the metabolism of intracellular H2O2 and to enable appropriate gene expression through both salicylic acid and jasmonic acid signaling pathways. Plant Physiol 153: 1144–1160 7. Han Y, Chaouch S, Mhamdi A et al (2013) Functional analysis of Arabidopsis mutants

points to novel roles for glutathione in coupling H2O2 to activation of salicylic acid accumulation and signaling. Antioxid Redox Signal 18:2106–2121 8. Han Y, Mhamdi A, Chaouch S, Noctor G (2013) Regulation of basal and oxidative stress-triggered jasmonic acid-related gene expression by glutathione. Plant Cell Environ 36:1135–1146 9. Dempsey DMA, Vlot AC, Wildermuth MC, Klessig DF (2011) Salicylic acid biosynthesis and metabolism. The Arabidopsis Book 9: e0156 10. Miersch O, Neumerkel J, Dippe M, Stenzel I, Wasternack C (2008) Hydroxylated jasmonates are commonly occurring metabolites of jasmonic acid and contribute to a partial switch-off in jasmonate signalling. New Phytol 177: 114–127 11. Acosta IF, Farmer EE (2010) Jasmonates. The Arabidopsis Book 8:e0129 12. Bartsch M, Bednarek P, Vivancos PD et al (2010) Accumulation of isochorismate-derived 2,3-dihydroxybenzoic 3-O-β-d-xyloside in Arabidopsis resistance to pathogens and ageing of leaves. J Biol Chem 285:25654–25665 13. Le Roux C, Del Prete S, Boutet-Mercey S, Perreau F, Balague´ C, Roby D, Fagard M, Gaudin V (2014) The hnRNP-Q protein LIF2 participates in the plant immune response. PLoS One 9:e99343

Part IV Systems Biology Approaches to Understand ROS Functions

Chapter 17 Targeted Mass Spectrometry Analysis of Protein Phosphorylation by Selected Ion Monitoring Coupled to Parallel Reaction Monitoring (tSIM/PRM) Jesu´s Pascual and Saijaliisa Kangasj€arvi Abstract Recent developments in targeted mass spectrometry-based proteomics have provided new methodological solutions for accurate and quantitative analysis of proteins and their posttranslational control, which has significantly advanced our understanding of stress responses in different plant species. Instrumentation allowing high-resolution, accurate-mass (HR/AM) analysis has provided new acquisition strategies for targeted quantitative proteomic analysis by targeted selected ion monitoring (tSIM) and parallel reaction monitoring (PRM). Here we report a sensitive and accurate method for targeted analysis of protein phosphorylation by tSIM coupled to PRM (tSIM/PRM). The tSIM/PRM method takes advantage of HR/AM mass spectrometers and benefits from the combination of highly sensitive precursor ion quantification by tSIM and highly confident peptide identification by spectral library matching in PRM. The detailed protocol describes tSIM/PRM analysis of Arabidopsis thaliana foliar proteins, from the building of a spectral library to sample preparation, mass spectrometry, and data analysis, and provides a methodological approach for specifying the molecular mechanisms of interest. Key words Targeted mass spectrometry, Selected ion monitoring, Parallel reaction monitoring, Protein phosphorylation

1

Introduction Technical developments in mass spectrometry-based proteomics together with the increasing availability of plant genomic resources and tandem mass spectrometry (MS/MS) data analysis algorithms have opened a new window for high-resolution analysis of stress responses in model plants, crops, and trees [1–8]. To date, transcriptomic studies have elucidated the dynamic nature of gene expression occurring in response to environmental cues, but gaps remain in understanding how the elicited metabolic and regulatory adjustments protect the plant against cellular damage [9–12]. Comprehensive understanding of plant stress responses therefore calls

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_17, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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for accurate and quantitative analysis of proteins and their posttranslational control. Reversible phosphorylation is one of the key mechanisms that posttranslationally control the activity, turnover, subcellular localization, and molecular interactions of proteins. Over the past decade, large-scale phosphoproteomic studies have yielded a wealth of proteomic maps consisting of the identity of the phosphoproteins and their exact phosphorylation sites upon exposure to stressful environmental cues in different plant species [13–17]. A classical approach has been coupling of phosphopeptide enrichment with nontargeted analysis by data-dependent acquisition (DDA) mass spectrometry, also known as “shotgun proteomics” [18]. This approach is an excellent tool for mapping a proteome in a discovery phase but is biased toward abundant peptides and suffers from poor reproducibility and inaccurate quantitative analysis of dynamic phosphoproteomes [18, 19]. Improvements in the accuracy and sensitivity of mass spectrometers have significantly advanced the quantitative analysis of proteins and their posttranslational modifications in complex biological samples. Also, detection of posttranslationally modified low-abundance proteins, especially phosphoproteins, has become feasible. The recently established data-independent acquisition (DIA) mass spectrometry offers an attractive choice for highresolution quantitative mapping of a proteome and a rich resource for post-acquisition data mining [19]. However, setting up DIA is laborious, and data processing is still a major bottleneck in these approaches. Modern large-scale nontargeted proteomics approaches can reveal entire biochemical pathways or regulatory networks elicited by environmental cues. Targeted approaches in turn can accurately record qualitative and quantitative changes in proteins and their posttranslational modifications and therefore offer methodological solutions for specifying the molecular mechanisms of interest. Targeted approaches offer powerful means for the analysis of peptides that are of low abundance or otherwise hard to detect, for example, due to incomplete ionization, which is often the case for phosphopeptides [20, 21]. Common to all targeted proteomic approaches, a list of peptides arising from the proteins of interest must be selected prior to data acquisition by mass spectrometry, and a priori knowledge of the peptides is required in the form of a so-called spectral library. Selected reaction monitoring (SRM) mass spectrometry has been widely used for sensitive and accurate quantitative analysis of protein isoforms and their posttranslational modifications [22– 25]. However, development of SRM assays can be timeconsuming, as it necessitates determination and selection of the best transitions, i.e., parent ion-fragment pairs, to be utilized in the analysis [26]. Moreover, SRM is performed on a triple quadrupole

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mass spectrometer, which has high selectivity power but lower resolution and scanning speed than the modern mass analyzers, such as Orbitrap. The development of instrumentation allowing high-resolution, accurate-mass (HR/AM) analysis, such as quadrupole-time-offlight (Q-TOF) or quadrupole-Orbitrap (Q-OT) mass spectrometers [27], has brought along new acquisition strategies for targeted quantitative proteomic analysis in both MS (targeted selected ion monitoring, tSIM) and MS/MS modes (parallel reaction monitoring, PRM). Compared to SRM, these strategies exhibit similar or better performance when it comes to selectivity, dynamic range, and sensitivity, and they are much less demanding in terms of method development time. Furthermore, the multiplexing capability of these instruments enhances the application of these acquisition methods to larger targeted proteomic studies. tSIM deploys HR/AM instrumentation to isolate target precursor ions and transfers them to the mass analyzer for detection. tSIM does not employ fragmentation of the parent ions, but the identity of the targeted peptide is confirmed by accurate-mass measurements in combination with information of the elution time. Hence, tSIM provides a simple but highly selective and sensitive method for quantification [26]. In PRM, as in tSIM, the target precursor ions are accurately selected using a quadrupole, but they are fragmented before being injected into the mass analyzer. Unlike in SRM, in which specific precursor fragment ions are targeted for MS analysis, in PRM, all target product ions are detected in parallel in one, concerted highresolution mass analysis. In this case, peptide identification is based on spectral library matching. Therefore, PRM necessitates a priori knowledge concerning the charge state, the elution time, and, preferably, the fragmentation of the peptides of interest. Both tSIM and PRM can be performed with the same instrument that is used in a preceding discovery-phase DDA (Q-TOF, Q-OT), which is yet another advantage when compared to SRM, which requires a triple quadrupole (QQQ). For absolute quantification, PRM and tSIM are performed by using isotopically labeled peptides as internal standards. Here we describe a method for targeted mass spectrometry analysis of protein phosphorylation by tSIM coupled to PRM (tSIM/PRM; Fig. 1). The tSIM/PRM method takes advantage of HR/AM mass spectrometers and combines the benefits arising from the high sensitivity of quantification at MS1 level by tSIM, and the high selectivity and highly confident peptide identification by spectral library matching in PRM. Additionally, both tSIM and PRM are feasible when efforts and time invested on method development are considered. Compared to the individual application of tSIM or PRM, the combined tSIM/PRM method is more timeconsuming in terms of MS analysis time, as there is a sequential

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Precursor

Fragmented ions

Quadrupole

C-trap HCD

Orbitrap

MS1

Precursor ion

MS2

Fragment ions

tSIM 1

PRM 1

MS1

Precursor ion

MS2

Fragment ions

tSIM 2

Isolation window (time)

PRM 2 150 m/z

Precursor isolation window (m/z)

2000 m/z

m/z

[...] Ion flow path

Fig. 1 Schematic representation of the combined targeted selected ion monitoring (tSIM) and parallel reaction monitoring (PRM) method (tSIM/ PRM) in a quadrupole-Orbitrap instrument (Q-OT). Digested protein samples are separated by liquid chromatography (LC). Peptides are electrospray ionized into the Q-OT (these are the precursor ions; black bars). As the ions flow into the mass spectrometer, in tSIM, the precursors are selected at quadrupole level (red box) using a narrow m/z isolation window. Isolated precursors are accumulated in the C-trap (yellow box) up to a fixed capacity or during a fixed time and thereafter transferred to the mass analyzer (Orbitrap; blue box) without any fragmentation step. In PRM, precursors are selected in the quadrupole and accumulated in the C-trap in the same way described for tSIM. However, in PRM the precursor ions are fragmented in a higher-energy collision dissociation cell (HCD; green box). The resulting fragment ions (black dots) are transferred back to the C-trap and then injected into the Orbitrap, where they are analyzed in parallel. tSIM and PRM scans occur one after another in a sequential way and during a previously determined isolation time window around the expected or known elution time of the targeted peptide/s

alternation between the two approaches. However, the number of peptides that can be potentially analyzed simultaneously, in a single run, can be significantly increased by scheduling and exploiting multiplexing possibilities in Q-OT instruments [26]. This protocol includes the major procedures involved in the development and performance of a tSIM/PRM method: building of a spectral library, sample preparation, LC-MS/MS, and data analysis. The protocol was developed for leaf samples from the model species

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Arabidopsis thaliana but can be adapted to other types of samples from this or other plant species. In order to complete this protocol successfully, the described laboratory procedures must be performed in a very clean environment and using mass spectrometrycompatible buffers and reagents.

2

Materials

2.1 Solutions (See Note 1)

1. Protein isolation buffer: 50 mM HEPES KOH pH 7.8, 10 mM MgCl2 supplemented with protease and phosphatase inhibitor cocktails (see Note 2). 2. 2X Laemmli sample buffer: 10% (w/v) SDS, 1 M Tris-HCl pH 6.8, 10% β-mercaptoethanol (add before use). 3. Gel fixing solution: 40% methanol/10% acetic acid. 4. 100% acetonitrile (ACN). 5. Mass spectrometry mobile-phase solvent A: water/ACN (98: 2 (v/v)) with 0.2% formic acid (FA) (v/v). 6. Mass spectrometry mobile-phase solvent B: can/water (80:20 (v/v)) with 0.2% FA (v/v). 7. 20 mM dithiothreitol (DTT). 8. 55 mM Iodoacetamide (IAA). 9. 100 mM ammonium bicarbonate (NH4HCO3). 10. 50% ACN/5% formic acid (HCOOH). 11. Bradford reagent and bovine serum albumin (BSA) for protein quantification (see Note 3).

2.2

Equipment

1. Spectrophotometer or plate reader for protein quantification. 2. Protein gel electrophoresis system. 3. Heat block. 4. Vacuum centrifuge. 5. NanoDrop, BioDrop, or equivalent for peptide quantification. 6. NanoLC-ESI-MS/MS system (see Note 4).

2.3

3

Software

1. Skyline (https://skyline.ms/project/home/software/Sky line/begin.view).

Methods

3.1 Generation of a Spectral Library and an Isolation List

1. Building of the spectral library is the core of this methodological approach and requires a priori information regarding the peptides to be targeted. This information includes the identity

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of the peptides, i.e., their amino acid sequences and possible posttranslational modifications, the protein/s they belong to, their mass spectrometric pattern including precursor and fragment ion m/z and relative fragment ion intensities, as well as their normalized retention times. The spectral library is defined as a curated, annotated, and nonredundant database of LC-MS/MS spectra. These can be gathered from data publicly available in specialized repositories/databases (Panorama, ProteomeXchange Consortium) or generated in a previously performed discovery phase by running the samples in DDA mode (see Note 5). 2. Build a spectral library in Skyline. The library can be built based on a wide variety of peptide spectrum matching pipeline output file formats, and Skyline can also directly read existing spectral libraries. 3. Generate an isolation list tSIM/PRM setup in the Skyline “Peptide Settings.” First, select the target peptides. Second, set an isolation window range. This determines the LC elution time windows in which the targeted peptides will be targeted (see Note 6). These isolation windows will cover a range of time around the expected or known retention time of the target peptides according to the spectral library previously built. 4. Export the list of elution time windows as an isolation list (see Note 7). 3.2 Isolation of Protein Samples

1. Grind Arabidopsis rosettes (~500 mg fresh weight) into a homogenous suspension in 400 μl of protein isolation buffer using pre-cooled mortar and pestle (see Note 8). 2. Incubate 10 min on ice. 3. Centrifuge 10 min at 20,000
g to remove cell debris and transfer the supernatant into a new tube. Repeat this step until all pieces of tissue are removed. 4. Quantify protein concentration with Bradford reagent (see Note 3). 5. Share the samples into approximately 50 μl aliquots to avoid repeated freezing and thawing during the following steps, and immediately freeze in liquid nitrogen. Store at 80  C.

3.3 Sample Preparation by In-Gel Protein Digestion for Mass Spectrometry Analysis 3.3.1 In-Gel Sample Denaturation and Purification (See Note 9)

1. Solubilize 25 μg of protein sample in Laemmli buffer at room temperature for 10 min (see Note 10), and thereafter run the samples 0.5 cm into a 1-mm-thick, 6% acrylamide (w/v) SDS-PAGE. 2. Fix the gel with 40% methanol/10% acetic acid for 2 h. Add enough fixing solution to cover the gel uniformly and incubate at room temperature under gentle shaking (see Note 11).

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3. Wash the gel with ultrapure water to remove the fixing solution and to rehydrate the gel. 4. Excise the gel area corresponding to the protein sample using a scalpel and chop into 1 mm3 gel cubes. 5. Transfer the gel pieces into a 2 mL tube (see Note 12). Here it is possible to stop and store the sample at 20  C. 3.3.2 Protein Reduction and Alkylation

1. Wash the gel pieces thoroughly three times with ultrapure water. Removing all the water possible will enhance the efficiency of the next step (see Note 13). 2. Shrink the gel pieces with 200 μL 100% ACN. Add the ACN, vortex, and wait until the gel pieces become hard as a piece of rock and turn completely white. This step can be repeated twice, as its efficiency can be affected by any ultrapure water leftover from the previous step (see Note 14). 3. Centrifuge 30 s at 20,000
g and remove the ACN completely. 4. Rehydrate the gel pieces with 150 μL of 20 mM DTT, and incubate 45 min at 56  C under constant shaking. 5. Centrifuge and remove the DTT completely. 6. Shrink gel pieces with 200 μL of 100% ACN. 7. Centrifuge 30 s at 20,000
g and remove the ACN completely. 8. Rehydrate with 150 μL of 55 mM IAA, and incubate at room temperature for 45 min under constant shaking in darkness (IAA is light sensitive). 9. After removing the IAA, wash three times with 100 mM NH4HCO3 (just add, vortex, centrifuge, and remove, without any incubation time). 10. Dehydrate with 100% ACN, centrifuge 30 s at 20,000
g, and remove the ACN completely (see Note 15).

3.3.3 Protein Digestion, Peptide Extraction, and Vacuum Drying

1. Add 2.5 μg of trypsin into each tube (1 μg of trypsin per 10 μg of protein included in sample preparation) in a volume of 150 μL of 40 mM NH4HCO3/10% ACN. 2. Leave the tubes for 30–45 min on ice, so that the gel pieces become completely saturated with trypsin solution. 3. Digest for 14 h at 37  C. 4. Extract the peptides three times. For one round of extraction, add 75 μL of 100% ACN, incubate at 37  C under constant shaking for 15 min, centrifuge, and collect the supernatant containing the peptides to a clean tube. Repeat twice with 150 μL of 50% ACN/5% HCOOH, combining the supernatants in the same tube.

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5. Dry the peptides in a vacuum centrifuge. 6. Store the peptides at 20  C until the moment of the MS analysis. 3.4 Mass Spectrometry Analysis 3.4.1 Finalization of Sample Preparation for Mass Spectrometry

1. Prior to MS analysis, dissolve the dried peptides in 25 μL of 2% HCOOH. Pipette up and down washing the walls of the tube thoroughly to ensure a complete resuspension (see Note 16). 2. Quantify the peptide concentration in NanoDrop or equivalent using absorbance at 280 nm (A280). 3. Centrifuge the sample for 5 min at 20,000
g to pellet any gel pieces, which could be present in the final peptide mixture and, notably, cause blocking of the LC system. 4. Transfer the volume corresponding to 100 ng of peptides into an MS vial, and fill the volume up to 5 μL with 2% HCOOH (see Note 17).

3.4.2 Running tSIM/PRM

This protocol is compatible for MS analysis in a LC-MS/MS system equipped with a UHPLC system and a mass spectrometer with electrospray ionization (ESI) and suitable for HR/AM, like a Q-OT. 1. LC settings: 100 ng of digested protein is loaded in a nanoflow UHPLC system equipped with a 20
0.1 mm i.d. pre-column combined with a 150 mm
75 μm i.d. analytical column, both packed with 5 μm Reprosil C18-bonded silica. From this step, the eluting peptides become injected to an ESI source tuned at 2.1 kV and 300  C capillary temperature. The mobile phase consists of solvent A or solvent B at a flow rate of 300 nL min1. Separation of the peptides is performed in a three-step elution gradient: from 3% to 43% solvent B in 45 min, followed by an increase to 100% solvent B in 5 min, and finally 100% solvent B for 10 min. 2. tSIM settings: resolution of 60,000, AGC target 1e6, maximum IT of 110 ms, an isolation window of 3.5 m/z, 0.8 m/z isolation offset, and 150–2000 m/z scan range (see Table 1). 3. PRM settings: resolution of 15,000, 2e5 AGC target, maximum IT of 30 ms, 1.6 m/z isolation window, 0.3 m/z isolation offset, and normalized collision energy of 27 (see Table 1, see Note 18).

3.5

Data Analysis

1. Set Skyline “Full-Scan” settings according to the used tSIM/ PRM settings and import the results. 2. Perform data curation and quality control. tSIM/PRM raw data is processed in Skyline, where it can be visually inspected. The software integrates and displays the chromatographic peaks corresponding to the experiment target peptides. Skyline

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Table 1 Instrument settings used for tSIM and PRM Parameter

Setting tSIM

Resolution:

60,000

AGC target:

1e6

Maximum IT:

110 ms

Isolation window:

3.5 m/z

Isolation offset:

0.8 m/z

Scan range:

150–2000 m/z PRM

Resolution:

15,000

AGC target:

2e5

Maximum IT:

30 ms

Isolation window:

1.6 m/z

Isolation offset:

0.3 m/z

Normalized collision energy:

27

automatically detects the best peak and sets its boundaries in each case. Automatic peak picking is generally reliable, but manual curation and quality control are very important to ensure a reliable quantification. The identification of the correct peaks (the one corresponding to the target peptide precursor and fragments) and setting its boundaries accurately are crucial. Good signal intensity, co-elution, and peak shape are spectral library-independent parameters that define a good peak. In the case of tSIM/PRM data, both tSIM and PRM peaks must co-elute and share a common peak shape. Additionally, there are several spectral library-based parameters that Skyline displays and that speak of a peak confidence. The correlation between precursor isotope peak intensities and expected isotope distribution (idotp) and the correlation between the peak intensities of the transition and those in the library reference spectrum for that peptide (dotp). Therefore, the idotp is a measure of the tSIM peak confidence, while the dotp is of the PRM peak. 3. Export transitions result using “Export Report” and the “Transition results” template in Skyline. 4. Calculate relative phosphorylation values. Peptide intensities are calculated as the integrated area of the extracted MS1 ion

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chromatograms of the monoisotopic masses of each peptide. Here we recommend to normalize the phosphopeptide of interest to the total abundance of the targeted protein quantified as the sum of three different proteotypic peptides, which are then used as endogenous internal standards. Final relative phosphorylation values can be obtained by comparing the normalized abundance values for untreated and treated samples according to the experimental design (see Note 19).

4

Notes 1. Use HPLC grade reagents. 2. This protein isolation buffer is meant for the extraction of soluble proteins from Arabidopsis leaf samples. The nature of the sample and the protein/s of interest needs to be considered to select a suitable protein isolation method. 3. The Bradford reagent is best suited for protein quantification in this protocol. There are several commercial formulations of the Bradford protein quantification reagent available in the market, but Bradford reagent can also be easily prepared in the laboratory. Dissolve 50 mg of Coomassie Blue G250 in methanol, add 100 mL of 85% H3PO4, mix, add 500 mL of H2O, mix, filter to remove any precipitate or insoluble particle, and add 350 mL of H2O. Store at 4  C protected from light. 4. tSIM and PRM require a high-resolution and mass accuracy instrument such as quadrupole-Orbitrap (Q-OT) or quadrupole-time-of-flight (Q-TOF). 5. Use the same instrument that will be used for the further tSIM/PRM analysis. If it is not possible, use a similar one with the same ionization and fragmentation method. 6. We recommend to start with a wide isolation window, e.g., 5 min, and to adjust it in successive setup runs. However, it can be risky to go below 1 min, although LC systems are nowadays very stable. 7. At least in the Q-Exactive HF software, the isolation list included in the MS method file must include each targeted precursor twice (one for the tSIM and another one for the PRM), so the rows of the table exported from Skyline must be doubled. 8. Try to keep the volume of the protein isolation buffer to the minimum to obtain a homogeneous but concentrated sample. A relatively concentrated sample is important to be able to fit the required volume of sample in an SDS-PAGE well, so that the protein amount required for the preparation of samples for MS analysis can be achieved.

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9. We do not describe any sample fractionation step, but gel fractionation could be implemented here to enrich the sample in the protein/s of interest. Further fractionation methods, such as phosphoenrichment, can be implemented in the protocol as required. 10. Heating the sample can have detrimental effects over PTMs, including phosphorylation. However, it can be necessary to accomplish a correct solubilization of the protein/s of interest. Therefore, we recommend to avoid heating unless it is necessary. 11. Staining of the gels is usually not necessary because plant samples are often colored and therefore visible by eye. Even if the samples are completely transparent, the distortion the protein creates in the gel matrix is usually visible. However, the gel can be stained if judged necessary. In that case, we recommend Coomassie staining. It is easy to perform and, most importantly, compatible with MS. 12. We recommend using 2 mL tubes as they have a round bottom compared to the 1.5 mL ones. This detail is important as a round bottom will prevent the gel pieces from getting stuck during the different shaking steps included in the sample preparation, enhancing the efficiency of these steps. 13. If the gel was stained, gel pieces must be destained before proceeding to the next steps. In the case of Coomassie-stained gel pieces, wash twice with 200 μl of solution containing 0.04 M NH4HCO3/50% ACN for 15 min at 37  C, or as long as required to remove all blue color. 14. An efficient performance of every step is crucial for a good sample preparation and therefore the obtention of high-quality and reproducible results. In this regard, removing every solution completely before adding the next one, although technically trivial, is highly relevant and has a great impact on the final quality of the samples. For example, an efficient protein reduction will be dependent on a good rehydration of the gel pieces with DTT. Any traces of ACN from the previous step will negatively affect the process and as a consequence the reduction as such. The same reasoning applies to every step in the sample preparation for MS analysis. 15. The protocol can be stopped here. Store samples at 20  C and when resuming the protocol shrink gel pieces with 200 μL of 100% ACN to ensure they are completely dehydrated before adding the trypsin solution. Sometimes there is water condensation inside the tubes when they are taken out of the freezer, and gel pieces could hence be incompletely dehydrated, which would have a negative impact over their rehydration with trypsin solution, reducing the digestion efficiency.

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16. In our experience, resuspending the peptides in a volume equal to the μg of loaded protein leads to peptide concentrations between 800 and 900 ng/μL, meaning that the peptide recovery rate is of 80–90%. The resuspension volume can be modified based on this empirical knowledge and depending on the amount of digested protein that will be injected into the mass spectrometer. Foam will be formed during the resuspension in an amount proportional to the protein amount. This is a good resuspension and peptide concentration indicator. Regarding the peptide extraction, the application of vortex, shaking at 37  C and ultrasound baths could theoretically improve the peptide recovery rate. 17. iRT peptides can be spiked in the sample for a better RT prediction during calibration runs. iRT peptides account for variation between LC system as well as LC system intrinsic variation between runs. In general, a better scheduling increases high-throughput potential. We recommend to run a blank with the tSIM/PRM method or with just iRT peptides to empirically measure the duty cycle time of the method and test that it will allow to record enough time points to reliably reconstruct, and therefore quantify, the chromatographic peaks corresponding to the targeted peptides. 18. tSIM and PRM selectivity can be increased by narrowing down the isolation window (as narrow as 0.4 Da in the case of tSIM). In Thermo Fisher Scientific instruments, the sensitivity can be improved by increasing the automatic gain control (AGC) of the number of ions that are accumulated in the C-trap before being transferred to the Orbitrap for MS analysis and/or the dwelling time (maximum injection time, maximum IT, in Thermo instruments). However, it needs to be considered that increasing these parameters slows down the mass spectrometer, meaning longer duty cycles, which can affect the accuracy of peak reconstruction, so of the quantification, and can reduce the number of peptides that can be reliably quantified simultaneously. Furthermore, a too high AGC can lead to detrimental overfilling effects, so this parameter must be finely optimized. 19. MS2-based quantification is also possible. However, the precursor signal detected in MS1 is divided into fragments in the case of MS2, introducing an extra step and a possible bias as a consequence. Nonetheless, in the case of targeted acquisition methods, this bias is expected to be minimum. If the quantification is performed at MS2 level, the consensus is to sum the area of the most abundant fragment or of several of the most abundant ones.

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Acknowledgments Development of the proteomic mass spectrometry method was carried out at the Turku Proteomics Facility, Turku Bioscience, University of Turku, and Åbo Akademi University. The facility is supported by Biocenter Finland. This study was funded by the Academy of Finland (decision numbers 307335, 307719, and 325122). References 1. Lamelas L, Valledor L, Escando´n M et al (2020) Integrative analysis of the nuclear proteome in Pinus radiata reveals thermopriming coupled to epigenetic regulation. J Exp Bot 71: 2040–2057. https://doi.org/10.1093/jxb/ erz524 2. Escando´n M, Valledor L, Pascual J et al (2017) System-wide analysis of short-term response to high temperature in Pinus radiata. J Exp Bot 68:3629–3641. https://doi.org/10.1093/ jxb/erx198 3. Pan R, He D, Xu L et al (2019) Proteomic analysis reveals response of differential wheat (Triticum aestivum L.) genotypes to oxygen deficiency stress. BMC Genomics 20:1–13. https://doi.org/10.1186/s12864-0185405-3 4. Hamzelou S, Pascovici D, Kamath KS et al (2020) Proteomic responses to drought vary widely among eight diverse genotypes of rice (Oryza sativa). Int J Mol Sci 21:363. https:// doi.org/10.3390/ijms21010363 5. Alegre S, Pascual J, Nagler M et al (2016) Dataset of UV induced changes in nuclear proteome obtained by GeLC-Orbitrap/MS in Pinus radiata needles. Data Br 7:1477–1482. https://doi.org/10.1016/j.dib.2016.03.074 6. Pascual J, Alegre S, Nagler M et al (2016) The variations in the nuclear proteome reveal new transcription factors and mechanisms involved in UV stress response in Pinus radiata. J Proteome 143:390–400. https://doi.org/10. 1016/j.jprot.2016.03.003 ˜ al MJ, Escando´n M et al (2017) 7. Pascual J, Can Integrated physiological, proteomic and metabolomic analysis of UV stress responses and adaptation mechanisms in Pinus radiata. Mol Cell Proteomics 16:485–501. https://doi. org/10.1074/mcp.M116.059436 8. Jorrı´n-Novo JV, Pascual J, Sa´nchez-Lucas R et al (2015) Fourteen years of plant proteomics reflected in proteomics: moving from model species and 2DE-based approaches to orphan species and gel-free platforms. Proteomics 15:

1089–1112. https://doi.org/10.1002/pmic. 201400349 9. Waszczak C, Carmody M, Kangasj€arvi J (2018) Reactive oxygen species in plant signaling. Annu Rev Plant Biol 69:209–236. https:// doi.org/10.1146/annurev-arplant042817-040322 10. Foyer CH, Ruban AV, Noctor G (2017) Viewing oxidative stress through the lens of oxidative signalling rather than damage. Biochem J 474:877–883. https://doi.org/10.1042/ BCJ20160814 11. Obata T, Fernie AR (2012) The use of metabolomics to dissect plant responses to abiotic stresses. Cell Mol Life Sci 69:3225–3243. https://doi.org/10.1007/s00018-0121091-5 12. Rasool B, Karpinska B, Pascual J et al (2020) Catalase, glutathione, and protein phosphatase 2A-dependent organellar redox signalling regulate aphid fecundity under moderate and high irradiance. Plant Cell Environ 43:209–222. https://doi.org/10.1111/pce.13669 13. van Wijk KJ, Friso G, Walther D et al (2014) Meta-analysis of Arabidopsis thaliana phospho-proteomics data reveals compartmentalization of phosphorylation motifs. Plant Cell 26:2367–2389. https://doi.org/10.1105/ tpc.114.125815 14. Kadota Y, Liebrand TWH, Goto Y et al (2019) Quantitative phosphoproteomic analysis reveals common regulatory mechanisms between effector-and PAMP-triggered immunity in plants. New Phytol 221:2160–2175. https://doi.org/10.1111/nph.15523 15. Amagai A, Honda Y, Ishikawa S et al (2018) Phosphoproteomic profiling reveals ABA-responsive phosphosignaling pathways in Physcomitrella patens. Plant J 94:699–708. https://doi.org/10.1111/tpj.13891 16. Roustan V, Bakhtiari S, Roustan PJ et al (2017) Quantitative in vivo phosphoproteomics reveals reversible signaling processes during nitrogen starvation and recovery in the biofuel

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model organism Chlamydomonas reinhardtii. Biotechnol Biofuels 10:280. https://doi.org/ 10.1186/s13068-017-0949-z 17. Nakagami H, Sugiyama N, Mochida K et al (2010) Large-scale comparative phosphoproteomics identifies conserved phosphorylation sites in plants. Plant Physiol 153:1161–1174. https://doi.org/10.1104/pp.110.157347 18. Hoffert JD, Knepper MA (2008) Taking aim at shotgun phosphoproteomics. Anal Biochem 375:1. https://doi.org/10.1016/j.ab.2007. 11.023 19. Bekker-Jensen DB, Bernhardt OM, Hogrebe A et al (2020) Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries. Nat Commun 11:1–12. https://doi. org/10.1038/s41467-020-14609-1 20. Steen H, Jebanathirajah JA, Rush J et al (2006) Phosphorylation analysis by mass spectrometry: myths, facts, and the consequences for qualitative and quantitative measurements. Mol Cell Proteomics 5:172–181. https://doi. org/10.1074/mcp.M500135-MCP200 21. Borra`s E, Sabido´ E (2017) What is targeted proteomics? A concise revision of targeted acquisition and targeted data analysis in mass spectrometry. Proteomics 17:1700180. https://doi.org/10.1002/pmic.201700180 22. Konert G, Trotta A, Kouvonen P et al (2014) Protein phosphatase 2A (PP2A) regulatory subunit B0 γ interacts with cytoplasmic

ACONITASE 3 and modulates the abundance of AOX1A and AOX1D in Arabidopsis thaliana. New Phytol 205:1250–1263. https:// doi.org/10.1111/nph.13097 23. Trotta A, Bajwa AA, Mancini I et al (2019) The role of phosphorylation dynamics of CURVATURE THYLAKOID 1B in plant thylakoid membranes. Plant Physiol 181:1615–1631. https://doi.org/10.1104/pp.19.00942 24. Angeleri M, Muth-Pawlak D, Aro EM et al (2016) Study of O-phosphorylation sites in proteins involved in photosynthesis-related processes in Synechocystis sp. strain PCC 6803: application of the SRM approach. J Proteome Res 15:4638–4652. https://doi.org/10. 1021/acs.jproteome.6b00732 25. Vuorijoki L, Isoj€arvi J, Kallio P et al (2016) Development of a quantitative SRM-based proteomics method to study iron metabolism of Synechocystis sp. PCC 6803. J Proteome Res 15:266–279. https://doi.org/10.1021/acs. jproteome.5b00800 26. Gallien S, Duriez E, Crone C et al (2012) Targeted proteomic quantification on quadrupole-orbitrap mass spectrometer. Mol Cell Proteomics 11:1709–1723. https://doi. org/10.1074/mcp.O112.019802 27. Lesur A, Domon B (2015) Advances in highresolution accurate mass spectrometry application to targeted proteomics. Proteomics 15: 880–890. https://doi.org/10.1002/pmic. 201400450

Chapter 18 Quantitative Analysis of Posttranslational Modifications of Plant Histones Hana Kucharˇı´kova´, Zuzana Plsˇkova´, Zbyneˇk Zdra´hal, Miloslava Fojtova´, Pavel Kerchev, and Gabriela Lochmanova´ Abstract Reshaping of the chromatin landscape under oxidative stress is of paramount importance for mounting an effective stress response. Unbiased systemic identification and quantification of histone marks is crucial for understanding the epigenetic component of plant responses to adverse environmental conditions. We describe a detailed method for isolation of plant histones and subsequent bottom-up proteomics approach for characterization of acetylation and methylation status. By performing label-free quantitative mass spectrometry analysis, relative abundances of histone marks can be statistically compared between experimental conditions. Key words Histone posttranslational modifications, Acetylation, Methylation, Mass spectrometry, Histone propionylation, Epigenetics, Arabidopsis, Solanum, Nicotiana

1

Introduction Accumulation of reactive oxygen species (ROS) is a hallmark of various abiotic and biotic stresses. Excessive amounts of ROS can impose damage to DNA, proteins, and redox-sensitive molecules ultimately leading to cell death. Versatile antioxidant systems, however, keep their damaging effects under control and facilitate the execution of ROS signaling cascades by fine-tuned doses of ROS [1]. ROS signaling has been implicated in various biological processes, and its impact on the plant transcriptome has been well documented [2]. Despite the well-defined ROS transcriptional signatures, our understanding of the molecular mechanisms that lead to global transcriptome reprogramming is still limited. Transcriptional responses need to be understood in the chromatin context which impacts the accessibility and effectiveness of the transcriptional machinery [3]. Abiotic and biotic stresses trigger extensive alterations in chromatin features such as histone posttranslational modifications (PTMs) and histone variants that have

Amna Mhamdi (ed.), Reactive Oxygen Species in Plants: Methods and Protocols, Methods in Molecular Biology, vol. 2526, https://doi.org/10.1007/978-1-0716-2469-2_18, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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been proposed to govern global transcriptional responses [4]. Moreover, evidence for a direct impact of ROS on histone modifying enzymes is starting to emerge. The redox-sensitive units of the H3K4-trimethylating complex COMPASS, for example, affect global histone methylation that leads to an increased life span in Caenorhabditis elegans [5]. Comprehensive analysis of changes in global histone marks upon ROS accumulation is imperative for understanding the signaling relays involved in plant responses to adverse environmental conditions. Histone PTMs have been predominantly studied using antibodies that specifically recognize individual histone marks or their combinations. In contrast, novel mass spectrometry-based approaches offer unprecedented and unbiased simultaneous identification and quantification of a wide range of histone marks [6, 7]. Bottom-up proteomics has been particularly used due to its higher sensitivity and standardized data analysis. A crucial step in this process is the chemical derivatization of unmodified and monomethyl histone lysine residues that prevents the generation of short hydrophilic peptides with poor chromatographic properties upon trypsin digestion. Here, we present a detailed protocol for quantitative analysis of PTMs of plant histones, including step-by-step description of the following procedures: nuclei isolation, chemical derivatization of histone proteins and peptides, protein purification and enzymatic digestion, desalting and sample preparation for liquid chromatography-tandem mass spectrometry (LC-MS/MS), LC-MS/MS, and data analysis. The performance of the methodology has been thoroughly examined by Ledvinová et al. [8]. The approach has been successfully used to quantify the impact of genetic and pharmacological perturbations of histone deacetylases on histone marks in Arabidopsis [9].

2 2.1

Materials Plant Material

2.2 Nuclei Enrichment and Histone Extraction

Generally, 0.5–1.0 g of plant material is used per one replicate. At least six replicates per condition are strongly recommended (see Note 1). The protocol was tested on the following plant material: Arabidopsis thaliana (7-day-old seedlings, leaves of 7-week-old plants, siliques, and calli), Solanum lycopersicum (leaves of 7-weekold plants), and Nicotiana benthamiana (leaves of eight-week-old plants). 1. Liquid nitrogen. 2. Mortar and pestle.

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3. Centrifuge (e.g., Eppendorf 5804 R with A-4-44 rotor incl. Adapters for 15/50 mL Falcon tubes and Eppendorf 5427 R with FA-45-30-11 rotor). 4. Standard 15 mL Falcon tubes. 5. Nylon mesh (20
20 cm, pore size 162 μm). 6. Glass funnel (75 mm diameter). 7. Percoll (e.g., P1644, Sigma-Aldrich). 8. Rotator (e.g., Multi RS-60, Biosan). 9. Spectrophotometer (e.g., BioSpectrometer, Eppendorf). 10. Microcuvettes (e.g., BRAND® UV cuvette micro, 759200, Brand). 11. Stock solutions for preparation of working buffers (see Note 2). 12. Extraction buffer 1 (EB1, freshly prepared; 20 mL per sample): Extraction buffer stock solution diluted 5
with deionized water, 100 mM β-mercaptoethanol. 13. Solutions for inhibition of protease and PTM preservation (hereafter referred to as “PTM inhibitors”) (see Note 3). 14. Percoll buffer (freshly prepared; 5 mL per sample) (see Note 4). 15. Washing buffer (WB, freshly prepared; 20 mL per sample) (see Note 5). 16. Extraction buffer 2 (EB2, can be stored at 4  C for several months; 400 μL per sample) (see Note 6). 17. 0.2 M H2SO4 (can be stored at 4  C for several months; 400 μL per sample). 18. Micro BCA™ Protein Assay Kit (23235, Thermo Fisher Scientific) (see Note 7). 2.3 Chemical Derivatization of Histones

1. Mixer (e.g., ThermoMixer C, Eppendorf). 2. Microcentrifuge (e.g., Microfuge 16 Centrifuge, Beckman Coulter). 3. Microcon-10 kDa centrifugal filter unit with Ultracel-10 membrane (Microcon filter unit, MRCPRT010, Millipore). 4. Propionic anhydride 99%. 5. 8 M urea in 0.1 M Tris-HCl, pH 8.0 (UA; freshly prepared). 6. Acetonitrile (ACN, LC-MS grade). 7. 0.5 M stock solution of ammonium bicarbonate (ABC, can be stored at 20  C for several months). 8. Ammonium hydroxide (28% NH3 in H2O). 9. Vacuum concentrator (e.g., Savant SPD121P concentrator, Thermo Fisher Scientific).

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2.4 Sample Preparation for Mass Spectrometry

1. Formic acid (FA, LC-MS grade). 2. Trifluoroacetic acid (TFA, LC-MS grade). 3. Trypsin (sequencing grade modified). 4. Microscale SPE (C-18) extraction tips (see Note 8). 5. Binding solution (BS): 0.1% TFA (370 μL per sample). 6. Elution solution 1 (ES1): 0.1% TFA in 50% ACN (120 μL per sample). 7. Elution solution 2 (ES2): 0.1% TFA in 75% ACN (40 μL per sample).

2.5

LC-MS/MS

1. iRT peptides to monitor system retention characteristics (e.g., iRT kit, Biognosys). 2. C-18 cartridge trap column μ-Precolumn (5 μm particles, ˚ , Thermo Fisher Scientific) (see Note 300 μm
5 mm, 100 A 9). 3. C-18 analytical column Acclaim PepMap 100 (3 μm particles, 75 μm
500 mm, 100 A˚, Thermo Fisher Scientific). 4. LC mobile-phase A: 0.1% (v/v) FA in water (both LC-MS grade). 5. LC mobile-phase B: 0.1% (v/v) FA in 80% ACN in water (all LC-MS grade). 6. High-resolution LC-MS/MS system (see Note 10).

2.6

Data Processing

1. Proteome Discoverer (Thermo Fisher Scientific). 2. Mascot search engine (Matrix Science). 3. Skyline software (MacCoss Lab software, University of Washington).

3

Methods

3.1 Nuclei Isolation and Histone Extraction

It is essential to keep the samples and the solutions between 0–4  C throughout the whole procedure to prevent protein degradation and minimize PTM changes. Day 1: 1. Grind the plant material under liquid nitrogen, and transfer the powder into 15 mL falcon tubes containing 10 mL of cold EB1 supplemented with PTM inhibitors. Homogenize the sample to “soft ice” consistency (see Notes 11 and 12). 2. Filter the homogenate through nylon mesh folded over four times in a glass funnel. Centrifuge for 10 min at 3900
g (4  C).

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3. Wash the pellet thoroughly with 5 mL EB1 and centrifuge (15 min, 3900
g, 4  C). Repeat this step once more with 3 mL EB1. 4. Resuspend the pellet in 2 mL Percoll buffer and centrifuge (15 min, 3900
g, 4  C). 5. Collect the upper layer containing the nuclear fraction together with the Percoll cushion. Transfer it to a new tube and add WB to a final volume of 14 mL. Resuspend the nuclei and centrifuge (5 min, 3900
g, 4  C). Discard the supernatant. 6. Resuspend pelleted nuclei in 1 mL WB. Transfer to a 1.5 mL tube and centrifuge (5 min, 5000
g, 4  C). Discard the supernatant. 7. Resuspend pelleted nuclei in 0.5 mL WB, and centrifuge (5 min, 5000
g, 4  C). Discard the supernatant (see Note 13). 8. Resuspend the pelleted nuclei in 200–400 μL cold EB2 supplemented with PTM inhibitors, incubate for 1 h on ice, and centrifuge (5 min, 10,000
g, 4  C). Discard the supernatant (see Note 14). 9. Resuspend the pelleted chromatin with 200 μL 50 mM Tris–HCl (pH 8.0), and centrifuge (5 min, 10,000
g, 4  C). Discard the supernatant. 10. Resuspend the pelleted chromatin in 200–400 μL ice-cold 0.2 M H2SO4, and incubate overnight on rotator at 4  C (see Note 15). Day 2: 11. Centrifuge the sample (8 min, 16,100
g, 4  C), and collect the supernatant containing histone proteins. 12. Take an aliquot of 3 μL from each sample, dilute to final volume of 50 μL with deionized water, and measure protein concentration using a Micro BCA™ Protein Assay Kit (see Note 16). 13. If desired, the protocol may be interrupted at this stage. Histone extract can be stored at 20  C for several weeks. For an overview of nuclei isolation and histone extraction from plant material, see Fig. 1. Day 3: 3.2 Chemical Derivatization of Lysines (Protein Level)

Chemical derivatization at the protein level is applied to block ε-amino groups of unmodified and monomethyl-lysine residues, giving longer peptides with better chromatographic retention following trypsin digestion.

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Fig. 1 General workflow for nuclei isolation and histone extraction from plant material

Use fume hood for the subsequent steps where propionic anhydride is used. 1. Take an aliquot containing 16 μg of histone protein extract in sulfuric acid, and adjust the pH with ammonium hydroxide to 8 using a pH indicator paper. 2. Prepare derivatization reagent by mixing propionic anhydride with ACN in a 1:3 ratio (v/v); i.e., mix 10 μL of propionic anhydride and 30 μL of ACN, vortex, and spin shortly down. Continue immediately without any interruption (see Note 17). 3. Add ~0.5 μL of ammonium hydroxide to the sample, and immediately add 10 μL of freshly prepared derivatization reagent. Add ~0.5 μL of ammonium hydroxide, check pH using a pH indicator paper, and adjust to 8 with additional ammonium hydroxide. Vortex and spin down shortly. 4. Incubate the samples in a thermomixer for 20 min at 750 rpm and 37  C. 5. Reduce the sample volume to 5 μL in a vacuum concentrator (~50 min). 6. Dilute the sample with 20 μL 50% ACN, and adjust the pH with ammonium hydroxide to 8. 7. Repeat steps 2–4 for the second round of propionylation. 3.3 Protein Purification and Enzymatic Digestion

1. Dilute the sample with 300 μL UA, transfer it to a Microcon filter unit, and centrifuge (~45 min, 14,000
g, RT). Discard the flow-through (see Note 18).

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2. In order to transfer the sample quantitatively, wash the original tube with 200 μL UA, add the solution to Microcon filter unit, and centrifuge (~45 min, 14,000
g, RT). Discard flowthrough fraction. 3. Wash the sample on the filter unit with 200 μL UA, and centrifuge (~45 min, 14,000
g, RT). Discard flow-through fraction (see Note 18). 4. Wash the sample on the filter unit with 100 μL of 100 mM ABC, and centrifuge (30 min, 14,000
g, RT). Discard flowthrough fraction. Repeat this step twice. Transfer the filter unit into a new tube prior to the next step. 5. Add 50 μL of trypsin solution in 100 mM ABC to the sample on the filter unit in an enzyme: protein ratio of 1:40. 6. Seal the vial with parafilm to avoid evaporation. Incubate the sample overnight at 37  C in an incubator with increased humidity (see Note 19). Day 4: 7. Collect the digest by centrifugation (~15 min, 14,000
g, RT), and wash the filter twice with 50 μL of 100 mM ABC. 8. Reduce the sample volume to 20 μL in a vacuum concentrator (~1 h).

3.4 Chemical Derivatization of Peptide N-Termini (Peptide Level)

Post-digestion labelling of newly generated N-termini of histone peptides is applied to improve chromatographic retention and detection during LC-MS/MS. 1. Check the sample pH with a pH indicator paper and adjust to 8 with ammonium hydroxide. 2. Prepare derivatization reagent by mixing propionic anhydride with ACN in the ratio 1:3 (v/v); i.e., mix 5 μL of propionic anhydride and 15 μL of ACN, vortex, and spin shortly down. Continue immediately without any interruption (see Note 17). 3. Add 5 μL of freshly prepared derivatization reagent to the sample. Add 0.5 μL of ammonium hydroxide, check pH using a pH indicator paper, and adjust to 8 with additional ammonium hydroxide, vortex, and spin down shortly. 4. Incubate the sample in a thermomixer for 20 min at 750 rpm and 37  C. 5. Reduce the sample volume to 5 μL in a vacuum concentrator (~20 min). 6. Dilute the sample with 20 μL of 50% ACN, and adjust the pH with ammonium hydroxide to 8. 7. Repeat steps 2–4 for a second round of propionylation.

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Fig. 2 Scheme of histone extract derivatization: from protein to labelled peptides

8. Dry the sample out in vacuum concentrator overnight. 9. If desired, the protocol may be interrupted at this stage. Alkylated peptides can be stored at 4  C for several weeks. The whole derivatization process, from histone extract to labelled peptides, is graphically represented in Fig. 2. Day 5: 3.5 Desalting and Sample Preparation for LC-MS/MS

1. Reconstitute the sample in 60 μL of 50% ACN, and reduce the sample volume to 10 μL in a vacuum concentrator. Add 90 μL of BS to the sample. Check that the pH is below 3 using a pH indicator paper. 2. Rehydrate the HyperSep™ Tip by loading 20 μL of ES1. Spin down in a microfuge (30 s, 1000
g, RT). Discard the flowthrough. Repeat this step four times. 3. Equilibrate the sorbent by loading 20 μL of BS on the HyperSep™ Tip, and spin down in microfuge (30 s, 1000
g, RT). Discard the flow-through. Repeat this step five times. 4. Load 50 μL of the sample on the HyperSep™ Tip, spin down in microfuge (1 min, 600
g, RT). Load another 50 μL of the

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sample on the HyperSep™ Tip; spin down in microfuge (1 min, 600
g, RT). Wash the tube with 20 μL of BS, load the solution on the HyperSep™ Tip, and spin down in microfuge (1 min, 600
g, RT). If required, save the flow-through. 5. Wash the sorbent by loading 20 μL of BS on the HyperSep™ Tip; spin down in microfuge (30 s, 1000
g, RT). Repeat this step five times. Discard the flow-through. Transfer the HyperSep™ Tip to a new collection tube. 6. Elute the sample with 10 μL of ES1 (1 min, 600
g, RT). Repeat this step once more. 7. Perform an additional elution with 20 μl of ES2 (1 min, 600
g, RT). Repeat this step once more. 8. Transfer the sample to an LC vial. Wash the collection tube with 30 μL of ACN, and add the solution to the LC vial. 9. Reduce the sample volume to 12 μL in vacuum concentrator (~15 min) (see Note 20). 10. Acidify the sample with 10% FA to a final concentration of 1%. 3.6

LC-MS/MS

Analyze propionylated peptides using high-resolution LC-MS/MS (see Note 21). 1. Perform chromatographic separation on nano-LC system online connected to mass spectrometer. (a) Equilibrate trap and analytical columns with mobile-phase 1% B at flow rate 500 nL/min and temperature 40  C. (b) Pre-concentrate and further desalt peptides on trap column with mobile-phase 1% B at flow rate 500 nL/min for 5 min. (c) Elute peptides from trap column to analytical column, and separate them using gradient of mobile-phase B: 1% to 70% over 85 min, 70% to 98% over 10 min, and finished with isocratic wash of 98% B for 5 min. 2. Analyze eluting peptides with electrospray ionization mass spectrometry in positive ion mode with data-dependent acquisition (see Note 22). (a) Set cycle time between survey scans (m/z 350–2000) to 3 s survey scan resolution to 60,000 (at m/z 200) with a target value of 4
105 and maximal injection time 54 ms. (b) Select precursors for HCD fragmentation (30% normalized fragmentation energy) in quadrupole: charge state from 2+ to 7+, intensity above 1
104, and isolation window 1.6 m/z. (c) Enable dynamic exclusion for 60 s after one MS/MS spectra acquisition.

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(d) Set ion accumulation for MS/MS analysis to target value of 5
104 or for maximal injection time 500 ms. Acquire tandem mass spectra in orbital trap at resolution 30,000 (at m/z 200) for ions from m/z 110. 3.7

Data Analysis

3.7.1 Peptide Identification

Search data (raw files) in program Proteome Discoverer using Mascot search engine algorithm (Matrix Science). 1. Create histone database for the respective organism. Select histone entries in the UniProt database and export them in FASTA format to create a database on Mascot server. 2. Modify the basic Proteome Discoverer workflows according to your experiment requirements, mainly the processing workflow as follows. 3. Specify the spectrum parameters in spectrum selector node (use MS1 precursors, precursor mass range 350–5000 Da, collisioninduced fragmentation) to select the data from spectrum files node. 4. Use the following databases for searches: cRAP (based on https://www.thegpm.org/crap/), created histone database, and UniProt database of the respective organism (e.g., UniProtKB Arabidopsis thaliana, UniProtKB Solanum lycopersicum, UniProtKB Nicotiana benthamiana) (see Note 23). 5. Define database specific settings, mass error tolerance for precursors (10 ppm for cRAP, 7 ppm for others) and fragments (0.05 Da for cRAP, 0.03 Da for others). 6. Define dynamic modifications for cRAP and UniProt databases, oxidation (M), deamidation (N, Q), acetylation (protein N-term, K), and propionylation (N-term, K), and for created histone database, acetylation (protein N-term, K), methylation (K, R), dimethylation (K), trimethylation (K), phosphorylation (S, T, Y), and propionylation (N-term, K, S, T, Y) (see Note 24). 7. Set enzyme specificity to semi-ArgC with two allowed missed cleavages for all databases (see Note 25). 8. Perform searches against the cRAP database followed by data refinement in fixed value PSM validator node to identify highly confident peptide spectrum matches (PSMs). Filter out cRAP database matches in spectrum confidence filter (settings, worse than high). 9. Perform searches against the histone database followed by data refinement in fixed value PSM validator node to identify highly confident PSMs. Filter out histone database matches in spectrum confidence filter (settings: worse than high).

Quantification of Histone Marks

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10. Perform searches against UniProt database followed by data refinement in percolator node to select PSMs with 1% false discovery rate (q-value