University of Florida Thesis Or Dissertation Formatting

METABOLIC RESPONSES OF CITRUS PLANTS TO THE BACTERIAL PATHOGEN Candidatus Liberibacter asiaticus AND ITS INSECT VECTOR Diaphorina citri

YASSER SOBHY AHMED NEHELA

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2018

To the memory of my mam and my brother Muhammed, who I will never ever forget them, To my beloved wife Doaa for always being there for me with unconditional love, To my children, Lojain, Malek, and Lana whose smiles give me a reason to wake up every day, To my parents and family for their love, endless support, encouragement and sacrifices.

ACKNOWLEDGMENTS

First and foremost, thanks to Allah “Subhanahu Wa Ta’ala”

Completion of this work would not have been successful without the support and guidance of many people who always believed in me and helped me in many ways. I would like to thank my graduate committee who lead me through my graduate program.

First of all, I would like to express my deep and sincere gratitude to my advisor and committee chair, Dr. Nabil Killiny, associate professor, department of plant pathology, CREC-

IFAS-UF, for supporting my academic career since my first steps as a research scholar in UF. I would like to thank him for his perpetual patience and empathy, support, encouragement, scientific guidance, and thoughtful advice toward both personal and professional development. I am highly indebted to his believing in me as a scientist, have confidence in my abilities, and for permitting me to become a member of his team, where I cultivated a wealth of technical skills and a solid research infrastructure to build my academic career. His high ethical standards and respectful views for the others will never be forgotten. without your trust, scientific inputs and personal mentorship, I would not be able to conclude this step.

In addition, I would like to convey my appreciation to my supervisory committee members who contributed to my personal advancement and aided in developing my research program. I would like to thank Dr. Jeff B. Jones - Professor, Department of Plant Pathology, UF for his valuable guidance and support throughout my doctorate. I would like to thank Dr. Bill

Dawson - Eminent Scholar, Department of Plant Pathology, CREC-IFAS-UF for being a great mentor and taking time out of his exceptionally busy schedules to serve on my Ph.D.

Additionally, my sincere thanks go to Dr. Larry W. Duncan - Professor, Department of

Entomology and Nematology, CREC-IFAS-UF for his suggestions, and guidance in composing my research and dissertation.

The conclusion of this step would never be possible without the support of special people. I would like to thank all supportive Killiny’s lab members that I had the privilege to interact and work with them throughout my doctorate. I would like to express my gratitude to my soulmate friend Dr. Faraj Hijaz for technical assistance with lab equipment and methods and for helping me in many personal and family issues since my first day in Florida and during these years abroad. Additionally, I would also like to thank Mrs. Shelley E. Jones for her help throughout my research, showing me the ropes around the lab, sharing her invaluable expertise, and always leading by example. I would also like to thank Floyd Butz and Lorraine Jones for the technical assistance, maintaining the trees in the greenhouse, maintaining the psyllid colonies and making the Killiny’s lab a fun and friendly place to work.

I would like to express my gratitude to my previous supervisors Dr. Hassan El-Zahaby and Dr. Abdelnaser Elzaawely – Department of Agricultural Botany, Faculty of Agriculture,

Tanta University, Egypt for their collaboration, helpful discussions, and support throughout the first steps of my program. In addition, I would like to thank the Cultural Affairs and Missions

Sector, Ministry of Higher Education, Egypt for funding my first two years in the USA as a research scholar. Thanks also are extended to the Egyptian cultural and educational bureau –

Washington DC for their overall concern with me particularly, and other fellows in general.

Lastly, my beloved family deserves the most thanks. They stood with me through the best and worst times. I would like to thank my brother Ramadan who helped me in many ways. My deep thank and love go to my wife, Doaa, who always encouraged me to follow my dream, and without her love and support, I would never be who I am today. Finally, I would like to express my sincere appreciation for everybody who contributes directly or indirectly in this study.

Thanks for all.

TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 10

LIST OF FIGURES ...... 12

LIST OF ABBREVIATIONS ...... 16

ABSTRACT ...... 27

CHAPTER

1 REVIEW OF LITERATURE ...... 29

Introduction ...... 29 The Genus Liberibacter and its Associated Species ...... 30 History of Huanglongbing (HLB) ...... 32 HLB Pathosystem ...... 33 The Causal Agents (Pathogens) ...... 34 The Rutaceous Host Plant(s) ...... 36 The Insect Vector(s) ...... 38 Geographical Distribution of HLB ...... 40 The Geographical Distribution of the Bacterial Pathogens ...... 40 The Geographical Distribution the Insect Vectors ...... 42 Proposed Objectives and Hypotheses of this Study ...... 43 Objective 1: To Understand the Role of Phytohormonal Cross-Talk and its Role in Citrus Response to HLB ...... 43 Sub-objective 1.1: To develop a GC/MS-based method for phytohormone profiling of Citrus sinensis (L.) tissues ...... 43 Sub-objective 1.2: To study the phytohormonal cross-talk that mediates the citrus responses to Ca. Liberibacter asiaticus and its vector D. citri ...... 43 Objective 2: To Study the Role of Citrus Leaf Pigments in Citrus Response to HLB and Disease Symptoms Development ...... 44 Objective 3: To Investigate the Role of Carboxylic Compounds in the Citrus Response to HLB ...... 44 Objective 4: To Study the Effect of CLas-Infection and/or D. citri-Infestation on the TCA Cycle of its Host Plant ...... 44

2 PHYTOHORMONE PROFILING OF THE SWEET ORANGE (Citrus sinensis (L.) OSBECK) LEAVES AND ROOTS USING GC-MS-BASED METHOD ...... 51

Introduction ...... 51 Materials and Methods ...... 52 Plant Materials ...... 52

Extraction of Phytohormones ...... 52 Derivatization of Phytohormones ...... 53 Phytohormones Standards Curves ...... 53 Method Evaluation ...... 53 Extraction recovery ...... 53 Limit of Detection and Limit of Quantification ...... 54 Reproducibility ...... 54 GC-MS Analyses ...... 54 Statistical Analysis ...... 54 Results...... 55 SAs is the Most Abundant Phytohormone Group in Citrus ...... 55 Auxins are Detected in Citrus Leaves only ...... 55 tJA and ABA ...... 55 Cytokinins Levels are Higher in the Root Tips Tissues ...... 56 GAs are Higher in the Root Tips Tissues ...... 56 Discussion ...... 56

3 MULTIPLE PHYTOHORMONAL SIGNALING MEDIATES CITRUS RESPONSES TO Candidatus Liberibacter asiaticus AND ITS VECTOR Diaphorina citri...... 62

Introduction ...... 62 Materials and Methods ...... 66 Plant Materials ...... 66 Analysis of Citrus Phytohormones using GC-MS ...... 67 Analysis of Phenylalanine, Tryptophan, and Linolenic Acid using GC-MS ...... 68 Analysis of Zeaxanthin using HPLC ...... 68 Gene Expression Analysis using Quantitative Real-Time PCR (RT-PCR) ...... 69 Statistical Analysis ...... 69 Results...... 70 Biotic Stresses Altered the Phytohormonal Profile of Citrus Plants ...... 70 Both CLas and D. citri Increased the Auxins Levels in Citrus Leaves ...... 70 CLas-Infection and D. citri-Infestation Increased ABA in Citrus Leaves ...... 71 Salicylic Acid is Associated with Citrus Defense for CLas Infection ...... 71 D. citri-Infestation Increased trans-Jasmonic Acid in Citrus Plants ...... 71 CLas Altered the Balance Between SA and tJA ...... 72 PCA and HCA Reveal Contrasting Phytohormonal-Defense Mechanisms ...... 72 3D Surface Plot Reveals the Correlation between Stress-Associated Phytohormones ...73 CLas-Infection and D. citri-Infestation Altered the Phytohormones’ Precursors ...... 74 CLas and D. citri Altered the Expression of Phytohormones Biosynthetic Genes ...... 74 Discussion ...... 75

4 ONE TARGET, TWO MECHANISMS: THE IMPACT OF Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri ON CITRUS LEAF PIGMENTS...... 92

Introduction ...... 92 Materials and Methods ...... 96 Plant Materials and Growth Conditions ...... 96

Extraction of Citrus Leaf Pigments ...... 97 High-Performance Liquid Chromatography Analysis ...... 98 ABA Determination using ELISA ...... 98 Colorimetric Determination of Starch and Sucrose ...... 99 Gene Expression Analysis ...... 99 Statistical Analysis ...... 100 Results...... 101 CLas and D. citri Alter Citrus Leaf Pigments Content ...... 101 Infection with CLas Increases Zeaxanthin and Decreases other Pigments ...... 102 Infestation with D. citri Increases Chlorophyllide a and Decreases other Pigments ....103 PCA and HCA Analyses Revealed the Differences among Treatments ...... 103 Relationships among Different Citrus Leaf Pigments Groups ...... 104 CLas-Infection Induces the Accumulation of Abscisic Acid and Starch ...... 105 CLas and D. citri Alter the Expression of Genes Implicated in Carotenoids and Chlorophylls Biosynthesis Pathways ...... 105 Discussion ...... 106

5 METABOLOMIC RESPONSE TO HUANGLONGBING: ROLE OF CARBOXYLIC COMPOUNDS IN Citrus sinensis RESPONSE TO Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri ...... 123

Introduction ...... 123 Materials and Methods ...... 127 Plant Materials and Growth Conditions ...... 127 Extraction of Citrus Leaf Metabolites ...... 128 MCF Derivatization of Amino Acids, Organic Acids, and Fatty Acids ...... 128 GC-MS Analyses ...... 129 Peak Identification and Quantification ...... 129 Gene Expression Analysis using Quantitative Real-Time PCR (RT-PCR) ...... 130 Statistical Analysis ...... 130 Results...... 131 CLas-Infection Increased Total Nonpolar AAs, while D. citri-Infestation Increased Total NPAAs and Total FAs ...... 131 CLas-Infection Increased the Amino Acids Abundances ...... 132 CLas-Infection and/or D. citri-Infestation Altered the Organic Acids Profile ...... 132 Fatty Acids Increased upon D. citri-Infestation ...... 133 PCA Analysis Revealed Differences between Citrus Response to CLas and D. citri ..133 3D Surface Plot Analysis Revealed Complex Interactions among AAs, OAs, FAs .....134 CLas and D. citri Altered Genes Expression of SA- and JA-Mediated Pathways ...... 135 Discussion ...... 137

6 Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri, AUGMENTS THE TCA CYCLE OF THEIR HOST VIA THE GABA SHUNT AND POLYAMINES PATHWAY ...... 151

Introduction ...... 151 Materials and Methods ...... 156

Plant Materials and Growth Conditions ...... 156 Analysis of Citrus Leaf NPAAs, PAs and TCA-Associated Compounds ...... 157 Extraction of citrus leaf NPAAs, PAs and TCA compounds ...... 157 Methyl chloroformate (MCF) derivatization of citrus leaf metabolites ...... 157 GC-MS analyses of citrus leaf NPAAs, PAs, and TCA compounds ...... 158 Identification of citrus leaf NPAAs, PAs and TCA compounds ...... 158 In silico Analysis of GABA Permease ...... 159 Gene Expression Analysis using Quantitative Real-Time PCR (qPCR) ...... 160 Statistical Analysis ...... 161 Results...... 162 NPAAs & PAs, PAAs, and TCA-Associated Compounds Detected in Citrus ...... 162 CLas-Infection Induces Greater Changes in the Total NPAAs & PAs, PAAs, and TCA-Associated Compounds ...... 162 CLas-Infection Alters the NPAAs and PAs in Citrus Leaves ...... 163 PCA Reveals Differences in NPAAs and PAs Metabolites ...... 164 CLas-Infection and D. citri-Infestation Alter PAAs of GABA-Shunt ...... 165 CLas-Infection and D. citri-Infestation Alter the TCA-Associated Compounds ...... 165 Citrus Genome Possesses a Putative GABA Permease ...... 165 CLas and D. citri Alter the Genes Expression of GABA-Shunt and PAs Pathway ...... 168 Discussion ...... 169

7 SUMMARY AND CONCLUSION REMARKS ...... 189

Deciphering the Role of Citrus Metabolites in HLB Symptoms Development ...... 189 Citrus Metabolites may Aid the Battle against Huanglongbing ...... 194 Phytohormone-Based Defense Responses ...... 195 Amino Acid-Based Defense Responses ...... 196 Fatty Acids-Based Defense Responses ...... 199 Polyamines-Based Putative Defense Responses ...... 200 Leaf Pigments-Based Defense Responses ...... 201 The Metabolomic Analysis of Citrus Leaf Extract could Help in Culturing of CLas ...... 202

APPENDIX

A SUPPLEMENTARY MATERIALS FOR CHAPTER 2 ...... 208

B SUPPLEMENTARY MATERIALS FOR CHAPTER 3 ...... 214

C SUPPLEMENTARY MATERIALS FOR CHAPTER 4 ...... 220

D SUPPLEMENTARY MATERIALS FOR CHAPTER 5 ...... 224

E SUPPLEMENTARY MATERIALS FOR CHAPTER 6 ...... 229

LIST OF REFERENCES ...... 241

BIOGRAPHICAL SKETCH ...... 274

LIST OF TABLES

Table Page

1-1 Diseases caused by the genus Liberibacter and its associated species, host plants, insect vectors, and geographical regions...... 45

2-1 Identification of phytohormones groups after MCF or MSTFA derivatization in citrus leaves in full-scan GC-MS ...... 59

2-2 Extraction recovery, limit of detection, limit of quantification and method reproducibility of representative phytohormones...... 60

4-1 Gradient profile used in HPLC for citrus leaves pigments determination...... 112

4-2 Chromatographic and spectral characteristics of different investigated pigments in citrus leaves using HPLC...... 113

5-1 Concentrations of different amino acids, organic acids, and fatty acids compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with ACP using GC-MS...... 145

B-1 Concentrations of different gibberellins and cytokinins compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM...... 215

B-2 Primer used for gene expression analysis of trans-jasmonic acid biosynthetic genes by real time RT-PCR...... 216

B-3 Primer used for gene expression analysis of abscisic acid biosynthetic genes by real time RT-PCR...... 217

B-4 Primer used for gene expression analysis of salicylates biosynthetic genes by real time RT-PCR...... 218

B-5 Primer used for gene expression analysis of auxins biosynthetic genes by real time RT-PCR...... 219

C-1 Primer used for gene expression analysis of carotenoids-biosynthetic enzymes by real time RT-PCR...... 220

C-2 Primer used for gene expression analysis of chlorophylls-biosynthetic enzymes by real time RT-PCR...... 222

D-1 Identification and the quantification equations of different carboxylic compounds detected in Valencia sweet orange (C. sinensis) leaves in full-scan GC-MS...... 224

D-2 Primer used for gene expression analysis of Jasmonic acid, salicylic acid, and proline-glutamine pathways by real time RT-PCR...... 226

E-1 Identification of different non-proteinogenic amino acids (NPAAs), polyamines (PAs), TCA-associated compounds and some proteinogenic amino acids (PAAs) detected in Valencia sweet orange (C. sinensis) leaves using GC-MS...... 229

E-2 Sequences producing significant alignments with Bidirectional amino acid transporter 1 of Arabidopsis thaliana (NP_565254.1; 516 aa; aka GABA permease) and used to create Figure E-1 and the phylogenetic tree in FIGURE E-2...... 230

E-3 List of sequences used in Figure E-3...... 231

E-4 Primer used for gene expression analysis of GABA shunt and polyamines biosynthetic enzymes by real time RT-PCR...... 232

LIST OF FIGURES

Figure Page

1-1 The disease pyramid for HLB pathosystem...... 47

1-2 Electron micrographs of ultrathin sections through sieve tubes of leaf midribs from HLB-infected plants...... 48

1-3 The geographical distribution of the HLB-associated pathogens...... 49

1-4 The geographical distribution of the HLB-associated vectors...... 50

2-1 Concentrations of different salicylates, auxins, abscisic acid, and trans-jasmonic acid, cytokinins, and gibberellins in Valencia sweet orange leaves, roots, or root tips using GC-MS-SIM...... 61

3-1 Total concentrations of different phytohormone groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM...... 83

3-2 Concentrations of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM...... 84

3-3 Effect of CLas infection and/or D. citri infestation on the ratio of (SA/tJA) in citrus plants...... 85

3-4 Principal component analysis (PCA) and two-way hierarchical cluster analysis (HCA) of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM...... 86

3-5 Three-dimensional surface plots among stress-associated phytohormones (SA, ABA, tJA) detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri...... 87

3-6 Concentrations of different phytohormones precursors detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri...... 88

3-7 Different biosynthesis phytohormone pathways and their implicated genes detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or infestation with D. citri...... 89

3-8 Hypothetical model of citrus phytohormones-depending defense system against CLas-infection and/or D. citri-infestation...... 91

4-1 Representative HPLC chromatogram of Valencia sweet orange (C. sinensis) leaf pigments after infection with CLas and/or herbivory with D. citri...... 114

4-2 Concentrations of total leaf pigments, pigment group concentrations, and percentage composition for pigment groups of Valencia sweet orange (C. sinensis) after infection with CLas and/or the herbivory with D. citri using HPLC...... 115

4-3 Concentrations of individual leaf pigments detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri using HPLC. .116

4-4 Principal component analysis (PCA) of different leaf pigments detected and quantified using HPLC in Valencia sweet orange (C. sinensis) after infection with CLas and/or herbivory with D. citri...... 117

4-5 Three-dimensional surface plots of leaf pigments groups detected using HPLC in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri...... 118

4-6 The abscisic acid, starch, and sucrose content of Valencia sweet orange (C. sinensis) after the infection with CLas and/or the infestation with D. citri...... 119

4-7 Plant pigment biosynthesis pathways and heat map diagrams of differential biosynthetic gene expression patterns of carotenoids and chlorophylls detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri...... 120

4-8 Schematic representation of a proposed model for the effect of infection with CLas and/or infestation with D. citri on Valencia sweet orange (C. sinensis) leaf pigments and citrus response...... 122

5-1 Concentrations of total amino acid, total fatty acid, and total organic acid groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with ACP using GC-MS-SIM...... 146

5-2 Principal components (PCA) of different citrus leaves amino acids, organic acids, fatty acids and total groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri using GC-MS...... 147

5-3 Three-dimensional surface plots of different citrus leaves amino acid, organic acid, and fatty acid groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri using GC-MS...... 148

5-4 Heat maps with cluster dendrograms of expressed genes involved in JA, SA, proline- glutamine pathways in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri...... 149

5-5 Schematic representation of amino acids, organic acids, and fatty acids biosynthesis and their roles in citrus response to CLas infection and/or D. citri attack...... 150

6-1 Detected proteinogenic amino acids (PAAs), non-proteinogenic amino acids (NPAAs), polyamines (PAs), and tricarboxylic acid- (TCA-) associated compounds of Valencia sweet orange (C. sinensis) leaves after derivatization with MCF...... 178

6-2 Two-way hierarchical cluster analysis (HCA) of individual non-proteinogenic amino acids (NPAAs) and polyamines (PAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS...... 179

6-3 Principal component analysis (PCA) of individual non-proteinogenic amino acids (NPAAs) and polyamines (PAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS. ....180

6-4 Concentrations of individual proteinogenic amino acids (PAAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS...... 181

6-5 Concentrations of different individual tricarboxylic acid- (TCA-) associated compounds detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS...... 182

6-6 In silico analysis of GABA permease of Valencia sweet orange (C. sinensis)...... 183

6-7 Relative gene expression of genes involved in the GABA-shunt and other PAs biosynthetic pathways in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or the infestation with D. citri...... 185

6-8 Hypothetical model of the effect of infection with CLas and/or the infestation with D. citri on the proteinogenic amino acids (AAs), non-proteinogenic amino acids (NPAAs), polyamines (PAs), and tricarboxylic acid- (TCA-) associated compounds of Valencia sweet orange (C. sinensis) leaves...... 187

7-1 Hypothetical model of the potential role(s) of citrus metabolites in the HLB symptoms development...... 205

7-2 Hypothetical model of the potential role(s) of citrus metabolites in citrus response(s) against the infection with CLas and/or the infestation with D. citri...... 206

A-1 GC-MS-SIM chromatograms of detected phytohormones in Valencia sweet orange leaves, roots, and root tips...... 208

A-2 Mass spectra for salicylates group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF...... 209

A-3 Mass spectra for auxins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF...... 210

A-4 Mass spectra for jasmonic acid and abscisic acid obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF...... 211

A-5 Mass spectra for cytokinins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MSTFA...... 212

A-6 Mass spectra for gibberellins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MSTFA...... 213

B-1 Total profile of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with ACP using GC-MS-SIM...... 214

E-1 Multiple sequence alignment of bidirectional amino acid transporter 1 (AtBAT1) of A. thaliana (NP_565254.1; aka AtGABP) and its matched sequences of Valencia sweet orange (C. sinensis)...... 235

E-2 Evolutionary relationships using an unrooted tree of protein sequences of bidirectional amino acid transporter 1 (AtBAT1) of A. thaliana (NP_565254.1; aka AtGABP) and its matched sequences of Valencia sweet orange (C. sinensis)...... 237

E-3 Multiple sequence alignment of the predicted amino-acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP) and the GABP (aka BAT1) protein sequences from various plants species...... 238

E-4 In silico analysis of the predicted amino-acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP)...... 240

LIST OF ABBREVIATIONS

12,13(S)-EOT 12,13(S)-epoxylinolenate

13(S)-HPOTE 13(S)-hydroperoxy-9(Z),11(E),15(Z)-octadecatrienoate

AAs Amino Acids

AB aldehyde Abscisic aldehyde

ABA Abscisic acid

ABI1 Abscisic acid insensitive 1 protein

ABI2 Abscisic acid insensitive 2 protein

ACP Asian citrus psyllid (Diaphorina citri Kuwayama)

AFB Auxin F-Box proteins

AHKs Hybrid histidine protein kinases

AHPs Histidine phosphotransfer proteins

ANOVA Analysis of variance

AOS Allene oxide synthase (A JA-biosynthetic enzyme)

ARFs Auxin response factors

AUX/IAA Aux/IAA proteins

AvrRpt2 The bacterial type III effector or avirulance protein

BA Benzoic acid

BA2H Benzoic acid-2-hydroxylase

B-CoA Benzoyl-CoA

BHT Butylated hydroxytoluene (used as an antioxidant)

BRs Brassinosteroids

CitAAE7 Acetate/butyrate-CoA ligase AAE7

CitAAO3 Abscisic aldehyde oxidase

CitAAT1 Alcohol acyl transferase

CitABA2 Short-chain alcohol dehydrogenase

CitACX1 Acyl-coenzyme A1

CitADT1 Arogenate dehydratase/prephenate dehydratase 1, chloroplastic

CitAIM1 Enoyl-CoA hydratase, mitochondrial-like

CitAIM2 Enoyl-CoA hydratase 2, peroxisomal-like

CitALA δ-Aminolevulinic acid dehydratase 1, chloroplastic-like

CitAOC Allene oxide cyclase

CitAOS Allene oxide synthase

CitASA1 Anthranilate synthase alpha subunit 1

CitASA2 Anthranilate synthase beta subunit 2

CitAST-1 Aspartate aminotransferase, cytoplasmic-like

CitAST-2 Aspartate aminotransferase, chloroplastic-like

CitCAO Chlorophyllide a oxygenase, chloroplastic-like

CitCBR Chlorophyll(ide) b reductase

CitCCS Capsanthin/capsorubin synthase

CitChlase Chloroplast chlorophyllase

CitChlase1 Chlorophyllase-1, chloroplastic-like

CitChlase2 Chlorophyllase-2, chloroplastic-like

CitChlG Chlorophyll synthase, chloroplastic-like

CitCHYb Carotenoid hydroxylase β-ring

CitCM2 Chorismate mutase 2

CitCM3 Chorismate mutase 3

CitCS Chorismate synthase

CitDVR Divinyl chlorophyllide a 8-vinyl-reductase, chloroplastic-like

CitFAD ω-3 Fatty acid desaturase

CitGluTR Glutamyl-tRNA reductase 1, chloroplastic-like

CitGSAT Glutamate-1-semialdehyde 2,1-aminomutase, chloroplastic-like

CitICS2 Isochorismate synthase 2

CitKAT 3-Ketoacyl-CoA thiolase, peroxisomal-like

CitLCYb Lycopene β-cyclase

CitLCYe Lycopene ε-cyclase

CitLHT1 Lysine histidine transporter 1-like

CitLOX Lipoxygenase

CitNCED Putative 9-cis-epoxycarotenoid dioxygenase 3

CitNIT4 Bifunctional nitrilase/nitrile hydratase NIT4A-like

CitNOL CBR-NYC1-Like (NOL), chloroplastic-like

CitNSY Neoxanthin synthase

CitNYC1 CBR-NON-YELLOW COLORING 1 (NYC1), chloroplastic-like

CitOPR3 12-Oxophytodienoate reductase 3

CitP5CDH δ-1-Pyrroline-5-carboxylate dehydrogenase 12A1, mitochondrial-like

CitPAL Phenylalanine ammonia-lyase

CitPDS Phytoene desaturase

CitPOR Protochlorophyllide reductase, chloroplastic-like

CitPPO Protoporphyrinogen oxidase, chloroplastic/mitochondrial-like

CitPPO1 Protoporphyrinogen oxidase 1, chloroplastic-like

CitProDH Proline dehydrogenase 1, mitochondrial-like

CitPYS Phytoene synthase

CitTAA2 Tryptophan aminotransferase-related protein 2-like

CitTAA4 Tryptophan aminotransferase-related protein 4-like

CitTAT Tyrosine aminotransferase

CitTDC1 Tyrosine decarboxylase1

CitTS Tryptophan synthase-like

CitTSA Tryptophan synthase alpha chain, chloroplastic-like

CitTSB Tryptophan synthase beta chain 1, chloroplastic-like

CitVDE Violaxanthin de-epoxidase

CitYUC2 Indole-3-pyruvate monooxygenase YUCCA2

CitYUC8 Indole-3-pyruvate monooxygenase YUCCA8

CitZDS ζ-Carotene desaturase

CitZEP Zeaxanthin epoxidase

CKs Cytokinins

CLaf Candidatus Liberibacter africanus

CLam Candidatus Liberibacter americanus

CLas Candidatus Liberibacter asiaticus

CLbr Candidatus Liberibacter brunswickensis

CLca Candidatus Liberibacter caribbeanus

CLeu Candidatus Liberibacter europaeus

CLps Candidatus Liberibacter psyllaurous

CLso Candidatus Liberibacter solanacearum

Col-0 Arabidopsis thaliana cv. Columbia

CREC Citrus Research and Education Center

CsADC Arginine decarboxylase-like

CsASA Argininosuccinate synthase, chloroplastic

CsASL Argininosuccinate lyase, chloroplastic

CsCS Cysteine synthase

CsDAO D-Amino acid oxidase PA4548

CsEF-1α Elongation factor-1 alpha

CsF-box F-Box/kelch-repeat protein

CsG5K Glutamate 5-kinase

CsGABA-T3 Gamma-aminobutyrate transaminase 3

CsGABP GABA permease (aka amino-acid permease BAT1-like isoform X1)

CsGAD Glutamate decarboxylase-like

CsGAD5 Glutamate decarboxylase 5-like

CsGAPC1 Glyceraldehyde-3-phosphate dehydrogenase, cytosolic (aka GAPDH)

CsGDH1 Glutamate dehydrogenase 1

CsGDH2 Glutamate dehydrogenase 2

CsGS Glutamate synthase [NADH], amyloplastic

CsODC Ornithine decarboxylase-like

CsOTC Ornithine carbamoyl transferase, chloroplastic

CsOXP1 5-Oxoprolinase

CsPAO Polyamine oxidase 1

CsPCP1 Pyrrolidone-carboxylate peptidase 1

CsQPCT Glutaminyl-peptide cyclotransferase

CsSAND SAND family protein

CsSAT1 Serine acetyltransferase 1, chloroplastic-like

CsSAT5 Serine acetyltransferase 5

CsSPDS Spermine synthase

CsSSADH Succinate-semialdehyde dehydrogenase, mitochondrial

CsTDC1 Tyrosine decarboxylase 1

Csγ-GCL Glutamate-cysteine ligase, chloroplastic

Csγ-GCT Gamma-glutamylcyclotransferase

Csγ-GT1-like Gamma-glutamyltranspeptidase 1-like

Csγ-GT3 Gamma-glutamyltranspeptidase 3

Csγ-GT3-like Gamma-glutamyltranspeptidase 3-like

DAMPs Damage-associated molecular patterns

DELLA DELLA protein

DMADP Dimethylallyl diphosphate

DMAPP Dimethylallyl diphosphate

DXP 1-deoxy-D-xylulose 5-phosphate

ELISA Enzyme-linked immunosorbent assay

ER Extraction Recovery

ET Ethylene

ETI Effector-triggered immunity

FAs Fatty Acids

FV/FM Maximal quantum yield of PSII

GA3 Gibberellic Acid

GA4 Gibberellin A4

GA7 Gibberellin A7

GABA γ-Aminobutyric acid

GABA-T GABA aminotransferase

GABP GABA permease

GAD Glutamate decarboxylase

GAI GA-Insensitive

GAs Gibberellins

GC-MS Gas chromatography–mass spectrometry

GC-MS-SIM GC-MS running in the selected ion monitoring mode

GGPP trans-geranyl-geranyl diphosphate

HAMPs Herbivore-associated molecular patterns

HCA Hierarchical cluster analysis

HLB Huanglongbing disease (aka citrus greening disease)

HMBDP 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate

HMG-CoA (S)-3-hydroxy-3-methylglutaryl-CoA

HMGr HMG-CoA reductase

HPLC High Performance Liquid Chromatography

HR Hypersensitive reaction

HTI Herbivore -triggered immunity

IAA Indole-3-acetic acid

IAN Indole-3-acetonitrile

IBA Indole-3-butyric acid

ICA Isochorismate

ICS Isochorismate synthase

IPA Indole-3-propionic acid iPDP N6-(Δ2-isopentenyl)-adenosine 5'-diphosphate

IPL Isochorismate pyruvate lyase iPMP N6-(Δ2-isopentenyl)-adenosine 5'-monophosphate

IPP Isopentenyl diphosphate iPTP N6-(Δ2-isopentenyl)-adenosine 5'-triphosphate

JAs Jasmonates

JAZs Jasmonate-ZIM domain k-PP Keto-phenylpyruvate

LAR Localized acquired resistance

Lcr Liberibacter crescens

LOD Limit of detection

LOQ Limit of quantification

LRIs Linear retention indices

MAMPs Microbe-associated molecular patterns

MAPKs Mitogen-activated protein kinase

MCF Methyl chloroformate

MDP Mevalonate-diphosphate

me-JA Methyl jasmonate

MSTFA N-Methyl-N-(trimethylsilyl) trifluoroacetamide

MTBE Methyl tert-butyl ether

MYCs Myelocytomatosis proteins

NMTβH Unidentified N-methyl-tyramine-β-hydroxylase

NPAAs Non-proteinogenic amino acids

NPQ Non-photochemical quenching

NPRs Nonexpressor of pathogenesis-related proteins1 (aka NIM1)

OAs Organic Acids

OPC3-3-k-CoA OPC3-3-ketoacyl-CoA

OPC8-3-k-CoA OPC8-3-ketoacyl-CoA

OPC8 3-Oxo-2-(cis-2'-pentenyl)-cyclopentane-1-octanoate

OPC8-CoA 3-Oxo-2-(cis-2'-pentenyl)-cyclopentane-1-octanoyl-CoA

OPC8-t-2-e-CoA OPC8-t-2-enoyl-CoA

OPDA 12-Oxo-cis-10,15-phytodienoate (aka 12-Oxophytodienoic acid)

P5C δ1-Pyrroline-5-carboxylate

PAL Phenylalanine ammonia lyase

PAMPs Pathogen-associated molecular patterns

PAs Polyamines

PCA Principal component analysis

PCR Polymerase chain reaction

PDF1.2 Plant defensin 1.2

Pin2 Proteinase inhibitor 2 (A defense transcript in the JA pathway)

PIs Proteinase inhibitors

PNMT Phenylethanolamine N-methyltransferase

PRRs Pattern recognition receptors

PRs Pathogenesis-related genes

PstDC3000 Pseudomonas syringae pv. tomato DC3000

PTI Pattern-triggered immunity (aka PAMP-triggered immunity)

PYL Pyrabactin resistance –like

PYR Pyrabactin resistance

RCAR Regulatory components of ABA receptors

RGA Repressor of GA1-3

RGLs RGA-like1

ROS Reactive oxygen species

RPAs Relative peak areas

RRTs Relative retention times

RSDs Relative standard deviations

RT Retention time

RT-PCR Real-Time PCR

SA Salicylic acid

SAR Systemic acquired resistance

SAs Salicylates

SCFCOI1 Skp1-cullin-F-box complex, coronatine-insensitive protein 1(COI1)

SCFSLY3 Skp1-cullin-F-box complex, F-box proteins SLEEPY1 (SLY1)

SCFTIR1 Skp1-cullin-F-box complex, transport Inhibitor-Response 1 (TIR1)

SIR Systemic induced resistance

SSADH Succinate semialdehyde dehydrogenase tCA trans-Cinamic acid

TCA Tricarboxylic acid cycle

TFs Transcriptional factors

TGAs TGA Transcription factors tJA trans-Jasmonic acid

TMV Tobacco mosaic virus

TNMT Tyramine N-methyltransferase

Tukey HSD Tukey-Kramer honestly significant differences test

Type-B ARRs type B Arabidopsis response regulators tZ trans-Zeatin tZR trans-Zeatin riboside

TβH Tyramine β-hydroxylase

VOCs Volatile organic compounds

WRKYs WRKY transcription factors

ZC Zebra chip disease

ФPSII Electron transport of photosystem II

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

METABOLIC RESPONSES OF CITRUS PLANTS TO THE BACTERIAL PATHOGEN Candidatus Liberibacter asiaticus AND ITS INSECT VECTOR Diaphorina citri

Yasser Sobhy Ahmed Nehela

December 2018

Chair: Nabil Killiny Major: Plant Pathology

Huanglongbing, a destructive citrus disease, is associated with the fastidious bacterium,

Candidatus Liberibacter asiaticus (CLas), and transmitted by the Asian citrus psyllid,

Diaphorina citri. Both CLas and its vector manipulate the host metabolism for their benefit to meet their nutritional needs and/or neutralize the host defense responses. Herein, we used integrative targeted-metabolomic and transcriptomic approaches to study the impact of CLas- infection and/or D. citri-infestation on Valencia sweet orange (Citrus sinensis) leaf metabolites including leaf pigments, phytohormones, carboxylic compounds, TCA-associated intermediates, polyamines, and GABA-shunt. Briefly, while amino acids such as phenylalanine are involved in citrus defense against CLas-infection through the activation of the SA-mediated pathway, fatty acids, were involved in defense against D. citri-infestation via the induction of JA-mediated pathway. Additionally, CLas and D. citri accelerated the conversion of α-ketoglutarate, causing an accumulation of TCA-associated intermediates and GABA. GABA-shunt and PAs pathway are alternative pathways that contribute to the flux towards succinate. In silico analysis showed that citrus genome possesses a putative GABA permease that connects the GABA-shunt with

TCA cycle. Furthermore, Both CLas and D. citri alter the citrus leaf pigments but use two

different mechanisms. While zeaxanthin was accumulated in CLas-infected plants, chlorophyllide a was increased in D. citri-infested ones. Finally, while SA, auxins, and ABA were associated with defense against CLas-infection and tJA was involved in response to D. citri-infestation, both cytokinins and gibberellins did not affect. Gene expression supported the findings from GC-MS and HPLC. Accordingly, we suggest that the citrus metabolic response could be a defensive reaction to defend themselves against CLas and/or D. citri using multifaceted defense systems. Otherwise, it may result from the manipulation of metabolic pathways by CLas and/or D. citri for their benefits to fulfill their nutritional needs or to help the symptoms development. This study provides more insights into citrus responses to HLB, which leads to developing novel strategies for the control of CLas and its vector. Additionally, it could be a further step that providing clues for understanding the nutritional needs of CLas, which could help in culturing CLas in the future.

CHAPTER 1 REVIEW OF LITERATURE

Chapter 1 reviews the history of huanglongbing (HLB) and the components of its pathosystem including the pathogen, host plant, and insect vector. In addition, it reviews the geographical distribution of both pathogen and vector. Finally, it discusses the proposed objectives and hypotheses of this study.

Introduction

The vector-borne phytopathogens have been intensely studied in recent decades because of the high-impact economic losses they cause. Insect-transmitted phytopathogens could be responsible for more than 700 plant diseases worldwide (Killiny 2016), most of them are vascular-limited colonizers. The plant vascular system consists of two different elements that include phloem and xylem. Both phloem and xylem work as transport pathways and provide the nutritional needs of many colonizers (Bové and Garnier 2003; Will et al. 2013; Perilla-Henao and Casteel 2016). However, most of the vascular-limited phytopathogens colonize the phloem vascular system specifically because of its richness in amino acids, proteins, sugars, and others

(Bové and Garnier 2003; Lough and Lucas 2006). These pathogens include numerous viruses, bacteria, mollicutes (such as spiroplasma and phytoplasma), and fungi (Eigenbrode et al. 2018).

In addition to the phytopathogenic microbes, several sap-sucking hemipterans, such as aphids, psyllids, whiteflies, and leafhoppers rely mainly on the phloem contents for their primary nutritional needs (Perilla-Henao and Casteel 2016). Insects from order “Hemiptera” can transmit a wide range of pathogens in animals and plants (Purcell 1982). However, regarding the vector specificity, a few hemipterans are able to transmit bacterial pathogens, while the majority are vectors for viral diseases (Perilla-Henao and Casteel 2016). Nevertheless, recently, insect- transmitted bacterial pathogens and their vectors have caused many devastating diseases in both

perennial and annual crops worldwide. The vector-borne bacterial pathogens, including Xylella fastidiosa, Spiroplasma spp., Candidatus Liberibacter spp., and ‘Ca. Phytoplasma spp.

The Genus Liberibacter and its Associated Species

Currently, Ca. Liberibacter spp. are associated with several diseases of both perennial and annual crops in different families (Table 1-1). Liberibacter crescens (Lcr), the only cultured

Liberibacter species until now (Wang et al. 2017), was isolated from Mountain papaya

(Vasconcellea pubescens; Caricaceae) (Leonard et al. 2012). Although other Ca. Liberibacter species are not cultured yet, sufficient evidence has established Ca. Liberibacter spp. as the causal agents of HLB, Zebra chip (ZC), and several other plant diseases (Table 1-1).

Ca. L. americanus (CLam), Ca. L. asiaticus (CLas), and Ca. L. africanus (CLaf) causing the Huanglongbing disease (HLB; aka citrus greening) on citrus and its relatives (Rutaceae)

(McClean and Oberholzer 1965; Capoor et al. 1967; Jagoueix et al. 1994; Garnier et al. 2000a;

Teixeira et al. 2005b; Cen et al. 2012; Bové 2006). In addition, CLaf can infect several species from the family Rutaceae including Ca. L. africanus capensis (CLafC) on cape chestnut

(Calodendrum capense) (Garnier et al. 2000b), Ca. L. africanus zanthoxyli (CLafZ) on small forest knobwood (Zanthoxylum sp.) (Roberts et al. 2015), Ca. L. africanus vepridis (CLafV) on white ironwood (Vepris lanceolata ) (Roberts et al. 2015), Ca. L. africanus tecleae (CLafT) on flaky cherry-orange (Teclea gerrardii) (Roberts et al. 2015), and Ca. L. africanus clausenae

(CLafCl) on horsewood (Clausena sp.) (Roberts and Pietersen 2017), and citrus expressing typical HLB symptoms (Roberts et al. 2017) (Table 1-1).

Ca. L. solanacearum causes the zebra chip disease on potatoes (Solanum tuberosum;

Solanaceae) (Hansen et al. 2008; Liefting et al. 2008; Liefting 2009; Nelson et al. 2011).

Additionally, CLso can cause multiple symptoms on various apiaceous crops including carrots

(Daucus carota; Apiaceae), celery (Apium graveolens; Apiaceae), parsnip (Pastinaca sativa;

Apiaceae), and parsley (Petroselinum crispum; Apiaceae) (Munyaneza et al. 2010a; Alfaro-

Fernández et al. 2012b, 2017; Vereijssen et al. 2018; EPPO 2015, 2018a, 2018c). Five haplotypes were described within the CLso species. The designated haplotypes CLso-A and

CLso-B can infect solanaceous plants in North America (Nelson et al. 2011; Vereijssen et al.

2018), while the haplotypes CLso-C, CLso-D, and CLso-E can infect apiaceous crops in Europe

(Munyaneza et al. 2010b, 2012a, 2012b, 2015, Nelson et al. 2011, 2013, Alfaro-Fernández et al. 2012a, 2017; Loiseau et al. 2014; Tahzima et al. 2014; Teresani et al. 2014, 2015; Hajri et al.

2017; Holeva et al. 2017; EPPO 2018b; Vereijssen et al. 2018) (Table 1-1).

Ca. L. europaeus (CLeu) was identified from asymptomatic trees of apple (Malus domestica; Rosaceae), blackthorn (Prunus spinosa; Rosaceae), hawthorn (Crataegus monogyna;

Rosaceae), and pear (Pyrus sp. ; Rosaceae) from Italy, Hungary (Raddadi et al. 2011), and also from scotch broom plants (Cytisus scoparius; Fabaceae) that showed multiple symptoms in

Australia, Europe, and New Zealand (Thompson et al. 2013). Likewise, Ca. L. brunswickensis

(CLbr) was identified from asymptomatic eggplant (Solanum melongena; Solanaceae) and cape gooseberry (Physalis peruviana; Solanaceae) from Australia (Morris et al. 2017)(Table 1-1). Ca.

L. caribbeanus (CLca) was identified from HLB-symptomatic sweet orange (Citrus sinensis;

Rutaceae) and orange jessamine (Murraya paniculate; Rutaceae) trees from Colombia, South

America (Keremane et al. 2015). Furthermore, Ca. L. psyllaurous (CLps) was identified from potato (Solanum tuberosum; Solanaceae) and tomato (Solanum lycopersicon; Solanaceae) plants that showed psyllid yellows disease in Texas, USA (Hansen et al. 2008). Interestingly, CLps is considered as a synonym for CLso haplotype A (Nelson et al. 2011), which showed an identical

16S rRNA genes. In all known Ca. Liberibacter-associated pathosystems, specific psyllids

(Haapalainen 2014), have been identified as the vectors (Wang et al. 2017) (Table 1-1).

Among the diseases caused by Ca. Liberibacter spp., HLB has rapidly spread across different geographical regions worldwide (Gottwald 2010) and become the point of interest of many researchers worldwide because it causes dramatic economic losses to citrus industries

(Wang et al. 2017). As a result of HLB, Florida growers lose over four billion U.S.D. annually, thousands of citrus industry workers lost their jobs (Gottwald 2010).

History of Huanglongbing (HLB)

The origin of HLB is a matter of intense debate. Some scientists believe that it originated in China (Reinking 1919; Lin 1956), while others insist that it was described initially in India

(Husain and Nath 1927; Capoor 1963; Beattie et al. 2008). As for the first party, they believe that

HLB originated in southern China in the late 1800s (Reinking 1919; Zhao 1981) where farmers observed a yellowing and leaf mottle symptoms on their citrus plants. HLB was described in the

Chaozhou district of southern China in 1956 (Lin 1956), where it was called by its Chinese name

“Huang Long Bing” since the late 19th century (Zhao 1981) and translated into “yellow dragon disease” in English (Halbert and Manjunath 2004). However, “Huang” meaning yellow, “Long” meaning shoot, “Bing” meaning disease, therefore, it was described as the “yellow shoot disease” in English (Lin 1956; Zhao 1981). In 2006, it was confirmed that the precise meaning of

“Long” is “shoot” in the Chinese language in the area where the disease was first observed

(Zhao 2006). Many researchers immortalized this theory (da Graça 1991; da Graça and Korsten

2004; Bové 2006; Gottwald 2010; Wang and Trivedi 2013).

On the other hand, the second party provides convincing evidence that HLB was described first in India (Husain and Nath 1927; Capoor 1963; Beattie et al. 2008). In India, several citrus decline/dieback problems were reported in the central provinces (in the 18th century), Assam province (in the late 19th century), and in the early 20th century in Bombay province (Capoor 1963). The reason(s) behind these problems was unknown, however, Capoor

attributed these symptoms to Citrus tristeza virus based on his biological indexing studies

(Capoor 1963). Later, it was shown that HLB was a major component of these problems

(Raychaudhuri et al. 1969, 1974). Furthermore, some citrus tree-damage problems, including decline and dieback, were reported in Punjab province, India in 1927 (Husain and Nath 1927).

They thought that these problems were caused by psyllid feeding (Husain and Nath 1927).

However, it resembled the description of HLB symptoms, particularly their description of

“insipid fruit” symptom (Husain and Nath 1927). This may be the first report of citrus psyllid to be associated with the HLB symptoms. Taken together, HLB was reported in India (as citrus dieback) before being spread to China (Gottwald et al. 2007).

HLB was detected in South America, in São Paulo, Brazil, in 2004 and in North America, in South Florida, the United States, in 2005 (Bové 2006; Gottwald 2010; Wang and Trivedi

2013). In August 2005, HLB was first confirmed in south Miami-Dade County in Florida, seven years after the first detection of its vector in 1998. HLB has been discovered in Louisiana

(2008), South Carolina and Georgia (2009), and recently, in Texas and California (2012) (Wang and Trivedi 2013). Additionally, it has been recorded in many Caribbean countries such as;

Belize, Cuba, Mexico, and Jamaica (Wang and Trivedi 2013).

HLB Pathosystem

Because HLB is a vector-borne disease, therefore, its development and epidemiology rely on more than the temporal and spatial convergence of a susceptible host, a virulent pathogen, and an environment favorable for disease development, which is referred to as the disease triangle

(Francl 2001). The epidemiological outcomes for HLB disease are determined by the interactions among the host plant, vector insect, bacterial pathogen, and various environmental factors and it is thus better to be described as a disease pyramid (Figure 1-1) rather than disease triangle, with

psyllids as an extra necessary component (Wang et al. 2017). Nevertheless, HLB pathosystem consists of three major components including the host plant, the pathogen, and the vector.

The Causal Agents (Pathogens)

Although Koch’s postulates of HLB have not been fulfilled yet due to the difficulty in culturing the putative bacterium, several pieces of evidence indicate that HLB is associated with a plant fastidious, phloem-limited, pathogenic bacterium given provisional Candidatus status,

Candidatus Liberobacter spp., a member of gram-negative α-proteobacteria, later changed to

Candidatus Liberibacter spp. (Jagoueix et al. 1994; Garnier et al. 2000b; Bové 2006; Gottwald

2010). Taxonomically, three bacterial species have been proposed to be associated with HLB based on the geographical distribution and the characteristic 16S rDNA sequence (Bové and

Ayres 2007; Tatineni et al. 2008; Gottwald 2010; Wang and Trivedi 2013). Ca. L. asiaticus

(CLas) is a heat-tolerant species spreading in Arabian Peninsula, Africa, Asia, and

Americas; Ca. L. americanus (Clam) is a heat-tolerant species spreading only in Brazil, and

Ca. L. africanus (CLaf) is a heat-sensitive species spreading in numerous countries in Africa (da

Graça 1991; Teixeira et al. 2005b; Bové 2006; Bové and Ayres 2007; Tatineni et al. 2008;

Gottwald 2010; Wang and Trivedi 2013). Among the three Ca. Liberibacter species, CLas is the dominant species and is causing huge economic losses to citrus production worldwide (Bové

2006; Gottwald 2010). The tree-to-tree transmission of Ca. Liberibacter could be by graft inoculation, and they are mainly transmitted by citrus psyllid insect vectors (Halbert and

Manjunath 2004); however, there is no evidence for transmission by seeds.

CLas is restricted to the sieve tubes of the phloem of infected plants. Transmission electron microscopy (TEM) studies revealed CLas was observed in two different shapes

(elongated bacilliform-like/ sinuous rods and pleiomorphic round/spherical shapes) (Garnier and

Bové 1983; Garnier et al. 1984; Teixeira et al. 2005a; Folimonova and Achor 2010; Hartung et

al. 2010; Shokrollah et al. 2010; Hilf et al. 2013) (Figure 1-2A). Interestingly, both shapes were observed in HLB-symptomatic Periwinkle (Vinca rosea) leaf midribs (Garnier and Bové 1983;

Garnier et al. 1984), Madam Vinous sweet orange (Citrus sinensis) leaves (Garnier and Bové

1983; Garnier et al. 1984), mandarin orange (C. reticulata) leaves (Shokrollah et al. 2010), and the vascular bundle of grapefruit (C. paradise) and ‘Liane’ pummelo (C. grandis) seed coats

(Hilf et al. 2013).

The length of elongated bacilliform-like particles ranged from 0.59 to 1.36 μm (~ 0.93

μm) and its width ranged from 0.20 to 0.81 μm (~ 0.41 μm) (Shokrollah et al. 2010). However, several studies reported that the bacilliform cells could have an uneven diameter within the ranges of 0.14-0.26 µm (Garnier and Bové 1983; Garnier et al. 1984; Teixeira et al. 2005a;

Folimonova and Achor 2010; Hartung et al. 2010; Hilf et al. 2013). On the other hand, the round bacterial cells appear larger than the transverse sections of the bacilliform shapes and had a diameter within the range of 0.30 to 0.99 μm (Hilf et al. 2013). Round forms could be observed in degenerating cells and were similar to those seen in citrus, dodder, and periwinkle plants in previous studies (Garnier and Bové 1983; Folimonova and Achor 2010; Hartung et al. 2010)

(Figure 1-2A).

At higher magnification of TEM, a thick envelope of 25 nm (~250 Å) was clearly visible in both shapes (Garnier and Bové 1983; Garnier et al. 1984)(Shokrollah et al. 2010) (Figure 1-

2B). Thin TEM sections examination reveals that the envelope of CLas is a double membrane structure, which consists of an outer and an inner membrane (cytoplasmic membrane) (Garnier and Bové 1983; Garnier et al. 1984; Teixeira et al. 2005a; Shokrollah et al. 2010) (Figure 1-2C).

The outer and inner membranes of the round forms were often separated over a certain length, suggesting that plasmolysis could have occurred (Garnier and Bové 1983). Furthermore, between

these two membranes an electron-dense layer similar to the peptidoglycan layer of certain Gram- negative bacteria was seen occasionally (Garnier and Bové 1983; Garnier et al. 1984) (Figures 1-

2D to 1-2F). The presence of a peptidoglycan layer has been confirmed by treating the bacterial cells from infected tissues with papain and lysozyme as described for Escherichia coli (de Petris

1967). This treatment showed that the envelope of the CLas is triple-layered structure is indistinguishable from that of E. coli and has a peptidoglycan layer located between the outer and the inner membranes like Gram-negative bacteria (Garnier and Bové 1983; Garnier et al.

1984; Shokrollah et al. 2010) (Figures 1-2D to 1-2F).

The Rutaceous Host Plant(s)

Huanglongbing is a disease of rutaceous plants that can infect most, if not all, citrus cultivars, hybrids, and some relatives. The genus Citrus belongs to family Rutaceae, sub-family

Aurantoideae (Tanaka 1977). The citrus genus has many important species such as pomelo

(Citrus maxima Merr., aka C. grandis), citron (C. medica L.), papeda citrus (Citrus micrantha), mandarin orange (C. reticulata Blanco) kumquats (C. japonica Thunb.), byeonggyul (C. platymamma Hort. ex Tanaka), and poncirus or trifoliate orange (C. trifoliata, aka Poncirus trifoliata (L.) Raf.). In addition, it has many hybrids including key lime (Citrus × aurantiifolia

(Christm.) Swingle), bitter orange (Citrus × aurantium L.), persian lime (Citrus × latifolia

Tanaka), lemon (Citrus × limon (L.) Osbeck), rangpur (Citrus × limonia Osbeck), grapefruit

(Citrus × paradisi Macfad.), sweet orange (Citrus × sinensis (L.) Osbeck), and tangerine (Citrus

× tangerine Tanaka). HLB severely affects sweet orange, mandarin and tangelo trees; however, many other species show different degrees of tolerance to the disease. Mexican lime (Citrus × aurantiifolia Swingle) is less susceptible than sweet orange and mandarin orange even though it is a preferred host of the vector D. citri (Bové and Garnier 1984).

In addition, several other genera in the Rutaceae family can harbor HLB including;

Atalantia monophylla, Balsamocitrus sp., cape chestnut (Calodendrum capense) (Garnier et al.

2000a, 2000b), Chinese box-orange (Severinia buxifolia), flaky cherry-orange (Teclea gerrardii)

(Roberts et al. 2015), horsewood or wampi (Clausena sp.) (Roberts and Pietersen 2017), limeberry (Triphasia trifolia), orange jasmine (Murraya paniculata), small forest knobwood

(Zanthoxylum sp.) (Roberts et al. 2015), and white ironwood (Vepris lanceolata ) (Roberts et al.

2015). Additionally, Toddalia lanceolate, which was infected by CLaf, was found as a host of the African citrus psyllid, Trioza erytreae (Korsten et al. 1996). Interestingly, M. paniculate and

S. buxifolia also are considered alternate host plants for the vector D. citri. However, a proposed strain of CLam has been identified in M. paniculata in Brazil (Coletta-Filho et al. 2005) and M. paniculata was found to be naturally infected with CLas in Florida (Zhou et al. 2007).

Furthermore, the three Ca. Liberibacters that infect citrus plants could be transmitted to

Madagascar rosy periwinkle (Vinca rosea, aka Catharanthus roseus; family Apocynaceae) plants by dodder (Cuscuta campestris) (Garnier and Bové 1983; Zhou et al. 2007; Bové 2006).

Cuscuta sp. could transmit CLas to tobacco (Nicotiana xanthi) (Garnier and Bové 1983; Bové

2006; Zhou et al. 2007) and tomato (Lycopersicon esculentum) (Duan et al. 2008), indicate that

CLas can infect solanaceous plants.

Currently, no commercial citrus cultivars are fully tolerant to HLB, however; several reports indicate that some citrus species are more tolerant to HLB than others (Folimonova et al.

2009; Albrecht and Bowman 2012; Cevallos-Cevallos et al. 2012; Killiny et al. 2017b, 2018a).

For instance, the mandarin hybrid ‘Sugar Belle®’ (previously known as LB8-9) as scion, on the sour orange rootstock, was potentially tolerant and maintained a healthy appearance and good yield over a five-year study (Stover et al. 2016). Surprisingly, both Sugar Belle’s parents

[‘Clementine’ mandarin (C. reticulata) × ‘Minneola’ tangelo (Citrus × Tangelo)] × [‘Duncan’ grapefruit (Citrus paradisi) × ‘Dancy’ tangerine (Citrus reticulata)] are HLB-susceptible cultivars (Folimonova et al. 2009; McCollum et al. 2016; Killiny et al. 2017b). Recently, Killiny and his group compared the volatile organic compounds and non-volatile leaf metabolite profiles of Sugar Belle® mandarin hybrid and its parents (‘Clementine’ mandarin, ‘Minneola’ tangelo,

‘Duncan’ grapefruit, and ‘Dancy’ tangerine) (Killiny et al. 2017b) or Sugar Belle® with HLB- tolerant cultivar- Australian finger lime, and a recently released mandarin hybrid ‘Bingo’(Killiny et al. 2018a) to identify compounds related to HLB tolerance.

The Insect Vector(s)

Although Ca. Liberibacter spp. could be transmitted by graft inoculation, they are mainly transmitted by psyllids (Halbert and Manjunath 2004). HLB is transmitted by two insect vectors; the African citrus psyllid, Trioza erytreae Del Guercio (Hemiptera: Triozidae), which transmits

CLaf in Africa (McClean and Oberholzer 1965; Bové 2006) and the Asian citrus psyllid,

Diaphorina citri Kuwayama (Hemiptera: Liviidae), which transmits both CLas and Clam in

Asia (Capoor et al. 1967; Martinez and Wallace 1967; Bové 2006) and recently has spread to other citrus growing regions. Globally, D. citri, a phloem-sucking insect, may be the most serious pest of citrus, particularly when CLas or CLam also are present (Halbert and Manjunath

2004) because it harms the new leaves and fruits in addition to its ability to transmit CLas.

D. citri transmits CLas in a circulative propagative manner (Hall et al. 2013). The circulative transmission means that CLas undergo part of its lifecycle within the body of D. citri, usually circulating within the hemolymph (aka haemolymph), trafficking to the salivary glands, and finally being injected with saliva into a new plant host during feeding (Fletcher et al. 1998).

The propagative/ persistent transmission means that CLas is able to multiply/replicate inside insect body, within the hemocoel (Fletcher et al. 1998). In this type of transmission, the insect

vector can transmit the pathogen for its whole life (Fletcher et al. 1998). Briefly, D. citri acquires CLas bacterium during feeding on the phloem sap of infected plants (acquisition). The acquired bacterial cells are trafficking from the gut to hemolymph, then to the salivary glands and other tissues. Finally, CLas can be inoculated into a susceptible plant with the saliva during subsequent feeding (Hall et al. 2013). The inoculation course could take 30 min of feeding or may take up to an hour of feeding if during an incubation period (3-20 days) (Xu et al. 1988;

Pelz-Stelinski et al. 2010). CLas multiplies in both nymphs and adult psyllids (Ammar et al.

2016) indicating that the hemolymph of D. citri contains all the necessary nutrition needed for

CLas propagation (Hall et al. 2013). In addition, CLas presumably multiplies within the vector

(Xu et al. 1988; Ammar et al. 2011; Inoue et al. 2009; Ammar et al. 2016) and can be sexually transmitted from male to female insects during courtship (Mann et al. 2011).

Our knowledge about the nature of CLas-D. citri interaction(s) is still limited, not fully understood and is not without controversy (Ammar et al. 2011; Pelz-Stelinski and Killiny 2016).

In addition, these interactions are difficult to study because the pathogenic bacteria have not been cultured yet (Perilla-Henao and Casteel 2016). However, these interactions extend from mutually advantageous to harmful (Pelz-Stelinski and Killiny 2016). The mutually beneficial interactions between CLas and D. citri were reported previously. For instance, CLas-infection increased the reproductive fitness of its vector, D. citri (Pelz-Stelinski and Killiny 2016). On the other hand, several previous studies emphasized the harmful/negative relationship in the case of the CLas-D. citri pathosystem. For example, CLas-infection increased the propensity for dispersal of D. citri

(Martini et al. 2015), increased susceptibility to insecticides due to the reduction of total protein content and general esterase activity (Tiwari et al. 2011) (Kruse et al. 2017), and decreased the survival and lifespan of CLas-infected psyllids (Pelz-Stelinski and Killiny 2016; Nehela and

Killiny 2018). In addition, CLas-infection negatively affected the defence responses of its vector

D. citri (Lu and Killiny 2017), suppressed insect’s immune system (Kruse et al. 2017), and exploited its tricarboxylic acid (TCA) cycle metabolic pathway (Killiny et al. 2018b; Kruse et al.

2017) and energy metabolism (Lu and Killiny 2017).

Geographical Distribution of HLB

Generally, the Asian form of HLB, Ca. Liberibacter asiaticus (CLas), is the most severe and geographically widespread (Bové 2006; Gottwald 2010; Wang and Trivedi 2013). It occurs throughout Asia, Arabian Peninsula, Africa, and Americas (Bové and Garnier 1984; Coletta-

Filho et al. 2004; Halbert 2005; Bové 2006; Gottwald 2010; Wang and Trivedi 2013;

OEPP/EPPO 2014). CLas distribution is typically associated with the distribution of its vector

Asian citrus psyllid, D. citri (Figures 1-3 and 1-4). On the other hand, the African form of HLB,

Ca. Liberibacter africanus is less severe and more restricted geographically. CLaf was found in

Africa and Asia ( only in Saudi Arabia and Yemen) (OEPP/EPPO 2014) and its distribution is typically associated with the distribution of its vector African citrus psyllid, T. erytreae.

Furthermore, the third form, Ca. L. americanus (CLam; American greening) was reported only in

Brazil and found to be transmitted by the Asian citrus psyllid (Figures 1-3 and 1-4).

The Geographical Distribution of the Bacterial Pathogens

In Asia, CLas was reported in China (Reinking 1919; Lin 1956; Zhao 1981), India

(Husain and Nath 1927; Capoor 1963; Beattie et al. 2008), Indonesia, Japan, Malaysia, Pakistan,

Philippines, Taiwan, Thailand, and Vietnam (OEPP/EPPO 2014) (Figure 1-3). It was also reported in Arabian peninsula including; Saudi Arabia, Syria, and Yemen (Bové and Garnier

1984; OEPP/EPPO 2014) and recently it is restricted-distributed in Iran (Faghihi et al. 2009;

Mohkami et al. 2011; Salehi et al. 2012; OEPP/EPPO 2014). On the other hand, CLaf (the

African form) was less severe in Asia and more restricted geographically, where reported only in

Saudi Arabia and Yemen (OEPP/EPPO 2014) (Figure 1-3)

In Africa, CLas was found to be present only in Ethiopia (Saponari et al. 2010) and restricted-distributed in Mauritius and Réunion (OEPP/EPPO 2014) (Figure 1-3). However, CLaf is more common in Africa than CLas, where it was found throughout eastern, central, and southern Africa (Figure 1-3). CLaf is present in Burundi, Cameroon, Central African Republic,

Comoros, Ethiopia, Kenya, Madagascar, Malawi, Mauritius, Réunion, Rwanda, Somalia,

Tanzania, Zimbabwe and South Africa (McClean and Oberholzer 1965; Jagoueix et al. 1994;

Garnier et al. 2000a) (Roberts et al. 2017) and recently was reported in Uganda, Kenya, and

Tanzania (Roberts et al. 2017)

In Americas, CLas was reported in South America in Brazil in 2004 (Coletta-Filho et al.

2004), then in North America in Florida, USA in 2005 (Halbert 2005; Bové 2006; Gottwald

2010; Wang and Trivedi 2013). Subsequently, CLas has spread all over the Central America and

Caribbean countries including Cuba in 2007 (Martínez et al. 2009), Dominican Republic in 2008

(Matos et al. 2009), Belize and Puerto Rico in 2010 (Manjunath et al. 2010; Estévez de Jensen et al. 2010), and then to Barbados, Costa Rica, French West Indies, Guadeloupe, Honduras,

Jamaica, Martinique, Nicaragua, and United States Virgin Islands (Cellier et al. 2014;

OEPP/EPPO 2014) in a relatively short period of time. In addition, the Ca. Liberibacter americanus (American greening pathogen) was only found in Sao Paulo, Brazil (Texeira et al.

2005) (Teixeira et al. 2008) (Figure 1-3). In the United States, after reported HLB in Florida in

2005 (Halbert 2005), it has been found in Louisiana in 2008 (Hummel and Ferrin 2010), Georgia and South Carolina in 2009 (Wang and Trivedi 2013), Texas in 2012 (Kunta et al. 2012), and most recently in California in 2013 (Kumagai et al. 2013).

The Geographical Distribution the Insect Vectors

Generally, the distribution of both D. citri and T. erytreae is typically associated with the distribution of its associated bacterial pathogens (CLas/CLam and CLaf, respectively) (Figure 1-

3 and Figure 1-4). Asian citrus psyllid, D. citri, exists primarily in tropical and subtropical areas of Asia and the Americas (Halbert and Núñez 2004). However, the distribution of D. citri is wider than the distribution of the pathogens which it transmits (CLas and CLam). For example, in addition to the geographical areas of CLas and CLam, D. citri occurs in Afghanistan, Macau, and Singapore where the bacterium has not been recorded. In the United States, D. citri was firstly detected in Florida in 1998 and recently was found in Louisiana, Georgia, South Carolina, and Texas. In addition, D. citri was recorded in some CLas-free states such as Alabama, Arizona,

Guam, Hawaii, and Mississippi (Figure 1-3). Therefore, National quarantine boundaries and eradication program have been instituted to prevent further spread of D. citri (USDA 2010).

Although CLaf is a heat-sensitive vector, and it is affected by hot and dry conditions

(Green and Catling 1971), CLaf in mainly spread in the tropical and subtropical areas of Africa

(Figure 1-4). The distribution of African citrus psyllid, T. erytreae, is associated with the distribution of its pathogen, CLaf and mainly focused on Africa. However, the geographical distribution of T. erytreae is wider than CLaf, the major pathogen it transmits. For instance, T. erytreae was recorded in the Congo Democratic Republic, St. Helena, Sudan, Uganda, Zambia and, recently, Madeira, where CLaf has not been recorded. In addition, CLaf was found in

Europe in Spain (Siverio et al. 2017), Italy, Netherlands, Portugal, and Belgium, though, HLB has not been confirmed yet in these countries. In the Arabian Peninsula, both D. citri and T. erytreae were recorded in Saudi Arabia and Yemen. D. citri was recorded in Saudi Arabia in

1974 (Wooler et al. 1974), which was widespread in the western, more equitable coastal areas. T. erytreae also occurs in Saudi Arabia but preferring the eastern and highland areas.

Proposed Objectives and Hypotheses of this Study

Recently, our recognition of physiological events associated with CLas-infection and/or

D. citri-infestation has greatly improved. However, the mechanisms of HLB-symptom development and the role(s) of different metabolites in citrus responses are still unexplored.

Understanding the relationships between different metabolic pathways in the HLB pathosystem may clarify the defense mechanisms of citrus against CLas and D. citri in order to find novel, sustainable strategies for HLB management. Additionally, this study seeks to understand the nutritional needs of CLas, which could help in culturing it in the future.

Objective 1: To Understand the Role of Phytohormonal Cross-Talk and its Role in Citrus Response to HLB

Sub-objective 1.1: To develop a GC/MS-based method for phytohormone profiling of Citrus sinensis (L.) tissues

Here, we aimed to develop a simple, accurate, sensitive, and efficient GC-MS-based method to analyze and profile a large number of phytohormones belonging to several/different groups from the same biological sample from the citrus tissue. Studying the phytohormonal profile of citrus will allow us to better understand the balance between hormones, to compare different varieties’ phytohormonal fingerprint, and to study phytohormonal balance changes due to environmental stresses such as CLas-infection and/or D. citri-infestation.

Sub-objective 1.2: To study the phytohormonal cross-talk that mediates the citrus responses to Ca. Liberibacter asiaticus and its vector D. citri

Herein, we investigated the phytohormonal response of Valencia sweet orange (Citrus sinensis) to CLas-infection and/or D. citri-infestation. We hypothesize that multiple phytohormone signaling to mediate the effect of the CLas-infection and/or D. citri-infestation on

C. sinensis.

Objective 2: To Study the Role of Citrus Leaf Pigments in Citrus Response to HLB and Disease Symptoms Development

To understand the mechanism and the development of HLB symptoms, we investigated the chlorophyll and carotenoid contents in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri. We hypothesize that both Clas and D. citri cause changes in the leaf pigments but through two different mechanisms. We believe that both chlorophylls and carotenoids play a role in the symptoms development of HLB. In addition, both chlorophylls and carotenoids might have a role in citrus response to HLB.

Objective 3: To Investigate the Role of Carboxylic Compounds in the Citrus Response to HLB

CLas and D. citri may cause metabolic changes in citrus leaves, but these changes could be dissimilar under various stressors. In addition, alteration in some metabolite abundances, especially phytohormone’s precursors, could lead directly to greater changes in phytohormones.

Objective 4: To Study the Effect of CLas-Infection and/or D. citri-Infestation on the TCA Cycle of its Host Plant

We believe that the changes in different leaf metabolite levels, particularly those involved in the tricarboxylic acid cycle (TCA) cycle, could also affect the abundance of both non- proteinogenic amino acids (NPAAs) and polyamines (PAs) and vice-versa. Our hypothesis is that both CLas-infection and D. citri-infestation induce metabolic changes in the TCA-associated compounds, NPAAs, and PAs in citrus plants. In addition, we hypothesized that both the GABA- shunt and the TCA cycle are functionally linked and the alteration in some metabolite levels, particularly the NPAAs and PAs, could lead indirectly to greater changes in the TCA cycle.

Table 1-1. Diseases caused by the genus Liberibacter and its associated species, host plants, insect vectors, and geographical regions. Subspecies/ Host plant Insect Vector Abbr. Disease Region Reference d Haplotype Specie Family Specie Family

Liberibacter crescens (Lcr) - Lcr Unknown Mountain papaya (Vasconcellea pubescens) Caricaceae Unknown Puerto Rico [1]

Ca. L. americanus (CLam) - CLam HLB Citrus and citrus relatives Rutaceae D. citri Psyllidae Brazil [2]

Ca. L. asiaticus (CLas) - CLas HLB Citrus and citrus relatives Rutaceae Diaphorina citri Psyllidae [3], [4] Widespread in Asia, Africa, and - HLB Various spp Rutaceae Trioza erytreae Triozidae [5] Americas - HLB Lemon (Citrus limon) Rutaceae Cacopsylla citrisuga Psyllidae [6]

Ca. L. africanus (CLaf) - CLaf HLB Citrus and citrus relatives Rutaceae T. erytreae Triozidae South Africa [5,7,8] capensis CLafC Unknown Cape chestnut (Calodendrum capense) Rutaceae T. erytreae Triozidae South Africa [9] zanthoxyli CLafZ Unknown Small forest knobwood (Zanthoxylum sp.) Rutaceae T. erytreae Triozidae South Africa [10] vepridis CLafV Unknown White ironwood (Vepris lanceolata) Rutaceae T. erytreae Triozidae South Africa [10] tecleae CLafT Unknown Flaky cherry-orange (Teclea gerrardii) Rutaceae T. erytreae Triozidae South Africa [10] clausenae CLafCl Unknown Horsewood (Clausena) Rutaceae T. erytreae Triozidae South Africa [11] clausenae CLafCl HLB Citrus expressing typical HLB symptoms Rutaceae T. erytreae Triozidae Uganda, Kenya, and Tanzania [12]

Ca. L. solanacearum (CLso) - CLso ZC Various species Solanaceae Bactericera cockerelli Triozidae Central America, US, New Zealand [13–16] - - Multiple symptoms a Carrots (Daucus carota) Apiaceae T. apicalis Triozidae Europe (Finland) [17] - - Multiple symptoms a Carrots (D. carota), Celery (Apium graveolens) Apiaceae Bactericera trigonica Triozidae Spain (Canary Islands) [18] Unknown - N/A Carrot (D. carota), Celery (A. graveolens) Apiaceae N/A - Austria [19] Unknown - N/A Carrots (D. carota) Apiaceae N/A - Belgium [20] Unknown - Multiple symptoms a Carrots (D. carota) Apiaceae N/A - Italy [21] A CLso-A Multiple symptoms a Various solanaceous crops Solanaceae B. cockerelli Triozidae Americas, New Zealand [22] B CLso-B ZC Various solanaceous crops Solanaceae B. cockerelli Triozidae Americas [16,22] C CLso-C Multiple symptoms a Carrots (D. carota) Apiaceae T. apicalis Triozidae Scandinavia [16,22] Finland, France, Germany, Sweden, C Carrots (D. carota) Apiaceae T. apicalis Triozidae [23–29] Norway, and Estonia b D CLso-D Multiple symptoms a Carrots (D. carota) Apiaceae B. trigonica Triozidae Europe (Spain), Morocco [22,30] D Carrots (D. carota) Apiaceae N/A - France, Greece, and Morocco [24,25,31,32] D Carrots, Celery, Parsnip (Pastinaca sativa), and Apiaceae N/A - Spain (mainland) [33] Parsley (Petroselinum crispum) Apiaceae D Carrots (D. carota) Apiaceae B. trigonica Triozidae Spain (Canary Islands) [33,34] D Carrots (D. carota) Apiaceae N/A - Spain (mainland) [33,34] D Celery (A. graveolens) Apiaceae N/A - Spain (Canary Islands) [33,35] E CLso-E Multiple symptoms a Carrot (D. carota), Celery (A. graveolens) Apiaceae B. trigonica Triozidae Spain, France, Morocco [22,32,35,36] E CLso-E Multiple symptoms a Carrots (D. carota) cv Mascot Apiaceae N/A - Morocco [32]

Table 1-1. Continued Subspecies/ Host plant Insect vector Abbr. Disease Region Reference d Haplotype Specie Family Specie Family

Ca. L. solanacearum (CLso) – Continued E CLso-E Multiple symptoms a Carrots, parsnip, parsley, and celery Apiaceae N/A - Spain (mainland) [33] E CLso-E Multiple symptoms a Carrots (D. carota) Apiaceae B. trigonica Triozidae Spain (Canary Islands) [33,34] E CLso-E Multiple symptoms a Carrots (D. carota) Apiaceae N/A - Spain (mainland) [33,34] E CLso-E Multiple symptoms a Parsley (P. crispum) Apiaceae N/A - Spain (Canary Islands) [33]

Ca. L. europaeus (CLeu) - CLeu Asymptomatic Apple (Malus domestica), Blackthorn (Prunus spinosa), Hawthorn (Crataegus monogyna), and Rosaceae Cacopsylla pyri Psyllidae Italy, Hungary [37] Pear (Pyrus sp.) - Multiple symptoms a Scotch broom (Cytisus scoparius) Fabaceae Arytainilla spartiophila Psyllidae Australia, Europe, and New Zealand, [38]

Ca. L. brunswickensis (CLbr) - CLbr No symptoms Eggplant (Solanum melongena) Solanaceae Acizzia solanicola Psyllidae Australia. [39] No symptoms Cape gooseberry (Physalis peruviana) Solanaceae

Ca. L. caribbeanus (CLca) - CLca HLB Sweet orange (Citrus sinensis) Rutaceae D. citri Psyllidae Colombia, South America. [40] HLB Orange jessamine (Murraya paniculate) Rutaceae

Ca. L. psyllaurous c (CLps) - Psyllid yellows Potato (Solanum tuberosum) Solanaceae CLps B. cockerelli Triozidae Texas, USA [13] disease Tomato (Solanum lycopersicon) Solanaceae a Symptoms includes one or more of the following symptoms; leaf curling, yellow, bronze, and purple discoloration of leaves, stunting of shoots and tap roots, yellows decline, shortened internodes, leaf dwarfing, and leaf tip chlorosis, and proliferation of secondary roots. b Haplotype C was confirmed in 4 samples of T. apicalis (out of 7) in Estonia (EPPO 2018b) c CLps considers as a synonym for CLso haplotype A (Nelson et al. 2011), which showed an identical 16S rRNA genes d Reference: [1] Leonard et al. 2012; [2] Teixeira et al. 2005a; [3] Capoor et al. 1967; [4] Bové 2006; [5] McClean and Oberholzer 1965; [6] Cen et al. 2012; [7] Jagoueix et al. 1994; [8] Garnier et al. 2000a; [9] Garnier et al. 2000b; [10] Roberts et al. 2015; [11] Roberts and Pietersen 2017; [12] Roberts et al. 2017; [13] Hansen et al. 2008; [14] Liefting et al. 2008; [15] Liefting 2009; [16] Nelson et al. 2011; [17] Munyaneza et al. 2010a; [18] Alfaro- Fernández et al. 2012b; [19] EPPO 2015; [20] EPPO 2018a; [21] EPPO 2018c; [22] Vereijssen et al. 2018; [23] Munyaneza et al. 2010b; [24] Loiseau et al. 2014; [25] Hajri et al. 2017; [26] Munyaneza et al. 2015; [27] Munyaneza et al. 2012a; [28] Munyaneza et al. 2012b; [29] EPPO 2018b; [30] Vereijssen et al. 2018; [31] Holeva et al. 2017; [32] Tahzima et al. 2014; [33] Alfaro-Fernández et al. 2017; [34] Alfaro-Fernández et al. 2012a; [35] Teresani et al. 2014; [36] Teresani et al. 2015; [37] Raddadi et al. 2011; [38] Thompson et al. 2013; [39] Morris et al. 2017; [40] Keremane et al. 2015.

Figure 1-1. The disease pyramid for HLB pathosystem. The figure is modified from (Wang et al. 2017). The four major components of HLB disease are positioned at the vertices.

Figure 1-2. Electron micrographs of ultrathin sections through sieve tubes of leaf midribs from HLB-infected plants. (A) Elongated bacilliform shape present in the sieve tubes of HLB-symptomatic plants; (B) both elongated bacilliform and pleiomorphic round/spherical shapes present in the sieve tubes of HLB-symptomatic plants; (C) The typical 25 nm (250 Å)-thick envelope; (D) both outer and inner membranes of CLas envelope; and (E & F) Papain digestion of CLas in the sieve tubes of HLB- symptomatic plant showing a peptidoglycan layer located between the outer and the inner membranes like Gram-negative bacteria. PG: peptidoglycan; OM: outer membrane; CM: cytoplasmic membrane; and IM: inner membrane. Sources: Panels A, C, and D are adapted from (Garnier and Bové 1983), (B) is adapted from (NRC 2010), E and F are adapted from (Garnier et al. 1984).

Figure 1-3. The geographical distribution of the HLB-associated pathogens. The distribution in this map is based on the available information at Invasive Species Compendium (ISC)- Centre for Agriculture and Bioscience International (CABI; https://www.cabi.org/isc/) database about Ca. Liberibacter asiaticus (Asian greening; https://www.cabi.org/isc/datasheet/16565), Ca. Liberibacter africanus (African greening; https://www.cabi.org/isc/datasheet/16564), and Ca. Liberibacter americanus (American greening; https://www.cabi.org/isc/datasheet/16566). Accessed on August 27th, 2018.

Figure 1-4. The geographical distribution of the HLB-associated vectors. The distribution in this map is based on the available information at Invasive Species Compendium (ISC)- Centre for Agriculture and Bioscience International (CABI; https://www.cabi.org/isc/) database about Diaphorina citri (Asian citrus psyllid; https://www.cabi.org/isc/datasheet/18615) and Trioza erytreae (African citrus psyllid; https://www.cabi.org/isc/datasheet/54914). Accessed on August 27th, 2018.

CHAPTER 21 PHYTOHORMONE PROFILING OF THE SWEET ORANGE (Citrus sinensis (L.) OSBECK) LEAVES AND ROOTS USING GC-MS-BASED METHOD

Herein, aimed to develop a simple, accurate, sensitive, and efficient GC-MS-based method in the selective ion monitoring (SIM) mode to analyze and profile a large number of phytohormones belonging to several/different groups the same biological sample from the citrus tissue. One extraction solvent mixture and two derivatization reagents were used.

Introduction

Phytohormones are defined as a group of natural, organic molecules, and small lipophilic substances that regulate the physiological process in plants even in low concentrations (Bai et al.,

2010; Bari and Jones, 2009). In the past, plant biologists were interested in only five classes of phytohormones based on their chemical structures and physiological functions, which included auxins, cytokinins, gibberellins (GAs), abscisic acid (ABA) and ethylene (ET) (Bai et al., 2010;

Bari and Jones, 2009). Currently, salicylates (SAs), jasmonates (JAs), brassinosteroids (BRs), peptide hormones and strigolactones (López-Ráez et al., 2009) are considered phytohormones.

Phytohormones play a key role in regulating developmental processes and growth, signaling networks and most physiological functions within plants including the root nodulation in leguminous plants, root growth, meristem implementation, shoot divaricating/branching, adjustment of fruit set and development, anther development, and responses to biotic and abiotic stress (Quecini et al., 2007; Santner et al., 2009). Since the discovery of phytohormones, great efforts has been invested to develop and improve analytical methods for the detection including bioassay (Bai et al., 2010), ELISA (Bai et al., 2010; Rosales and Burns, 2011), HPLC (Chiwocha

1 The results of Chapter 2 were published in the Journal of Plant Physiology as “Nehela, Y., Hijaz, F., Elzaawely, A. A., El-Zahaby, H. M., and Killiny, N. 2016. Phytohormone profiling of the sweet orange (Citrus sinensis (L.) Osbeck) leaves and roots using GC-MS-based method. J. Plant Physiol. 199:12–17”.

et al., 2003) and gas chromatography (GC) (Luo et al., 2013; Müller et al., 2002). Among previous methods, GC-MS was the most widely used. Generally, one compound (Rosales and

Burns, 2011), one class (Ozga et al., 2009), or two or a few classes (Luo et al., 2013) were usually analyzed.

In this study, we aimed to analyze a large number of phytohormones belonging to six groups in citrus tissues using an improved GC-MS-based method. Studying the phytohormonal profile of citrus will allow us to better understand the balance between hormones and to study phytohormonal changes due to environmental stresses.

Materials and Methods

Plant Materials

Valencia sweet orange (Citrus sinensis (L.) Osbeck) trees were 18 months old, and

100±10 cm tall when used. Trees were grown in a USDA-APHIS approved secured greenhouse under conditions ideal for citrus (28–32 °C, 16:8 L:D photoperiod, and 65% RH). For leaf sampling, three leaves were collected from each tree (from the top, middle and base areas and were chopped into small pieces and mixed together. For root tips, 2-3 mm from the end of the secondary roots, were cut and collected together for each plant. The remainder of the secondary roots was chopped into small pieces. All samples were kept at -80 °C until extraction.

Extraction of Phytohormones

Citrus tissues were ground using liquid nitrogen and 0.1±0.002 g was transferred to a 1.5 mL centrifuge tube. 750 µL of the extraction solvent (methanol: water: HCl (6N); 80: 19.9: 0.1; v/v/v) was added, vortexed for 30 sec, then kept on ice for 10 min. Samples were centrifuged at

15,000 rpm for 5 min at 25 °C. The supernatants were transferred to 2 mL tubes. Samples were extracted three times and the supernatants were combined then concentrated to 50 µL under a nitrogen stream and stored at -80 °C until analysis.

Derivatization of Phytohormones

Acidic phytohormones, including auxins, SAs, JAs, and ABA, were derivatized with

MCF as described by (Hijaz and Killiny, 2014). Briefly, 50 µL of the supernatant was derivatized with 40 µl of MCF then concentrated to 20 µL under a nitrogen stream and about 0.5 mg sodium sulfate was added to dry the organic phase. For cytokinins and GAs, 50 µL from the supernatant was dried and derivatized with 100 µL of N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) by heating at 85 °C for 45 min. For GC-MS analysis, 1µL was injected into the GC-MS-SIM.

Phytohormones Standards Curves

To determine the mass spectra and the retention time for each phytohormone, 1 µL of

200 ppm of derivatized standards mixture was injected into GC-MS in the full scan mode.

Additionally, a 1 µL of 40, 20, 10, 5, 2.5, and 1.25 ppm of derivatized standard mixtures were injected in the SIM-mode to establish the standard curve. Typically, in the SIM-mode, three to five ions are monitored for each compound and the ratios/abundances of those ions should be similar to those of the authentic standards (Luo et al., 2013; Poling and Maier, 1988; Talón et al.,

1990).

Method Evaluation

Extraction recovery

The extraction recovery (% ER) was estimated by spiking five ground samples with 5 μl of 200 ppm standard mixture then phytohormones were extracted as described above. To calculate the ER %, the detected amount of phytohormone in non-spiked samples extracted from the detected amount in the spiked sample was divided by the supplementary standard amount.

Limit of Detection and Limit of Quantification

Limit of detection (LOD) and limit of quantification (LOQ) were calculated based on a signal-to-noise (S/N) ratio of 3:1 and 10:1, respectively. The limits were calculated using standard curves of the authentic standards.

Reproducibility

Sample extracts were repeatedly injected (five times) to test the reproducibility of the method. The reproducibility was estimated as relative standard deviations, RSDs (RSD=100×SD

/mean) for retention times (relative retention times, RRTs) and peak areas (relative peak areas,

RPAs) for each compound.

GC-MS Analyses

We used Clarus 680 GC with SQ8-T Mass Spectrometer system (Perkin Elmer, Waltham,

MA, USA) fitted with an Elite-5MS capillary column (low bleed, 30 m × 0.25 mm × 0.025 µm film thickness; Perkin Elmer, Waltham, MA, USA). Helium was the carrier gas with a flow rate of 1 mL min-1. The temperature program for acidic phytohormones was as follows; the column was held at 50 °C for three min, and then increased to 200 °C at a rate of 4 °C min-1, held for 5 min. While the program for cytokinins and GAs was as follows; the column was held at 60 °C for 2 min and then increased to 160 °C at 20 °C min-1 and finally to 290 °C at 5 °C min-1. The injector and the detector temperatures were set at 250 °C and 260 °C, respectively. TurboMass software version 6.1 (Perkin Elmer, Waltham, MA, USA) was used to analyze chromatograms.

Identification of all phytohormones was performed by comparing their retention time, linear retention indices (LRIs), and the selected ions with those of authentic standards.

Statistical Analysis

ANOVA was performed to compare the concentrations of phytohormones in different tissues. For ABA, T-test was applied to compare the concentrations between leaves and roots.

Post hoc pairwise comparisons between treatments were performed with the Tukey honestly significant difference test.

Results

SAs is the Most Abundant Phytohormone Group in Citrus

Benzoic (BA), trans-cinnamic (tCA) and salicylic (SA) acids were detected as salicylates

(Table 2-1 and Figure A-1). SAs had the highest levels in all tissues. SAs were higher in leaves than roots or root tips (Figure 2-1A). BA was the highest in leaves and roots (2067.5 ng g-1 FW and 462.2 ng g-1 FW, respectively) followed by SA (672.1 ng g-1 FW and 193.8 ng g-1 FW, respectively) and tCA (540.3 ng g-1 FW and 182.9 ng g-1 FW, respectively) (Figure 2-1A). The

SAs %ER ranged from 42.7±1.7 (BA) to 61.9±3.7 % for tCA. While the LOD ranged from 0.02 ng g-1 FW for tCA to 0.04 ng g-1 FW for BA, the LOQ ranged from 0.08 ng g-1 FW to 0.12 ng g-1

FW. The methods showed good reproducibility (RSDs) of relative retention times (RRTs; 0.04-

0.10 %) and relative peak areas (RPAs; 3.61- 5.87 %) for each compound (Table 2-2).

Auxins are Detected in Citrus Leaves only

Three auxins were detected in leaves (Indole-3-acetic acid (IAA), Indole-3-propionic acid

(IPA), and Indole-3-butyric acid (IBA) (Figure A-1). Figure 2-1B shows that auxins concentration ranged from 221.9 ng g-1 FW (IAA) to 258.5 ng g-1 FW (IPA, the highest auxin).

The auxins’ %ER ranged from 109.4±4.7 (IAA) to 131.3±3.1 % (IPA) and the LOD ranged from

0.05 ng g-1 FW (IPA) to 0.07 ng g-1 FW for IBA; while LOQ ranged from 0.15 ng g-1 FW (IPA) to 0.22 ng g-1 FW for IBA. The method showed good RSDs of RRTs (between 0.049- 0.098%) and RPAs (between 3.58- 5.16%) for each compound (Table 2-2). tJA and ABA

ABA was detected in leaves and roots but not in root tips (Figure A-1). Data in

Figure 2-1C show that ABA concentration was 312.2 ng g-1 FW and 181.1 ng g-1 FW in leaves

and roots, respectively. The tJA was detected only in leaves (226ng g-1 FW) (Figure 2-1D). tJA had a better %ER, LOD, LOQ, RRT, and RPA than ABA (Table 2-2).

Cytokinins Levels are Higher in the Root Tips Tissues

trans-Zeatin (tZ) and trans-Zeatin riboside (tZR) were detected as cytokinins (Figure A-

1). Cytokinins levels were higher in root tips than roots and leaves (Figure 2-1E). Figure 2-1E shows that tZ was higher in leaves (14.5 ng g-1 FW), and tZR was the highest in roots and root tips (35.1 and 47.0 ng g-1 FW, respectively). The %ER of cytokinins was 100.71±8.44 for tZ and

111.88±7.68 % for tZR. The LOD was 0.081 and 0.072 ng g-1 FW for tZ and tZR, respectively; and the LOQ was 0.270 ng g-1 FW for tZ and 0.240 ng g-1 FW for tZR. Additionally, cytokinins showed RSDs of RRTs (0.093 and 0.111% for tZ and tZR, respectively) and RPAs (4.28- 6.86% for tZ and tZR, respectively) (Table 2-2).

GAs are Higher in the Root Tips Tissues

Three gibberellins (GA3, GA4, and GA7) were detected in all tissues (Figure A-1). GAs were higher in root tips than leaves and roots (Figure 2-1F). The GA7 level was the highest while the GA4 level was the lowest in all tissues. Data in Table 2-2 show that the GAs %ER ranged

-1 from 104.76±5.65 for GA3 to 115.95±4.92 % for GA4. The LOD ranged from 0.023 ng g FW to

0.062 ng g-1 FW, and the LOQ ranged from 0.078 ng g-1 FW to 0.206 ng g-1 FW. Additionally,

GAs showed a good RSDs of RRTs (between 0.085- 0.151%) and RPAs (between 3.25- 5.98%) for each compound (Table 2-2).

Discussion

In the current study, GC-MS-SIM was used to profile the phytohormones from Valencia sweet orange (C. sinensis) leaves, roots, and root tips. GC-MS is one of the best techniques for phytohormones determination (Luo et al., 2013; Müller et al., 2002). However, the analysis of phytohormones is still difficult because of their low abundance in plant samples (Bai et al., 2010;

Müller et al., 2002), the extraction procedures are complex, and phytohormones have several and different structural isomers and chemical properties with varying bioactivity (Bai et al., 2010;

Müller et al., 2002).

Six different phytohormone groups were detected in our study: auxins, cytokinins, GAs,

JAs, SAs, and ABA. Among detected phytohormone groups, SAs were the most abundant in all studied tissues. This finding is in agreement with (Luo et al., 2013). Of these, BA had the highest concentration among all studied phytohormones, followed by SA and tCA. The mechanism of production of BA from tCA is not well understood and might be a step-limiting in SA biosynthesis (Quecini et al., 2007). In the current study, we detected auxins only in leaf extracts.

The auxins levels in the roots might be below the LOD because of the activity of 2-oxindole-3- acetic acid (oxIAA; the major catabolite of IAA), which is formed in root tissues (Pencík et al.,

2013).

To our knowledge, few studies exist in citrus with respect to the analysis of auxins content; most of these studies focused on IAA (Koshita and Takahara, 2004; Rosales and Burns,

2011), but currently, auxins include a large number of compounds such as IPA and IBA.

The absence of tJA from roots and root tips may be due to the variation in JA distribution in the higher plants, which varies due to the function of tissues and cell type (Creelman and

Mullet, 1997). Another reason for the JA absence is that it may be under the LOD due to the formation of JA-conjugated metabolites. JA-conjugation plays a key role in regulating the levels of the biologically active jasmonates (Rowe and Staswick, 2013; Schneider et al., 1989).

Many previous studies were carried out to determine GAs in different tissues of citrus such as shoots (Poling and Maier, 1988), seeds (Turnbull, 1989), fruitlets (Manzi et al., 2015;

Turnbull, 1989), immature fruits (Poling, 1991), and developing fruits (Talón et al., 1990). In C.

sinensis, many GAs were detected in fruits such as GA3 (Turnbull, 1989), GA4 (Poling, 1991), and both of them in addition to GA7 (Manzi et al., 2015).

We have also demonstrated that GA7 was the highest among all studied GAs and this may be due to the accumulation of GA7 because it formed from GA12 in 3β-hydroxy GA pathway

(Farrow and Facchini, 2014). Previous studies concluded that the earlier compounds in the GAs pathway are biologically active and proceed finally to GA1 (Poling and Maier, 1988).

In conclusion, we used a modified GC-MS-based method for the determination of a large number of phytohormones using one extraction solvent from a small amount of plant tissue (100 mg fresh weight). After derivatization with MCF or MSTFA, the concentration of 13 phytohormones from six different groups was calculated. The results from this study will help elucidate differences between the phytohormonal profiles of citrus from different tissues under normal and stressful conditions. In addition, the modified method reduces time spent in sample preparation and purification.

Table 2-1. Identification of phytohormones groups after MCF or MSTFA derivatization in citrus leaves in full-scan GC-MS * Peak a No. Phytohormone Standards (abbr.) RT b LRI c Constituent Ion m/z (relative abundance)

Salicylates 1 Benzoic acid (BA)1 13.69 1080 77 (50) 105 (100) 136 (44) 2 trans-Cinamic acid (tCA)2 23.75 1408 77 (45) 103 (67) 131 (100) 162 (52) 3 Salicylic acid (SA)1 29.12 1584 107 (10) 135 (100) 210 (20)

Jasmonates 4 trans-Jasmonic acid (tJA)1 31.72 1668 82 (27) 83 (100) 153 (25) 156 (33)

Auxins 5 Indole-3-acetic acid (IAA)1 36.12 1812 103 (10) 130 (100) 131 (11) 189 (20) 6 Indole-3-propionic acid (IPA)3 38.46 1888 115 (10) 130 (100) 143 (15) 203 (31) 7 Indole-3-butyric acid (IBA)3 41.05 1973 103 (10) 130 (100) 143 (23) 217 (30)

Abscisic acid 8 Abscisic acid (ABA)1 42.94 2034 125 (55) 134 (50) 162 (47) 190 (100)

Cytokinins 9 trans-Zeatin (tZ)1 14.67 2501 192 (47) 232 (45) 260 (100) 273 (68) 13 trans-Zeatin riboside (tZR)1 22.98 3782 156 (70) 188 (60) 201 (100) 230 (40) 320 (20)

Gibberellins 12 1 Gibberellic Acid (GA3) 16.70 2814 207 (100) 221(60) 281 (74) 311 (70) 427 (90) 1 10 Gibberellin A4 (GA4) 16.03 2710 224 (100) 225 (37) 229 (12) 342 (14) 386 (13)

11 Gibberellin A7 (GA7) 15.79 2673 201 (38) 222 (100) 224 (70) 311 (24) 339 (50) a Peak No. represents the numbers in Figure A-1 b RT: Retention time, c LRI: Liner retention index, 1 Standards were purchased from Sigma-Aldrich Co. LLC. (Missouri, USA), 2 Standards were purchased from Fluka (Sigma-Aldrich Co. LLC., St. Louis, Missouri, USA), 3 Standards were purchased from MP Biomedicals (California, USA). * For full mass spectra for each compound, see the supplementary material (Figure A-2 to A-6)

Table 2-2. Extraction recovery, limit of detection, limit of quantification and method reproducibility of representative phytohormones (n=10). Peak Reproducibility (RSD4) ER (%)1 LOD2 LOQ3 No. Phytohormone Standards (abbr.) 5 6 Mean±SD (ng g-1) (ng g-1) RRT RPA (%) (%) Salicylates 1 Benzoic acid (BA)1 42.72±1.72 0.036 0.121 0.102 3.61 2 trans-Cinamic acid (tCA)2 61.88±3.70 0.022 0.075 0.070 3.93 3 Salicylic acid (SA)1 45.13±2.23 0.030 0.101 0.043 5.87

Jasmonates 4 trans-Jasmonic acid (tJA)1 87.42±5.16 0.038 0.127 0.072 5.23

Auxins 5 Indole-3-acetic acid (IAA)1 109.38±4.70 0.054 0.193 0.049 5.16 6 Indole-3-propionic acid (IPA)3 131.31±3.06 0.046 0.154 0.084 5.01 7 Indole-3-butyric acid (IBA)3 119.22±3.48 0.066 0.217 0.098 3.58

Abscisic acid 8 Abscisic acid (ABA)1 67.15±4.68 0.086 0.291 0.077 5.56

Cytokinins 9 trans-Zeatin (tZ)1 100.71±8.44 0.081 0.270 0.093 4.28 13 trans-Zeatin riboside (tZR)1 111.88±7.68 0.072 0.240 0.111 6.86

Gibberellins 1 12 Gibberellic Acid (GA3) 104.76±5.65 0.062 0.206 0.149 3.25 1 10 Gibberellin A4 (GA4) 115.93±4.92 0.023 0.078 0.085 4.26 11 Gibberellin A7 (GA7) 108.95±7.16 0.038 0.127 0.151 5.98 1 ER Extraction Recovery = (Found-Detected)/Added × 100), The extraction recovery (% ER) was estimated by spiking five ground samples with 5 μl of 200 ppm standard mixture then phytohormones were extracted using the solvents as described above. To calculate the ER %, the detected amount of phytohormone in non-spiked samples extracted from the detected amount in the spiked sample was divided by the supplementary standard amount (20 ppm). 2 LOD limit of detection 3 LOQ limit of quantification For each phytohormone, limit of detection (LOD) and limit of quantification (LOQ) were calculated based on a signal-to-noise (S/N) ratio of 3:1 and 10:1 respectively. The limits were calculated using standard curves of the authentic standards. 4 RSD relative standard deviations, 5 RRT Relative Retention time (%), 6 RPA Relative Peak area (%). Sample extracts were repeatedly injected (five times) to test the reproducibility of the method. The reproducibility was estimated as relative standard deviations, RSDs (RSD=100×SD/mean) for retention times (relative retention times, RRTs) and peak areas (relative peak areas, RPAs) for each compound.

Figure 2-1. Concentrations of different salicylates (A), auxins (B), abscisic acid (C), and trans- jasmonic acid (D), cytokinins (E), and gibberellins (F) in Valencia sweet orange leaves, roots, or root tips using GC-MS-SIM. Phytohormones were extracted in methanol and derivatized with MCF or MSTFA (n=10). Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest number of data. Different letters indicate statistically significant differences while “ns” means no significant differences (P<0.05).

CHAPTER 32 MULTIPLE PHYTOHORMONAL SIGNALING MEDIATES CITRUS RESPONSES TO Candidatus Liberibacter asiaticus AND ITS VECTOR Diaphorina citri.

In this chapter, the role of phytohormones in mediating the effect of the CLas-infection and/or D. citri-infestation on Citrus sinensis was investigated using GC-MS-SIM, followed by gene expression analysis. Overall, we quantified 13 phytohormones belonging to six different groups (auxins, salicylates, jasmonates, abscisic acid (ABA), cytokinins, and gibberellins).

Introduction

Plants activate their defense responses upon the perception of the pathogen and/or insect attacks. Plant defenses are mainly regulated by small signaling molecules called phytohormones

(Hatcher et al. 2004; Lazebnik et al. 2014). Besides their role in plant defense response, phytohormones also play an important role in plant growth, development, and many other vital processes. Upon alteration of phytohormones, the host plant reprograms its transcriptome leading to changes in plant proteome and metabolome. Changes in plants’ metabolites in response to the pathogen or insect attacks can alter how plants interact in the host-pathogen-vector pathosystems

(Dicke et al. 2009).

In the beginning, phytohormones were limited to auxins, cytokinins (CKs), gibberellins

(GAs), abscisic acid (ABA), and ethylene (ET) (Pieterse et al. 2009). Recently salicylates (SAs), jasmonates (JAs), brassinosteroids (BRs) and some peptides were considered as phytohormones

(Pieterse et al. 2009). Most of these classes are involved directly or indirectly in stress responses.

Briefly, SA, JA, and ET are recognized as stress-associated phytohormones (Robert-Seilaniantz et al. 2007). Recent studies indicated that auxins, CKs, GAs, ABA, BRs and peptide hormones are also involved in plant response to both biotic and abiotic stress (Bari and Jones 2009).

2 The results of Chapter 3 were published in the Physiological and Molecular Plant Pathology as “Nehela, Y., Hijaz, F., Elzaawely, A. A., El-Zahaby, H. M., and Killiny, N. 2018. Citrus phytohormonal response to Candidatus Liberibacter asiaticus and its vector Diaphorina citri. Physiol. Mol. Plant Pathol. 102:24–35”.

Alteration in host-derived phytohormones induced by pathogens and insects differs depending on their feeding activity (Glazebrook 2005; Bari and Jones 2009). For example, SA- mediated pathways are associated with defense response for biotrophic (long-term feeding) and hemibiotrophic pathogens and has a great role in the establishment of systemic acquired resistance (SAR) (Bari and Jones 2009; Hatcher et al. 2004; Glazebrook 2005). On the other hand, JA/ET-mediated pathways (wound response pathways) are associated with defense against necrotrophic pathogens and insects herbivory (Bari and Jones 2009; Hatcher et al. 2004;

Glazebrook 2005). There is a controversy about the interaction between SA and JA/ET. Some scientists believe that the SA and JA/ET defense pathways are antagonistic (Bari and Jones

2009), and the activation of one usually suppresses the other (Robert-Seilaniantz et al. 2007; Bari and Jones 2009), while other scientists insist that the SA and JA/ET interaction is mutually synergistic (Kunkel and Brooks 2002).

Furthermore, the phytohormones crosstalk in plant response is more than just SA/JA interaction (Robert-Seilaniantz et al. 2011). For instance, the role of auxin-cytokinin interaction varies among different pathosystems (Naseem and Dandekar 2012; Navarro et al. 2006; Wang et al. 2007). Recent studies showed that the roles of auxins and cytokinins in plant response are independent (Naseem and Dandekar 2012). For example, auxins promote susceptibility of

Arabidopsis plants against the infection with the bacterial pathogen, Pseudomonas syringae pv. tomato DC3000 (Chen et al. 2007; Naseem and Dandekar 2012). In contrast to auxin, cytokinins promote resistance in Arabidopsis against the same pathogen through increasing the antimicrobial phytoalexin synthesis (Grosskinsky et al. 2011). However, auxin-cytokinin interaction is crucial in plant immunity networks.

In nature, multiple organisms can attack higher plants simultaneously. When pathogens and herbivores attack the same plant, they may interact directly or indirectly (Hatcher et al. 2004;

Lazebnik et al. 2014). The main direct interaction among pathogens, insects, and host plants is that insects can act as alternative vector hosts for pathogens (Nadarasah and Stavrinides 2011).

On the other hand, the indirect tritrophic interactions among phytopathogen, insect vector, and host plant could occur at two different levels: mechanical/ecological and/or cellular/molecular levels (Hatcher et al. 2004; Lazebnik et al. 2014). However, the mechanisms that control the tritrophic interactions are poorly understood.

Many factors could affect the phytohormone response after multiple attacks such as herbivores feeding mode (Bonaventure 2012), pathogen trophic type (Pieterse et al. 2012), and host plant susceptibility (Martinez de Ilarduya et al. 2003). In addition, the change in phytohormonal profile differs depending on which is the first stressor, and which is the subsequent attacker (Lazebnik et al. 2014). In case of pathogen infection is before herbivory, little information is available, and no clear evidence for the effect of different trophic types of pathogens on subsequent herbivore attack, especially for phloem feeders (Hatcher et al. 2004;

Al-Naemi and Hatcher 2013).

On the other hand, when insect herbivory occurs first, insects stimulate plant resistance against biotrophs and hemibiotrophs (Lazebnik et al. 2014). For example, the pre-infestation of tomato with the silver leaf whitefly Bemisia argentifolii minimized the disease incidence with

Erysiphe cichoracearum, the biotrophic fungal pathogen of tomato powdery mildew disease

(Mayer et al. 2002). Additionally, the pre-infestation with the white-backed leafhopper Sogatella furcifera (Hemiptera: Delphacidae), a phloem feeder, induced disease resistance in rice to

Pyricularia grisea, the fungal pathogen of rice blast disease (Satoh et al. 2010). Likewise, the

foliar infestation of pepper by the green peach aphid Myzus pericae enhanced its immunity against Xanthomonas axonopodis, the biotrophic bacterial pathogen of leaf spot of pepper disease (Lee et al. 2012).

Citrus (genus Citrus; family Rutaceae; sub-family Aurantoideae) is considered one of the most widely grown fruit crops in the world (Liu et al. 2012). Countries, where citrus grow, are located within 35˚-40˚ north and south latitude (Gottwald 2010; Liu et al. 2012). Citrus species are considered to be native to the tropical and subtropical areas (Gottwald 2010; Liu et al. 2012).

Brazil, USA, and China are the major producers (Liu et al. 2012; Hijaz and Killiny 2014). Citrus trees are attacked by a wide range of insects, fungi, prokaryotes, nematodes, and viruses.

Huanglongbing (HLB) which is also known as citrus greening disease, is a destructive disease causing great losses in citrus industries worldwide (Bové 2006). During the last ten years, HLB approximately destroyed 100,000 citrus acres in Florida. Additionally, Florida’s economy has lost about $3.6 billion from its revenues and 6,611 jobs since 2006 due to the HLB disease

(Alvarez et al. 2016). HLB is caused by Candidatus Liberibacter asiaticus (CLas), a fastidious, gram-negative, phloem-limited -proteobacterium (Bové 2006). CLas is transmitted by the

Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae) (Tatineni et al. 2008). D. citri transmits the CLas bacterium while feeding on the phloem sap of citrus plants. Direct feeding on the phloem sap and production of large amounts of honeydew may also contribute to further economic losses (Ammar et al. 2013).

Many studies have been devoted to explaining how phytohormones mediate the host- pathogen interactions (Glazebrook 2005; Robert-Seilaniantz et al. 2007) or host-vector interactions (Mithöfer and Boland 2012). However, the role of phytohormones in mediating the tripartite interactions (host-pathogen-vector interactions) is poorly studied. Additionally, most of

the previous studies on phytohormones analyzed only one compound (Östin et al. 1992; Meyer et al. 2003), one group (Novák et al. 2003; Ozga et al. 2009), few compounds from the same group, or few metabolites related to phytohormones (Luo et al. 2013; Matsuura et al. 2009). Herein, we hypothesized that multiple phytohormone signaling mediate the effect of the CLas-infection and/or D. citri-infestation on Valencia sweet orange (Citrus sinensis (L.) Osbeck).

Materials and Methods

Plant Materials

Valencia sweet orange (Citrus sinensis (L.) Osbeck) was used in this study. All the trees were about 18 months old and around 80±5 cm tall. Trees were maintained in a USDA-

APHIS/CDC-approved secured greenhouse (28±1°C, 60±5% relative humidity, L16: D8 h photoperiod) at the Citrus Research and Education Center (CREC), University of Florida, Lake

Alfred, Florida. Plants were watered twice a week and fertilized once a week using 20-10-20 fertilizer (Allentown, PA, USA). Four treatments (five biological replicates, two technical replicates for each; n=10), including healthy (control), CLas-infected, D. citri-infested and double-attacked plants (CLas-infected and D. citri-infested together), were tested. To obtain the

CLas-infected plants, ten-months-old, HLB-free trees were graft-inoculated with budwoods from a PCR-positive HLB source and maintained in the same conditions as described above. Upon initial symptom development, about seven months later, the infection was confirmed using PCR

(Tatineni et al. 2008). For both, D. citri-infested and the double-attacked trees, 16 months-old healthy or CLas-infected Valencia sweet orange plants, with enhanced new flushes, were exposed to 100 healthy adult psyllids (PCR negative) per plant and caged individually using insect rearing cages (60×60×90 cm) and maintained in growth room at the same conditions as described above. One month later, both D. citri-infested and double-attacked plants were cleaned from all D. citri stages (nymphs and adults). For sampling, three symptomatic leaves were

collected per tree (about 18-months old) from different positions and different ages; juvenile leaf from the top, recently matured one from the middle, and a mature leaf from the lower part of the plant. The collected leaves were chopped, mixed together and immediately kept on ice. Plant materials were kept at -80 °C until analysis.

Analysis of Citrus Phytohormones using GC-MS

Phytohormones were extracted from leaves using methanol 80% containing 0.1% HCl 6N according to Nehela et al. (2016). Before derivatization, each sample was spiked with 5 µl aliquot of 200 ppm heptadecanoic acid, which is not found in citrus leaves, as an internal standard. For phytohormones derivatization, acidic phytohormones (auxins, salicylates, jasmonic acid and abscisic acid) were derivatized with methyl chloroformate (MCF) as described by

(Hijaz and Killiny 2014), while cytokinins and gibberellins were derivatized with N-Methyl-N-

(trimethylsilyl) trifluoroacetamide (MSTFA) as described by (Nehela et al. 2016). For GC-MS analysis, 1 µl of the derivatized sample was injected into the GC-MS running in selective ion monitoring mode (SIM mode). In the SIM-mode, three to five ions were monitored for each compound and the ratios/abundances of those ions were similar to those of our previously published data (Nehela et al. 2016). Derivatized samples and standards were analyzed using a

Clarus 500 GC-MS system (Perkin Elmer, Waltham, MA, USA) fitted with a ZB-5MS GC column (5% Phenyl-Arylene 95% Dimethylpolysiloxane; low bleed, 30 m × 0.25 mm × 0.25 µm film thickness; Phenomenex, Torrance, CA, USA). The GC thermo-program, MS ion identification, and GC-MS chromatograms analysis were performed according to (Nehela et al.

2016). Identification of phytohormones was confirmed by comparing their retention time, linear retention indices (LRIs), and the selected ions with those of authentic standards. Compound peak areas were normalized to the internal standards (heptadecanoic acid). Quantification of different phytohormones was based on the peak areas obtained from a series of reference standards (20,

10, 5, 2.5, 1.25, and 0.2 ppm) derivatized and injected under the same conditions as samples.

Calibration curves were constructed from the linear regressions obtained by plotting the concentration vs. peak area for each standard.

Analysis of Phenylalanine, Tryptophan, and Linolenic Acid using GC-MS

The abundances of phenylalanine, tryptophan, and linolenic acid in citrus leaves were determined in the same biological samples using the same extraction method described by

(Nehela et al. 2016), then derivatized with MCF after spiking of each sample with 5 µl aliquot of

200 ppm heptadecanoic acid, which is not found in citrus leaves, as internal standard. All derivatized samples and standards were analyzed as described by (Killiny and Nehela 2017a).

Identification of phenylalanine, tryptophan, and linolenic acid was further confirmed by comparing their retention time, linear retention indices (LRIs) and mass spectra with authentic standards. Compound peak areas were normalized to the internal standards (heptadecanoic acid).

Quantification of phenylalanine, tryptophan, and linolenic acid was based on the peak areas obtained from a series of reference standards derivatized and injected under the same conditions as samples. Calibration curves were constructed from the linear regressions obtained by plotting the concentration vs. peak area for each standard.

Analysis of Zeaxanthin using HPLC

Zeaxanthin was extracted from the same plant samples according to the methods of

Norris et al. (1995) modified by Killiny and Nehela (2017b). The HPLC system consisted of an

Agilent 1200 system with photodiode array detector (Agilent Technologies, Santa Clara, CA,

USA). Chromatographic separation was performed using a C30 YMC carotenoid column,

250×4.6 mm I.D., S-5 μm (YMC America, Allentown, PA, USA). The mobile phase composition and the gradient profile used was as described by (Killiny and Nehela 2017b). The

HPLC-output data were analyzed using ChemStation software, B.03.02, (Agilent Technologies,

CA, USA). Peaks were first identified by comparing experimental retention time and UV-visible spectra with that of published literature (Killiny and Nehela 2017b), as well as with authentic standard obtained from Sigma-Aldrich (USA), and used to establish a calibration curve which used to calculate the zeaxanthin concentration in citrus leaves.

Gene Expression Analysis using Quantitative Real-Time PCR (RT-PCR)

TriZol® reagent (Ambion®, Life Technologies, NY, USA) was used to extract total RNA from samples. The quantity and quality of isolated RNA were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA). SuperScript first-strand synthesis system

(Invitrogen) with random hexamer primers as described by the manufacturer’s instructions was used to synthesize cDNA. SYBR Green PCR master mix (Applied Biosystems) was used to perform the qPCR on an ABI 7500 Fast-Time PCR System (Applied Biosystems). Samples were analyzed in triplicate for each biological replicate for each treatment. Primers for 38 genes involved in six phytohormone biosynthetic pathways; auxins, SAs, JA, and ABA were used to measure the gene expression (Table B-2 to B-5). The relative expression of the consensus

−ΔΔC sequence among PCR products was done according to the 2 T method (Livak and Schmittgen

2001). Four genes were used as endogenous genes (reference genes) to normalize the data of gene expression including; elongation factor 1-alpha (EF1), F-box/kelch-repeat protein (F-box), glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (GAPC1, aka GAPDH), and

SAND family protein (SAND) (Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b)

Statistical Analysis

Analysis of variance (ANOVA) was performed to compare the phytohormone levels in different treatments. Post hoc pairwise comparisons between the four treatments were performed with the Tukey-Kramer honestly significant differences test (Tukey HSD). Statistical significance was established at P<0.05. Principal component analysis (PCA) and hierarchical

cluster analysis (HCA) were performed using the whole data matrices for the four treatments. In addition, the loading-plots associated with the PCA were generated using the singular value decomposition (SVD). HCA using the means, based on the Bray-Curtis distance (with 95% confidence) between groups from the discriminant function analysis (DFA), was also used to construct the similarity dendrograms. 3D-surface plots were performed with the data of the matrices for the four studied treatments.

Results

Biotic Stresses Altered the Phytohormonal Profile of Citrus Plants

Overall, we were able to identify and quantify 13 phytohormones belonging to six different groups (auxins, SAs, JAs, ABA, GAs, and CKs). We found that the infection with CLas and/or infestation with D. citri altered the levels of total auxins, SAs, JA, and ABA as groups, but did not affect the levels of GAs and CKs (Table B-1). Auxins were increased to higher levels in all treatments compared to control. SAs and ABA in CLas-infected plants were higher than other treatments and the control (2.5 folds, and 6.1 folds, respectively), while the JA in D. citri- infested plants was higher than CLas-infected and double-attacked plants (1.5 fold) (Figure 3-1 and Figure B-1). Interestingly, we have observed an intermediate effect on SAs, JA, and ABA in the double-attacked plants (Figure 3-1).

Both CLas and D. citri Increased the Auxins Levels in Citrus Leaves

Three auxins were detected (Indole-3-acetic acid, IAA; Indole-3-propionic acid, IPA; and

Indole-3-butyric acid, IBA) (Figure 3-2A). The infection with CLas and/or the infestation with

D. citri increased the levels of these auxins. The concentration of auxins ranged from 188.6±8.4 ng g-1 FW (for control-IAA) to 1389.6±96.3 ng g-1 FW (for IPA in CLas-infected plants). IAA was higher in CLas-infected plants (993.5±68.1 ng g-1 FW), followed by double-attacked and D. citri-infested plants (Figure 3-2A) (849.7±170.8 and 780.4±129.2 ng g-1 FW, respectively),

compared to control (188.6±8.5 ng g-1 FW). The effect of the infection with CLas on IAA was moderated when plants were also infested with D. citri simultaneously. The levels of IPA and

IBA were significantly higher in all treatments compared to the control (Figure 3-2A) without any significant differences between the treated plants.

CLas-Infection and D. citri-Infestation Increased ABA in Citrus Leaves

As shown in Figure 3-2B, the level of ABA was significantly higher in all treatments compared to the control. The highest amount of ABA was found in the CLas-infected plants

(1752.8±421.7 ng g-1 FW) followed by double-attacked and D. citri-infested (1398.9±247.5 and

933.2±317.6 ng g-1 FW, respectively). Additionally, these results showed that ABA concentration was mitigated in the double-attack plants (Figure 3-2B).

Salicylic Acid is Associated with Citrus Defense for CLas Infection

Three salicylate phytohormones (benzoic acid, BA; trans-cinnamic acid, tCA; and salicylic acid, SA) were detected in the citrus leaves (Figure 3-2C). BA was the most abundant in all treatments (2763.4 ng g-1 FW, as a mean of for treatments), followed by SA and tCA (1539.5 and 863.1 ng g-1 FW, respectively). CLas-infected plants showed greater increases in BA, tCA, and SA abundances (3570.1±517.4, 1222.0±301.4, and 2601.2±609.4 ng g-1 FW, respectively) than D. citri-infected plants (2376.6±389.5, 746.5±158.0, and 1106.2±227.4 ng g-1 FW, respectively) (Figure 3-2C). Additionally, the BA, tCA, and SA levels were mitigated when plants were simultaneously infected with CLas and infested with D. citri (3098.9±435.6,

1061.0±245.8, and 1896.4±370.1 ng g-1 FW, respectively) (Figure 3-2C). SA was the most highly induced phytohormone upon CLas infection (approximately 4.7 folds).

D. citri-Infestation Increased trans-Jasmonic Acid in Citrus Plants

The abundance of tJA in treated plants was significantly higher than the control.

Furthermore, the concentration of tJA in D. citri-infested plants (384.9±52.5 ng g-1 FW) was

significantly higher than that of CLas-infected and control plants (282.2±20.6 and 248.7±20.6 ng g-1 FW, respectively). In the same manner, the level of tJA was moderated in the double-attacked trees (333.2±32.6 ng g-1 FW) (Figure 3-2D).

CLas Altered the Balance Between SA and tJA

Due to the high increase in SA in CLas-infected plants, the ratio of SA/tJA in CLas- infected (9.2.6±1.8) and double-attacked plants (5.7±0.7) were significantly higher than that of the control (2.2±0.3) (Figure 3-3). On the other hand, due to the increase in both of SA and tJA in D. citri-infested plants, the ratio of SA/tJA (2.9±0.5) was not significantly different from the control (Figure 3-3). These results indicated that CLas infection disrupts the phytohormonal balance of citrus plants more than D. citri-infestation.

PCA and HCA Reveal Contrasting Phytohormonal-Defense Mechanisms

In agreement with the analysis of variance (ANOVA) results, the principal component analysis (PCA) showed that the phytohormonal profiles of the four treatments were different from each other. As shown in Figure 3-4A, the CLas-infected, D. citri-infested, and double- attacked plants were totally separated from each other and from the control group. The double- attacked plants clustered between the D. citri-infested and CLas-infected plants (Figure 3-4A).

As shown in the loading plot (Figure 3-4B), while tJA was positively associated with D. citri attack, salicylates and ABA were positively correlated with CLas infection.

The heat map (Figure 3-4C) also showed that the level of tJA in D. citri-infested leaves was higher than other treatments, whereas the levels of BA, tCA, SA, and ABA were the highest in CLas-infected leaves (Figure 3-4C). Two important clusters can be observed in the total hierarchical cluster analysis (HCA) dendrogram (Figure 3-4C) which was conducted using the individual phytohormones data. The first one is the phytohormonal cluster of auxins (around 60

% similarity); the second cluster is the SAs and ABA (around 45% similarity) and the tJA is

separated in the right end of the dendrogram (less than 15% similarity). Furthermore, the total two-way HCA dendrogram of treatments showed that CLas-infected plants were closer to the double-attacked plants (about 90% similarity) than D. citri-infested (about 75% similarity) and control plants (about 59% similarity).

3D Surface Plot Reveals the Correlation between Stress-Associated Phytohormones

The effect of SA and ABA content (as two input parameters) on tJA content (as an associated performance metric) was obtained in different treatments (Figures 3-5A to 3-5D).

Unlike the control, the total net profits (TNP) of tJA content in CLas-infected and double- attacked plants appeared to be higher in high-ABA and high-SA conditions. In D. citri-infested,

TNP of tJA was not affected by ABA levels (Figure 3-5C). These results indicate that there is a linear relationship between tJA content and SA content after CLas-infection and/or D. citri- infestation. However, no relationship between tJA content and ABA was observed in all treatments except in double-attacked plants.

Figures 3-5E to 3-5H show the effect of tJA and ABA content on SA content in different treatments. Similar with TNP of control, the SA content in CLas-infected, D. citri-infested, and double-attacked plants appeared to be higher in high-ABA and high-tJA conditions (Figures 3-5F to 3-5H). These findings indicate that there is a positive linear relationship between ABA, tJA, and SA content after infection with CLas and/or infestation with D. citri.

The effect of SA and tJA content on ABA content in control, CLas-infected, D. citri- infested, and double-attacked plants is presented in Figures 3-5I to 3-5L. The TNP of ABA of control, CLas-infected, and double-attacked plants (flat plateaus) were very different compared with D. citri-infested (sharp peak). Additionally, the TNP of ABA in D. citri-infested plants appeared to be lower at different levels of SA and tJA (Figure 3-5K). Also, the TNP of ABA in double-attacked plants was more similar to the TNP of ABA in CLas-infected than D. citri-

infested plants. These results indicate that there is a linear relationship between ABA and SA content after CLas-infection and/or D. citri-infestation. The results of the 3D surface plot analysis indicated that the correlation between these phytohormones is complex.

CLas-Infection and D. citri-Infestation Altered the Phytohormones’ Precursors

Results presented in Figure 3-6 showed the effect of CLas-infection and/or D. citri- infestation on the phytohormones’ precursors abundance in citrus leaves. Briefly, both amino acids L-phenylalanine (the precursor of SA) and L-tryptophan (the precursor of auxin IAA) were increased in CLas-infected plants compared to control (Figures 3-6A and 3-6B). On the other hand, linolenic acid (the precursor of JA) abundance was higher in D. citri-infested plants compared to other treatments. Linolenic acid levels in CLas-infected and double-attacked plants were also higher than control, but lower than those exposed to D. citri only (Figure 3-6C).

Furthermore, the plant pigment zeaxanthin (the precursor of ABA) was higher in all treatments compared to control (Figure 3-6D). Both CLas-infected and double-attacked plants had the highest abundance of zeaxanthin without significant differences between them (Figure 3-6D).

CLas and D. citri Altered the Expression of Phytohormones Biosynthetic Genes

The transcript levels of 38 genes involved in four phytohormone biosynthetic pathways

(auxins, SAs, JA, and ABA) in Valencia sweet orange leaves were investigated (Figure 3-7A) and the fold changes in the expression of these genes are shown (Figures 3-7B to 3-7E). Gene expression data were normalized using four reference genes (EF1, F-box, GAPDH, and SAND), which previously showed high stability for transcript normalization in different citrus organs under biotic stress (Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b). The normalizing expression levels using the four reference genes were very similar to each other (Data not shown). Overall, 22 out of the 38 genes were expressed at higher levels in CLas-infected plants,

14 genes in D. citri-infested plants, and only two in double-attacked plants. Figure 3-7B shows

that the expression of genes which are involved in the biosynthesis of JA including CitFAD,

CitLOX, CitAOS, CitAOC, CitOPR3, CitAAE7, CitACX1, CitAIM1, CitAIM2, and CitKAT, were upregulated in D. citri-infested plants compared to control (2.5 to 4.1 folds).

On the other hand, the ABA-biosynthetic pathway genes had diverse expression patterns.

CitZEP, CitVDE, and CitAAO3 were highly expressed in CLas-infected plants (up to 6.0 folds), while the highest expression of CitNSY, CitNCED, and CitABA2 was found in D. citri-infested leaves (Figure 3-7C). Furthermore, Figure 3-7D shows that the genes CitCM2, CitCM3,

CitADT1, CitAST-1, CitAST-2, CitTAT, CitPAL, CitKAT, and CitAAT, which are involved in the biosynthesis of SA were upregulated in CLas-infected plants (5.5 to 8.1 folds). Likewise, most of the auxins’ biosynthetic genes in CLas-infected plants including CitASA1, CitASA2, CitTS,

CitTSA, CitTSB, CitTAA2, CitYUC2, and CitYUC8, were expressed at higher levels (4.8 to 6.1 folds) compared with other treatments (Figure 3-7E). In agreement with our GC-MS results, the transcripts of cytokinins and gibberellins biosynthetic genes remained at the same levels in all treatments (data not shown). Generally, the expression levels of most of the phytohormones biosynthetic genes increased after the infection with CLas and/or infestation with D. citri.

(Figure 3-7) and these results are supporting our GC-MS findings.

Discussion

The infection with pathogens and/or herbivory with insects induce many phytohormonal signaling pathways in plants including the three main pathways (SA, JA, and ET) (Hatcher et al.

2004; Robert-Seilaniantz et al. 2007; Lazebnik et al. 2014). In agreement with the previous observations, our results showed that the levels of most of the phytohormones (ABA, JA, SAs, and auxins) were induced in CLas-infected, D. citri-infested, and double-attacked plants. On the other hand, no effect was observed on the levels of CKs and GAs, which were present at very

low concentration in the citrus leaves. This result indicated that CLas and D. citri attack did not affect CKs and GAs in citrus leaves.

The GC-MS results showed that salicylate phytohormones and its precursor phenylalanine were induced at a higher level in CLas-infected compared with D. citri-infested plants. In agreement with our results, a previous study also showed that salicylic acid was increased in CLas-infected citrus plants (Lu et al. 2013). In addition, SA biosynthetic genes were expressed at a higher level in CLas-infected plants compared with D. citri-infested plants. These results indicated that the salicylic acid defense pathway is activated in the citrus plants upon

CLas infection. Recently, it has been reported that CLas might use salicylate hydroxylase (SahA) to degrade SA and suppress citrus defenses (Li et al. 2017). However, the citrus plants may negate this enzymatic activity by more induction of SA as we shown in our study and a previous study by (Lu et al. 2013).

In general, SA is associated with plant defense response to biotrophic pathogens

(Glazebrook 2005; Bari and Jones 2009; Robert-Seilaniantz et al. 2007; Lazebnik et al. 2014).

Effector-triggered immunity (ETI) and pattern-triggered immunity (PTI) are the two common immunity mechanisms used by host plants against biotrophs and they are positively correlated with endogenous SA levels and its conjugates (Tsuda et al. 2009). Recent studies on citrus showed that citrus plants have both ETI and PTI mechanisms (Shi et al. 2014; Pitino et al. 2014).

Citrus may employ either ETI or PTI or both of them depending on the bacterial pathogen and its lifestyle (Pitino et al. 2014). For example, citrus uses both mechanisms upon infection with

Xanthomonas citri subsp citri, the bacterial pathogen of citrus canker disease, (Pitino et al.

2014). In another case, it has also been shown that citrus only initiates PTI (Shi et al. 2014). The high levels of SA and the high expression of its biosynthetic genes in CLas-infected plants

suggests that the infection with CLas triggers the PTI which is also known as basal resistance

(Erb et al. 2012; Kushalappa and Gunnaiah 2013).

In higher plants, SA is synthesized through the shikimate-phenylpropanoid pathway using two different routes (Guidetti-Gonzalez et al. 2007). Biochemical studies showed that SA can be derived from cinnamate produced by phenylalanine ammonia lyase (PAL), (Guidetti-

Gonzalez et al. 2007; Chen et al. 2009b). Other studies showed that the SA can be synthesized from isochorismate through two reactions. The first reaction is catalyzed by isochorismate synthase (ICS) and the second reaction is catalyzed by isochorismate pyruvate lyase (IPL) (Chen et al. 2009b). Although ICS is well characterized in citrus (Guidetti-Gonzalez et al. 2007) and was expressed at higher levels in CLas-infected plants, there is no evidence for the presence of

IPL in citrus. The high expression of PAL in CLas-infected plants suggested that SA in citrus is synthesized from cinnamate. In agreement with our results, silencing and chemical inhibition of

PAL genes in plants indicated that the synthesis of SA from cinnamate (produced from phenylalanine) was the most important pathway during pathogen infection (Chen et al. 2009b).

The level of SA was also elevated in D. citri-infected plants but to a lesser extent than

CLas-infected plants. The increase in SA in D. citri-infected plants was also supported by the increase in the gene expression of SA biosynthetic genes. Additionally, previous studies showed that the nymphs of the phloem feeder, Bemisia tabaci biotype B, also increased the expression of

SA-regulated genes and decreased JA- and ET-regulated genes in Arabidopsis thaliana (Walling

2008). These results indicated that B. tabaci manipulates plant signaling to suppress the effective defense (JA- regulated defenses that deter nymph development) (Walling 2008). SA was also involved in response to aphid colonization in many plants including Arabidopsis, barley, tomato, and soybean (Studham and MacIntosh 2012). Interestingly, Mann et al. (2012) found that CLas-

infected plants were more attractive to D. citri than non-infected plants, which may enhance the dissemination of CLas from infected plants to healthy ones. The attraction of CLas-infected plants to D. citri was attributed to methyl salicylate which was released at a higher level in CLas- infected plants (Mann et al. 2012).

On the other hand, the infestation with D. citri increased the level of tJA and its precursor

(linolenic acid). In addition, the expression of all of the selected JA-biosynthetic genes was upregulated upon D. citri infestation more than CLas infection. The key role of JA as a herbivore-associated phytohormone has been extensively studied (Robert-Seilaniantz et al. 2007;

Bari and Jones 2009; Lazebnik et al. 2014). Previous studies demonstrated that exogenous application of JA or its derivative methyl jasmonate (me-JA) triggers the activity of several defense mechanisms against the chewing herbivore beet armyworm, Spodoptera exigua, on

Arabidopsis (Cipollini et al. 2004). In addition, me-JA application reduces the performance of the phloem-feeding psyllid Agonoscena pistaciae on pistachio (Pistacia vera) leaves

(Shahabinejad et al. 2014). In fact, the JA-mediated pathway is associated with other response activities such as antioxidant activity augmentation (Shahabinejad et al. 2014), hypersensitive reaction, HR (Schilmiller and Howe 2005), and systemic acquired resistance, SAR (Thaler et al.

2010).

Genetically, transcripts of the defense genes related to JA such as allene oxide synthase

(AOS; a JA-biosynthetic enzyme) and proteinase inhibitor 2 (Pin2; a defense transcript in the JA pathway) have been upregulated by the feeding activity of young tomato psyllid nymphs,

Bactericerca cockerelli (Casteel et al. 2012). In agreement with the previous data, we also found that the expression of AOS in D. citri-infested and in double-attacked plants was higher compared to control plants.

The ratio of SA/JA was not affected in the D. citri-infested plants, while it was increased more than four folds in the CLas-infected plants due to the increase of SA. These results indicated that CLas infection disrupts the phytohormonal balance in citrus. Although the levels of SA and JA were determined in many studies after biotic and abiotic stresses, the ratio of these two important phytohormones was not compared. For example, inoculation of tobacco with tobacco mosaic virus (TMV) increased the level of SA (187 fold) and JA (11 fold) and increased the ratio of SA/JA from 3 in the control plants to 50 in TMV-infected plants (Matsuura et al.

2009). On the other hand, the SA/JA ratio in Arabidopsis remained constant upon the infection with the necrotrophic bacterium, Xanthomonas campestris pv. campestris (O’Donnell et al.

2003). In this case, both SA and JA were increased which did not affect the ratio. Taken together the change of SA/JA ratio could be associated with the trophic-type of the pathogen.

While biotrophic and hemibiotrophic pathogens increased the ratio, necrotrophic pathogen and insect herbivory do not affect the ratio of SA/JA.

Auxins are mainly implicated in plant development. However, recently it has been shown that they are also involved in response to biotic and abiotic stresses (Ghanashyam and Jain

2009). Ghanashyam and Jian (2009) showed that 55 and 37 of the auxin genes were induced in rice seedlings (Oryza sativa) after infection with Manaporthe grisea and Striga hermonthica, respectively. IAA was also increased in the fruits (Rosales and Burns 2011; Martinelli et al.

2012) and flowers from CLas-infected plants (Lahey et al. 2004). In addition, the bacterial pathogen Pseudomonas syringae pv. tomato DC3000 (PstDC3000) significantly induced the

IAA level in Arabidopsis thaliana cv. Columbia (Col-0) (Schmelz et al. 2003). Previous studies also showed that levels of IAA were elevated in insect-attacked plants (Erb et al. 2012). It is believed that there is a positive relationship between JA and auxins; JA enhances auxins

biosynthesis and vice versa (Erb et al. 2012). In agreement with the previous results, we found a significant increase in the levels of auxins in CLas-infected, D. citri-infested, and double- attacked plants. The increase in auxins levels was supported by an upregulation of the expression levels of auxins biosynthetic genes.

The performance of auxins during pathogen infections is complex, and most of the previous studies focused on the role of auxins in pathogenesis (Fu and Wang 2011). Pathogens may alter the host physiological processes and signaling to fulfill their needs. Bacterial pathogens could modulate IAA production in plants to promote virulence and disease development (Chen et al. 2004), to get more nutrients (Lindow and Brandl 2003), or to use it as a signaling molecule in order to improve their survival under stress conditions (Remans et al. 2006).

Although ABA is also known as an abiotic stress-associated phytohormone (drought and salinity stress), ABA is also involved in disease tolerance against biotrophs, necrotrophs, and herbivores (Bari and Jones 2009; Robert-Seilaniantz et al. 2007). Infection with CLas enhanced the production of ABA in citrus leaves. This finding was supported by the upregulation of its biosynthetic genes. In agreement with our results, ABA was also found to increase in CLas- infected citrus fruits and petals infected by Colletotrichum acutatum (Martinelli et al., 2012;

Rosales and Burns 2011; Lahey et al., 2004). Additionally, previous studies showed that ABA level was positively correlated with susceptibility to Magnaporthe oryzae in rice (Koga et al.

2004) and PstDC3000 and Peronospora parasitica in Arabidopsis (Mohr and Cahill 2003).

The effect of ABA on SA and JA is still controversial. (Robert-Seilaniantz et al. 2007;

Bari and Jones 2009) showed that ABA seems to regulate the SA-mediated and JA/ET-mediated pathways negatively in higher plants. On the other hand, other studies showed that ABA has a positive effect with JA against insect attack and negative effect with salicylic acid against some

pathogens (Thaler and Bostock 2004). In the current study, higher levels of ABA were accompanied with higher levels of SA (in Clas-infected) and JA (in D. citri-infected). The higher level of ABA in CLas-infected and D. citri-infested plants suggested that it could also result from drought stress. Plugging and collapse of the phloem in CLas-infected plants may compromise water passage and result in drought stress. In addition, the loss of roots in CLas- infected plants decreases water uptake (Graham et al. 2013). In fact, field and greenhouse observation also showed that symptomatic leaves from CLas-infected plants were more dehydrated than healthy leaves. In addition, leaf damage caused by insect feeding can result in dehydration in infested plants (Thaler and Bostock 2004).

The levels of most phytohormones were moderated in double-attacked plants. In agreement with this result, the gene expressions of double-attacked plants were also reduced compared to single-attacked plants. In our earlier report, we found that the effects of CLas and

D. citri on citrus leaf volatiles were moderated when plants were simultaneously attacked by D. citri and CLas (Hijaz et al. 2013). Activation of more than one defense pathway in double- attacked plants increases energy consumption and this could compromise plant responses. In addition, plants attacked by multiple attackers can produce some compounds that may cause synergistic or antagonistic effects on other pathways. For example, SA and its functional analogues that are induced after pathogen attack cause down-regulation of JA-induced defense gene expression (Pieterse and van Loon 1999).

To summarize our findings and postulation, a hypothetical model for the phytohormonal pathways response in citrus to CLas-infection and/or D. citri-infestation was created and presented in Figure 3-8. Citrus plants develop a multi-layered defensive system to protect themselves. The defense mechanisms include accumulation of defense molecules, alteration of

plant signaling system, changes in primary and secondary metabolites, and other biochemical and physiological modifications. Mainly, SA- and JA-mediated pathways are the most common defensive pathways in citrus. Briefly, as a primary response, citrus activate ETI and/or PTI against the CLas-infection, which leads to up-regulation of auxins, SAs, and ABA biosynthetic genes. On the other hand, activation of the herbivore-triggered immunity (HTI) against the D. citri induces a higher expression of tJA-biosynthetic genes. Both together lead to significant accumulation of these phytohormone compounds. The cross-talk between different groups of phytohormones is possible and complicated. Finally, the changes in phytohormone levels alter the expression of defense signaling molecules, which leads to the activation of SA- and JA- mediated pathways.

Figure 3-1. Total concentrations of different phytohormone groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM. All phytohormones were extracted in methanol and derivatized with MCF (n=10). Auxins group was calculated as a total of IAA, IPA, and IBA; salicylates (SAs) group was calculated as a total of BA, tCA, and SA. Different letters indicate statistically significant differences among the studied treatments, while “ns” signify no significant differences between them (p<0.05).

Figure 3-2. Concentrations of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM. (A) Auxins, (B) ABA, (C) SAs, and (D) tJA. All phytohormones were extracted in methanol and derivatized with MCF (n=10). Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, whiskers reflect the highest and the lowest number of the data, and different letters indicate statistically significant differences among treatments, while “ns” signify no significant differences between them (p<0.05).

Figure 3-3. Effect of CLas infection and/or D. citri infestation on the ratio of (SA/tJA) in citrus plants. Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest number of the data. Different letters indicate statistically significant differences among treatments (p<0.05).

Figure 3-4. Principal component analysis (PCA) and two-way hierarchical cluster analysis (HCA) of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM. (A) PCA-scatter blot, (B) PCA-loading-plot, and (C) two-way HCA dendrograms (n=10).

Figure 3-5. Three-dimensional surface plots among stress-associated phytohormones (SA, ABA, tJA) detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri. (A, B, C, and D) Effect of salicylic acid (SA) content, abscisic acid (ABA) content, and their reciprocal interaction on trans- jasmonic acid (tJA) content in different treatments; (E, F, G, and H) effect tJA content, ABA content, and their reciprocal interaction on SA content in different treatments; and (I, G, K, and L) effect of tJA content, SA content, and their reciprocal interaction on ABA content in different treatments, (n=10).

Figure 3-6. Concentrations of different phytohormones precursors detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri. (A) phenylalanine, the precursor of SA; (B) tryptophan, the precursor of IAA; (C) linolenic acid, the precursor of JA; and (D) zeaxanthin, the precursor of ABA. Phenylalanine, tryptophan, and linolenic acid were extracted in methanol, derivatized with MCF and determined using GC-MS-SIM (n=10), while zeaxanthin was extracted with acetone 80% followed by ethyl acetate and determined using HPLC. Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest number of the data. Different letters indicate statistically significant differences among treatments, while “ns” signify no significant differences between them (p<0.05).

Figure 3-7. Different biosynthesis phytohormone pathways and their implicated genes detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or infestation with D. citri. Different biosynthesis phytohormone pathways and their implicated genes detected in Different phytohormones groups biosynthesis pathways (A), and heat map diagrams of differential gene expression patterns of tJA- biosynthetic genes (B), ABA-biosynthetic genes (C), SAs-biosynthetic genes (D), and auxins-biosynthetic genes (E). Each row represents a single gene and each column shows a single treatment, data is normalized for each gene in each row, (n=30). Lower expression levels are colored green and higher expression levels are colored red (see scale at the bottom of each heat map). At the top of the heat map diagram, there is a hierarchical clustering order of the four tested treatments, which named in the bottom. For the full list of genes, accession ID, and primers, see the supplementary data (Table B-2 to B-5). For the full names and abbreviations, see the abbreviations list.

Figure 3-8. Hypothetical model of citrus phytohormones-depending defense system against CLas-infection and/or D. citri-infestation. I) As generalized model, while CLas- infection triggers MAMPs, PAMPs and/or DAMPs, which is recognized by PRRs and lead to PTI, D. citri-infestation triggers MAPKs and HAMPs which lead to HTI. To combat, pathogen effectors try to suppress the PTI and D. citri-effectors-like molecules try to suppress the HTI. Simultaneously, the host plant resists CLas- invasion and D. citri-herbivory by expressing R genes. II) The PTI and/or ETI might upregulate the expression of auxins-, SAs-, and ABA-biosynthetic genes, while the activation of HTI could induce a higher expression of tJA-biosynthetic genes. III) The accumulations of auxins-, SAs-, JAs- and ABA -biosynthetic genes lead to significant accumulation of these compounds. The cross-talk between these groups of phytohormones is complicated, and it might be synergistic or antagonistic. IV) The changes in phytohormone levels alter the expression of defense signaling molecules, leading to the activation of SA- and/or JA-mediated pathways. Additionally, both auxins and ABA were accumulated after exposure to CLas and/or D. citri, which indicate that auxins and ABA maybe implicated in activation of SA- and JA-mediated pathways. The solid lines with arrows signify positive reaction, the dashed lines with bar-ends indicate negative correlation, and round-dotted lines with arrows represent hypothetical mechanisms or uncharacterized elements. For the full names and abbreviations, see the abbreviations list.

CHAPTER 43 ONE TARGET, TWO MECHANISMS: THE IMPACT OF Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri ON CITRUS LEAF PIGMENTS

Herein, we examined the effect of HLB pathogen, Candidatus Liberibacter asiaticus- infection and/or its vector, Diaphorina citri-infestation on Valencia sweet orange leaf pigments using HPLC, followed by gene expression analysis for 46 involved genes in carotenoids- and chlorophylls-biosynthesis pathways.

Introduction

Infection by pathogenic bacteria, fungi, oomycetes, and viruses can cause morphological, biochemical, and physiological alterations in the host plant (Lobato et al. 2010; Xie et al. 2011;

Prokopová et al. 2010b, 2010a; Rosales and Burns 2011; Wei et al. 2014a, 2014b).

Photosynthesis is one of the most affected physiological processes in the autotrophic life of the infected plants (Prokopová et al. 2010b, 2010a; Lobato et al. 2010; Kangasjärvi et al. 2012). For example, both tomato genotypes Lycopersicon chmielewskii (moderately resistant) and

Lycopersicon esculentum (susceptible) showed a deterioration of photosynthesis after infection by powdery mildew fungus Oidium neolycopersici (Prokopová et al. 2010a). Furthermore, in lettuce plants (Lactuca sativa) infected by Bremia lactucae, the oomycete pathogen of lettuce downy mildew, increased NPQ (non-photochemical quenching) and deficiency in photosynthetic pigment content, electron transport of photosystem II (ФPSII), and the maximal quantum yield of

PSII (FV/FM) were reported (Prokopová et al. 2010b).

Many factors can affect the rate of photosynthesis, such as light intensity, CO2 concentration, and photosynthetic pigment content of the leaves (Smith 1938; Terry 1980). The

3 The results of Chapter 4 were published in the Molecular Plant-Microbe Interactions (MPMI) as “Killiny, N., and Nehela, Y. 2017. One target, two mechanisms: The impact of ‘Candidatus Liberibacter asiaticus’ and its vector, Diaphorina citri, on citrus leaf pigments. Mol. Plant-Microbe Interact. 30:543–556”.

photosynthetic pigments are responsible for the absorption of light energy through the light- dependent reactions phase of photosynthesis (Tanaka et al. 2011; Lobato et al. 2010; Gough et al. 2003). The photosynthetic pigments include the chlorophyll, carotenoids, and other pigments

(Lobato et al. 2010).

The chlorophylls are the most abundant pigments in higher plants (Gough et al. 2003;

Wettstein et al. 1995; Reinbothe et al. 2010). The structure of chlorophylls are tetrapyrrole macrocycles (porphyrin rings) containing Mg+2 in the center, a phytol chain, and a characteristic fifth ring consisting of a methyl group as in chlorophyll a, or a formyl group as in chlorophyll b

(Wettstein et al. 1995; Tanaka and Tanaka 2007). Chlorophylls play a key role in photosynthesis by harvesting the sunlight energy and transferring the electrons to the other molecules in the reaction center (Reinbothe et al. 2010; Tanaka and Tanaka 2007; Tanaka et al. 2011). In addition, chlorophyll derivatives, such as chlorophyllide, result from the removal of the phytol chain by chlorophyllase, a hydrolase common in most plants that located in the endoplasmic reticulum (ER) and tonoplast (Hu et al. 2015). Chlorophyllide was found to be formed after herbivory or when chlorophyllase was freed from the ER by cell disruption. Its toxicity plays a critical defense role against chewing insects such as Spodoptera litura (Hu et al. 2015) and the necrotrophic fungus, Alternaria brassicicola (Kariola et al. 2005) in Arabidopsis thaliana plants.

Carotenoids are a large group of tetraterpenoids, which are produced from eight isoprene molecules and contain 40 carbon atoms with polyene chains that may contain up to 15 conjugated double bonds (Tanaka et al. 2008; Vershinin 1999). In higher plants, carotenoids are synthesized in the chloroplasts and chromoplasts by nuclear-encoded enzymes (Cunningham and

Gantt 1998; Tanaka et al. 2008; Cazzonelli 2011). While there are over 700 different known carotenoids (Kato 2012), only 115 carotenoid compounds were identified in citrus fruits (Rouseff

et al. 1996; Matsumoto et al. 2007). Carotenoids are divided into two classes. Carotenes, which are purely hydrocarbons and do not contain O2 and xanthophylls which contain O2. In higher plants, carotenoids play an important role in the variegation of leaves, flowers, fruits, and other organs (Cazzonelli 2011; Tanaka et al. 2008). Additionally, they serve as norisoprenoid precursors for many biologically important compounds (Bauernfeind 1972; Vershinin 1999;

Tanaka et al. 2008). Carotenoids with unsubstituted beta-ionone rings (such as α-carotene, β- carotene, β-cryptoxanthin, and γ-carotene) are precursors for vitamin A and can also act as antioxidants (Cunningham and Gantt 1998; Bauernfeind 1972). Furthermore, carotenoids are not only responsible for the specific coloration patterns in plants, but they also play a key role in the photosynthetic process (Armstrong and Hearst 1996; Vershinin 1999). Carotenoids protect chlorophyll pigments from photo-damage, in addition to their role as accessory light-harvesting pigments in all plants, while they absorb light energy for the use in photosynthesis (Armstrong and Hearst 1996; Vershinin 1999).

Huanglongbing (HLB), also known as citrus greening disease, the most serious disease in citrus, originated in East Asia at the end of 1800s (Gottwald et al. 1989; da Graça and Korsten

2004; Bové 2006; Gottwald 2010). HLB is caused by the fastidious phloem-restricted bacterium

Candidatus Liberibacter spp., a member of the Gram-negative α-proteobacteria, and is currently not available in culture (Bové 2006; Gottwald 2010; Jagoueix et al. 1994). Taxonomically, based on the characteristic 16S rDNA sequences and geographical distribution, three Ca. Liberibacter species have been proposed. Ca. L. asiaticus (CLas) in Asia (Bové and Ayres 2007; Gottwald

2010; Wang and Trivedi 2013), Ca. L. africanus in Africa (Da Graca 1991; Planet et al. 1995), and Ca. L. americanus in Brazil (Coletta-Filho et al. 2004; Teixeira et al. 2005a). Among the three Liberibacter species, CLas is the most dominant species and has caused huge economic

losses to citrus production worldwide (Bové 2006; Gottwald 2010). The tree-to-tree transmission of the bacterium occurs by grafting infected material, or by the psyllid vectors. The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae) in Asia and Americas (Bové 2006;

Gottwald 2010; Wang and Trivedi 2013), and the African psyllid, Trioza erytreae (Del Guercio) in Africa (Da Graca 1991). These two vectors are responsible for the wide geographical distribution of HLB disease in the infected areas (Teixeira et al. 2005b).

The characteristic symptoms of HLB infected citrus trees are due to alteration in many physiological aspects such as phytohormonal levels, carbohydrate status (Rosales and Burns

2011), and carotenoid content (Wei et al. 2014a, 2014b). Symptoms of HLB are induced by both the pathogen and its vector and include blotchy mottle and yellow veins on leaves (Schneider

1968; Bové 2006). In addition, young flushes on infected trees appear yellow, with small and upright leaves showing various chlorotic patterns (Schneider 1968; Bové 2006; Da Graca 1991;

Sagaram et al. 2009). These symptoms are usually visible only on some branches of the tree, while other branches are non-symptomatic (Schneider 1968). Stunted growth, twig dieback, and poor flowering are secondary HLB-symptoms (Schneider 1968; Bové 2006; Mishra et al. 2011).

The fruits from the infected trees are small, lopsided, and distorted with color inversion (Bové

2006; Mishra et al. 2011), which often contain abnormal and brown seeds. Furthermore, the fruit yield of infected trees decreases until the trees become non-productive, while juvenile infected trees may never bear fruit (Sagaram et al. 2009).

On the other hand, D. citri feeding causes waxy deposits, sugary honeydew, and sooty mold. High populations of psyllids feeding on new shoots can kill the growing flush. Feeding of moderate psyllid population can result in deformation of leaves and shoots, twisted leaves, and asymmetrical yellowing on leaves (Hoy and Nguyen 2000). In general, all of these symptoms do

not exist simultaneously on the same infected tree (Sagaram et al. 2009). Taking together, HLB- symptoms involve chlorosis/discoloration due to the degradation of photosynthetic pigments such as chlorophylls and carotenoids.

Recently, our recognition of physiological events associated with CLas-infection and/or

D. citri-infestation has been greatly improved. However, the mechanisms of HLB-symptom development are still unexplored. In order to understand the mechanism of discoloration development, we investigated the chlorophyll and carotenoid contents in Valencia sweet orange

(Citrus sinensis (L.) Osbeck) leaves after the infection with CLas and/or the infestation with its vector, D. citri. Herein, we tested the hypothesis that both Clas and D. citri cause changes in the leaf pigments but through two different mechanisms.

Materials and Methods

Plant Materials and Growth Conditions

Citrus sinensis (L.) Osbeck (Valencia sweet orange) were used as plant materials in this study. All trees were about 80±5 cm tall, around 18 months old, and maintained in an approved

USDA-APHIS/CDC-secured greenhouse, at 28±3°C; 65±5% RH; 16:8 L/D photocycle hours, at the Citrus Research and Education Center (CREC), University of Florida, Lake Alfred, Florida.

Weekly, plants were irrigated twice and fertilized once using 20-10-20 NPK fertilizer

(Allentown, PA, USA). In this study, four treatments (five replicates for each) were tested included; control, CLas-infected, D. citri-infested and double-attacked (CLas-infected and D. citri-infested) trees. To obtain the CLas-infected trees, ten months old, HLB-free Valencia sweet orange trees were graft-inoculated with budwoods from a PCR-positive HLB source (HLB- infected citrus trees) and maintained in same conditions as described above. Upon initial symptom development, approximately seven months later, the infection with CLas was confirmed by PCR (Tatineni et al. 2008). To obtain D. citri-infested plants, 100 healthy D. citri

(previously reared on Bergera koenegii, non-host for CLas) were transferred to healthy citrus plant, which is trimmed one-week prior the infestation to enhance the production of new flushes.

Infested plants were caged individually for one month. To obtain the double-attacked plants,

CLas-infected trees, with enhanced flushing as described above, were exposed to100 CLas- negative adult psyllids per tree for one month All plants used in this study, with or without D. citri infestations, were caged individually using insect rearing cages (60×60×90 cm) and maintained in the same conditions as described above. One month later, both D. citri-infested and double-attacked plants were cleaned from all D. citri stages (nymphs and adults). For sampling, three symptomatic leaves were collected per tree from different positions. Collected leaves were from different ages; juvenile leaf from the top, moderate-age one from the middle, and mature leaf from the lower part of the plant. The collected leaves were chopped, mixed together and immediately kept on ice. Plant materials were kept at -80°C until analysis.

Extraction of Citrus Leaf Pigments

Plant tissues were placed into a frozen mortar and pest and then ground in liquid nitrogen into a fine powder and citrus leaf pigments were extracted according to the methods of (Norris et al. 1995) with slight modifications as follow. Briefly, about 0.1 g ground material was transferred to a 1.5 ml amber tube. For each sample, a 400 µL of acetone 80% was added, followed by 240 µL of ethyl acetate and vortexed for 30 s. Samples were left in the dark on ice for 10 min and the vortexing was repeated twice. Later, 280 µL of water was added, and the mixture was centrifuged at 8500 x g for 5 min at 4o C. Then, the upper layer was transferred to a new 500 µL amber tube and dried under a nitrogen stream. The dried extract was resuspended in

200 µL ethyl acetate and analyzed immediately by high-performance liquid chromatography

(HPLC) or stored in the dark at -20o C.

High-Performance Liquid Chromatography Analysis

HPLC analysis of citrus leaf pigments was carried out as described previously by (Wei et al. 2014a, 2014b). The HPLC system consisted of an Agilent 1200 system with photodiode array detector (Agilent Technologies, Santa Clara, CA, USA). Chromatographic separation was performed using a C30 YMC carotenoid column, 250×4.6 mm I.D., S-5 μm (YMC America,

Allentown, PA, USA). The mobile phase composition and the gradient profile was as described by (Mouly et al. 1999) with slight modifications. Briefly, a step-wise linear elution gradient of methanol, methyl tert-butyl ether (MTBE), and water and was used (Table 4-1). The column temperature was adjusted at 25 °C, mobile phase flow rate was 1 ml min−1, and the injection volume was 20 μL. The absorbance of the various citrus leaf pigments and peak responses were monitored at several spectral wavelengths (230, 278, 350, 430 and 486 nm). The HPLC-output data were analyzed using ChemStation software, B.03.02, (Agilent Technologies, CA, USA).

Peaks were first identified by comparing experimental retention times and UV-visible spectra with that of published literature (Table 4-2), as well as with authentic standards. Chlorophyll a, chlorophyll b, α-carotene, β-carotene, lutein, and zeaxanthin were obtained from Sigma-Aldrich

(USA) and used to establish a calibration curve from which to calculate the pigments concentration in the extract for those compounds. The rest of the pigments were calculated tentatively using the lutein calibration curve.

ABA Determination using ELISA

ABA was determined according to (Ross et al. 1987) with slight modifications. Briefly,

ABA was extracted from 300 mg leaves tissues with 80% methanol containing 100 mg L−1 butylated hydroxytoluene (BHT; as an antioxidant) for 18h at 4 °C in the dark. The extract was centrifuged at 8500 x g for 10 min at 4 °C. The supernatant was recovered and purified using a

TM Sep-Pak C18 classic short cartridge (360 mg Sorbent per cartridge, 55-105 µm particle size,

Waters, MA, USA), connected to a Titan2® 5 μm nylon filter (SUN-Sri, Thermo Fisher

Scientific, TN, USA). The eluted samples were dried under a nitrogen stream to 20 μL, then diluted with 180 μL TRIS-buffered saline, 1X (TBS; 0.53 g L–1 Tris base, 3.25 g L–1 Tris HCl,

–1 –1 5.84 g L NaCl, and 0.2 g L MgCl2; pH 7.5). Samples were analyzed and quantified by competitive direct enzyme-linked immunosorbent assay (ELISA), using a Phytodetek® ABA test kit (Agdia Inc., IN, USA). The ELISA procedure used in this study was performed following the manufacturer’s instructions. ABA concentration was estimated using the standard curve prepared in the same immunoassay plate.

Colorimetric Determination of Starch and Sucrose

Starch and sucrose were extracted according to (Cimò et al. 2013) with slight modifications. Briefly, starch and sucrose were extracted from 100±3 mg ground leaf tissues using 500 μL distilled water and vortexed for 30 s. The extract was boiled in a water bath for 10 min then vortexed for 10 s. Following centrifugation at low speed (650 x g), the supernatant was divided into two portions; 300 μL for starch determination (Cimò et al. 2013) and 100 μL for sucrose determination (van Handel 1968). Starch was determined by monitoring the color change at 595 nm using a microplate spectrophotometer (Model 680, BIO-RAD Laboratories, CA,

USA). Rice starch from Sigma-Aldrich (USA) was used as a standard. Sucrose determination was accomplished at 620 nm using PharmaSpect ultraviolet 1700 spectrophotometer (Shimadzu

Corporation, Japan).

Gene Expression Analysis

Total RNA was extracted using TriZol® reagent (Ambion®, Life Technologies, NY,

USA). NanoDrop 2000 spectrophotometer (Thermo Scientific, USA) was used to estimate the quantity and quality of isolated RNA. For synthesizing cDNA, the SuperScript first-strand synthesis system (Invitrogen) with random hexamer primers was used as described by the

manufacturer’s instructions. SYBR® Green PCR master mix (Applied Biosystems) was used to perform quantitative PCR (qPCR) on an ABI 7500 Real-Time PCR System (Applied

Biosystems). For each treatment, two technical replicates per biological replicate and five biological replicates per treatment were analyzed in three replicates. Primers for 48 genes were used to measure the gene expression (Table C-1 and C-2). The 2−ΔΔCT method was used to determine the relative expression of genes (Livak and Schmittgen 2001). Elongation factor 1- alpha (EF1), F-box/kelch-repeat protein (F-box), glyceraldehyde-3-phosphate dehydrogenase

GAPC1, cytosolic (GAPC1, also known as GAPDH), and SAND family protein (SAND) were used as endogenous gene (reference gene) to normalize the data of gene expression (Mafra et al.,

2012; Wei et al., 2014a and Wei et al., 2014b).

Statistical Analysis

For HPLC, five biological and two technical replicates per treatment were analyzed. All pigment concentrations were statistically analyzed using the analysis of variance (ANOVA). Post hoc pairwise comparisons between the four studied treatments were performed using a Tukey-

Kramer honestly significant difference test (Tukey HSD). Principal component analysis

(PCA) associated with loading-plots were generated to differentiate between treatment. Two way-hierarchical cluster analysis (HCA) was also performed with the means of the matrices for the four studied treatments. Distance and linkage were done using the Bray-Curtis similarity measure method (Michie 1982). 3D-surface plots were performed among the three pigments groups (as a total for each group) with the matrices of data for the four studied treatments.

Multivariate genes similarities were presented as a heat-map using the averages of fold change where gene expression in healthy plants considered 1, combined with two way-HCA as described above.

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Results

Using HPLC to study citrus leaf pigments, we were able to detect and quantify 15 different pigments belonging to three groups (carotenes, xanthophylls, and chlorophylls) (Figure

4-1 and Table 4-2). Four pigments were detected from the chlorophyll group (chlorophyll a, chlorophyll b, pheophytin a, and chlorophyllide a). Eight pigments were identified as xanthophylls (neoxanthin, trans-violaxanthin, cis-violaxanthin, zeaxanthin, lutein, isolutein, α- cryptoxanthin, and β-cryptoxanthin). Lastly, cis-β-carotene, α-carotene, and β-carotene were detected from carotenes group.

CLas and D. citri Alter Citrus Leaf Pigments Content

The total pigments content was significantly reduced by CLas-infection (518.61±75.28

μg g-1 FW) followed by D. citri-infestation (1022.75±145.55 μg g-1 FW) compared to control plants (1294.66±158.78 μg g-1 FW). Interestingly, this effect was compromised in the double- attacked plants (626.08±109.55 μg g-1 FW) (Figure 4-2A). Additionally, the total chlorophylls, xanthophylls, and carotenes content as groups, were significantly decreased in CLas-infected plants (111.97±24.78, 331.47±64.76, and 75.16±25.77 μg g-1 FW, respectively), followed by D. citri-infested plants (514.22±92.63, 358.35±46.18, 150.19±40.51 μg g-1 FW, respectively) compared to control (680.64±135.83, 330.58±29.99, and 283.44±57.00 μg g-1 FW, respectively).

The total chlorophylls, xanthophylls, and carotenes contents were compromised in double- attacked plants (165.21±35.86, 345.63±82.89, and 115.23±24.84 μg g-1 FW, respectively)

(Figure 4-2B)

The percentages of total chlorophylls, xanthophylls, and carotenes were similar in both

CLas-positive and double-attacked; and slightly different from D. citri-infested and control plants (Figure 4-2C and 4-2D). While chlorophylls were the most abundant group in control

(49%) and D. citri-infested plants (50%), chlorophylls were lower in CLas-positive and double-

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attacked plants (27% and 26%, respectively). Xanthophylls group composes the majority of total leaf pigments (55%) in CLas-positive and double-attacked plants (Figure 4-2C). These data suggest that infestation with D. citri does not change the pigment percentages while infection by

CLas was responsible for the reduction of chlorophylls and increase in xanthophylls percentages.

Total carotene percentage was unaffected by either psyllid infestation or CLas infection.

Infection with CLas Increases Zeaxanthin and Decreases other Pigments

The pigment profiles of CLas-infected and double-attacked plants were more affected than D. citri-infested plants compared to control (Figure 4-3A, 4-3B, and 4-3C). All chlorophyll compounds were reduced significantly within the profile of CLas-infected and double-attacked plants. The highest reduction was found in chlorophyll a content in CLas-infected leaves

(21.65±8.30 μg g-1 FW), followed by double-attacked plants (21.85±9.87 μg g-1 FW) compared to control (379.25±97.06 μg g-1 FW) (Figure 4-3A). In xanthophylls group, CLas-infected plants had the lowest concentrations of all detected xanthophylls followed by the double-attacked plants, except for zeaxanthin (Figure 4-3B). No significant differences were found in β- cryptoxanthin among all studied treatments and control. Zeaxanthin was significantly induced at higher levels in double-attacked leaves (104.80±52.21 μg g-1 FW) and CLas-infected

(91.07±62.51 μg g-1 FW) compared to control (34.79±15.96 μg g-1 FW). The concentration of zeaxanthin in D. citri-infested leaves (55.85±29.68 μg g-1 FW) was not significantly affected compared to control plants (Figure 4-3B). All detected carotenes, including cis-β-carotene, α- carotene, and β-carotene, were significantly reduced after CLas-infection (2.29±0.95,

61.12±21.27, and 11.75±4.95 μg g-1 FW, respectively) compared to control (5.68±0.65,

245.43±49.77, and 32.33±7.51 μg g-1 FW, respectively). However, levels of cis-β-carotene were similar in the three treatments, whereas α- and β-carotene showed differences between treatments. (Figure 4-3C).

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Infestation with D. citri Increases Chlorophyllide a and Decreases other Pigments

Among the four detected chlorophyll compounds in the D. citri-infested plants, only chlorophyll a and chlorophyll b were decreased (178.16±62.01 and 115.41±23.49 μg g-1 FW, respectively) compared to control (379.25±97.06 and 139.34±24.37 μg g-1 FW, respectively)

(Figure 4-3A). Furthermore, chlorophyllide a was dramatically increased in D. citri-infested plants (127.46±52.77 μg g-1 FW) compared to control (47.13±15.10 μg g-1 FW). No significant differences were found in pheophytin a between them (Figure 4-3A). Likewise, among the eight detected xanthophylls, four compounds were significantly decreased in D. citri-infested plants including α-cryptoxanthin (2.97±2.09 μg g-1 FW), trans-violaxanthin (18.58±3.43 μg g-1 FW), neoxanthin (45.99±10.05 μg g-1 FW), and lutein (154.56±31.77 μg g-1 FW) compared to control

(4.82±1.70, 23.05±9.57, 62.18±18.47, and 211.89±25.19 μg g-1 FW, respectively). Meanwhile,

D. citri infestation did not affect levels of other xanthophylls (Figure 4-3B). In carotenes group, all compounds, include cis-β-carotene, α-carotene, and β-carotene, were reduced in D. citri- infested plants (3.48±1.33, 121.05±30.39 and 25.65±11.18 μg g-1 FW, respectively) compared to control (5.68±0.65, 245.43±49.77 and 32.33±7.51 μg g-1 FW, respectively) (Figure 4-3C).

PCA and HCA Analyses Revealed the Differences among Treatments

The score plot obtained from principal components analysis (PCA) showed a clear separation among CLas-infected and double-attacked (as overlapping groups), control, and D. citri-infested plants with respect to PC1 (53.4%) and PC2 (12.3%) (Figure 4-4A). The loading- plot showed that zeaxanthin was positively correlated with CLas-infection and double-attacked treatments, while the rest of the pigments were positively correlated with control and D. citri- infested plants (Figure 4-4B). In addition, the two-way hierarchical cluster analysis (HCA) and heatmap were performed using the individual compounds. The citrus pigment profile in the leaves from CLas-infected plants was more similar to the double-attacked plants (about 85%

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similarity) than D. citri-infested (about 70% similarity) and healthy plants (less than 55% similarity). For the cluster between compounds, chlorophylls, except chlorophyllide a, were very close to each other (more than 96% similarity), carotenes were clustered together also (less than

80% similarity) (Figure 4-4C). Chlorophyllide a (less than 56% similarity) and zeaxanthin (less than 48% similarity) were clustered separately from their groups at the end of right side of the dendrogram. Additionally, the presented heatmap supports the previous findings that the pigments profile from CLas-infected plants is closer to double-attacked plants than D. citri- infested or control plants (Figure 4-4C).

Relationships among Different Citrus Leaf Pigments Groups

The 3D surface plots were obtained using the whole data matrix to understand the relationships between chlorophylls, xanthophylls, and carotenes in citrus leaves in the studied four conditions (Figure 4-5A-5L). Overall, the relationships among these groups are complex.

The effect of xanthophylls and carotenes on chlorophyll content was obtained and presented in

Figures 4-5A to 4-5D. The total net profits (TNP) of chlorophyll content in CLas-infected

(Figure 4-5B) and D. citri-infested plants (Figure 4-5C) appeared to be higher in high-carotenes.

Additionally, the TNP of double-attacked plants showed compromising for the effect of CLas- infection and D. citri-herbivory, without any effect of xanthophyll and carotene content on chlorophylls-TNP (Figure 4-5D). Furthermore, the effect of xanthophyll and chlorophyll on carotene content is presented in Figures 4-5E to 4-5H. Generally, the TNP of carotenes was similar in all treatments compared to control plants, which had a sharp peak (Figure 4-5E). The carotenes TNP in CLas-infected (Figure 4-5F) and D. citri-infested plants (Figure 4-5G) were higher in high-xanthophyll and high-chlorophyll conditions. The effect of carotenes and chlorophylls content on xanthophylls content is presented in Figures 4-5I to 4-5L. The xanthophylls TNP of CLas-infected, D. citri-infested, and double-attacked plants was very

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different compared to control, which had a sharp peak in low-chlorophylls and high-carotenes condition, with clearly flat plateaus (Figure 4-5I). The xanthophylls TNP in CLas-infected

(Figure 4-5J), D. citri-infested plants (Figure 4-5K) appeared to be higher in high-carotenes and high-chlorophylls conditions (Figure 4-5J).

CLas-Infection Induces the Accumulation of Abscisic Acid and Starch

Abscisic acid, starch, and sucrose levels were determined and presented in Figures 4-6A to 4-6C to explore the effect of citrus leaf pigment deficiency on other metabolites. CLas- infection induced the accumulation of ABA (1564.3±742.7 ng g-1 FW) and starch (171.53±18.92 mg g-1 FW), but it did not affect the sucrose level (69.81±4.66 mg g-1 FW) compared to the control (121.0±44.4 ng g-1 FW, 14.68±0.75, and 69.07±6.73 mg g-1 FW, respectively). On the other hand, while D. citri-infestation did not alter the ABA (403.8±212.4 ng g-1 FW) or starch levels (29.17±5.91 mg g-1 FW), it reduced the sucrose content (40.61±3.94 mg g-1 FW) compared to the control. The effects of CLas and D. citri were compromised in the double- attacked plants (Figure 4-6).

CLas and D. citri Alter the Expression of Genes Implicated in Carotenoids and Chlorophylls Biosynthesis Pathways

The transcription levels of 46 genes involved in biosynthetic pathways of carotenoids (29 genes) and chlorophylls (17 genes) were investigated in Valencia sweet orange leaves (Figure 4-

7). Gene expression data were normalized using four reference genes (EF1, F-box, GAPDH, and

SAND). Previous work showed the high stability of these genes for transcript normalization in different citrus organs under biotic stress (Mafra et al., 2012; Wei et al., 2014a and Wei et al.,

2014b). The normalizing expression levels using the four reference genes were very similar

(Data not shown). The presented heatmap in Figure 4-7B shows that 15 carotenoid biosynthetic genes were down-regulated, and 14 genes were up-regulated including carotenoid hydroxylase β-

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ring (CitCHYbs), zeaxanthin epoxidase (CitZEPs), violaxanthin de-epoxidase (CitVDE), capsanthin/capsorubin synthase (CitCCS), neoxanthin synthase (CitNSY), 9-cis-epoxycarotenoid dioxygenase 3 (CitNCED), short-chain alcohol dehydrogenase (CitABA2), and abscisic aldehyde oxidase (CitAAO3) after CLas-infection and/or D. citri-infestation. Furthermore, the hierarchical clustering dendrogram (HCD) among treatments in Figure 4-7B shows that CLas-infected plants were closer to double-attacked (more than 90% similarity), than to D. citri-infested (less than

64% similarity) and to control (less than 45% similarity). HCD among the studied genes represents high similarity in the expression of CitCHYbs and CitZEPs, which are clustered separately in two clusters within the same group (more than 70% similarity). In addition, ABA- biosynthetic genes (CitNSY, CitNCED, CitABA2, and CitAAO3) shared similar patterns and clustered together (Figure 4-7B). Likewise, all chlorophyll biosynthetic genes were down- regulated except for chlorophyllase (CitChlases, also known as CLHs) and chlorophyll(ide) b reductase (CitCBRs) including chlorophyll(ide) b reductase -NON-YELLOW COLORING 1

(CitNYC1) and chlorophyll(ide) b reductase -NYC1-Like (CitNOL). CitChlases and CitCBRs

(CitNYC1 and CitNOL) which were highly expressed in D. citri-infested plants compared to control (Figure 4-7C). HCD among treatments indicates that while CLas-infected plants were very similar to double attacked plants (over 80% similarity), D. citri-infested plants clustered separately (about 64% similarity). HCD among studied chlorophyll-biosynthetic genes revealed two main clusters; the first cluster for CitCBRs (more than 80% similarity) and the second cluster containing CitChlases genes (more than 70% similarity) (Figure 4-7C). Accordingly, the gene expression analysis supported our findings of HPLC and ELISA analyses.

Discussion

Our findings showed that CLas-infection and/or D. citri-infestation altered citrus leaf pigments dramatically, with a greater effect in CLas-infected trees. Out of 15 detected pigments,

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13 compounds were decreased in CLas-infected leaves, and nine pigments were reduced in D. citri-infested leaves. Many previous studies were carried out to examine the effect of pathogen infection or insect herbivory on plants pigment groups, especially carotenoids and chlorophylls

(Blanchfield et al. 2006, 2007; Huang et al. 2013; Kumar and Sharma 2014). However, these studies were primarily focused on the effect of viral pathogens on leaf pigments. For example, a reduction in photosynthetic pigments (chlorophyll a, chlorophyll b, β-carotene, neoxanthin, violaxanthin, and lutein) was observed in infected potato plants, Solatium tuberosum, with potato virus YNTN (PVYNTN) (Milavec et al. 1999). As well, papaya ring spot virus-papaya strain

(PRSV-P) infection caused a decrease in cellular pigments (chlorophyll a, chlorophyll b, and β- carotene) in papaya plants, Carica papaya (Rahman et al. 2008). Tobacco mosaic virus (TMV) infection resulted in a reduction of chlorophyll a and chlorophyll b in several pepper varieties,

Capsicum annuum L. (Pazarlar et al. 2013). Similarly, bacterial pathogens alter the photosynthetic pigments in their hosts. A higher level of total carotenoid and total chlorophylls were recorded in healthy different rice genotypes in comparison with infected ones by

Xanthomonas oryzae pv. oryzae, the casual of bacterial blight disease in rice (Kumar et al.

2013). Additionally, changes in photochemical/nonphotochemical quenching parameters and chlorophyll fluorescence were found in citrus leaves after CLas-infection (Sagaram et al. 2009).

The current study demonstrated that the infection with CLas induces zeaxanthin to a higher level in citrus leaves. Zeaxanthin plays a photo-protection role (Niyogi et al. 1997; Nayak et al. 2001). In oxygenic photosynthetic eukaryotes, such as green algae, the xanthophyll pigments such as zeaxanthin are bound with chlorophyll molecules to integral membrane proteins (Green and Durnford 1996; Grossman et al. 1995). This complex provides an important functional role in photosynthetic light-harvesting complexes (LHCs), converting the light energy

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into chemical energy (Niyogi et al. 1997). For example, zeaxanthin plays a role in protecting

Chlamydomonas reinhardtii, a single-celled green alga, from photo-oxidative effect (Niyogi et al. 1997). In citrus leaves, the increase in zeaxanthin might be a result of enhanced-biosynthesis of β-arm carotenoids; the gene expression of CitCHYbs was especially up-regulated in the presence of CLas. Another reason for the accumulation of zeaxanthin could be due to the conversion of violaxanthin by CitVDE, which was up-regulated in the presence of CLas (Wu et al. 2014; Sajilata et al. 2008). Additionally, the increase in zeaxanthin levels in CLas-infected plants was associated with a decrease in chlorophyll pigments, together resulting in alteration of the pigment composition in citrus leaves. Xanthophylls were a big proportion of total leaf pigments in CLas-infected plants (more than half) compared with control (around one third).

More importantly, our findings showed that CLas-infection significantly induced ABA concentration (up to 13-fold) in citrus plants. The accumulation of ABA in CLas-infected leaves presumably due to an increased availability of its precursor, zeaxanthin, as well as the upregulation of gene expression for ABA-biosynthetic genes (CitNSY, CitNCED, CitABA2, and

CitAAO3). In other pathosystems, ABA accumulated at a higher level in the infection site of viral

(Alazem et al. 2014), fungal (Sánchez-Vallet et al. 2012; Schmidt et al. 2008), and bacterial pathogens (Torres-Zabala et al. 2007; Rosales and Burns 2011), and was associated with tolerance for those pathogens (Torres-Zabala et al. 2007; Bari and Jones 2009; Robert-

Seilaniantz et al. 2007). For example, ABA-deficient mutants were more susceptible to bacterial infection with Pseudomonas syringae pv. tomato DC3000 (Pst) (Robert-Seilaniantz et al. 2007;

Melotto et al. 2006). Likewise, the overexpression of CONSTITUTIVE DISEASE

SUSCEPTIBILITY2-1D (cds2-1D) in NCED5 mutant showed higher levels of ABA and induced resistance to Alternaria brassicicola in Arabidopsis plants (Fan et al. 2009). Furthermore, Ton

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and Mauch-Mani (2004) showed that exogenous treatment of Arabidopsis with ABA has induced resistance against A. brassicicola and Plectosphaerella cucumerina. ABA modulated the plant defenses through the activation of stomatal closure (Melotto et al. 2006; Uraji et al. 2012) or by stimulating callose deposition (Ton and Mauch-Mani 2004). In citrus, ABA-accumulation has also observed in citrus flowers challenged with Colletotrichum acutatum (Lahey et al. 2004) and in HLB-infected fruits (Rosales and Burns 2011). Additionally, ABA induced leaf yellowing in rice (Kusaba et al. 2007). Nevertheless, the ABA role in plant defense is very complicated and can differ among different pathosystems (Bari and Jones 2009). Based on these facts, our findings suggest that ABA may play a role in HLB symptom development, but the mechanism regarding this is still unclear and requires more investigations.

On the other hand, our results clearly showed that out of 15 detected pigments, nine were decreased in D. citri-infested plants. Four compounds remained the same (α-cryptoxanthin, cis- violaxanthin, zeaxanthin, and isolutein), and only the chlorophyllide a was increased after D. citri infestation. As in the control plants, chlorophylls were the most abundant pigments in D. citri-infested plants (around 50%). Many studies showed a significant reduction in total chlorophyll and total carotenoid content after herbivore attack (Blanchfield et al. 2007, 2005;

Kumar and Sharma 2014). For example, the leaves of Pinot Noir and Cabernet Sauvignon grapevines (Vitis vinifera) infested by grape phylloxera (Daktulosphaira vitifoliae) were significantly lower in total chlorophyll and total carotenoid content in field trials, and Shiraz grapevines showed further reduction in both chlorophyll and carotenes in greenhouse trials

(Blanchfield et al. 2007, 2005). D. citri, however, feeds on the phloem of young shoots of citrus trees by piercing, rather than chewing, and so does not damage the leaves as severely as other

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forms of herbivory. Nevertheless, chlorophyllide a level was increased by D. citri feeding indicating that chlorophyllase was stimulated by the cellular disruption.

Likewise, the chlorophyll and carotenoid contents of guava, Dalbergia sissoo, were reduced after infestation by Aonidiella orientalis compared with the healthy plants (Kumar and

Sharma 2014). A significant reduction in relative chlorophyll content in tomato plants (Solanum lycopersicum) after infestation with a high-density of the mealybug, Phenacoccus solenopsis

(Huang et al. 2013) provides more evidence that herbivory alone can alter chlorophyll content.

Furthermore, a significant loss of both chlorophyll a and chlorophyll b in four Fabaceae species, faba bean (Vicia faba L.), clover (Trifolium pretense L.), pea (Pisum sativum L.), and alfalfa

(Medicago sativa L.) after feeding by pea aphids, Acyrthosiphon pisum (Goławska et al. 2010) has been reported. Additionally, attack by adults of chrysomelid flea beetles, Podagrica spp, caused a significant reduction in chlorophyll concentrations of okra plants, Abelmoschus esculentus L. (Ekoja et al. 2012).

In this study, challenging citrus plants with D. citri resulted in higher levels of chlorophyllide a (almost three-fold) compared with control. Additionally, CitCBRs and

CitChlases the key enzymes in chlorophyllide production from chlorophyll molecules, were upregulated in D. citri-infested plants (Tsuchiya et al. 1999). Taken together, these findings suggest that chlorophyllide a and CitChlases are implicated in the citrus defense against D. citri.

Chlorophyllide, one of the tetrapyrrole pigments, shows toxicity toward fungal and animal cells

(Meskauskiene et al. 2001; Kariola et al. 2005) and could be a part of the defense system (Hu et al. 2015). For example, down-regulation of chlorophyllase (AtCLH) reduced Arabidopsis resistance to the fungus A. brassicicola (Kariola et al. 2005). Additionally, the treatment of

Arabidopsis plants with exogenous chlorophyllide or the overexpression of CLH increased the

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toxicity against S. litura larvae (Hu et al. 2015). Furthermore, the application of methyl jasmonate, a derivative of the jasmonic acid, increased the expression levels of AtChlase in

Arabidopsis plants (Tsuchiya et al. 1999) and OsNYC1 in rice leaves (Kusaba et al. 2007). Both

Chlase and NYC1 promote the conversion of chlorophyll to chlorophyllide. Interestingly, jasmonic acid was increased in D. citri-infected plants (data non-shown), thus, we hypothesize that chlorophyllide is associated with the jasmonic acid-mediated pathway in citrus.

Based on these findings, a hypothetical model regarding how CLas and/or D. citri affect the citrus leaf pigments and their roles in stimulating citrus response system was proposed

(Figure 4-8). We hypothesize that both CLas and D. citri affect the leaf pigments but through two different mechanisms. 1) Our findings showed that CLas decreased all chlorophylls and carotenoids compounds but resulting in accumulation of zeaxanthin. In addition to the photoprotective role of zeaxanthin, it is also the precursor of ABA, which is considered a stress- associated phytohormone. Both chlorophyll degradation and ABA accumulation are therefore implicated in HLB-symptom development (Figure 4-8A). However, more investigations are required to clarify if CLas directly manipulates the citrus pigments or it is a plant response to the attack. 2) In this study, D. citri Herbivory reduced all chlorophylls and most of carotenoids pigments but leading to an accumulation of chlorophyllide a. Chlorophyllide a is implicated in the citrus defense against D. citri. Together, chlorophyll and carotenoid biosynthesis reduction, are implicated in the development of HLB-symptoms (Figure 4-8B). Based on this hypothetical model, while CLas and D. citri alter citrus pigments, citrus plants try to defend themselves using a multi-faced defense system; including zeaxanthin, chlorophyllide a, JA, and ABA production.

The pigment-dependent defense system may vary based on the stressor type (CLas, D. citri, or both together). More studies are needed to investigate these complex systems. Complete understanding of these mechanisms may be useful for the study of other vector-borne diseases.

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Table 4-1. Gradient profile used in HPLC for citrus leaves pigments determination.

Timea Mobile phase (% vol) (min.) MTBE b Methanol water 0 5 90 5 12 5 95 0 25 11 89 0 40 25 75 0 60 50 50 0 62 5 90 5 65 5 90 5 a Equilibrating time 13 min. b Methyl tert-butyl ether

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Table 4-2. Chromatographic and spectral characteristics of different investigated pigments in citrus leaves using HPLC. λmax observed (nm) λmax literature(nm) RT a No. Plant Pigments Ref. (min.) Peak Peak Peak Peak Peak Peak Peak Peak I II III IV I II III IV 1 trans-Violaxanthin c 12.02 415, 439, 468 416, 439, 469 (Wei et al. 2014b) 2 Neoxanthin c 13.10 413, 438 468 412, 434, 463 (Rodrigo et al. 2004) 3 cis-Violaxanthin c 14.70 327, 412, 436, 464 325, 411, 434, 463 (Rodrigo et al. 2004) 4 Chlorophyllide a 15.04 413, 431, 461 412, 431, 460, 662 (Milenković et al. 2012) 5 Chlorophyll b b 19.07 439, 469 438, 468 (Edelenbos et al. 2001) 6 Lutein b 22.50 421, 444, 472 420, 444, 472 (Wei et al. 2014b) 7 Chlorophyll a b 27.01 339, 386, 416, 432 338, 386, 414, 432 (Edelenbos et al. 2001) 8 Zeaxanthin b 27.83 424, 449, 476 424, 450, 477 (Wei et al. 2014b) 9 Isoluiein c 32.96 416, 440, 468 416, 440, 468 (Wei et al. 2014b) 10 cis-β-Carotene c 43.91 340, 421, 445, 472 340, 422, 446, 473 (Rodrigo et al. 2004) 11 β-Cryptoxanthin c 44.76 425, 450, 477 426, 451, 478 (Wei et al. 2014b) 12 α-Carotene b 46.46 422, 445, 473 421, 446, 473 (Wei et al. 2014b) 13 β-Carotene b 54.68 427, 451, 475 426, 451, 473 (Rodrigo et al. 2004) 14 α-Cryptoxanthin c 58.21 418, 440, 476 419, 445, 472 (Rodrigo et al. 2004) c 15 Pheophytin a 61.75 328, 410, 506, 537 328, 410, 505, 535 (Edelenbos et al. 2001) a RT, Retention time. b Identified using authentic standards. c Tentative identification by comparison with data available in the literature.

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Figure 4-1. Representative HPLC chromatogram of Valencia sweet orange (C. sinensis) leaf pigments after infection with CLas and/or herbivory with D. citri. Chromatographic and spectral characteristics of different detected peaks are listed in Table 4-2. mAU, milli-absorbance units at 486 nm.

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Figure 4-2. Concentrations of total leaf pigments (A), pigment group concentrations (B), and percentage composition for pigment groups (C) of Valencia sweet orange (C. sinensis) after infection with CLas and/or the herbivory with D. citri using HPLC. The total leaf pigment content was calculated as a total of chlorophyll, xanthophyll, and carotene groups; chlorophyll group contains chlorophyll a, chlorophyll b, pheophytin a, and chlorophyllide a; xanthophyll group contains neoxanthin, trans- violaxanthin, cis-violaxanthin, zeaxanthin, lutein, isolutein, α-cryptoxanthin, and β- cryptoxanthin; and carotene group contains cis-β-carotene, α-carotene, and β- carotene. Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values (n=10), whiskers reflect the highest and the lowest value of data. Different letters indicate statistically significant differences among treatments (p<0.05), while “ns” signify no significant differences among treatments.

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Figure 4-3. Concentrations of individual leaf pigments detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri using HPLC. (A) chlorophyll, (B) xanthophyll, and (C) carotene groups. Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values (n=10), whiskers reflect the highest and the lowest value of data. Different letters indicate statistically significant differences among treatments (p<0.05), while “ns” signify no significant differences among treatments.

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Figure 4-4. Principal component analysis (PCA) of different leaf pigments detected and quantified using HPLC in Valencia sweet orange (C. sinensis) after infection with CLas and/or herbivory with D. citri (n=10). (A) PCA-scatter plot, (B) PCA-loading plot, and (C) two-way HCA dendrograms.

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Figure 4-5. Three-dimensional surface plots of leaf pigments groups detected using HPLC in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri. (A, B, C, and D) the reciprocal interaction of carotenes and xanthophylls on chlorophyll content; (E, F, G, and H) the reciprocal interaction of chlorophylls and xanthophylls on carotene content; and (I, J, K, and L) the reciprocal

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interaction of carotenes and chlorophylls on xanthophyll content in different treatments.

Figure 4-6. The abscisic acid (A), starch (B), and sucrose content (C) of Valencia sweet orange (C. sinensis) after the infection with CLas and/or the infestation with D. citri. Horizontal thick lines indicate the medians, black/white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values (n=10), whiskers reflect the highest and the lowest values of data. Different letters indicate statistically significant differences among treatments (p<0.05), while “ns” signify no significant differences among treatments.

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Figure 4-7. Plant pigment biosynthesis pathways (A) and heat map diagrams of differential biosynthetic gene expression patterns of carotenoids (B) and chlorophylls (C) detected in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or herbivory with D. citri. Rows represent the genes while the columns represent the treatments (n=30). Lower expressions levels are colored green and higher expressions are colored red. Treatments and genes are organized using two-way HCA based on similarities in auto-scaled values and correlations, respectively. Numbers in yellow and green circles represent the genes named in panel B and C, respectively. The full lists of expressed genes, names, accession numbers, and primers are available in supplementary Tables C-1 and C-2. Values in panel B, C represent fold change in gene expression compared to healthy plants. For the full names and abbreviations, see the abbreviations list.

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Figure 4-8. Schematic representation of a proposed model for the effect of infection with CLas and/or infestation with D. citri on Valencia sweet orange (C. sinensis) leaf pigments and citrus response. A) CLas might reduce most of the citrus leaf pigments (chlorophylls and carotenoids) but result in zeaxanthin-accumulation and development of HLB-symptoms. Zeaxanthin is a photoprotector pigment and precursor of ABA, which is a stress-associated phytohormone. B) D. citri might induce the development of HLB-symptoms-like via decreasing both carotenoid and chlorophyll biosynthesis, but causing accumulation of chlorophyllide a, which induce jasmonic acid-mediated pathway and both together have an anti-herbivory role in citrus. C) Presence of both stressors results in ABA accumulation and symptom development in the similar mechanism of CLas-infection. The up-arrow (▲) indicates increasing, down-arrow (▼) indicates decreasing, and equal sign (═) indicate no changes in compound levels. The dotted-lines with arrows represent hypothetical mechanisms or uncharacterized elements. For the full names and abbreviations, see the abbreviations list.

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CHAPTER 54 METABOLOMIC RESPONSE TO HUANGLONGBING: ROLE OF CARBOXYLIC COMPOUNDS IN Citrus sinensis RESPONSE TO Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri

The impact of CLas-infection and/or D. citri-infestation on Valencia sweet orange (Citrus sinensis) leaf metabolites was investigated using a targeted-GC-MS method, followed by gene expression analysis for 37 genes involved in jasmonic acid (JA), salicylic acid (SA), and proline- glutamine pathways. We hypothesize that both CLas and D. citri may cause metabolic changes in citrus leaves, but these changes could be dissimilar under various stressors. In addition, alteration in some metabolite abundances, especially the phytohormonal precursors, could lead directly to greater changes in the stress-associated phytohormone levels.

Introduction

Huanglongbing (HLB), also known as citrus greening disease, is one of the oldest diseases in citrus. Most of the previous studies suggested that HLB originated in East Asia at the end of 1800s (Gottwald et al. 1989; da Graça and Korsten 2004; Bové 2006; Gottwald 2010). It was described first in Chinese as huanglongbing in 1956 or the "yellow shoot disease" in

English (Lin 1956). HLB was detected in São Paulo, Brazil in 2004 and in South Florida (US) in

2005 (Bové 2006; Gottwald 2010; Wang and Trivedi 2013). In August 2005, HLB was first confirmed in south Miami-Dade County, seven years after the first report of its vector in the US.

Afterward, HLB has been discovered in Louisiana (2008), South Carolina and Georgia (2009), and recently, in Texas and California (2012). Additionally, it has been recorded in many

Caribbean countries including Belize, Cuba, Mexico, and Jamaica (Wang and Trivedi 2013).

4 The results of Chapter 5 were published in the Molecular Plant-Microbe Interactions (MPMI) as “Killiny, N., and Nehela, Y. 2017. Metabolomic response to Huanglongbing: Role of carboxylic compounds in Citrus sinensis response to ‘Candidatus Liberibacter asiaticus’ and its vector, Diaphorina citri. Mol. Plant-Microbe Interact. 30:666–678”.

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HLB is one of the most destructive diseases in citrus groves which threatens citrus production across the world (Graça 1991; Bové 2006; Gottwald 2010; Wang and Trivedi 2013).

Among the most important problem adding to the threat of HLB disease is the delay of disease symptom expression following inoculation. For example, the disease symptoms in young trees may appear as early as six months after infection and might take 1-5 years to appear on mature trees (Bové 2006; Wang and Trivedi 2013). The characteristic symptoms of HLB are yellow shoots, blotchy-mottled leaves, stunted shoots, and in many trees there is branch dieback and sometimes tree death as the disease progresses (Bové 2006; Wang and Trivedi 2013). In addition, many diseased trees produce misshapen, small, and discolored fruits that are unusable for fresh sale fruit or for processing. (Bové 2006; da Graça and Korsten 2004; Halbert and

Manjunath 2004; Wang and Trivedi 2013).

HLB is caused by the plant pathogenic, phloem-limited, unculturable bacterium

Candidatus Liberibacter spp., a member of gram-negative, and α-proteobacterium (Bové 2006;

Gottwald 2010). Based on the characteristic 16S rDNA sequences, taxonomically, there are three

HLB-associated species: C. L. asiaticus (CLas), Ca. L. africanus, and Ca. L. americanus (Bové and Ayres 2007; Gottwald 2010; Wang and Trivedi 2013), named for their presumptive origins of Asia, Africa, and the Americas, respectively (Wang and Trivedi 2013). The tree-to-tree transmission of Liberibacters can occur by budwood or citrus psyllid (Hemiptera: Liviidae) insect vectors: the Asian citrus psyllid (ACP), Diaphorina citri Kuwayama in Asia and America, and the African psyllid, Trioza erytreae Del Guercio in Africa (Graça 1991; Bové 2006;

Gottwald 2010; Wang and Trivedi 2013). Among the three Liberibacter species, CLas is the most dominant species, causing huge economic losses to citrus production worldwide (Bové

2006; Gottwald 2010). Although HLB affects most, if not all, citrus varieties, certain varieties

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have been reported to be more resistant than others (Folimonova et al. 2009; Cevallos-Cevallos et al. 2012).

Upon pathogen infection and/or insect herbivory, plants develop multiple mechanisms of defense responses to protect themselves (Durrant and Dong 2004; Liechti et al. 2006; Fu and

Dong 2013). Although many studies have been carried out to understand plant defense responses against biotic stressors, only a few studies about the role of amino acids (AAs), organic acids

(OAs), and fatty acids (FAs) pathways in regulating plant defense responses have been reported.

Among the many metabolic changes that may occur in stressed plants, changes in AAs and OAs profiles are clearly reported after biotic stress (Chen et al. 2009a; Malik et al. 2014), and abiotic stresses such as zinc deficiency (Cevallos-Cevallos et al. 2011) and water stress (Malik et al.

2014). Previously, many metabolomics-based studies reported that pathogen infection and vector infestation may cause major changes in metabolite composition of citrus (Cevallos-Cevallos et al. 2011; Slisz et al. 2012; Chin et al. 2014; Malik et al. 2014) and potato (Wallis et al. 2012,

2014, 2015) plants. Changes in AAs as a plant response is due to different mechanisms such as the transaction of pathogenesis-related proteins (PRs), the generation of reactive oxygen species

(ROS), activation of nonexpressor of pathogenesis-related proteins1 (NPR1), or induction of salicylic acid (SA) biosynthesis (Rojas et al. 2014; Durrant and Dong 2004).

In plant-pathogen-vector pathosystems, it has been suggested that the role of plant metabolites is to save the energy requirements for plant defense responses, however, more important roles have been reported (Bolton 2009; Kangasjärvi et al. 2012). The changes in plant metabolites might contribute directly to plant defense responses. For example, phenylalanine is the precursor of SA (Rojas et al. 2014). SA is a stress-associated phytohormone, which is implicated in defense response against biotrophic and hemibiotrophic pathogens, and plays an

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important role in the induction of systemic acquired resistance (SAR) (Bari and Jones 2009;

Hatcher et al. 2004; Glazebrook 2005). Likewise, α-linolenic acid (C18:3) is the precursor of trans-jasmonic acid (tJA) (Tooker and De Moraes 2009; War et al. 2012). tJA is another stress- associated phytohormone, which is involved in defense against insect herbivory and necrotrophic pathogens (Bari and Jones 2009; Hatcher et al. 2004; Glazebrook 2005).

In citrus, complex metabolic signaling involved in defense responses have been described, including amino acids (Cevallos-Cevallos et al. 2011, 2012; Slisz et al. 2012; Chin et al. 2014; Malik et al. 2014), polyamines (Malik et al. 2014), organic acids (Cevallos-Cevallos et al. 2011; Slisz et al. 2012), fatty acids (Tooker and De Moraes 2009; Cevallos-Cevallos et al.

2012), phytohormones (Tooker and De Moraes 2009; War et al. 2012), and other secondary metabolites (War et al. 2012). Recently, the vital role of small RNA (sRNAs) in plant defense against various pathogens was reported (Seo et al. 2013; Zhao et al. 2013). In citrus, CLas increases generation of several microRNAs (miRNAs) and small interfering RNAs (siRNAs), which could be used as diagnostic markers of HLB (Zhao et al. 2013). Nonetheless, the existing defense mechanisms in plants, however advanced, are usually not enough to overcome the harmful effects of the pathogen.

Although many previous studies focused on the changes in citrus metabolites after different stressors, this is the first controlled comparison between healthy, CLas-infected, D. citri-infested and double-attacked Valencia sweet orange plants. We hypothesize that both CLas and D. citri may cause metabolic changes in leaves, but these changes could be dissimilar under various stressors. In addition, alteration in some metabolite abundances, especially the phytohormonal precursors, could lead directly to greater changes in the stress-associated phytohormone levels. Due to the current inability to culture CLas, our knowledge about its

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virulence mechanism is still limited (Wang and Trivedi 2013). We believe that the expanded knowledge about the metabolic changes which occur after infection with CLas could help provide clues for understanding the pathogen’s effect on Valencia sweet orange. Therefore, this study is a further step to clarify citrus defense mechanisms against CLas as well as D. citri in order to find novel, sustainable management strategies for HLB control.

Materials and Methods

Plant Materials and Growth Conditions

Citrus sinensis (L.) Osbeck (Valencia sweet orange) were used as plant materials in this study. All trees were about 80±5 cm tall, around 18 months old, and maintained in a USDA-

APHIS/CDC-approved secured greenhouse, at 28±3°C; 65±5% RH; 16 h:8 h L/D photocycle, at the Citrus Research and Education Center (CREC), University of Florida, Lake Alfred, Florida.

Weekly, plants were irrigated twice and fertilized once using 20-10-20 NPK fertilizer

(Allentown, PA, USA). In this study, four treatments (five biological replicates, two technical replicates for each; n=10) included: 1) control, 2) CLas-infected, 3) D. citri-infested and 4) double-attacked (CLas-infected and D. citri-infested) trees were tested. To obtain the CLas- infected trees, ten-months-old, HLB-free Valencia sweet orange trees were graft-inoculated with budwoods from a PCR-positive HLB source (HLB-infected Valencia sweet orange trees) and maintained in the same conditions described above. Upon initial symptom development, approximately seven months later, the infection with CLas was confirmed by PCR (Tatineni et al. 2008). To obtain both D. citri-infested and double-attacked plants, healthy D. citri adults

(previously reared on Bergera koenegii, non-host for CLas) were transferred to 16 months-old healthy or CLas-infected Valencia sweet orange plants, with new flushes (100 insect per tree) and caged individually using insect rearing cages (60×60×90 cm) and maintained in the growth room under the same conditions as described above. One month later, both D. citri-infested and

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double-attacked plants were cleaned from all D. citri nymphs and adults. For sampling, three symptomatic leaves were collected per tree from different positions and different ages; juvenile leaf from the top, moderate-age one from the middle, and mature leaf from the lower part of the plant. The collected leaves were chopped, mixed together and immediately kept on ice. Plant materials were kept at -80 °C until analysis.

Extraction of Citrus Leaf Metabolites

Citrus leaf amino acids, organic acids, and fatty acids were extracted from the frozen tissue as follow. Briefly, about 100 mg leaf tissues were ground to a fine powder using liquid nitrogen and transferred to a 1.5-ml centrifuge tube. 750 µl solvent (methanol: water: HCl 6N,

80: 19.9: 0.1; v/v/v) was added to the samples and vortexed for 30 s, then samples were kept on ice for 10 min then centrifuged at 1428 × g for 5 min at 5°C. All the supernatant was transferred to a new 2-ml tube. The extraction was repeated twice more, and the supernatant was combined.

The collected supernatant was concentrated to 50 µl under a nitrogen stream and stored at -80°C for further work.

MCF Derivatization of Amino Acids, Organic Acids, and Fatty Acids

Before derivatization, each sample was spiked with 5 µl of 200 ppm heptadecanoic acid, which is not found in citrus leaves, as an internal standard. Acidic compounds (amino acids, organic acids, and fatty acids) were derivatized with Methyl chloroformate (MCF) as described by (Hijaz and Killiny 2014) with slight modification. Briefly, 50-µl of the methanol extract was transferred to a 1-ml silanized conical ul insert (Wheaton; Millville, NJ, USA) and mixed with

180 µl of sodium hydroxide (NaOH, 1N). Then the alkaline mixture was mixed with 170 µl of methanol and 34 µl of pyridine (5:1) and vortexed for 10 s. 20 µl of MCF was added and vortexed again for 30 sec (twice). Fifty-µl of chloroform was added with vortex for 10 s, followed by 200 µl of sodium bicarbonate (50 mM) with vigorous mixing for 10 s. After

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discarding the upper layer, about 40 µl of the organic layer was transferred to a new insert tube.

Then, a few milligrams of sodium sulfate (2-3 crystals) were added to dry the organic layer. For

GC-MS analysis, 1 µl was injected in the scan mode for carboxylic compounds analysis.

GC-MS Analyses

All derivatized samples and standards were analyzed using an Autosystem XL GC-MS system (Perkin Elmer, Waltham, MA, USA) fitted with a ZB-5MS capillary GC column (5%

Phenyl-Arylene 95% Dimethylpolysiloxane; low bleed, 30 m × 0.25 mm × 0.25 µm film thickness; Phenomenex, Torrance, CA, USA). Hydrogen gas was used as the carrier with a flow rate of 1 ml/min. The GC temperature program was as follows: initial temperature was held at

70 °C for 4 min, and then increased to 280 °C at a rate of 10 °C/min, held for 5 min. The injector and the MS detector temperatures were set at 250 °C and 180 °C, respectively. The GC interface temperature was 200 °C. The injector was fitted with a 2-mm i.d. liner in splitless mode.

Peak Identification and Quantification

GC-MS chromatograms were analyzed using TurboMass software version 6.1 (Perkin

Elmer, Waltham, MA, USA). Peaks were first identified by comparing their mass spectra with library entries of NIST 2011 (National Institute of Standards and Technology, Gaithersburg,

MA, USA) and Wiley 9th edition (John Wiley and Sons, Inc., Hoboken, NJ, USA). Identification of amino acids, organic acids, and fatty acids was further confirmed by comparing their retention time, linear retention indices (LRIs) and mass spectra with authentic standards. Compound peak areas were normalized to the internal standard (heptadecanoic acid). Quantification of leaf metabolites was based on the peak areas obtained from a series of reference standards derivatized and injected under the same conditions as samples (Table D-1). Calibration curves were constructed from the linear regressions obtained by plotting the concentration vs. peak area for each standard.

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Gene Expression Analysis using Quantitative Real-Time PCR (RT-PCR)

(Invitrogen) with random hexamer primers as described by the manufacturer’s instructions was used to synthesize cDNA. SYBR Green PCR master mix (Applied Biosystems) was used to perform the qPCR on an ABI 7500 Fast-Time PCR System (Applied Biosystems). Samples were analyzed in triplicate for each biological replicate for each treatment. Primers for 21 various genes were used to measure the gene expression (Table D-2). The relative expression of the

−ΔΔC consensus sequence among PCR products was done according to the 2 T method (Livak and

Schmittgen 2001). Normalization of gene expression was performed using four endogenous genes (reference genes) including; elongation factor 1-alpha (EF1), F-box/kelch-repeat protein

(F-box), glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (GAPC1, aka GAPDH), and SAND family protein (SAND) (Mafra et al. 2012; Wei et al. 2014a and Wei et al. 2014b)

Statistical Analysis

All compound concentrations were statistically analyzed according to the analysis of variance technique (ANOVA). Post hoc pairwise comparisons between the four studied treatments were performed with the Tukey-Kramer honestly significant different test (Tukey

HSD). Principal component analysis (PCA) was performed and the associated loading-plots were generated using the concentrations of detected metabolites. Two-ways hierarchical cluster analysis (HCA) was performed using the average of each metabolite in each treatment. Distance and linkage were done using the Ward method (Ward 1963), and multivariate genes similarities were presented as a heatmap. 3D-surface plots were performed with the data of the matrices for the four studied treatments.

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Results

Overall, 36 compounds were detected in leaf extracts using GC-MS;22 amino acids

(AAs), nine organic acids (OAs), and five fatty acids (FAs) (Table 5-1). Out of 22 AAs, there were no significant differences among the treatments for L-aspartic acid, L-cysteine, L-histidine,

L-leucine, L-tyrosine, and L-valine. Additionally, three compounds increased (L-threonine, L- tryptophan, and citric acid) and three compounds decreased (L-glutamine, L-lysine, and L- methionine) in all studied treatments without any significant differences among them (Table 5-

1). Although the abundances of total OAs were not significantly different between treatments, many important differences were found between individual compounds as well as the sub-groups of OAs. For total FAs, all non-control treatments showed significant changes.

CLas-Infection Increased Total Nonpolar AAs, while D. citri-Infestation Increased Total NPAAs and Total FAs

The total AA abundance was significantly increased after CLas-infection (65084±2985 ng g-1 FW), followed by D. citri-infested (54540±3254 ng g-1 FW), double-attacked

(53598±3844 ng g-1 FW), and controls (47779±4711 ng g-1 FW), but without significant differences between D. citri-infested and double-attacked plants (Table 5-1 and Figure 5-1A).

The total AAs category was divided into five groups, depending on their chemical properties, including non-proteinogenic, basic, acidic, polar side chain, and non-polar side chain amino acids. Although the CLas-infection did not affect the total polar AAs abundance, it induced the accumulation of total non-polar AAs abundances and decreased both basic and acidic AAs compared to control (Figure 5-1B). On the other hand, D. citri-infestation induced the accumulation of total FAs (10461±325 μg g-1 FW) and total non-proteinogenic AAs (6979±792 ng g-1 FW) compared to control (5281±174 μg g-1 FW and 2617±658 ng g-1 FW, respectively)

(Figure 5-1A and 5-1B). Additionally, both CLas-infection and/or D. citri-infestation did not

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affect the total OAs. While CLas-infection did not change either mono-carboxylic or dicarboxylic OAs, D. citri-infestation reduced the mono-carboxylic OAs abundance (7013±1042 ng g-1 FW) compared to control plants (10080±946 ng g-1 FW) (Figure 5-1C).

CLas-Infection Increased the Amino Acids Abundances

In CLas-infected plants, seven compounds increased compared to control (glycine, L- isoleucine, L-phenylalanine, L-proline, L-serine, L-threonine, and L-tryptophan) and four compounds were decreased (L-glutamic acid, L-glutamine, L-lysine, and L-methionine) (Table 5-

1). L-Proline, the most abundant amino acid in all treatments, was significantly higher in CLas- infected leaves (34549±2654 ng g-1 FW) followed by double-attacked (27915±3788 ng g-1 FW),

D. citri-infested (26230±3606 ng g-1 FW), and control (16910±2846 ng g-1 FW) (Table 5-1).

Interestingly, some AAs that are phytohormone precursors increased significantly after CLas and/or D. citri attack. Briefly, L-phenylalanine, the precursor of SA, increased in CLas-infected

-1 -1 plants (465±46 ng g FW) compared to control (361±88 ng g FW). Furthermore, L-tryptophan, the precursor of auxin, also increased in CLas-infected leaves (222±80 ng g-1 FW) compared to control (47±26 ng g-1 FW) (Table 5-1).

CLas-Infection and/or D. citri-Infestation Altered the Organic Acids Profile

Nine organic acids compounds were detected in Valencia sweet orange leaves (Table 5-

1). Although the infection with CLas and/or infestation with D. citri altered the nine organic acids compounds abundances, the total OAs abundance remained the same. While tJA remained at a similar level within the OAs profile of CLas-infected plants, five OAs (benzoic acid, citric acid, fumaric acid, SA, and succinic acid) increased, and three (ferulic acid, malic acid, and quinic acid) decreased significantly (Table 5-1). On the hand, the organic acid profile from D. citri -infested plants was similar to the control with the exception of four OAs that increased

(citric acid, fumaric acid, tJA, and quinic acid) and ferulic acid that was decreased (Table 5-1).

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Malic acid, the most abundant OA in all treatments, was significantly lower in CLas-infected leaves (17937±4439 ng g-1 FW) compared to control (39713±8163 ng g-1 FW). Benzoic acid

(BA) and SA, which are considered phytohormones, increased in CLas-infected plants

(5344±739 and 2521±646 ng g-1 FW, respectively) compared to control (2539±438 and 915±74 ng g-1 FW, respectively). On the other hand, tJA was significantly higher in D. citri-infested leaves (432±16 ng g-1 FW) followed by double-attacked (356±23 ng g-1 FW), CLas-infected

(297±17 ng g-1 FW), and control (242±11 ng g-1 FW) (Table 5-1).

Fatty Acids Increased upon D. citri-Infestation

Five FAs were detected in citrus leaves using GC-MS, including palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and α-linolenic acid (C18:3). All detected FA abundances were higher in D. citri-infested plants compared to other treatments.

The concentrations of these FAs in CLas-infected trees and double-attacked trees were higher than in the control but lower than those exposed to D. citri only. Furthermore, no significant differences were observed between CLas-infected plants and double-attacked plants for total FAs or linoleic acid. Likewise, no significant differences were observed between CLas-infected plants and D. citri-infested trees for oleic acid (Table 5-1).

PCA Analysis Revealed Differences between Citrus Response to CLas and D. citri

For the amino acids, the PCA-scatter plot presented in Figure 5-2A shows good discrimination between the four treatments (PC1 and PC2 were 57.4 and 26.6%, respectively). Furthermore, the associated loading-plot is presented in Figure 5-2B. Clearly, 11 amino acids (glycine, L-alanine, L-valine, L-tyrosine, L-isoleucine, L-proline, L-phenylalanine, L- tryptophan, L-threonine, L-cysteine and L-serine) were positively associated with CLas infection and double-attacked plants.

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Likewise, for the organic acids, the PCA-scatter plot (Figure 5-2C), and its associated loading-plot (Figure 5-2D) were obtained. Figure 5-2C shows a good separation between the

CLas-infected and double-attacked plants (as a group) and both control and D. citri-infested plants (PC1 and PC2 were 57.2, and 21.8%, respectively). Additionally, Figure 5-2D shows that while five OAs were positively associated with CLas-infection (benzoic acid, fumaric acid, succinic acid, citric acid, and SA), the rest were positively correlated with D. citri-infestation.

The PCA-scatter plot and loading-plot of the FAs are presented in Figures 5-2E and 5-2F.

Data presented in Figure 5-2E provided evidence of well-defined clustering into the four distinct treatment groups with PC1 (80.2%) and PC2 (12.5%). The PCA analysis showed that FAs were strongly associated with D. citri-infestation (Figure 5-2).

For further data analyses, AAs were divided chemically into five groups; non- proteinogenic, basic, acidic, polar side chain-, nonpolar side chain amino acids. Likewise, OAs were divided into three groups; mono-carboxylic, di-carboxylic, tri-carboxylic OAs. The PCA- scatter plot (Figure 5-2G) and loading-plot (Figure 5-2H) using the total concentration for each group were obtained. Figure 5-2G shows good separation between the CLas-infected and double- attacked plants (as a group) and both control and D. citri-infested plants (PC1 and PC2 were

38.2, and 23.1%, respectively). Additionally, data presented in Figure 5-2H shows that while mono-carboxylic organic acids, tri-carboxylic OAs, nonpolar, and polar AAs were positively associated with CLas infection, whereas the FAs and non-proteinogenic amino acids were positively correlated with D. citri herbivory.

3D Surface Plot Analysis Revealed Complex Interactions among AAs, OAs, FAs

For a further understanding of relationships among AAs, OAs, and FAs in Valencia orange leaves, three-dimensional surface plots were obtained (Figures 5-3A to 5-3L). Generally, the interaction among amino acids, organic acids, and fatty acids is complex. Briefly, the effect

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of FAs and OAs (as two input parameters) on AAs content (as an associated performance metric) was obtained. Unlike the control (Figure 5-3A), the total effect of AA content in CLas-infected plants appeared to be higher in low-FA conditions (Figure 5-3B). By contrast, the AA content in

D. citri-infested plants appeared to be higher in low-OA conditions and to be lower in high-OA conditions, without any effect on FA content (Figure 5-3C). These findings indicate a negative linear relationship between AA and OA content after infestation with D. citri. In addition, the total effect of double-attacked plants showed an intermediate effect for CLas infection and D. citri herbivory (Figure 5-3D).

Likewise, data presented in Figure 5-3E, 5-3F, 5-3G, and 5-3H demonstrates the effect of FA and AA content (as two input parameters) on OA content (as an associated performance metric) in different treatments. Generally, the total effect of OAs was similar to the total effect of

AAs in all conditions with the exception of CLas-infected plants, which had a sharp peak (Figure

5-3F).

The effect of OA and AA content (as two input parameters) on FA content (as an associated performance metric) was performed and is presented in Figure 5-3I, 5-3J, 5-3K, and

5-3L. Generally, the total effect of FAs in CLas-infected, D. citri-infested, and double-attacked plants was very different compared to the control, which had more flat plateaus. The total effect of FAs in CLas-infected plants, which had a clear peak, appeared to be lower in high-OA and low-AA conditions (Figure 5-3J). Furthermore, the total effect of FA in double-attacked plants was more similar to the total effect of FA in D. citri-infested than CLas-infected plants (Figure

5-3L).

CLas and D. citri Altered Genes Expression of SA- and JA-Mediated Pathways

We investigated the transcript levels of 37 genes involved in biosynthetic pathways of JA

(23 genes), SA (7 genes), and glutamine-proline metabolism (7 genes) in Valencia sweet orange

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leaves (Figure 5-4). Gene expression data were normalized using four reference genes (EF1, F- box, GAPDH, and SAND), which previously showed high stability for transcript normalization in different citrus organs under biotic stress (Mafra et al., 2012; Wei et al., 2014a and Wei et al.,

2014b). The normalizing expression levels using the four reference genes were very similar

(Data not shown). Generally, the expression of all investigated genes increased after the infection with CLas and/or infestation with D. citri. Comparisons of the relative fold changes of the 23 genes involved in the JA pathway, including ω-3 fatty acid desaturase (CitFADs), linoleate lipoxygenase (CitLOXs), allene oxide synthase (CitAOSs), allene oxide cyclase (CitAOCs), and

12-Oxophytodienoate reductase 3 (CitOPR3), are shown as a heatmap (Figure 5-4A). The gene expression of all involved genes in the JA pathway were upregulated in D. citri-infested plants compared to control (up to 6.5 folds). Additionally, the hierarchical clustering dendrogram

(HCD) among treatments in Figure 5-4A showed that CLas-infected plants were very similar to control (dissimilarity distance around 1.8), while D. citri-infested plants were closer to the double-attacked treatment (dissimilarity distance around 5.0). Likewise, HCD among the studied genes represents high similarity in the expression of individual genes, and the data in Figure 5-

4A shows that genes within the same group (CitFADs, CitLOXs, CitAOSs, CitAOCs, and

CitOPR3) shared similar patterns and clustered together.

On the other hand, phenylalanine ammonia-lyase (CitPAL) and isochorismate synthase

(CitICS), which are involved in SA-biosynthesis, were highly expressed in CLas-infected plants

(up to 8.0 folds) compared with control (Figure 5-4B). HCA among treatments indicated that while the double attacked plants were very similar to CLas-infected trees (dissimilarity distance around 2.9), followed by D. citri-infested (dissimilarity distance around 6.2) and control trees

(dissimilarity distance around 10.6). HCA dendrogram between studied genes in Figure 5-4B

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also indicates two main clusters; the first cluster was for CitICSs (dissimilarity distance around

1.7) and the second cluster contained other tested genes (CitPALs; dissimilarity distance around

2.4).

Additionally, while proline dehydrogenase 1(CitProDH) and δ-1-pyrroline-5-carboxylate dehydrogenase 12A1(CitP5CDH), genes implicated in glutamine and proline metabolism, showed the highest expression levels (4.8 to 6.1 folds) after CLas infection, lysine histidine transporter 1(CitLHT1) was highly expressed in double-attacked plants (up to 8.1 folds) (Figure

5-4C). Like the SA-biosynthetic genes, the double-attacked plants were very similar to CLas- infected plants (dissimilarity distance around 1.8), followed by D. citri-infested plants

(dissimilarity distance around 3.1) and control (dissimilarity distance around 11.3). According to these findings, the gene expression results support our findings from the GC-MS work.

Discussion

In this study, metabolomic analysis of Valencia sweet orange leaves revealed that CLas- infection and/or D. citri-infestation altered the amino acids, organic acids, and fatty acids abundances compared to control plants. Most of our results agreed with previous studies on CLas

(Slisz et al. 2012; Malik et al. 2014; Chin et al. 2014) and were also consistent with results found for Candidatus Liberibacter solanacearum, the pathogen of Zebra chip disease of potato (Wallis et al. 2012, 2014, 2015).

L-Proline was found to be higher in CLas-infected leaves compared to other treatments and control. Our findings are in agreement with the previous studies on CLas-infected citrus leaves (Cevallos-Cevallos et al. 2011; Rivas et al. 2008), citrus seedlings (Cevallos-Cevallos et al. 2012), potato tubers (Wallis et al. 2012, 2014), and potato leaves (Wallis et al. 2015), but were in contrast to what was found in citrus fruits (Slisz et al. 2012; Chin et al. 2014). The increase in proline might serve to protect the infected plants from reactive oxygen species (ROS)

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(Wallis et al. 2015). In this study, genes involved in proline biosynthesis (CitProDH and

CitP5CDH) were upregulated after CLas-infection and/or D. citri-infestation and positively regulated the generation of ROS (Rojas et al. 2014).

Likewise, the abundance of L-phenylalanine was higher in CLas-infected plants in agreement with previous studies on citrus (Slisz et al. 2012; Chin et al. 2014) and potato (Wallis et al. 2012, 2014). Previous studies suggested that the higher abundances of L-phenylalanine could be due to the inhibition of the phenylpropanoid biosynthesis pathway by the phytopathogens. Phenylalanine ammonia-lyase (PAL) is the enzyme responsible for converting phenylalanine to cinnamic acid (CA), then to BA and SA (Macarisin et al. 2007; Slisz et al.

2012). Indeed, our findings disagree with this suggestion (Macarisin et al. 2007; Slisz et al.

2012) because BA and SA and their biosynthetic genes (CitPALs and CitICSs) increased after infection with CLas, suggesting that CLas cannot suppress the host response by inhibiting PAL.

L-Serine and L-threonine abundances were significantly higher in CLas-infected leaves compared to control in agreement with previous studies on citrus leaves (Cevallos-Cevallos et al.

2011), citrus fruits (Cevallos-Cevallos et al. 2012), potato tubers (Wallis et al. 2012, 2014), and potato leaves (Wallis et al. 2015). The accumulation of L-serine and L-threonine are commonly associated with bio-stress responses in plants, mainly due to the increase in photorespiration and/or overexpression of peptidases and proteases (Cevallos-Cevallos et al. 2012). For example, serine carboxypeptidase-like gene has been found to be upregulated after biotic stress in rice (Liu et al. 2008) and oats (Mugford et al. 2009). Accordingly, the accumulation of serine and threonine suggests that they may play a role in plant defense response against CLas and its vector, D. citri (Cevallos-Cevallos et al. 2012; Rojas et al. 2014).

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On the other hand, methionine, glutamine, glutamic acid, and lysine were reduced after infection with CLas. The reduction of those amino acids might be due to CLas, which being a phloem-restricted bacterium may utilize these amino acids, which are found in citrus phloem sap

(Hijaz and Killiny, 2014), for its growth and reproduction, and/or to inhibit the defense mechanisms of the host plant (Slisz et al. 2012). Kyoto Encyclopedia of Genes and Genomes

(KEGG) online database showed that sequencing of the CLas genome revealed a functional tricarboxylic acid (TCA) cycle allowing CLas to utilize a wide range of amino acids, such as glutamate, tyrosine, cysteine, histidine, and methionine in addition to glucose, as energy sources

(Duan et al. 2009; Slisz et al. 2012). In addition, the degradation of lysine plays a key role in activation of SAR (Yang and Ludewig 2014). We suggest that lysine produces pipecolic acid by the activity of the AGD2-like defense response protein 1 (ALD1) then SA (Yang and Ludewig

2014) to coordinate the SAR via SA-mediated pathway (Bernsdorff et al. 2016). Many previous studies support our suggestion because the loss of ALD1 gene reduced the SA abundances and decreased the plant resistance to Pseudomonas syringae in Arabidopsis (Song et al. 2004; Yang and Ludewig 2014).

The reduction of two organic acids (quinic acid and ferulic acid) is in agreement with previous studies in potato tubers (Wallis et al. 2014, 2015). In addition, previous studies showed that some organic acids were accumulated in citrus after CLas infection including citrate in leaves and fruits (Cevallos-Cevallos et al. 2011; Slisz et al. 2012) and succinate in the fruits

(Slisz et al. 2012). The accumulation of TCA-cycle related OAs might be due to the catabolism of some proteinogenic amino acids (Stipanuk 2006). Generally, glucogenic amino acids are broken down into pyruvate, α-ketoglutarate, succinyl CoA, fumarate or oxaloacetate, while ketogenic amino acids are broken down into acetoacetate or acetyl-CoA. Finally, α-ketoglutarate

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or oxaloacetate act as the amino group acceptor in all amino acid catabolism pathways (Forest and Wightman 1972).

Our results showed that the infestation with D. citri significantly changed the abundances of several amino acids in citrus leaves. Briefly, only four amino acids (L-proline, L-tryptophan, L- serine, and L-threonine) were higher in D. citri-infested leaves compared to control. This is consistent with the previous findings in potato leaves after the feeding of potato psyllid

(Bactericera cockerelli) (Yang et al. 2011), and in D. citri-infested citrus leaves (Malik et al.

2014). The observed proline accumulation in this study could be injury-induced by D. citri feeding because higher abundances of proline were observed also in potato foliage attacked by

Colorado potato beetle (Leptinotarsa decemlineata) and potato leafhopper (Empoasca fabae)

(Tomlin and Sears 1992). Additionally, insect feeding could induce senescence of leaves and the correlation between serine abundances and senescence of leaves was reported (Malik 1982; Yang et al. 2011), explaining the higher abundances of serine found in D. citri-infested leaves.

Moreover, four amino acids were decreased in D. citri-infested leaves including L- methionine, L-asparagine, L-glutamine, and L-lysine. This is in agreement with previous studies, which showed a significant reduction in asparagine, glutamate, and lysine (Yang et al. 2011;

Malik et al. 2014). The reduction of glutamate and aspartate abundances could partially be a result of D. citri feeding. As a phloem-feeding insect, D. citri consumes large amounts of glutamate and aspartate from the host plants (Douglas 1993; Yang et al. 2011). Another reason for glutamate and aspartate reduction could be due to their conversion into amino acids (Yang et al. 2011). For example, lysine could be synthesized from aspartate (Matthews and Hughes 1993).

Therefore, the lysine reduction in this study may be due to the decrease in the available aspartate for lysine synthesis (Yang et al. 2011). As another example, proline is synthesized from

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glutamate and arginine (Boggess 1976; Malik et al. 2014). Therefore, in this study, the lower concentrations of glutamate found in D. citri-infested leaves partially could be due to its conversion to proline (Boggess 1976; Yang et al. 2011).

Interestingly, D. citri strongly influenced the linoleic acid and α-linolenic acid abundances in D. citri-infested leaves. This is in agreement with previous studies on different herbivores and different hosts including the gall-inducing caterpillars Gnorimoschema gallaesolidaginis and Heliothis virescens on Solidago altissima stems and leaves (Tooker and De

Moraes 2009), and the Hessian fly, Mayetiola destructor on rice and wheat (Zhu et al. 2011). α-

Linolenic acid is strongly associated with chloroplasts and tends to be lower in weakly photosynthetic or non-photosynthetic leaves (Río-Celestino et al. 2008). Prior studies showed that linoleic acid and α-linolenic acid could be synthesized de novo by some insect species to satisfy their need for these compounds (Buckner and Hagen 2003). Furthermore, citrus plants themselves might induce fatty acid biosynthesis to activate the JA-mediated pathway.

Fatty acids and their metabolites, including 12-oxophytodienoic acid (OPDA), JA, and methyl jasmonate (me-JA), could induce plant defense responses against herbivory (Farmer and

Ryan 1992; Tooker and De Moraes 2009; Zeier 2013). JA, which appears to be in higher abundances in D. citri-infested plants in this study, has a key role in plant defense against herbivore attack (herbivore antifeedants) (Bennett and Wallsgrove 1994; Shivaji et al. 2010;

Zeier 2013). Also, large numbers of plant mechanisms involved in defense against herbivores are regulated by JA including anti-oxidative enzymes, proteinase inhibitors (PIs), volatile organic compounds (VOCs), alkaloid production, and secretion of extra-floral nectar (EFN) (Bennett and

Wallsgrove 1994; Shivaji et al. 2010; War et al. 2012).

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Based on those findings, a hypothetical model of amino acids, organic acids, and fatty acids and their roles in citrus response is presented in Figure 5-5. As shown in Figure 5-5, multiple signaling carboxy-molecules are involved in citrus response to CLas-infection and/or D. citri-infestation through three major pathways; I) induction of SA-mediated pathway, which is associated with defense response for biotrophic pathogens (Bari and Jones 2009; Hatcher et al.

2004; Glazebrook 2005) such as CLas; II) induction of JA-mediated pathway, which is associated with defense against insects herbivory of insect such as D. citri (Robert-Seilaniantz et al. 2007; Bari and Jones 2009; Lazebnik et al. 2014); and III) induction of glutamine-proline pathway, which is implicated in ROS generation.

The SA-mediated pathway (I) could be induced by the pathogen-associated molecular patterns (PAMPs), and/or damage-associated molecular patterns (DAMPs), which are triggered by the pathogen (Erb et al. 2012; Kushalappa and Gunnaiah 2013). PAMPs and/or DAMPs are perceived by pattern recognition receptors (PRRs), and lead to pattern-triggered immunity (PTI)

(Erb et al. 2012; Kushalappa and Gunnaiah 2013). The higher abundances of SA might be delivered by two different routes. The first route starts by conversion of phenylalanine to CA by the activity of PAL (Guidetti-Gonzalez et al. 2007; Chen et al. 2009b) then to SA by benzoic acid-2-hydroxylase (BA2H) through BA (Coquoz et al. 1998; Dong et al. 2014). The second route for SA biosynthesis is from isochorismate by the activity of isochorismate synthase (ICS) then isochorismate pyruvate lyase (IPL) (Chen et al. 2009b). Both, PAL and ICS, were expressed at higher levels in CLas-infected plants, but there is no evidence for the existence of either BA2H or IPL in citrus, particularly, as they were not found in the CitEST database (Guidetti-Gonzalez et al. 2007). Additionally, the SA-mediated pathway could be induced by pipecolic acid

(Bernsdorff et al. 2016) and hypersensitive reaction (HR) (Zhao et al. 2005; Guidetti-Gonzalez et al. 2007)

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Induction of the JA-mediated pathway (II) is thought to be related to mitogen-activated protein kinase (MAPKs) and herbivore-associated molecular patterns (HAMPs). In citrus, these may be triggered by D. citri-infestation and lead to herbivore-triggered immunity (HTI) (Erb et al. 2012), thereby inducing the accumulation of α-linolenic acid and leading to increased JA abundances (Figure 5-5). In the chloroplast, chewing of plant leaves by insects causes the deoxygenation of linoleic acid and α-linolenic acid at C9 or C13 by specific lipoxygenase pathways (LOXs) to form (9S)- or (13S)-hydroperoxy-octadecadi(tri)enoic acids, which are converted into 12-oxo-phytodienoic acid (OPDA). Then, OPDA is transferred to the peroxisome, and reduced to JA by OPDA reductase 3 (OPR3) (War et al. 2012). In this study, the expression of the enzymes involved in JA-biosynthesis was upregulated after D. citri-infestation. These ezymes include serine palmitoyl transferase; (SPT), suppressor of SA-insensitivity 2 (SSI2), ω-3 fatty acid desaturase 7 (FAD7), ω-3 fatty acid desaturase 8 (FAD8), lipoxygenase (LOX), allene oxide synthase (AOS), allene oxide cyclase (AOC), and 12-oxophytodienoate reductase 3 (OPR3)

(Wasternack and Hause 2013; Kachroo et al. 2003). In agreement with our findings, previous iTRAQ proteome and transcriptome study showed that the LOX protein was upregulated in

CLas-infected sweet orange plants compared with control (Fan et al. 2011). Both SA and JA play important roles in the generation of ROS and the induction of SAR during the activation of nonexpressor of pathogenesis-related proteins1 (NPR1) (Liechti et al. 2006; Rojas et al. 2014;

Zhang et al. 2015).

Induction of glutamine-proline pathway (III), which is implicated in ROS generation due to the activity of proline dehydrogenase (ProDH) and δ 1-pyrroline-5-carboxylate dehydrogenase (P5CDH) (Rojas et al. 2014). In addition, the high activities of SPT and

FAD7/FAD8, and the increase in the abundance of α-linolenic acid suggested that they play key

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roles in accumulation of ROS, which lead to HR (Rojas et al. 2014). HR and SAR are often associated together in infected plant tissues (Kombrink and Schmelzer 2001).

Based on those findings, we tried to understand how CLas and/or D. citri reconfigure the host plant metabolism. We reported potential changes in orange leaf physiology after CLas- infection and/or D. citri-infestation, including particular alterations in amino acids, organic acids, fatty acids, and gene expression. These changes could be implicated directly or indirectly in the expression of plant defense related genes against CLas and/or D. citri. Finally, understanding and analyzing the variation in citrus physiology after CLas-infection and/or D. citri-infestation could lead to a comprehensive picture of defense responses to CLas and its vector, D. citri in Valencia sweet orange and perhaps other citrus. Further studies are needed to examine the relationships between metabolomic changes, defense-related mechanisms and regulation of host genes.

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Table 5-1. Concentrations of different amino acids (ng g-1 FW), organic acids (ng g-1 FW), and fatty acids (μg g-1 FW) compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with ACP using GC-MS (n=10) y. Concentration (mean±standard deviation) z compounds Control CLas-infected D. citri-infested Double-attacked Amino acids Non-proteinogenic amino acids c b a b γ-Aminobutyric acid 1262±656 3685±599 5809±821 4697±1181 a bc b c L-Pyroglutamic acid 405±23 284±31 301±41 252±25 a b a a Tyramine 950±73 416 ±270 869±130 773±193 Basic amino acids ns ns ns ns L-Histidine 2453±100 2315±233 2356±216 2350±135 a b b b L-Lysine 195±13 96 ±33 105±27 130±30 Acidic amino acids ns ns ns ns L-Aspartic acid 814±331 642±136 588±304 365±158 a b a b L-Glutamic acid 3493±701 1268±276 2681±215 704±140 Polar side amino acids a ab b ab L-Asparagine 10490±1095 8312±991 5909±2987 8284±1615 ns ns ns ns L-Cysteine 24±5 49±16.68 40±18 27±3 a b b b L-Glutamine 5442±2758 4014±1763 4821±1237 2299±399 b a ab ab L-Serine 3215±1429 6642±1679 2799±1974 2698±1275 b a a a L-Threonine 134±101 188±50 149±67 168±17 ns ns ns ns L-Tyrosine 354±57 352±163 310±144 387±35 Non-polar side amino acids b ab b a L-Alanine 700±106 949±155 704±248 1251±245 Glycine 27±4 b 63±11 a 39±14 b 38±9 b b a ab a L-Isoleucine 67±12 173±60 106±36 158±39 ns ns ns ns L-Leucine 65±6 60±6 63±4 59±4 a b b b L-Methionine 219±57 183±26 150±64 190±33 b a b a L-Phenylalanine 361±88 465±46 186±73 475±57 c a b b L-Proline 16910±2846 34549±2654 26230±3606 27915±3788 b a a a L-Tryptophan 47±26 222±80 206±111 210±55 ns ns ns ns L-Valine 152±55 158±72 121±59 164±62 Total amino acids 47779±4711 c 65084±2985 a 54540±3254 b 53598±3844 b Organic acids Mono-carboxylic organic acids Benzoic acid 2539±438 b 5344±739 a 2433±147 b 4444±334 a Ferulic acid 4607±755 a 1928±421 b 984±283 c 1729±461 ab t-Jasmonic acid 242±11 c 297±17 c 432±16 a 356±23 b Quinic acid 1776±445 b 715±226 c 2401±411 a 633±184 c Salicylic acid 915±74 b 2521±646 a 1363±298 b 2345±485 a Di-carboxylic organic acids Fumaric acid 4001±246 b 6740±733 ab 9119±642 a 7302±298 a Malic acid 39713±8163 a 17937±4439 b 33373±6071 ab 20741±4711 ab Succinic acid 7619±340 c 17431±3327 ab 11486±2991 bc 19465±3830 a Tri-carboxylic organic acids Citric acid 3859±396 b 9574±715 a 7130±395 a 7809±255 a Total organic acids 65272±2214 ns 62487±8620 ns 68721±7378 ns 64825±9420 ns Fatty acids Linoleic acid (C18:2) 1433±195 c 2169±237 b 3194±250 a 2418±235 b α-Linolenic acid (C18:3) 560±62 d 830±102 c 1615±110 a 1162±107 b Oleic acid (C18:1) 1288±216 b 1936±377 a 2422±322 a 1104±174 b Palmitic acid (C16:0) 1937±5 d 2303±59 c 2919±61 a 2496±85 b Stearic acid (C18:0) 62±14 c 202±42 ab 312±83 a 185±93 b Total fatty acids 5281±174 c 7440±169 b 10461±325 a 7366±210 b y five biological replicates (two technical replicates for each) was used. z Different letters indicate statistically significant differences among the studied treatments, while “ns” signify no significant differences between them according to Tukey’s honestly significant difference test (P < 0.05).

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Figure 5-1. Concentrations of total amino acid, total fatty acid, and total organic acid groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with ACP using GC-MS-SIM. (A) Total amino acid, total fatty acid, and total organic acid groups, (B) different amino acid groups, and (C) different organic acid groups. All compounds were extracted in methanol and derivatized with methyl chloroformate. Different letters indicate statistically significantly differences among the studied treatments (n=10), while “ns” signify no significant differences between them.

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Figure 5-2. Principal components (PCA) of different citrus leaves amino acids, organic acids, fatty acids and total groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri using GC-MS. (A, B, and C) PCA-scatter plot using the concentrations of the amino acids, organic acids, and fatty acids, respectively (n=10). (D, E, and F) PCA-loading-plots using the concentrations of the amino acids, organic acids, and fatty acids, respectively. (G) PCA-scatter plot using the concentrations of the all carboxylic acids and its PCA- loading-plot (H).

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Figure 5-3. Three-dimensional surface plots of different citrus leaves amino acid, organic acid, and fatty acid groups detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri using GC-MS. (A, B, C, and D) effect of fatty acids (FA) content, organic acids (OA) content, and their reciprocal interaction on amino acids (AA) content in different treatments; (E, F, G, and H) effect of fatty acids (FA) content, amino acids (AA) content, and their reciprocal interaction on organic acids (OA) content in different treatments; and (I, J, K, and L) effect of amino acids (AA) content, organic acids (OA) content, and their reciprocal interaction on fatty acids (FA) content in different treatments.

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Figure 5-4. Heat maps with cluster dendrograms of expressed genes involved in JA (A), SA (B), proline-glutamine (C) pathways in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or infestation with D. citri. Genes are presented in columns and treatments are presented in rows. Treatments and genes are organized using two-way hierarchical cluster analysis (HCA) based on similarities in auto- scaled values and correlations, respectively. The complete list of expressed genes is available in supplementary Table D-2. For the full names and abbreviations, see the abbreviations list.

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Figure 5-5. Schematic representation of amino acids, organic acids, and fatty acids biosynthesis and their roles in citrus response to CLas infection and/or D. citri attack. As a generalized model, multiple signaling carboxy-molecules participate in Valencia orange response against CLas-infection and/or D. citri-infestation through three major pathways; I) induction of SA-mediated pathway using phenylalanine, which is mainly associated with defense response for biotrophic pathogens such as CLas. II) Induction of JA-mediated pathway, which is associated with defense against insect herbivory such as D. citri. Induction of the JA-mediated pathway is thought to be related to the accumulation of α-linolenic acid. The interaction between SA- and JA-mediated pathways is controversial. The interaction may be antagonistic or synergistic. Both SA and JA play important roles in the generation of ROS and the establishment of SAR during the activation of non-expressor of pathogenesis-related proteins1 (NPR1). III) The activation of glutamine-proline pathway, which is implicated in ROS generation due to the activity of proline dehydrogenase (ProDH) and δ 1-pyrroline-5-carboxylate dehydrogenase (P5CDH). The solid lines represent the amino acid, organic acid, and fatty acid metabolic pathways, and the dashed lines represent hypothetical mechanisms of response pathways in Valencia sweet orange; with arrows indicating positive reaction, while blunt-ended lines indicate negative regulation or unknown reaction. For the full names and abbreviations, see the abbreviations list.

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CHAPTER 65 Candidatus Liberibacter asiaticus AND ITS VECTOR, Diaphorina citri, AUGMENTS THE TCA CYCLE OF THEIR HOST VIA THE GABA SHUNT AND POLYAMINES PATHWAY

Both CLas and its vector manipulate the host metabolism for their benefit to meet their nutritional needs and neutralize the host defense responses. We used a targeted GC-MS-based method, gene expression analysis, bioinformatics, and in silico analyses to explore the connection between TCA cycle, γ-aminobutyric acid (GABA)-shunt and polyamines (PAs) pathways in citrus. In Chapter 5, we found that CLas infection decreased α-ketoglutarate, while it increased succinate, fumarate, and citrate. We hypothesize that citrus plants might have additional or alternative pathway(s) that may contribute to this flux towards succinate rather than as an intact TCA cycle. These alternative fluxes might occur in citrus under specific abiotic and biotic stresses such as CLas-infection and D. citri-infestation. In addition, we hypothesize that both the GABA-shunt and the TCA cycle are functionally linked and the alteration in some metabolite levels, particularly the NPAAs and PAs, could lead indirectly to greater changes in the TCA cycle metabolic pathway.

Introduction

Vector-borne phytopathogens cause many destructive diseases in economic crops worldwide. For instance, Huanglongbing (HLB, also known as citrus greening), is the most serious bacterial disease in citrus across many different geographical regions worldwide

(Gottwald 2010). HLB is costing growers over four billion U.S.D. annually, and thousands of citrus industry workers have lost their jobs (Gottwald 2010).

5 The results of Chapter 6 were accepted for publishing in the Molecular Plant-Microbe Interactions (MPMI) as “Nehela, Y. and Killiny, N. 2018. Candidatus Liberibacter asiaticus and its vector, Diaphorina citri, augments the TCA cycle of their host via the GABA shunt and polyamines pathway. Mol. Plant-Microbe Interact. Accepted article.

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Although Koch’s postulates have not been fulfilled due to the difficulty in culturing the putative bacterium, significant evidence indicates that HLB is associated with a plant fastidious, phloem-limited, pathogenic bacterium given provisional Candidatus status, Candidatus

Liberobacter spp., a member of gram-negative α-proteobacteria, and later changed to Candidatus

Liberibacter spp. (Jagoueix et al. 1994; Garnier et al. 2000b; Bové 2006; Gottwald 2010).

Taxonomically, based on the geographical distribution and the characteristic 16S rDNA sequence, three of Ca. Liberibacter species have been proposed to be associated with HLB; Ca.

L. asiaticus (CLas) in Asia and Americas (Bové 2006; Gottwald 2010), Ca. L. africanus (CLaf) in Africa (da Graça 1991), and Ca. L. americanus (CLam) in Brazil (Teixeira et al. 2005a).

Among the three Liberibacter species, CLas is the most dominant species, causing huge economic losses to citrus production worldwide (Bové 2006; Gottwald 2010). HLB affects most, if not all, citrus varieties; however, certain varieties have been reported to be more susceptible than others (Folimonova et al. 2009; Cevallos-Cevallos et al. 2012; Killiny and Hijaz 2016; Hijaz et al. 2016; Killiny 2017; Killiny et al. 2017b, 2018a). To our knowledge, until now the mechanisms or the internal factors responsible for HLB susceptibility/tolerance in citrus are yet to be explored.

Although Ca. Liberibacter spp. are mainly transmitted by psyllids, they can be transmitted by graft inoculation, however, there is no evidence for transmission by seeds

(Halbert and Manjunath 2004). Two psyllid vectors are responsible for the spread of HLB

(Teixeira et al. 2005a); the Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera:

Liviidae) in Asia and Americas (Bové 2006; Gottwald 2010), and the African psyllid, Trioza erytreae Del Guercio (Hemiptera: Triozidae) in Africa (da Graça 1991).

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Previously, we described the chemical composition of citrus phloem sap because it contains all the required nutrients for multiplication of CLas and its vector, D. citri (Hijaz and

Killiny 2014). Citrus phloem-sap contains many sugars (sucrose, glucose, and inositol), organic acids (succinic, malic, benzoic, and citric acids), and about 20 proteinogenic amino acids (PAAs)

(Hijaz and Killiny 2014). It has been suggested that the role of plant metabolites in plant- pathogen-vector interactions is to secure the energy requirements for plant defense responses

(Bolton 2009; Kangasjärvi et al. 2012); however, this is not the main role. The changes in plant metabolites might contribute directly to plant defense responses. Our previous studies showed that both CLas-infection and D. citri-infestation can cause many biochemical and metabolic alterations in citrus plants. For example, both CLas-infection and D. citri-infestation altered the volatile organic compounds (Hijaz et al. 2013), amino acids (AA), organic acids, fatty acids

(Killiny and Nehela 2017a), leaf pigments (Killiny and Nehela 2017b), and phytohormones

(Nehela et al. 2018). However, it remains unclear whether these changes benefit CLas and its vector, or if they are a plant response, or both. Nonetheless, in the HLB-infected citrus plants, the existing defense mechanisms, however advanced, are usually not enough to overcome the harmful effects of CLas.

In citrus, the vital and complex roles of leaf metabolites involved in plant defense response against various biotic stressors have been reported. These metabolites included amino acids (Cevallos-Cevallos et al. 2011, 2012; Slisz et al. 2012; Malik et al. 2014; Killiny and Hijaz

2016; Killiny and Nehela 2017a), polyamines (PAs) (Malik et al. 2014), organic acids (Cevallos-

Cevallos et al. 2011; Slisz et al. 2012; Killiny and Nehela 2017a), fatty acids (Cevallos-Cevallos et al. 2012; Killiny and Nehela 2017a), phytohormones (Rosales and Burns 2011; Nehela et al.

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2018), and other secondary metabolites. However, the contribution of non-proteinogenic amino acids (NPAAs) and PAs pathways in citrus defense responses are poorly understood.

Biochemically, the NPAAs are those not encoded or found in the genetic code of an organism and are not normally found as products of protein hydrolysis (Bell 2003). In eukaryotes, in addition to the 21 common amino acids (AA) used for protein biosynthesis, plants also produce numerous NPAAs. Over 140 amino acids are known to occur naturally in plants and thousands more may occur in nature or be synthesized in the laboratory. Many NPAAs are important because they are highly recognizable as intermediates or end products of primary metabolism in both plants and animals (Bell 2003). In addition, NPAAs form post-translationally in proteins, and play many physiological roles in plants. For example, the NPAA, γ-aminobutyric

(GABA), was detected in the phloem sap of citrus (Hijaz and Killiny 2014). Additionally, many other NPAAs including octopamine, synephrine, tyramine, N-methyltyramine, hordenine, and putrescine were found in citrus leaves (Wheaton and Stewart 1970), and they could play a key role in citrus defense responses to HLB (Killiny and Nehela 2017a).

Additionally, PAs are ubiquitous, aliphatic amines, polycationic, and low molecular weight nitrogen-containing compounds found in all living organisms (Cohen 1998). For instance, putrescine (di-amine), spermidine (tri-amine) and spermine (tetra-amine) are the major PAs and occur ubiquitously in plants (Kaur-Sawhney et al. 2003). At physiological pH, PAs are positively-charged; therefore, they are known to bind to negatively-charged molecules, such as nucleic acids, acidic phospholipids and various types of proteins (Cohen 1998). PAs are implicated in several biological processes for growth and development in both prokaryotes and eukaryotes (Tiburcio et al. 1997; Kaur-Sawhney et al. 2003). Moreover, PAs modulate the plant response(s) to various environmental (Kaur-Sawhney et al. 2003) and biotic stressors, including

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plant-microbe interactions. It has been reported that the PAs pathway is altered after phytopathogen infections (Walters 2003b, 2003a).

Although there are many studies focused on the metabolic effects of CLas-infection on its vector, the effect of CLas-infection on the energy metabolism, and the TCA cycle metabolic pathway of its host plant is poorly studied. For instance, it has been recently shown that citrate and other TCA cycle intermediates are the main energy sources for Liberibacter crescens growth on chemically defined media (Cruz-Munoz et al. 2018). Furthermore, our previous studies showed that CLas-infection exploits the energy metabolism, defense responses, and the tricarboxylic acid cycle (TCA cycle; aka Krebs cycle or citric acid cycle) of its insect vector, D. citri (Lu and Killiny 2017; Killiny et al. 2017a, 2018b). However, more studies are required to explore the roles of the TCA cycle metabolic pathway in plant defenses and in fulfilling the nutritional needs of D. citri and CLas.

Herein, we describe a comprehensive study on the effect of CLas-infection on the TCA cycle, NPAAs, and PAs of its host plant, including the different natural scenarios (healthy, CLas- infected, D. citri-infested and double-attacked plants). We believe that the changes in different leaf metabolites levels, particularly those involved in the TCA cycle, could also affect the abundance of both NPAAs and PAs and vice-versa. Our hypothesis is that both CLas-infection and D. citri-infestation induce metabolic changes in the TCA-associated compounds, NPAAs and PAs in citrus plants, but these changes could be different under different stresses. In addition, we hypothesize that both the GABA-shunt and the TCA cycle are functionally linked and the alteration in some metabolite levels, particularly the NPAAs and PAs, could lead indirectly to greater changes in the TCA cycle metabolic pathway. This study is a further step to providing clues for understanding the nutritional needs of CLas, which could help in culturing

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CLas. In addition, knowledge of the relationships between these pathways in the HLB pathosystem may clarify the defense mechanisms of citrus against CLas and D. citri in order to find novel, sustainable strategies for HLB management.

Materials and Methods

Plant Materials and Growth Conditions

Valencia sweet orange (Citrus sinensis (L.) Osbeck) trees 80±5 cm tall, and around 18 months-old at the time of sampling, were used for this study. Trees were maintained in an approved USDA-APHIS/CDC secured greenhouse, at 28±2°C, with 65±5% relative humidity and 16h-light: 8h-dark photoperiod. The facility is located at the Citrus Research and Education

Center (CREC), University of Florida, Lake Alfred, Florida. Trees (caged or non-caged) were randomly placed in the greenhouse, were irrigated twice weekly and fertilized monthly with

20:10:20 NPK water soluble fertilizer (Allentown, PA, USA). In this study, four treatments were tested including; control (healthy), CLas-infected, D. citri-infested, and double-attacked trees

(CLas-infected and D. citri-infested together). For each treatment, ten biological replicates were analyzed (two technical replicates for each). The technical replicates were used only to test the reproducibility and variability in the extraction protocol and GC-MS machine, but not used for statistical analysis. Since our method showed a high reproducibility, the values of each pair of technical replicates were very close to each other.

To obtain the CLas-infected trees, ten-months-old, HLB-free Valencia trees were graft- inoculated with budwoods from a PCR-positive HLB-infected citrus tree and maintained in the same conditions as described above. Upon initial symptom development, approximately seven months later, the infection with CLas was confirmed by PCR (Tatineni et al. 2008). To obtain both D. citri-infested and double-attacked plants, 16 months-old healthy or CLas-infected trees, with new growth flush, were exposed to 100 healthy adult psyllids (PCR negative; previously

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reared on Bergera koenegii, non-host for CLas) per plant and caged individually using insect rearing cages (60×60×90 cm) and maintained in the growth room under the same conditions as described above. One month later, D. citri-infested and double-attacked plants were cleaned from all D. citri stages.

For sampling, three leaves were collected per tree from different positions and different ages; juvenile leaves from the top, intermediate-aged leaves (fully expanded, but not hardened) from the middle, and mature leaves (deep green and hardened) from the lower part of the plant.

The collected leaves were chopped, mixed together and immediately kept on ice. Plant materials were kept at -80 °C until further analysis.

Analysis of Citrus Leaf NPAAs, PAs and TCA-Associated Compounds

Extraction of citrus leaf NPAAs, PAs and TCA compounds

Citrus leaf NPAAs, PAs and TCA-associated compounds (2-ketoglutaric acid, succinic acid, fumaric acid, and citric acid) were extracted from frozen tissue using methanol 80% containing 0.1% HCl 6N as described in our previous studies (Nehela et al. 2016; Killiny and

Nehela 2017a). The extraction was repeated three times from the same biological sample and the supernatants were combined. The collected supernatant was concentrated to 50 µl under a nitrogen stream and stored at -80°C for further work.

Methyl chloroformate (MCF) derivatization of citrus leaf metabolites

Before derivatization, each sample was spiked with 5 µl aliquot of 200 ppm heptadecanoic acid, which is not found in citrus leaves, as an internal standard. Citrus leaf

NPAAs, PAs, and TCA-associated compounds were derivatized with methyl chloroformate

(MCF) following the protocol of (Hijaz and Killiny 2014) with slight modifications as described by (Killiny and Nehela 2017a). Briefly, a 50-µl of the methanol extract of citrus leaves was derivatized twice with 20 µl of MCF, then extracted into chloroform. After derivatization, about

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40 µl of the organic layer was transferred to a new insert tube. Then, a few milligrams of sodium sulfate (2-3 crystals) were added to dry the organic layer. For GC-MS analysis, 1 µl was injected into GC-MS running in the full scan mode for NPAAs, PAs, and TCA-associated compounds analysis.

GC-MS analyses of citrus leaf NPAAs, PAs, and TCA compounds

All derivatized samples and standards were analyzed using a Clarus 680 GC-MS system

(Perkin Elmer, Waltham, MA, USA) fitted with a ZB-5MS GC column (5% Phenyl-Arylene

95% Dimethylpolysiloxane; low bleed, 30 m×0.25 mm×0.25 µm film thickness; Phenomenex,

Torrance, CA, USA). Helium gas was used as the carrier gas with a flow rate of 1 ml min-1. The

GC thermo-program, MS ion identification, and GC-MS chromatograms analysis were performed according to (Killiny and Nehela 2017a).

Identification of citrus leaf NPAAs, PAs and TCA compounds

All studied NPAAs, PAs and TCA-associated compounds were first identified by comparing their mass spectra with library entries of NIST 2011 (National Institute of Standards and Technology, Gaithersburg, MA, USA) mass spectral database (MSD), Wiley 9th edition

MSD (John Wiley and Sons, Inc., Hoboken, NJ, USA), with spectra found in published literature and/or the Golm Metabolome Database (http://gmd.mpimp-golm.mpg.de/). The identification was further confirmed by comparing the retention times, linear retention indices (LRIs) and mass spectra with those of authentic reference standards treated identically to samples. Quantification of different citrus leaf metabolites was based on the peak areas obtained from a series of reference standards (0, 5, 10, 25, and 50 ppm) derivatized and injected under the same conditions as samples. Calibration curves were constructed from the linear regressions obtained by plotting the concentration vs. peak area for each standard.

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In silico Analysis of GABA Permease

The bioinformatics and in silico analyses were carried out using the available data of C. sinensis cv. Valencia v2.0 genome from chromosome level HZAU assembly (Xu et al. 2013), on the Citrus Genome Database website (https://www.citrusgenomedb.org/organism/Citrus/sinensis) and GenBank, the National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). Briefly, the protein sequence of bidirectional amino acid transporter 1 (AtBAT1) of Arabidopsis thaliana (NP_565254.1; aka GABA permease [AtGABP]) was matched with eight genes of C. sinensis using the protein-protein BLAST (BLASTP 2.8.0+)

(Altschul et al. 1997, 2005), based on recent available data on NCBI GenBank.

These protein sequences, in addition to AtBAT1 from A. thaliana, were used to generate the multiple sequence alignment by ClustalW (http://www.genome.jp/tools-bin/clustalw) (Larkin et al. 2007) and BoxShade-version 3.21(https://embnet.vital-it.ch/software/BOX_form.html) was used to visualize conserved regions in the alignment. The evolutionary history of the all matched genes was inferred using unrooted phylogenetic tree analysis using the Neighbor-Joining method

(Saitou and Nei 1987), with a 1000-bootstrap test (Felsenstein 1985) and the evolutionary distances were computed using the Poisson correction method (Zuckerkandl and Pauling 1965).

Evolutionary analyses were conducted in MEGA7 software (Kumar et al. 2016). Additionally, the protein functional analysis was obtained using InterPro Scan

(https://www.ebi.ac.uk/interpro/) to look for the conserved domains.

The SWISS-MODEL server (https://swissmodel.expasy.org/) (Biasini et al. 2014), I-

TASSER server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) (Roy et al. 2012; Yang and

Zhang 2015) and the protein homology/analogy recognition engine [Phyre2 web portal-version

2.0] (http://www.sbg.bio.ic.ac.uk/~phyre2/html/page.cgi?id=index) (Kelley et al. 2015) were used for protein structure homology-modelling, generating a three-dimensional (3D) structure

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and a model for the molecular surface of the predicted amino-acid permease BAT1-like isoform

X1 of C. sinensis (XP_006468761.1; CsAAP-BAT1-X1; described as CsGABP to indicate its

GABA‐permease activity). Chimera package (version 1.12)

(https://www.cgl.ucsf.edu/chimera/download.html) was used for interactive visualization of the predicted macromolecule (PDB format). In addition, the prediction of RNA secondary structure for CsGABP was performed from the DNA sequence using RNAfold web server

(http://rna.tbi.univie.ac.at//cgi-bin/RNAWebSuite/RNAfold.cgi) (Lorenz et al. 2011).

Gene Expression Analysis using Quantitative Real-Time PCR (qPCR)

The total RNA was extracted from the same biological samples using TriZol® reagent

(Ambion®, Life Technologies, NY, USA). The quantity and quality of isolated RNA were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA). SuperScript first- strand synthesis system (Invitrogen) with random hexamer primers was used to synthesize cDNA as described by the manufacturer’s instructions. SYBR Green PCR master mix (Applied

Biosystems, Foster City, CA, USA) was used to perform the qPCR on an ABI 7500 Fast-Time

PCR System (Applied Biosystems, Foster City, CA, USA). Samples were analyzed in triplicate for each biological replicate for each treatment (three biological replicates, two technical replicates each, triplicate analysis, n=30). Primers for 32 various genes involved in GABA-shunt cycle and other PAs pathways, in addition to CsGABP, were used to measure the gene expression (Table E-4). The relative expression of the consensus sequence among PCR products

−ΔΔC was done according to the 2 T method (Livak and Schmittgen 2001). Normalization of gene expression was performed using four endogenous genes (reference genes) including; elongation factor 1-alpha (EF1), F-box/kelch-repeat protein (F-box), glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (GAPC1, also known as GAPDH), and SAND family protein

(SAND) (Mafra et al. 2012; Wei et al. 2014).

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Statistical Analysis

All experiments were designed in a completely randomized design. In all experiments, ten biological and two technical replicates per treatment were analyzed (n=10). For statistical analysis, we analyzed only 10 biological replicates. Each biological replicate is a mean of two technical replicates because our method showed a high reproducibility and the values of each pair of technical replicates were very close to each other. The technical replicates themselves were not used in the statistical analysis to avoid the possibility of pseudoreplication. Data were normally distributed. Two-way hierarchical cluster analysis (HCA) was performed with the standardized and non-standardized means of the matrices for the four studied treatments.

Distance and linkage were done using the Bray-Curtis similarity measure method (Michie 1982) with 95% confidence between groups from the discriminant function analysis (DFA) to construct the similarity dendrograms. Multivariate compound similarities were presented as a heat map, combined with two-way HCA as described above. In addition, principal component analysis

(PCA) was performed using normalized data of individual metabolites and the associated loading-plots were generated using the singular value decomposition (SVD). All data were statistically analyzed according to the analysis of variance technique (ANOVA). Post hoc pairwise comparisons between the four studied treatments were performed with the Tukey-

Kramer honestly significant difference test (Tukey HSD), and statistical significance was established at p<0.05. The transcript levels of various genes involved in the GABA-shunt cycle and PAs pathway were presented as a heat map combined with two-way HCA. HCA was performed using standardized means of the matrices for all studied treatments. Distance and linkage were done as described above.

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Results

NPAAs & PAs, PAAs, and TCA-Associated Compounds Detected in Citrus

We used a targeted GC-MS-based method to study the effect of CLas-infection and/or D. citri-infestation on the NPAAs, PAs, TCA-associated compounds, and some PAAs implicated in

GABA-shunt cycle and PAs pathway. We focused on these compounds after derivatization with methyl chloroformate (MCF). MCF derivatization resulted in highly reproducible chromatograms (Figure 6-1A). Overall, we detected 19 different compounds in all studied treatments (Table E-1 and Figure 6-1A). Although more than 12 authentic reference standards of

NPAAs and PAs were successfully derivatized with MCF and detected using the GC-MS, only nine of them were detected in citrus leaves, whereas α-aminobutyric acid, β-alanine, and N- acetyl cysteine were not detected or were below the limit of detection. In addition, we detected four organic acids implicated in the TCA cycle (citric acid, 2-ketoglutaric acid, succinic acid, and fumaric acid) and six PAAs involved in the GABA-shunt and other PAs pathways. These detected PAAs included L-proline, L-serine, L-glutamine, L-glutamic acid, L-cysteine, and L- tyrosine. Furthermore, L-arginine was detected only in CLas-infected plants (data not shown) after the derivatization with trimethylsilylation (TMS), whereas it was not detected at all when derivatized with MCF. The retention times, linear retention indices, and the main fragments of all detected compounds are shown in Table E-1.

CLas-Infection Induces Greater Changes in the Total NPAAs & PAs, PAAs, and TCA- Associated Compounds

The total targeted PAAs content was significantly increased in all treatments compared with control plants; however, CLas-infected trees had the highest PAAs levels, followed by D. citri-infested and double-attacked plants (p<0.0001; Figure 6-1B). Likewise, the total detected

TCA-associated compounds were significantly higher in all treatments compared with control

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plants. Nevertheless, the induction of these compounds was significantly greater in the presence of CLas (CLas-infected and double-attacked plants), followed by D. citri-infested plants

(p<0.0001; Figure 6-1C). On the other hand, infestation alone did not influence the total NPAAs and PAs content, but the presence of CLas induced accumulation of these compounds in both

CLas-infected and double-attacked plants (p<0.0001; Figure 6-1D).

CLas-Infection Alters the NPAAs and PAs in Citrus Leaves

After MCF derivatization, nine NPAAs and PAs compounds were detected among the four studied treatments (Figure 6-2). The non-standardized two-way hierarchical cluster analysis

(HCA) showed that the peak areas of detected compounds ranged from 4.0×104 to 11.0×108

(Figure 6-2A). Synephrine was the most abundant metabolite among all NPAAs and PAs in all studied treatments, which was separately clustered in the top of the cluster dendrogram (Figure

6-2A). On the other hand, seven metabolites (out of nine compounds) had a small peak area less than 1.4×107. Ornithine, from D. citri plants, had the lowest peak area (approximately 4.0×104) among all detected metabolites (Figure 6-2A).

Additionally, the standardized two-way HCA combined with ANOVA analysis and

Tukey’s HSD test (using the means of peak areas of individual NPAAs and PAs) were used to differentiate the individual metabolites among the studied treatments (Figure 6-2B). The differences in the metabolite abundances are also visualized and presented as a heat map. The total HCA dendrogram among treatments (presented in the bottom of Figure 6-2B) showed that the metabolite profile of citrus leaves from CLas-infected plants was closer to the profile of double-attacked ones (more than 80% similarity), whereas that of D. citri-infested plants was closer to control (less than 70% similarity) (Figure 6-2B).

Additionally, the HCA dendrogram between NPAAs and PAs metabolites showed that all detected compounds separated into four clusters. Cluster I (C-I) included only the mono-amine,

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synephrine, which was significantly higher in double-attacked plants compared to other treatments and clustered separately in the top of the cluster dendrogram (Figure 6-2B). Cluster II

(C-II) included four metabolites which were higher in CLas-infected plants and split into two separate groups. The first group included two metabolites (ornithine and ρ-aminobenzoic acid) which were significantly higher only in CLas-infected plants compared to all other treatments, whereas both putrescine and octopamine clustered together in the second group and were significantly higher in both CLas-infected and double-attacked plants without any significant differences between them (Figure 6-2B). Cluster III (C-III) included only GABA which was higher in D. citri-infested plants and clustered separately in the middle of the dendrogram

(Figure 6-2B). Cluster IV (C-IV) included three metabolites (O-acetyl serine, pyroglutamic acid, and tyramine), which were decreased significantly in all treatments compared with control

(Figure 6-2B).

PCA Reveals Differences in NPAAs and PAs Metabolites

The principal component analysis (PCA) performed using the peak area of individual

NPAAs and PAs metabolites and its associated loading-plot are shown in Figures 6-3A and 6-

3B, respectively. The scatter plot obtained from the PCA showed a clear separation among all studied treatments, except CLas-infected and double-attacked plants which overlapped each other slightly in the right side of the scatter plot (Figure 6-3A). PC1 and PC2 were responsible for 85.11 % of the variation. Furthermore, the loading plot (Figure 6-3B) showed that three compounds (O-Acetyl serine, pyroglutamic acid, and tyramine) were positively correlated with control and four compounds (putrescine, octopamine, ornithine, and ρ-aminobenzoic acid) were correlated positively with CLas-infected plants. Only one compound was positively correlated with D. citri-infested (GABA) and synephrine was correlated with double-attacked plants.

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CLas-Infection and D. citri-Infestation Alter PAAs of GABA-Shunt

For metabolic dissecting of the biosynthetic pathways of NPAAs and PAs, we targeted six PAAs involved in the GABA-shunt and PAs pathways in citrus leaves (Table E-1 and Figure

6-4). L-cysteine was increased slightly in CLas-infected and D. citri-infested treatments, but L- tyrosine remained unchanged in all tested treatments (Figure 6-4A and 6-4B, respectively). L- proline, the most abundant AA, was significantly increased in all studied treatments, with greater effect for CLas-infection (p<0.0001; Figure 6-4C), and L-serine also increased significantly in

CLas-infected leaves (p<0.0001; Figure 6-4D). On the other hand, L-glutamine was reduced significantly in all studied treatments compared with control plants (p<0.0081; Figure 6-4E).

Additionally, L-glutamic acid was decreased in the presence of CLas (CLas-infected and double- attacked plants), while it remained at the same level in D. citri-infested plants as much as control

(p<0.0001; Figure 6-4F).

CLas-Infection and D. citri-Infestation Alter the TCA-Associated Compounds

Four metabolites associated with the TCA cycle were detected in citrus leaves. These compounds included citric acid, 2-ketoglutaric acid, succinic acid, and fumaric acid (Table E-1 and Figure 6-5). The earliest organic acid in the TCA cycle, citric acid, was significantly increased in all studied treatments, with greater effect for CLas-infection (p<0.0001; Figure 6-

5A). Additionally, both succinic acid and fumaric acid, which appear later in the TCA cycle, were increased significantly in all studied treatments compared to the control plants (Figure 6-5B and 6-5C, respectively). On the other hand, 2-ketoglutaric acid was significantly reduced in all studied treatments compared with the control plants (p<0.0001; Figure 6-5D).

Citrus Genome Possesses a Putative GABA Permease

In silico analysis using the BLASTp tool showed that the Citrus sinensis genome possesses eight sequences with a significant similarity to AtBAT1(NP_565254.1; aka GABA

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permease [AtGABP]) from Arabidopsis thaliana (Table E-2). The multiple sequence alignment of the AA sequence of AtGABP protein with the eight matched sequences from the citrus genome revealed the similarity and the conserved sequences of both AA permease subfamily and

AA/polyamines transporter I domains between them (Figure E-1). In addition, the phylogenetic analysis using the neighbor-joining method revealed that the PREDICTED: amino-acid permease

BAT1 (CsAAP-BAT1), PREDICTED: amino-acid permease BAT1-like isoform X1 (CsAAP-

BAT1-X; described as CsGABP in this study), and PREDICTED: amino-acid permease BAT1- like isoform X2 (CsAAP-BAT1-X2) proteins from C. sinensis (XP_006469954.1,

XP_006468761.1, and XP_006468762.1, respectively) were phylogenetically closer to GABA permease from A. thaliana (AtGABP) than the PREDICTED: amino-acid permease BAT1-like

(XP_006472841.2) and Hypothetical proteins CISIN_1g010352mg from C. sinensis

(KDO57518.1, KDO57519.1, KDO57520.1, and KDO57522.1) with high bootstrap values as described in Figure E-2.

Data presented in Table E-2, Figure E-1, and Figure E-2 showed that CsGABP protein encoded by the citrus locus LOC102610833 has a relatively high homology with AtGABP protein encoded by the Arabidopsis locus AT2G01170 than other found sequences. Therefore, we focused on this protein for further in silico analysis.

The AA sequence of CsGABP was aligned with the sequences of AtGABP (Figure 6-6A).

The alignment showed high similarity and conserved sequences in both AA permease subfamily and AA/polyamines transporter I domains. Furthermore, the AA sequence of CsGABP had high similarity and conserved sequences when aligned with the BAT1 sequences from other plant species (Table E-3) including A. thaliana, C. clementina, Brassica napus, Carica papaya,

Glycine max, Nicotiana tabacum, Populus trichocarpa, Theobroma cacao, and Vitis vinifera

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(Figure E-3). The homology of CsGABP to proteins from other plant species was more than 90% identity (Figure E-3).

The bioinformatic analysis of amino acid sequences using the InterPro Scan tool and the

Phyre2 web portal to predict the conserved domains suggests a high topological similarity between AtGABP and the CsGABP (Figure 6-6B). Both sequences have an AA permease subfamily (PF13520; aka AA_permease_2) and AA/polyamines transporter I (PIRSF006060; aka AA_transporter), which contain 12 transmembrane regions that have been predicted in the sequence to adapt the topology (Figure 6-6B and Figure E-4A). Moreover, CsGABP sequence has a conserved site of amino acid permease (PS00218; aka AA_permease_1) (Figure 6-6B).

Additionally, like other transporters, CsGABP is predicted to have 12 transmembrane helices with internal N- and C-termini (Figure 6-6B and Figure E-4A).

The predicted 3D secondary structure of CsGABP and ligand binding residues in the conserved motif site are shown in Figure 6-6C. The 3D secondary structure model of CsGABP protein showed that about 87% of the sequence (452 residues out of 521 aa) have been modeled with 100.0% confidence by the single highest scoring template with the structure of glutamate-

GABA antiporter GadC (4DJI) from Escherichia coli (strain K12) in the protein data bank (PDB, https://www.rcsb.org/). Furthermore, the predicted normalized B-factor by ResQ obtained by I-

TASSER server, and associated with the predicted 3D model, showed that most of the residues are relatively more stable in the structure, where most of them had negative normalized B-factor values (Figure E-4B). Moreover, the predicted mRNA hairpins (minimum free energy [MFE] and centroid) secondary structure of CsGABP and the strengths of base pairing probabilities are shown in Figure E-4C and Figure E-4D, respectively.

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Taken together, these results suggest that the citrus genome contains the locus

XM_006468698.3 (1927 bp) which encodes for a putative C. sinensis amino-acid permease

BAT1-like-protein (LOC102610833), transcript variant X1 (Cs2g13200.1; aka GABA permease

[CsGABP]). This protein is conserved and contains 521 amino acids. The AA sequence and predicted topology of CsGABP resemble those of the mitochondrial GABA permease (AtGABP) of A. thaliana.

CLas and D. citri Alter the Genes Expression of GABA-Shunt and PAs Pathway

In addition to CsGABP, we investigated the transcript levels of 32 genes involved in the

GABA-shunt and PAs biosynthetic pathway in Valencia sweet orange leaves (Figure 6-7). Gene expression data were normalized using four reference/housekeeping genes (Table E-4), which previously showed high stability for transcript normalization in citrus under biotic stress (Mafra et al. 2012; Wei et al. 2014). The normalized expression levels using the four housekeeping genes were similar to each other (data not shown). Generally, the expression levels of all investigated genes increased after the infection with CLas and/or infestation with D. citri.

Comparisons of the relative fold change of the CsGABP gene, which connects the TCA cycle and GABA-shunt, showed that CsGABP was up-regulated in all treatments compared with control plants (Figure 6-7A). CsGABP was expressed at higher levels (up to 4-folds) in CLas- infected and D. citri-infested plants, followed by double-attacked plants (about 2.2-folds) (Figure

6-7A). In addition, the differences in relative expression levels of the 32 investigated genes involved in the GABA-shunt and PAs biosynthetic pathways are visualized as a heat map combined with a standardized two-way HCA and presented in Figure 6-7B. The total HCA- dendrogram among treatments (presented in the bottom of Figure 6-7B) showed that the transcript levels of CLas-infected plants were closer to the profile of D. citri-infested ones

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(approximately 90% similarity) than double-attacked plants (just less than 85% similarity)

(Figure 6-7B).

Furthermore, total HCA-dendrogram among the investigated genes showed that all 32 genes separated into three distinct clusters. Cluster I includes 19 genes which were expressed at higher levels after D. citri infestation. Most of these genes are involved in the GABA-shunt, PAs biosynthesis, and glutamate pathway (Figure 6-7B). Cluster II includes 10 genes, which were higher in CLas-infected plants than other treatments and split into two separate clusters (cluster

II-1 and cluster II-2). Interestingly, cluster II contains the predicted C. sinensis serine acetyltransferase 1, chloroplastic-like (CsSAT1; XM_006474855.2) and predicted C. sinensis serine acetyltransferase 5 (CsSAT5; XM_006475346.2). These two genes are involved in O- acetyl serine biosynthesis. Furthermore, cluster II also contains the predicted C. sinensis tyrosine decarboxylase 1 (CsTDC1; XM_006479363.2), the only gene in the synephrine biosynthetic pathway that has been isolated and cloned from a plant source (Figure 6-7B). Cluster III includes only three genes which were higher in the presence of CLas and/or D. citri compared with control plants (Figure 6-7B). Interestingly, cluster III contains the predicted C. sinensis polyamine oxidase 1 gene (CsPAO; XM_006482854.1) which catalyzes the oxidation of spermidine to GABA, resulting in accumulation of H2O2 within the apoplast. According to these findings, the gene expression results support our findings from the GC-MS work.

Discussion

TCA cycle is a commonly ubiquitous metabolic hub for ensuring availability of the required cellular energy via the metabolism of carbohydrates, lipids, and amino acids under aerobic conditions (Sweetlove et al. 2010; Araújo et al. 2012). Due to its importance in energy metabolism and other biological processes, TCA cycle has been intensively investigated in many species belonging to both prokaryotes and eukaryotes (Blank and Sauer 2004; Bolton 2009;

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Cavalcanti et al. 2014; Xiong et al. 2014). However, we are just beginning to better understand the roles of the TCA cycle in the HLB pathosystem. Our previous studies showed that CLas manipulates the TCA cycle of its vector, D. citri for its benefit (Lu and Killiny 2017; Killiny et al. 2017a, 2018b; Killiny and Jones 2018), by inducing metabolic changes that can help meet its nutritional needs or to neutralize the host defense responses. Recently, it has been shown that citrate and other TCA-associated compounds are necessary as energy sources for L. crescens growth on chemically defined media (Cruz-Munoz et al. 2018). However, more studies are required to explore the roles of the TCA cycle metabolic pathway in fulfilling the nutritional needs of D. citri and CLas.

Although the mitochondria possess all enzymes for an intact TCA cycle, several lines of evidence from metabolic networking studies suggest that the TCA cycle in plants may work as independent or partial sets of reactions based on the metabolic and physiological needs of the cells (Sweetlove et al. 2010). In the current study, we found that the infection with CLas and the infestation with D. citri altered the TCA cycle of the host plant. For instance, both CLas- infection and D. citri-infestation reduced the α-ketoglutarate and induced the accumulation of succinate, fumarate, and citrate. We hypothesize that citrus plants might have an additional or alternative pathway(s) that may contribute to this flux towards succinate rather than as an intact

TCA cycle. These alternative fluxes might occur in citrus under specific abiotic and biotic stresses such as CLas-infection and D. citri-infestation. Both the GABA-shunt and PAs pathway are potential candidates for these alternative pathways (from α-ketoglutarate to succinate) and they might be enhanced after the major flux from α-ketoglutarate to glutamate biosynthesis.

The GABA-shunt is the first potential alternative route that could provide a connection between α-ketoglutarate and succinate outside the TCA cycle (Fait et al. 2008; Xiong et al.

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2014). It has been suggested that GABA contributes to citrate degradation, and the GABA-shunt is involved in the central carbon and nitrogen metabolism (Cercós et al. 2006; Michaeli et al.

2011). The GABA-shunt is a short pathway conserved in many prokaryotic and eukaryotic species, which bypasses two steps of 2‐oxoglutarate‐to‐succinate conversion outside the TCA cycle (Bouché and Fromm 2004; Xiong et al. 2014). The biological function of the GABA-shunt in plants is still not well understood (Xiong et al. 2014). However, GABA plays a key role in plant growth and development (Palanivelu et al. 2003), oxidative stress sensing and tolerance

(Bouché et al. 2003), quorum-sensing signaling in plant‐bacteria systems (Chevrot et al. 2006), extracellular signaling (Roberts 2007), defense response (Bolton 2009), and carbon/nitrogen balancing. In addition, it has been reported that exogenous GABA supplementation greatly enhanced citrate and amino acid accumulation (including glutamate, alanine, serine, aspartate, and proline) and improved the fruit quality of citrus (Sheng et al. 2017).

In higher plants, the GABA-shunt is linked with the TCA cycle through the production of succinate using either α-ketoglutarate or glutamate as precursors (Shelp et al. 1999; Bolton

2009; Bouché and Fromm 2004). In addition, it has been shown that citric acid catabolism is connected to the GABA-shunt in citrus fruits (Hussain et al. 2017; Sheng et al. 2017). Briefly, citric acid is catalyzed in the cytosol to α-ketoglutaric acid, then to glutamic acid, then to GABA via isocitrate dehydrogenase, aspartate aminotransferase (or alanine aminotransferase), and glutamate decarboxylase (GAD) activities, respectively (Bown and Shelp 1997; Cercós et al.

2006). Subsequently, GABA is transported from the cytosol to the mitochondria using mitochondrial GABA permease (GABP), and then converted to succinic semialdehyde, paving the way for re-entry of succinate to the TCA cycle, by GABA aminotransferase (GABA-T) and succinate semialdehyde dehydrogenase (SSADH), respectively (Cercós et al. 2006; Fait et al.

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2008). Interestingly, our findings showed that both CLas-infection and D. citri-infestation enhanced the succinate level. This might be due to the catabolism of GABA to succinate directly or through the conversion to succinate-semialdehyde by CsGABA-T, then to succinate using

CsSSADH in sequential reactions. Thus, our findings indicate that succinate could be biosynthesized via the GABA-shunt rather than from α-ketoglutarate, which supports the previous study (Shelp et al. 1999).

Other enzymes involved in this pathway include glutamate dehydrogenase (GDH), glutamate synthase (GS), γ-Glutamylcysteine synthetase (γ-GCS), and glutamate 5-kinase (G5K)

(Shelp et al. 1999, 2017). Our findings showed that these enzymes were expressed at higher levels upon the CLas-infection and D. citri-infestation indicating that the reduction of α- ketoglutarate could be due to the acceleration of its conversion to glutamate (L-glutamine and L- glutamic acid) or pyroglutamic acid, resulting in an accumulation of GABA by these enzymes.

Moreover, our finding showed that L-glutamine, L-glutamic acid, and pyroglutamic acid were also decreased after CLas-infection and/or D. citri-infestation. Taken together, these findings support the hypothesis that CLas and D. citri accelerate the conversion of α-ketoglutarate to glutamate (L-glutamine, L-glutamic acid, and pyroglutamic acid), and also accelerate the conversion of glutamate to GABA, causing an accumulation of GABA in the cytosol

However, GABA is mainly biosynthesized from glutamate by GAD, which is a key enzyme in this pathway (Bouché and Fromm 2004; Fait et al. 2008; Liu et al. 2014). We identified two GAD genes in the C. sinensis genome; glutamate decarboxylase-like (CsGAD;

NM_001288909.1) and glutamate decarboxylase 5-like (CsGAD5; XM_006478039.2). Both genes are upregulated after CLas-infection and D. citri-infestation. The HCA and gene expression results indicated that CsGAD was mainly expressed in D. citri-infested plants and

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CsGAD5 was mainly expressed in CLas-infected plants. Taken together, the gene expression results suggest that different stressors could induce different CsGADs transcripts. The previous study on CsGADs of citrus plants showed that CsGAD1 and CsGAD2 transcripts were mainly expressed in flowers and in fruit juice sacs, respectively (Liu et al. 2014).

The functional connection between the GABA-shunt and the TCA cycle in higher plants and its role in primary carbon metabolism has been reported previously (Fait et al. 2008; Rocha et al. 2010; Michaeli et al. 2011). However, the linkage between the TCA cycle and GABA- shunt in citrus is unknown. Recently, Michaeli et al. (2011) reported that a mitochondrial GABA permease (GABP) connects the GABA-shunt and TCA cycle and plays a key role in normal carbon metabolism in A. thaliana (Michaeli et al. 2011). The C. sinensis genome could encodes for a putative amino-acid permease BAT1-like-protein, transcript variant X1. This protein was described in the current study as CsGABP indicating its predicted GABA‐permease activity.

CsGABP may play a key role in connecting the GABA-shunt and the TCA cycle, acting as a

GABA-transporter, may be essential for primary carbon metabolism. Its function as GABA- transporter was suggested due to its high gene expression levels upon CLas-infection and D. citri-infestation. The accumulated GABA in the cytosol needs to be transported into the mitochondria where it is converted to succinate and integrated into the TCA cycle (Fait et al.

2008; Michaeli et al. 2011). CsGABP could play an important role in this process similar to the role of AtGABP in Arabidopsis (Michaeli et al. 2011). However, further studies are required to clarify the functional and/or regulatory roles of CsGABP in citrus.

The second suggested pathway that could be involved in the enrichment of the TCA cycle is the PAs biosynthetic pathway. We showed that CLas-infection induced the biosynthesis of

PAs, leading to an accumulation of ornithine and putrescine. In plants, putrescine is synthesized

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through two different routes; from arginine using arginine decarboxylase (ADC) or from ornithine mediated by ornithine decarboxylase (ODC) (Moschou et al. 2012). In this study, ornithine was increased after CLas-infection. In addition, arginine was detected only in CLas- infected plants (data non-shown). Moreover, both CsADC and CsODC were expressed at higher levels in CLas-infected plants indicating that both putrescine biosynthetic pathways are jointly working to enhance the PAs content. However, the role of PAs in HLB pathosystem is poorly understood. We believe that although PAs might play a role in citrus defense against CLas and its vector, they could also be involved in disease symptom development via the production of

H2O2. Briefly, diamine oxidase (DAO) and polyamine oxidase (PAO) catalyze the oxidation of putrescine and spermidine, respectively, to produce GABA and resulting in accumulation of

H2O2 within the apoplast (Walters 2000, 2003a).

The accumulation of H2O2 in citrus plants after the infection with CLas has been reported previously (Pitino et al. 2017). In our study, D-amino acid oxidase PA4548 (aka diamine oxidase

CsDAO) and polyamine oxidase 1 (CsPAO) were expressed at higher levels in CLas-infected plants, which agreed with this common feature of pathogen-host interaction in many previous studies (Walters 2000, 2003a). Thus, we hypothesize that the induction of PAs and their catabolic genes (CsDAO and CsPAO) are correlated with the accumulation of GABA and H2O2 which are working as a response to HLB to create an incompatible interaction. Nevertheless, the alteration in DAO and PAO, and the accumulation of H2O2 have to occur in the appropriate location of the plant to be effective in the creation of incompatible interactions between the host and the pathogen (Walters 2003a). Interestingly, CLas could survive the toxic effects of accumulated H2O2 using its own peroxidase (Pitino et al. 2017). The detoxification system of citrus plants, however, might not be sufficient to reduce the high H2O2 levels, which may

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eventually become toxic to the leaf tissue and cause the characteristic blotchy mottle symptoms of HLB (Pitino et al. 2017).

In addition, the PAs biosynthesis pathway could be involved in the enrichment of the

TCA cycle directly through the production of the dicarboxylic acid fumarate. Fumarate could be produced during the conversion of citrulline to argininosuccinate by argininosuccinate synthase

(ASS), then to the amino acid arginine using argininosuccinate lyase (ASL; aka argininosuccinase) which splits argininosuccinate to release fumarate and arginine (Haines et al.

2011). Our findings showed that both CsASS and CsASL were upregulated after CLas-infection, which resulted in the accumulation of arginine (detected only in CLas-infected plants). Together, this might be enhancing the TCA cycle intermediate fumarate directly. Similar induction of fumarate was observed during the necrotrophic phase of rice blast fungus Magnaporthe grisea

(Parker et al. 2009) and the maize anthracnose, Colletotrichum graminicola (Voll et al. 2011).

Furthermore, the phenolic monoamine synephrine (Figure 6-8) and its precursor, octopamine, are compounds that might be involved in the defense response against HLB.

Synephrine was reported previously in several citrus species and cultivars (Arbo et al. 2008;

Dragull et al. 2008). In citrus, it is believed that synephrine is biosynthesized from tyrosine via a pathway involving tyramine, N-methyltyramine, then to synephrine using tyrosine decarboxylase

(TDC), tyramine N-methyltransferase (TNMT), and an unidentified N-methyl-tyramine-β- hydroxylase (NMTβH), respectively (Wheaton and Stewart 1969; Dragull et al. 2008; Bartley et al. 2010). In animals, synephrine is biosynthesized from tyrosine through tyramine, octopamine, then to synephrine using TDC, tyramine β-hydroxylase (TβH) and phenylethanolamine N- methyltransferase (PNMT), respectively (Wheaton and Stewart 1969). Although octopamine is not an important intermediate in plants as in animals, our results showed that the octopamine

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level was elevated in the presence of CLas. Although the transcript level of CsTDC was increased in all studied treatments, tyramine level was decreased in CLas-infected plants, but not other treatments. This might be due to the acceleration of the conversion of tyramine to synephrine via N-methyltyramine (most common in plants) or via octopamine (most common in animals). Because only the TDC has been isolated and cloned from plants, while other enzymes

(TNMT & NMTβH in plants and TβH & PNMT in animals) have not yet been cloned (Bartley et al. 2010), our image about this pathway (synephrine-polyamine pathway) and the reason(s) behind tyramine reduction is not fully understood and it might require further studies. Taken together, our findings indicate that CsTDC is involved in synephrine biosynthesis in citrus in agreement with Bartley et al. (2010).

To summarize our findings, a hypothetical model for the connection between the TCA cycle, PAs pathway, and GABA-shunt in citrus was suggested and presented in Figure 6-8. In this model, we proposed that CLas and its insect vector, D. citri, augments the TCA cycle of citrus plant indirectly via the GABA shunt-cycle and PAs pathways to increase the flux towards succinate thereby increasing the availability of fumarate and citrate above that provided by the

TCA cycle alone. Briefly, CLas-infection might accelerate the conversion of α-ketoglutarate to glutamate, then to GABA, which results in an accumulation of GABA in the cytosol.

Subsequently, GABA is transported from the cytosol to the mitochondria using the GABA permease (GABP), to support the accumulation of succinate directly or indirectly. Another pathway that could be involved in the enrichment of the TCA cycle is the PAs biosynthesis pathway. PAs pathway might be connected directly to the TCA cycle through the production of the dicarboxylic acid fumarate during the catabolism of argininosuccinate to arginine using argininosuccinate lyase (ASL; aka argininosuccinase), or indirectly via the enhancement of

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GABA-shunt. In addition, α-ketoglutarate is involved in many other metabolic pathways such as the amino acid proline biosynthesis. Proline is biosynthetically derived from the glutamate via the δ1-pyrroline-5-carboxylate (P5C). In Figure 6-8, we hypothesize that there might be a connection between proline and GABA to enhance the GABA content. However, this connection/hypothetical route between proline and GABA requires further investigation to be confirmed

The importance of this study is not only to provide a clue about the role of TCA cycle,

GABA-shunt, and PAs biosynthetic pathway in citrus response against HLB but possibly underline the functional connection between the GABA-shunt and the TCA cycle. This connection was not reported previously in citrus. Furthermore, this study may provide some insights into the understanding of the nutritional needs of CLas, which may lead to successful culturing of this bacterium. Finally, understanding the metabolic changes in citrus after CLas- infection or D. citri-infestation could lead to a comprehensive picture of defense responses to

HLB in citrus, which is critical to finding novel and sustainable management strategies for HLB.

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Figure 6-1. Detected proteinogenic amino acids (PAAs), non-proteinogenic amino acids (NPAAs), polyamines (PAs), and tricarboxylic acid- (TCA-) associated compounds of Valencia sweet orange (C. sinensis) leaves after derivatization with MCF. (A) Representative chromatogram of 19 detected metabolites in healthy citrus leaves using GC-MS running in full-scan mode. Chromatographic characteristics, retention times, linear retention indices, and the main fragments of different detected peaks are listed in Table E-1. (B) Concentrations of total PAAs, (C) concentrations of total TCA-associated compounds and (D) concentrations of total NPAAs and PAs groups detected in Valencia sweet orange (C. sinensis) after infection with CLas and/or the infestation with D. citri using GC-MS (n=10). Horizontal thick lines indicate the medians, black or white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest value of the data. Different letters indicate statistically significant differences among treatments using Tukey-Kramer honestly significant difference test (Tukey HSD; p <0.05).

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Figure 6-2. Two-way hierarchical cluster analysis (HCA) of individual non-proteinogenic amino acids (NPAAs) and polyamines (PAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC- MS. (A) HCA using the non-standardized means of individual metabolites (n=10) and (B) HCA using the standardized means of individual metabolites of the matrices for the four studied treatments. The differences in the metabolites abundances between the four treatments are visualized in the heat map diagram. Rows represent the individual metabolites, while columns represent the treatments. Lower peak areas are colored green and higher peak areas are colored red (see the scale at the right corner of the bottom of the heat map). Metabolites and treatments were organized using HCA based on similarities in auto-scaled values and correlations, respectively, with 95% confidence between groups from the discriminant function analysis (DFA) to construct the similarity dendrograms. In panel (B), different letters indicate statistically significant differences among treatments, while cells with the same letter signify no significant differences among them using Tukey-Kramer honestly significant difference test (Tukey HSD; p <0.05). The p-values are listed to the right side of the heat map.

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Figure 6-3. Principal component analysis (PCA) of individual non-proteinogenic amino acids (NPAAs) and polyamines (PAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS. (A) PCA-scatter-blot(n=10); (B) PCA-loading-plot.

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Figure 6-4. Concentrations of individual proteinogenic amino acids (PAAs) detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS. (A) L-Cysteine (B) L-tyrosine, (C) L-proline, (D) L-serine, (E) L-glutamine, and (F) L-glutamic acid. Horizontal thick lines indicate the medians, black or white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest value of data. Different letters indicate statistically significant differences among treatments (n=10), while “ns” or the same letter signify no significant differences among treatments using Tukey-Kramer honestly significant difference test (Tukey HSD; p <0.05).

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Figure 6-5. Concentrations of different individual tricarboxylic acid- (TCA-) associated compounds detected in Valencia sweet orange (C. sinensis) leaf extracts after infection with CLas and/or the infestation with D. citri using GC-MS. (A) citric acid (B) succinic acid, (C) fumaric acid, and (D) 2-ketoglutaric acid. Horizontal thick lines indicate the medians, black or white dots indicate the means, boxes show the interquartile ranges including 25-75% of the values, and whiskers reflect the highest and the lowest value of data. Different letters indicate statistically significant differences among treatments (n=10), while “ns” signify no significant differences among treatments using Tukey-Kramer honestly significant difference test (Tukey HSD; p <0.05).

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Figure 6-6. In silico analysis of GABA permease (GABP) of Valencia sweet orange (C. sinensis). (A) Multiple sequence alignment of GABP amino acid sequences of bidirectional amino acid transporter 1 (AtBAT1) of A. thaliana (NP_565254.1; aka AtGABP) and the predicted amino acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP). Conserved amino acids are indicated with black shading and those with high similarity score are in gray. The conserved domains of AtGABP are marked by red and blue lines for AA permease subfamily and AA/polyamines transporter I, respectively. Whiskers reflect the start and the end of each domain. Numbers before and after whiskers denote amino acid residue number for the start and end, respectively. (B) The protein functional and conserved domains analysis of AtGABP (NP_565254.1) and CsGABP (XP_006468761.1) using InterPro Scan (https://www.ebi.ac.uk/interpro/). (C) The predicted three-dimensional (3D) secondary structure model of CsGABP (XP_006468761.1), with 87% similarity with 100.0% confidence by the single highest scoring template with the structure of glutamate-GABA antiporter GadC (4DJI) from Escherichia coli (strain K12) in the protein data bank (PDB, https://www.rcsb.org/). All bioinformatic analyses were carried out using the available data of C. sinensis cv. Valencia v2.0 genome from chromosome level HZAU assembly (Xu et al. 2013), available on Citrus Genome Database website (https://www.citrusgenomedb.org/organism/Citrus/sinensis) and the recently available data on the GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/).

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Figure 6-7. Relative gene expression of genes involved in the GABA-shunt and other PAs biosynthetic pathways in Valencia sweet orange (C. sinensis) leaves after infection with CLas and/or the infestation with D. citri. (A) Relative gene expression of the predicted amino acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP). Horizontal thick lines indicate the medians, black or white dots indicate the means, boxes show the interquartile ranges including 25- 75% of the values, and whiskers reflect the highest and the lowest value of data. Different letters indicate statistically significant differences among treatments, while the same letters signify no significant differences among treatments using Tukey- Kramer honestly significant difference test (Tukey HSD; p <0.05). (B) Two-way hierarchical cluster analysis (HCA) and its associated heat map diagram of differential standardized gene expression patterns of 32 genes involved in the GABA- shunt and PAs biosynthetic pathway. Rows represent the genes while the columns represent different treatments. Low expression levels are colored green and high expression levels are colored red (see the scale at the right corner at the bottom of the heat map). Treatments and genes were organized using HCA based on similarities in auto-scaled values and correlations, respectively, with 95% confidence between groups from the discriminant function analysis (DFA) to construct the similarity dendrograms. Gene expressions were normalized using four housekeeping genes (EF1, F-box, GAPC1, and SAND), which previously showed high stability for transcript normalization in different citrus organs under biotic stress (Mafra et al. 2012; Wei et al. 2014). The changes in gene expression were analyzed with the −ΔΔC 2 T method. Samples were analyzed in triplicate for each technical replicate (five biological replicates, two technical replicates each/treatment; n=30). The listed genes were assembled based on the available data of C. sinensis cv. Valencia v2.0 genome from chromosome level HZAU assembly (Xu et al. 2013), available on Citrus Genome Database website (https://www.citrusgenomedb.org/organism/Citrus/sinensis) and the recently available data on the GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). The full list of expressed genes, names, accession numbers, and primers are available in supplementary Table E-4. For the full names and abbreviations, see the abbreviations list.

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Figure 6-8. Hypothetical model of the effect of infection with CLas and/or the infestation with D. citri on the proteinogenic amino acids (AAs), non-proteinogenic amino acids (NPAAs), polyamines (PAs), and tricarboxylic acid- (TCA-) associated compounds of Valencia sweet orange (C. sinensis) leaves. Briefly, we suggest that CLas-infection and/or D. citri-infestation augments the TCA cycle of citrus plant indirectly via the GABA shunt-cycle and polyamines pathway. CLas-infection and/or D. citri- infestation might accelerate the conversion of α-ketoglutarate to glutamate, which eventually results in the accumulation of GABA. Subsequently, GABA is transported from the cytosol to the mitochondria via GABA permease (GABP), to support the accumulation of succinate directly or indirectly. These findings indicate that succinate is biosynthesized predominantly via the GABA-shunt rather than from α- ketoglutarate. Another pathway that could be involved in the enrichment of the TCA cycle is the PAs biosynthetic pathway. PAs pathway might be connected directly to the TCA cycle through the production of the dicarboxylic acid fumarate during the catabolism of argininosuccinate to arginine using ASL, or indirectly via the enhancement of GABA-shunt. Taken together, we suggest a functional connection between the GABA-shunt and the TCA cycle in citrus plants via the GABP. Solid lines with arrows signify positive reaction, and round-dotted lines with arrows represent hypothetical mechanisms or uncharacterized elements. The yellow bars signify the metabolites level, while the green-black-red ones indicate the non- standardized gene expression levels (see the figure key at the right top corner of the figure). The full list of expressed genes, names, accession numbers, and primers are available in supplementary Table E-4. For the full names and abbreviations, see the abbreviations list.

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CHAPTER 7 SUMMARY AND CONCLUSION REMARKS

Metabolomics attempts to measure the unique chemical fingerprints and small-molecule metabolite profiles (Hollywood et al. 2006) present in a specific tissue or fluid at a specific time point (Hall 2011). Metabolomic approaches became a key tool for understanding how plant metabolism is affected by pathogens and pests attack. In addition, metabolomics provides an appropriate tool to study the plant responses to various biotic and abiotic stressors (Hall 2011). In the current study, we used integrative metabolomics and transcriptomics approaches to understand the citrus response(s) against the bacterial pathogen Candidatus Liberibacter asiaticus

(CLas) and/or its insect vector Diaphorina citri. We believe that the metabolic responses of citrus plants may result from host cellular functions for defense reactions, or it may result from the manipulation of metabolic pathways by CLas and/or D. citri for their benefits to fulfill their nutritional needs, or to induce symptoms development.

Deciphering the Role of Citrus Metabolites in HLB Symptoms Development

The most characteristic symptom of HLB is the blotchy mottle, which is an asymmetrical discoloration/chlorosis across the mid-vein of the leaf with patches of yellow and green islands

(Schneider 1968; Bové 2006). Symptoms of HLB are induced by both the pathogen and its vector, due to alteration in many physiological aspects such as phytohormonal levels, carbohydrate status (Rosales and Burns 2011), and carotenoid content (Wei et al. 2014a, 2014b).

In the current study, we showed that CLas-infection and/or D. citri-infestation dramatically altered citrus leaf pigments (total chlorophylls, xanthophylls, and carotenes content as groups), with a greater effect in CLas-infected trees. Additionally, out of 15 detected pigments, 13 compounds were decreased in CLas-infected leaves, and nine pigments were reduced in D. citri- infested leaves. Furthermore, all chlorophyll biosynthetic genes were down-regulated except for

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chlorophyllase (Chlases, also known as CLHs) and chlorophyll(ide) b reductase (CBRs). In addition, the infection with CLas and the infestation with D. citri down-regulated the early/shared steps in the carotenoids biosynthesis pathway, while they up-regulated the late/specific steps. The early/shared steps of carotenoids biosynthesis is a plastid-localized step and begin with the MEP pathway (Finkelstein 2013). The early/shared steps contain two characteristic branches; alpha-arm refers to the α-carotene branch which leads to lutein synthesis, and beta-arm refers to β-carotene branch. In this study, all the compounds involved in both arms in the early/shared steps were decreased and their biosynthetic genes were down- regulated (15 genes). Taken together, we conclude that the blotchy mottle symptoms of HLB are due to the degradation of chlorophylls, xanthophylls, and carotenes rather than only chlorophylls or carotenoids only (Figure 7-1).

On the other hand, the compounds involved in late/specific steps in the carotenoids biosynthesis pathway were increased causing accumulation of zeaxanthin and ABA. It is well- known that β-carotene pool is tightly regulated in photosynthetic tissues (Finkelstein 2013). In other words, only a small proportion of β-carotene is metabolized to zeaxanthin using β-carotene hydroxylases (aka Carotenoid hydroxylase β-ring [CHYb]) enzyme (Jaschke et al. 1997;

Milborrow 2001; Nambara and Marion-Poll 2005). The transcript levels of CsCHYb was increased in this study, which indicates the accelerated-conversion of β-carotene to zeaxanthin.

Subsequently, zeaxanthin is converted to violaxanthin via the intermediate antheraxanthin using zeaxanthin epoxidase (ZEP), then to neoxanthin using Neoxanthin synthase (NSY) (Jaschke et al.

1997; Milborrow 2001; Nambara and Marion-Poll 2005). Our results showed that all genes involved in late/specific steps in the carotenoids biosynthesis pathway were up-regulated after

CLas-infection and/or D. citri-infestation including CitCHYbs, CitZEPs, CitVDE,

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capsanthin/capsorubin synthase (CitCCS), neoxanthin synthase (CitNSY), 9-cis-epoxycarotenoid dioxygenase 3 (CitNCED), short-chain alcohol dehydrogenase (CitABA2), and abscisic aldehyde oxidase (CitAAO3) causing accumulation of ABA. It has been proposed previously that ABA could play a positive role in the induction of leaf yellowing in cut Stock (Matthiola incana) flowers (Ferrante et al. 2004) and rice (Oryza sativa) plants (Kusaba et al. 2007). Based on these facts, our findings suggest that ABA may play a role in HLB symptom development (Figure 7-

1), but the mechanism regarding this is still unclear and requires more investigation.

In addition, polyamines might be involved in HLB symptom development via the production of H2O2. Briefly, diamine oxidase (DAO) and polyamine oxidase (PAO) catalyze the oxidation of putrescine and spermidine, respectively, to produce GABA and resulting in accumulation of H2O2 within the apoplast (Walters 2000, 2003). The accumulation of H2O2 in citrus plants after the infection with CLas has been reported previously (Pitino et al. 2017). In our study, GABA was accumulated and both D-amino acid oxidase PA4548 (aka diamine oxidase CsDAO) and polyamine oxidase 1 (CsPAO) were expressed at higher levels in CLas- infected plants. Thus, we hypothesize that the induction of PAs and their catabolic genes

(CsDAO and CsPAO) are correlated with the accumulation of GABA and H2O2 which are working as a response to HLB to create an incompatible interaction. Nevertheless, the alteration in DAO and PAO, and the accumulation of H2O2 have to occur in the appropriate location of the plant to be effective in the creation of incompatible interactions between the host and the pathogen (Walters 2003a). Interestingly, CLas could survive the toxic effects of accumulated

H2O2 using its own peroxidase (Pitino et al. 2017). The detoxification system of citrus plants, however, might not be sufficient to reduce the high H2O2 levels, which may eventually become toxic to the leaf tissue and cause the characteristic blotchy mottle symptoms that appear after

CLas-infection (Pitino et al. 2017).

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Another characteristic symptom of HLB is the leathery leaves. In advanced stages of the disease, thicker and leathery leaves were observed in sour orange (C. aurantium) and key lime

(C. aurantiifolia) CLas-infected plants (McClean and Schwarz 1970; Bové 2006). The extensive accumulation of starch grains in the photosynthetic cells, phloem elements, vascular parenchyma and all other parenchyma cells of the HLB-symptomatic leaves and petioles may explain this leathery leaves symptom (McClean and Schwarz 1970; Etxeberria et al. 2009; Whitaker et al.

2014) (Figure 7-1). Our findings showed that CLas-infection induced the starch accumulation in the infected leaves. In addition, we suggest that auxins accumulation, shown in this study, might be involved in the development of leathery leaves symptom. The treatment of cotton (Gossypium hirsutum) plants with α-naphthalene acetic acid (NAA; a synthetic plant growth regulator in the auxin family) caused thicker and more leathery leaves (Singh and Greulach 1949).

Moreover, it is well-known that CLas-infection reduces the production of new flushes on the infected trees. Additionally, on severely affected trees, some branches can have small, upright leaves develop a symptom commonly known as “rabbit-ears (Gómez 2008; Dewdney

2012). We believe that different phytohormones could be involved in disease symptom development, particularly, the reduction in the frequency of vegetative flushes and of leaf size.

Based on the facts that (1) shoot branching, the process that a dormant bud activates and becomes an actively growing branch, is complex and very finely tuned (Ongaro and Leyser

2007); (2) bud outgrowth and shoot system architecture are controlled by several environmental factors and endogenous signals such as phytohormones, particularly auxins and cytokinins

(Ongaro and Leyser 2007; Shimizu-Sato et al. 2009; Martín-Trillo and Cubas 2010; Müller and

Leyser 2011); (3) auxins are synthesized in the apical meristems and then translocated basipetally (downward through the phloem) and suppresses axillary bud outgrowth (Ongaro and

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Leyser 2007; Shimizu-Sato et al. 2009); (4) cytokinins are synthesized in the root tip meristems, travel acropetally (upward through the xylem), and promote/stimulate axillary bud outgrowth

(Ongaro and Leyser 2007; Shimizu-Sato et al. 2009); (5) both auxins and cytokinins interact antagonistically, it has been reported that kind of organogenesis is control by relative concentrations of auxins and cytokinins (Ongaro and Leyser 2007; Shimizu-Sato et al. 2009;

Martín-Trillo and Cubas 2010; Müller and Leyser 2011); and (6) Our findings showed that CLas- infection induced the accumulation of auxins but did not affect the cytokinin content, which affects the ratio of auxin to cytokinins. Therefore, we suggest that the auxin/cytokinins ratio in citrus tissues determines the initiation of shoot buds. Since auxins were higher after CLas- infection, this could inhibit bud outgrowth and reduces the frequency of vegetative flushes. In addition, we hypothesize that inhibitory effect(s) of auxins are mediated by a second signaling.

Candidate signals include cytokinin and ABA (Figure 7-1).

In addition, several bud-specific proteins are involved in the auxin-cytokinin interactions to control the shoot branching. All the bud-specific genes, that were functionally identified, are members of the Teosinte branched, Cycloidea, Proliferating cell factors (TCP) family of transcription factors (Müller and Leyser 2011). These genes including teosinte branched1 (TB1), grassy tillers1 (GT1), branched1 (BRC1), or fine culm1 (FC1), which contains a TCP domain and can act locally to prevent bud outgrowth (Martín-Trillo et al. 2011; Whipple et al. 2011). For example, TB1 gene negatively regulates the bud growth (Martín-Trillo and Cubas 2010; Müller and Leyser 2011; Ongaro and Leyser 2007; Shimizu-Sato et al. 2009). Likewise, GT1 promotes apical dominance (Whipple et al. 2011) and BRC1 regulates the lateral branching (Chen et al.

2013). Interestingly, all the bud-specific proteins are regulated by auxins-cytokinins interaction

(Figure 7-1).

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Furthermore, we suggest that the high levels of ABA after CLas-infection could induce the bud dormancy causing a reduction in the frequency of vegetative flushes. Several previous studies showed that ABA and its biosynthetic genes (NCED, ABA2, and AAO3) were activated during dormancy of grapevine (Vitis sp.) (Fennell et al. 2015), peach (Prunus persica) (Wang et al. 2016), leafy spurge (Euphorbia esula) (Chao et al. 2017), and pear (Pyrus pyrifolia) (Li et al.

2018). In addition, the treatment with exogenous ABA had a significant inhibitory effect on dormancy release of grapevine buds (Zheng et al. 2015). Taken together, this supports our hypothesis that ABA could be involved in the reduced frequency of new flushes of HLB-infected trees via the regulation of bud dormancy (Figure 7-1).

Citrus Metabolites may Aid the Battle against Huanglongbing

In this study, metabolomic analysis of Valencia sweet orange leaves revealed that CLas- infection and/or D. citri-infestation altered the abundances of leaf pigments (chlorophylls, carotenes, and xanthophylls), the phytohormones (BA, tCA, SA, IAA, IBA, IPA, tJA, and ABA), the carboxylic compounds (amino acids, organic acids, and fatty acids), TCA cycle, polyamines, and GABA-shunt. Most of our results agreed with previous studies on CLas (Rosales and Burns

2011; Martinelli et al. 2012; Slisz et al. 2012; Malik et al. 2014; Chin et al. 2014; Lu et al. 2013) and were also consistent with results found for Candidatus Liberibacter solanacearum, the pathogen of Zebra chip disease of potato (Wallis et al. 2012, 2014, 2015). Based on those findings, we tried to understand the role of the reported potential changes after CLas-infection and/or D. citri-infestation in citrus physiology in general, and in citrus response(s) to HLB particularly. These metabolic changes could be implicated directly or indirectly in citrus response(s) and in the expression of plant defense-related genes against CLas and/or D. citri. We believe that citrus plants depend on multi-layered defense responses to mediate the effect of the

CLas-infection and/or D. citri-infestation. These defense mechanisms include accumulation of

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defense molecules, alteration of plant signaling system, changes in primary and secondary metabolites, and other biochemical and physiological modifications. In the next paragraphs, we are going to discuss the potential metabolic responses of citrus plants (Figure 7-2).

Phytohormone-Based Defense Responses

The infection with pathogens and/or herbivory with insects induce many phytohormonal signaling pathways in plants including the three main pathways (SA, JA, and ET) (Hatcher et al.

2004; Robert-Seilaniantz et al. 2007; Lazebnik et al. 2014). In agreement with the previous observations, our results showed that the levels of most of the phytohormones (BA, tCA, SA,

IAA, IBA, IPA, tJA, and ABA) were affected in CLas-infected, D. citri-infested, and double- attacked plants. On the other hand, no influence was observed on the levels of cytokinins and gibberellins, which were found at very low concentration in the citrus leaves. This result indicated that CLas and D. citri attack did not affect cytokinins and gibberellins in citrus leaves.

We believe that multiple phytohormonal signaling mediates the citrus response to the bacterial pathogen CLas and its vector, D. citri. Moreover, we suggest that the phytohormone-based defense response starts early in their biosynthetic pathways, since most of the phytohormone precursors and their biosynthetic genes were activated/induced upon CLas-infection and/or D. citri-infestation (Figure 7-2).

Our results indicated that the SA-mediated pathway was activated in citrus plants upon

CLas infection, since the GC-MS results showed that SA and its precursor phenylalanine were induced at a higher level in CLas-infected plants, in agreement with previous studies (Lu et al.

2013). In addition, SA-biosynthetic genes were up-regulated in CLas-infected plants. Recently, it has been reported that CLas might use salicylate hydroxylase (SahA) to degrade SA and suppress citrus defenses (Li et al. 2017). However, the citrus plants may negate this enzymatic activity by

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more induction of SA as we and a previous study have shown (Lu et al. 2013). However, the SA- based response could not be sufficient to combat bacterial invasion completely.

On the other hand, the infestation with D. citri increased the level of tJA and its precursor

(linolenic acid) and upregulated the expression of JA-biosynthetic genes. The key role of JA as a herbivore-associated phytohormone has been extensively studied (Robert-Seilaniantz et al. 2007;

Bari and Jones 2009; Lazebnik et al. 2014). Taken together, we conclude that JA-mediated pathway is activated in citrus plants upon D. citri-infestation. SA-mediated pathway and JA- mediated pathway are the most common defensive pathways in higher plants (Robert-Seilaniantz et al. 2007; Bari and Jones 2009; Glazebrook 2005) (Figure 7-2).

In addition to the well-known role of SA and JA in the activation of SA- and JA- mediated pathways, respectively, we suggest that ABA and auxins play key roles in mediating the HLB disease. Both auxins and ABA might be involved in the induction of citrus response directly or indirectly during the activation of both SA- and JA-mediated pathways. This leads to complex cross-talk among different phytohormone groups which interact positively or negatively together, which can be linked back to the SA- and JA-mediated pathway. However, further research focusing on the role of ABA and auxins in inducing SA- and JA-mediated pathways is required for better understanding of citrus response to HLB disease (Figure 7-2).

Amino Acid-Based Defense Responses

Previously, many metabolomics-based studies reported that pathogen infection and vector infestation may cause major changes in metabolite composition of citrus (Cevallos-Cevallos et al. 2011; Slisz et al. 2012; Chin et al. 2014; Malik et al. 2014) and potato (Wallis et al. 2012,

2014, 2015) plants. Changes in AAs as a plant response is due to different mechanisms such as the transaction of pathogenesis-related proteins (PRs), the generation of reactive oxygen species

(ROS), activation of nonexpressor of pathogenesis-related proteins1 (NPR1), or induction of

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salicylic acid (SA) biosynthesis (Rojas et al. 2014; Durrant and Dong 2004). In plant-pathogen- vector pathosystems, it has been suggested that the role of plant metabolites, such as amino acids, is to save the energy requirements for plant defense responses, however, more important roles have been reported (Bolton 2009; Kangasjärvi et al. 2012). The changes in amino acids might contribute directly to plant defense responses. For example, phenylalanine is the precursor of SA (Rojas et al. 2014), which is implicated in defense response against biotrophic and hemibiotrophic pathogens, and plays an important role in the induction of systemic acquired resistance (SAR) (Bari and Jones 2009; Hatcher et al. 2004; Glazebrook 2005). Likewise, tryptophan is the precursor of auxins, which are involved in plant growth and development. One of the most characteristic host responses to CLas-infection is an increase in total amino acid abundance, indicating benefits to both pathogen and host defense (Killiny and Hijaz 2016;

Killiny and Nehela 2017a) (Figure 7-2).

The abundance of phenylalanine was higher in CLas-infected plants in agreement with previous studies on citrus (Slisz et al. 2012; Chin et al. 2014) and potato (Wallis et al. 2012,

2014). Phenylalanine is the precursor of SA, which also increased after CLas-infection, which support our hypothesis that the phytohormone-based defense response starts early in their biosynthetic pathways. Likewise, our results showed that the infection with CLas and the infestation with D. citri significantly increased the abundance of tryptophan. Tryptophan is involved in several biosynthesis pathways in higher plants, such as auxins biosynthesis. Again, our results showed that all auxins (IAA, IBA, and IPA) were activated against HLB, which support our hypothesis that the phytohormone-based defense response starts early in their biosynthetic pathways (Figure 7-2).

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Additionally, proline was found to be higher in CLas-infected leaves compared to other treatments (D. citri-infested and double-attacked plants) and the control. Our findings are in agreement with the previous studies on CLas-infected citrus leaves (Cevallos-Cevallos et al.

2011; Rivas et al. 2008), citrus seedlings (Cevallos-Cevallos et al. 2012), potato tubers (Wallis et al. 2012, 2014), and potato leaves (Wallis et al. 2015), but were in contrast to what was found in citrus fruits (Slisz et al. 2012; Chin et al. 2014). Proline is involved in the induction of glutamine-proline pathway, which is implicated in ROS generation due to the activity of proline dehydrogenase (ProDH) and δ 1-pyrroline-5-carboxylate dehydrogenase (P5CDH) (Rojas et al.

2014). Furthermore, serine and threonine abundances were significantly higher in CLas-infected leaves compared to the control in agreement with previous studies on citrus leaves (Cevallos-

Cevallos et al. 2011), citrus fruits (Cevallos-Cevallos et al. 2012), potato tubers (Wallis et al.

2012, 2014), and potato leaves (Wallis et al. 2015). The accumulation of serine and threonine are commonly associated with bio-stress responses in plants, mainly due to the increase in photorespiration and overexpression of peptidases and proteases (Cevallos-Cevallos et al. 2012)

(Figure 7-2).

On the other hand, lysine was reduced after infection with CLas. The degradation of lysine plays a key role in the activation of SAR (Yang and Ludewig 2014). We suggest that lysine produces pipecolic acid by the activity of the AGD2-like defense response protein 1

(ALD1) then SA (Yang and Ludewig 2014) to coordinate the SAR via SA-mediated pathway

(Bernsdorff et al. 2016). Many previous studies support our suggestion because the loss of ALD1 gene reduced the SA abundances and decreased the plant resistance to Pseudomonas syringae in

Arabidopsis (Song et al. 2004; Yang and Ludewig 2014). However, further studies are required to explore the role of lysine and pipecolic acid in the activation of the SA-mediated pathway.

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Fatty Acids-Based Defense Responses

Fatty acids and their metabolites, including 12-oxophytodienoic acid (OPDA), trans- jasmonic acid (tJA), and methyl jasmonate (me-JA), could induce plant defense responses against herbivory (Farmer and Ryan 1992; Tooker and De Moraes 2009; Zeier 2013).

Interestingly, D. citri strongly influenced the linoleic acid and α-linolenic acid abundances in D. citri -infested leaves. This is in agreement with previous studies on different herbivores including the gall-inducing caterpillars Gnorimoschema gallaesolidaginis and Heliothis virescens on

Solidago altissima stems and leaves (Tooker and De Moraes 2009), and the Hessian fly,

Mayetiola destructor on rice and wheat (Zhu et al. 2011). We suggest that citrus plants might induce fatty acid biosynthesis to activate the JA-mediated pathway to protect themselves against

D. citri. The levels of tJA, its precursor (linolenic acid), and JA-biosynthetic genes were increased upon D. citri infestation more than CLas infection, which supports our point of view

(Figure 7-2).

Large numbers of plant mechanisms involved in defense against herbivores are regulated by JA including anti-oxidative enzymes, proteinase inhibitors (PIs), volatile organic compounds

(VOCs), alkaloid production, and secretion of extra-floral nectar (EFN) (Bennett and Wallsgrove

1994; Shivaji et al. 2010; War et al. 2012). In addition, the JA-mediated pathway is associated with other response activities such as antioxidant activity augmentation (Shahabinejad et al.

2014), hypersensitive reaction, HR (Schilmiller and Howe 2005), and systemic acquired resistance, SAR (Thaler et al. 2010). The enhanced gene expression of serine palmitoyl transferase; (SPT), ω-3 fatty acid desaturase 7 (FAD7), ω-3 fatty acid desaturase 8 (FAD8), and the increase in the abundance of α-linolenic acid suggested that they play key roles in the accumulation of ROS, which lead to HR (Rojas et al. 2014). HR and SAR are often associated together in infected plant tissues (Kombrink and Schmelzer 2001).

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Polyamines-Based Putative Defense Responses

We showed that CLas-infection induced the biosynthesis of polyamines (PAs), leading to an accumulation of ornithine and putrescine. In plants, putrescine is synthesized through two different routes; from arginine using arginine decarboxylase (ADC) or from ornithine using ornithine decarboxylase (ODC) (Moschou et al. 2012). In this study, arginine was detected only in CLas-infected plants. In addition, ornithine was increased after CLas-infection. Moreover, both CsADC and CsODC were expressed at higher levels in CLas-infected plants indicating that both putrescine biosynthetic pathways are jointly working to enhance the PAs content (Figure 7-

2). However, the role of PAs in HLB pathosystem is poorly understood. We believe that although PAs might play a role in citrus defense against CLas and its vector, they could also be involved in disease symptom development via the production of H2O2 as described above.

Additionally, synephrine (phenolic monoamine) and its precursor, octopamine, are compounds that might be involved in the defense response against HLB. Synephrine was reported previously in several citrus species and cultivars (Arbo et al. 2008; Dragull et al. 2008).

In citrus, synephrine is biosynthesized from tyrosine via a pathway involving tyramine, N- methyltyramine, then to synephrine using TDC, TNMT, and NMTβH, respectively (Wheaton and

Stewart 1969; Dragull et al. 2008; Bartley et al. 2010). While it synthesized through tyramine, octopamine, then to synephrine in animals, using TDC, TβH and PNMT, respectively (Wheaton and Stewart 1969). Although octopamine is not an important intermediate in plants as in animals, our results showed that the octopamine level was elevated in the presence of CLas. Furthermore, the transcript level of CsTDC was increased in all studied treatments. Because only TDC has been isolated and cloned from plants, while other enzymes have not yet been cloned (Bartley et al. 2010), our image about synephrine-polyamine pathway is not fully understood and it might require further studies.

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Leaf Pigments-Based Defense Responses

In addition to leaf metabolites, we believe that leaf pigments also might play a key role in citrus response against HLB. Although both CLas-infection and D. citri-infestation reduced almost all studied leaf pigments, there is a remarkable induction of two compounds.

Chlorophyllide a (a tetrapyrrole pigment from chlorophylls pathway) was induced to higher levels in D. citri-infested plants, while zeaxanthin (from carotenoids pathway) was increased in

CLas-infected plants.

We suggest that chlorophyllide a might be implicated in the citrus defense against D. citri

(Figure 7-2). Briefly, in this study, challenging citrus plants with D. citri increased the levels of chlorophyllide a and up-regulated its biosynthetic genes chlorophyllase (Chlases, also known as

CLHs) and chlorophyll(ide) b reductase (CBRs) including chlorophyll(ide) b reductase -NON-

YELLOW COLORING 1 (NYC1) and chlorophyll(ide) b reductase -NYC1-Like (NOL). Chlases and CBRs (CitNYC1 and CitNOL) are key enzymes in chlorophyllide production from chlorophyll molecules (Tsuchiya et al. 1999). We hypothesize that chlorophyllide might be activated via the JA-mediated pathway in citrus. The application of me-JA increased the expression levels of AtChlase in Arabidopsis (Tsuchiya et al. 1999) and OsNYC1 in rice (Kusaba et al. 2007). Both Chlase and NYC1 promote the conversion of chlorophyll to chlorophyllide.

Interestingly, JA has increased in D. citri-infected plants, in addition, both Chlase and NYC1 were up-regulated. Taken together, these findings support our idea that chlorophyllide might be activated via the JA-mediated pathway in citrus. In addition, chlorophyllide showed toxicity toward fungal and animal cells (Meskauskiene et al. 2001; Kariola et al. 2005) and could be a part of the defense system (Hu et al. 2015).

In addition, the current study demonstrated that the infection with CLas induces zeaxanthin to a higher level in citrus leaves. Zeaxanthin plays a photo-protection role (Niyogi et

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al. 1997; Nayak et al. 2001). In citrus leaves, the increase in zeaxanthin might be a result of enhanced-biosynthesis of β-arm carotenoids; the gene expression of CHYbs was especially upregulated in the presence of CLas. Another reason for the accumulation of zeaxanthin could be due to the conversion of violaxanthin by CitVDE, which was up-regulated in the presence of

CLas (Wu et al. 2014; Sajilata et al. 2008). More importantly, our findings showed that CLas- infection significantly induced ABA accumulation in citrus plants. ABA accumulation presumably due to an increased availability of its precursor, zeaxanthin (Figure 7-2), as well as the up-regulation of gene expression for ABA-biosynthetic genes (CitNSY, CitNCED, CitABA2, and CitAAO3). In other pathosystems, ABA accumulated at a higher level in the infection site of viral (Alazem et al. 2014), fungal (Sánchez-Vallet et al. 2012; Schmidt et al. 2008), and bacterial pathogens (Torres-Zabala et al. 2007; Rosales and Burns 2011), and was associated with tolerance for those pathogens (Torres-Zabala et al. 2007; Bari and Jones 2009; Robert-

Seilaniantz et al. 2007).

The Metabolomic Analysis of Citrus Leaf Extract could Help in Culturing of CLas

The Kyoto Encyclopedia of Genes and Genomes (KEGG) online database showed that

CLas genome sequence obtained through metagenomics revealed a functional tricarboxylic acid

(TCA) cycle (Duan et al. 2009). This functional TCA cycle allows CLas to utilize a wide range of amino acids as energy sources. These include glutamate, alanine, aspartate, glycine, serine, threonine, methionine, cysteine, arginine, proline, histidine, tyrosine, phenylalanine, and tryptophan (Duan et al. 2009; Slisz et al. 2012). In this study, except arginine, all other amino acids listed above have been identified in citrus leaves extract when derivatized with methyl chloroformate (MCF) and may act as the primary source of these amino acids for CLas. While other metabolites, present at lower levels, may restrict pathogen nutrient acquisition (Hijaz et al.

2013, 2016; Albrecht et al. 2016; Killiny and Nehela 2017a). Interestingly, arginine was

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detected only in CLas-infected plants after the derivatization with trimethylsilylation (TMS), whereas it was not detected at all when derivatized with MCF. Furthermore, the reduction of some amino acids (methionine, glutamine, glutamic acid, and lysine) and organic acids (quinic acid and ferulic acid) might be due to CLas, which being a phloem-restricted bacterium may utilize these amino acids, which are found in citrus phloem sap (Hijaz and Killiny 2014), for its growth and reproduction, and/or to inhibit the defense mechanisms of the host plant (Slisz et al.

2012).

The tricarboxylic acid cycle (TCA cycle; aka Krebs cycle or citric acid cycle) has been intensively investigated in many species belonging to both prokaryotes and eukaryotes (Blank and Sauer 2004; Bolton 2009; Cavalcanti et al. 2014; Xiong et al. 2014) due to its importance in energy metabolism. Although there are many studies focused on the metabolic effects of CLas- infection on its vector, the effect of CLas-infection on the energy metabolism, and the TCA cycle metabolic pathway of its host plant is poorly studied. However, we are just beginning to better understand the roles of the TCA cycle in the HLB pathosystem. Previous studies showed that

CLas exploits the energy metabolism and manipulates the TCA cycle of its vector, D. citri for its benefit (Lu and Killiny 2017; Killiny et al. 2017a, 2018; Killiny and Jones 2018), by inducing metabolic changes that can help meet its nutritional needs or to neutralize the host defense responses. Recently, it has been shown that citrate and other TCA-associated intermediates are necessary as energy sources for L. crescens growth on chemically defined media (Cruz-Munoz et al. 2018). Interestingly, previous studies showed that citrate was accumulated in citrus leaves and fruits after CLas infection (Cevallos-Cevallos et al. 2011; Slisz et al. 2012; Killiny and Nehela

2017a). The accumulation of TCA-cycle related OAs might be due to the catabolism of some proteinogenic amino acids (Stipanuk 2006). Generally, glucogenic amino acids are broken down

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into pyruvate, α-ketoglutarate, succinyl CoA, fumarate or oxaloacetate, while ketogenic amino acids are broken down into acetoacetate or acetyl-CoA. Finally, α-ketoglutarate or oxaloacetate act as the amino group acceptor in all amino acid catabolism pathways (Forest and Wightman

1972). Taken together, the findings of this study afford a new insight into the importance of amino acids and TCA-associated intermediates when designing a new chemically defined media.

However, more studies are required to explore the roles of the TCA cycle metabolic pathway in fulfilling the nutritional needs of D. citri and CLas.

204

Figure 7-1. Hypothetical model of the potential role(s) of citrus metabolites in the HLB symptoms development. Briefly, HLB symptoms are induced by both the pathogen and its vector, due to alteration in many physiological aspects such as phytohormones, polyamines, carbohydrate status, and pigments content. The most characteristic symptom of HLB, the blotchy mottle, might are due to the degradation of both chlorophylls and carotenoids. Additionally, ABA could induce the leaf yellowing, which might help the development of the blotchy mottle symptoms. Furthermore, polyamines might be involved in HLB symptom development via the production of H2O2, which may eventually become toxic to the leaf tissue and cause the characteristic blotchy mottle symptoms that appear after CLas-infection. Another characteristic symptom of HLB is the leathery leaves, which could be due to the extensive accumulation of starch grains in the photosynthetic cells, phloem elements, vascular parenchyma and all other parenchyma cells of the HLB-symptomatic leaves. In addition, we suggest that the auxins accumulation, showed in this study, might be involved in the development of leathery leaves symptom via the formation of the thicker cell wall in the photosynthetic cells. Moreover, it is well-known that CLas- infection reduces the production of new flushes on the infected trees. We believe that the reduced new flushes symptom could be due to the phytohormonal imbalance, particularly the auxins/cytokinins ratio. The solid lines with arrows signify positive reaction, the dashed lines with bar-ends indicate negative correlation, and round- dotted lines represent hypothetical mechanisms or uncharacterized elements, with arrows (positive) or bar-ends (negative). For the full names and abbreviations, see the abbreviations list.

205

Figure 7-2. Hypothetical model of the potential role(s) of citrus metabolites in citrus response(s) against the infection with CLas and/or the infestation with D. citri. As a generalized model, citrus plants depend on multi-layered defense responses to mediate the effect of the CLas-infection and/or D. citri-infestation. These defense mechanisms include accumulation of defense molecules, alteration of plant signaling system, changes in primary and secondary metabolites, and other biochemical and physiological modifications. I) In the amino acids-based defense responses, the changes in amino acids might contribute directly to plant defense responses. For example, proline is involved in the induction of glutamine-proline pathway, which is implicated in ROS generation due to the activity of proline dehydrogenase (ProDH) and δ 1-pyrroline-5- carboxylate dehydrogenase (P5CDH). Furthermore, serine and threonine are commonly associated with bio-stress responses in plants, mainly due to the increase in photorespiration and overexpression of peptidases and proteases. In addition, phenylalanine and tryptophan are the precursors of the phytohormone salicylic acid (SA) and auxins, respectively, which are implicated in defense response against biotrophic such as CLas pathogens and plays an important role in the induction of systemic acquired resistance (SAR). In addition, arginine and tyrosine are involved in the II) Polyamines-based putative defense responses, leading to an accumulation of putrescine and its precursor, ornithine, or synephrine and its precursor, octopamine. III) in the phytohormone-based defense responses, CLas-infection might upregulate the expression of auxins-, SAs-, and ABA-biosynthetic genes, while D. citri could induce a higher expression of tJA-biosynthetic genes. The activation of these genes leads to significant accumulation of different phytohormones. The cross-talk between different groups of phytohormones is complicated, and it might be synergistic or antagonistic. IV) The fatty acids-based defense response is thought to be related to the accumulation of α-linolenic acid, the precursor of JA, and involved in the induction of the JA-mediated pathway, which is associated with defense against insect herbivory such as D. citri. V) In the leaf pigments-based defense responses, although both CLas-infection and D. citri-infestation reduced almost all studied leaf pigments, there is a remarkable induction of zeaxanthin (from carotenoids pathway and the precursor of ABA) was increased in CLas-infected plants and could be involved in the activation of citrus response. Likewise, chlorophyllide a (a tetrapyrrole pigment from chlorophylls pathway) was induced to higher levels in D. citri-infested plants, which might be associated with the JA-mediated pathway in citrus. The solid lines with arrows signify positive reaction, the dashed lines with bar- ends indicate negative correlation, and round-dotted lines represent hypothetical mechanisms or uncharacterized elements, with arrows (positive) or bar-ends (negative). For the full names and abbreviations, see the abbreviations list.

206

207

APPENDIX A SUPPLEMENTARY MATERIALS FOR CHAPTER 2

“Phytohormone profiling of the sweet orange (Citrus sinensis (L.) Osbeck) leaves and roots using GC-MS-based method”

Figure A-1. GC-MS-SIM chromatograms of detected phytohormones in Valencia sweet orange leaves, roots, and root tips. (A) auxins, salicylates, jasmonates and abscisic acid after MCF derivatization of 20 ppm standards mixture, or in real sample of Valencia sweet orange leaves (B), and roots (C); while, (D) cytokinins and gibberellins after MSTFA derivatization of 20 ppm standards mixture, or in real sample of Valencia sweet orange leaves (E), and roots (F); peaks numbers refer to the numbers listed in Table 1-1.

208

Figure A-2. Mass spectra for salicylates group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF. For the full names and abbreviations, see the abbreviations list.

209

Figure A-3. Mass spectra for auxins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF. For the full names and abbreviations, see the abbreviations list.

210

Figure A-4. Mass spectra for jasmonic acid and abscisic acid obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MCF. For the full names and abbreviations, see the abbreviations list.

211

Figure A-5. Mass spectra for cytokinins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MSTFA. For the full names and abbreviations, see the abbreviations list.

212

Figure A-6. Mass spectra for gibberellins group obtained using GC-MS from standards mix (200 ppm) in Full Scan mode or from Valencia sweet orange leaves or roots in SIM-mode after derivatization using MSTFA. For the full names and abbreviations, see the abbreviations list.

213

APPENDIX B SUPPLEMENTARY MATERIALS FOR CHAPTER 3

"Multiple phytohormonal signaling mediates citrus responses to Candidatus Liberibacter asiaticus and its vector Diaphorina citri"

Figure B-1. Total profile of different phytohormones compounds detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with ACP using GC-MS-SIM. Asterisks indicate statistically significant differences among the studied treatments at p<0.01(**) or p<0.05 (*), while “ns” indicate no significant differences between them (p<0.05). For the full names and abbreviations, see the abbreviations list.

214

Table B-1. Concentrations of different gibberellins and cytokinins compounds (ng g-1 FW) detected in Valencia sweet orange (C. sinensis) leaves after the infection with CLas and/or the infestation with D. citri using GC-MS-SIM. Compound Control CLas-infected D. citri-infected Double-attacked p-value

Gibberellins GA3 34.7±5.7 a 22.9±0.7 b 28.7±5.2 ab 29.0±3.4 ab 0.0044 GA4 14.5±0.1 ns 14.4±0.1 ns 14.4±0.1 ns 14.4±0.1 ns 0.5317 GA7 110.3±19.6 ns 134.4±20.1 ns 144.7±28.1 ns 131.0±26.7 ns 0.1853 Total 159.4±22.9 ns 171.6±20.7 ns 187.7±33.4 ns 174.3±29.7 ns 0.4559

Cytokinins tZ 14.4±0.1 ns 14.7±0.3 ns 14.5±0.4 ns 14.5±0.2 ns 0.6546 tZR 13.8±0.0 ns 13.9±0.1 ns 14.0±0.3 ns 13.9±0.2 ns 0.3685 Total 28.2±0.1 ns 28.6±0.4 ns 28.6±0.5 ns 28.4±0.2 ns 0.3556 All phytohormones were extracted in methanol and derivatized with MSTFA (n=10). Different letters indicate statistically significant differences among treatments, while “ns” signify no significance differences between them (p<0.05). For the full names and abbreviations, see the abbreviations list.

215

Table B-2. Primer used for gene expression analysis of trans-jasmonic acid biosynthetic genes by real-time RT-PCR a. Primer TM Amplicon size Gene Accession ID (Forward and Reverse) (°C) (bp) CitFAD XM_006480990.2 F CAGATCCCGCATTACCACTT 59.96 203 R GAAGAGCCGTTAAGCTGTGG 60.02 CitLOX XM_006483993.1 F TGGCTGTCCAAGACACTCTG 60.02 198 R CAGCACCACATCTGCCTTTA 59.86 CitAOS NM_001288906.1 F GTTTCAGCTCGCTCCGTTAC 60.02 199 R GAGGTTGTGACACGCTTCCT 60.31 CitAOC NW_006260521.1 F GCGAGTGGGAATTACAGCAG 60.80 201 R TTAACCTGCCCACTCACTCC 60.11 CitAAE7 XM_006488806.2 F CCACCAGAGGACACAATCCT 59.96 201 R CTGAGCTTCGAAAGGGAGTG 60.13 CitOPR3 XM_006475468.2 F ATGGTGCTGATTTGGTAGCC 59.96 200 R ACCCACTCAAAGGCGTGATA 60.52 CitACX1 XM_006477083.2 F CCATACTGGAGGCCTTTGAA 60.07 199 R ACCCCCTTTCCTGGTATGTC 60.05 CitAIM1 XM_006488772.2 F TAATCCTCGTGACCCGAGAC 60.07 203 R CTCTGCTGACGTCAAATCCA 59.98 CitAIM2 XM_006473681.2 F CGATCTATGCCTTGGGTGTT 59.96 203 R TTGTCCATGCAGCAAAAGTC 59.85 CitKAT XM_006480138.2 F AAAGGATGGGACGACAACTG 59.97 198 R GACTTCACCGCAGCAGGTAT 60.29 CitEF-1α b AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box b XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 b XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND b XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on the literatures (Itoh and Izawa, 2011; Lahey et al., 2004; Quecini et al., 2007) and recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b.

Abbreviations CitFAD: ω-3 fatty acid desaturase CitLOX: lipoxygenase CitAOS: allene oxide synthase CitAOC: allene oxide cyclase CitOPR3: 12-oxophytodienoate reductase 3 CitAAE7: acetate/butyrate-CoA ligase AAE7 CitACX1: acyl-coenzyme A1 CitAIM1: probable enoyl-CoA hydratase, mitochondrial-like CitAIM2: enoyl-CoA hydratase 2, peroxisomal-like CitKAT: 3-ketoacyl-CoA thiolase , peroxisomal-like CitEF-1α: Citrus sinensis elongation factor-1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1(also known as GAPDH) CitSAND: Citrus sinensis SAND family protein

216

Table B-3. Primer used for gene expression analysis of abscisic acid biosynthetic genes by real- time RT-PCR a. Primer TM Amplicon Gene Accession ID (Forward and Reverse) (°C) size (bp) CitZEP XM_006466537.2 F GGTTTCGTCCGTCAGACACT 60.16 204 R TAGTGCGCCAATAAATGCTG 59.86 CitVDE NM_001288881.1 F GGGAATTTCCTGTCCCTGAT 60.13 203 R GGTGAAAAAGCCACCATCTG 60.50 CitNSY NM_001288932.1 F TACCGTATGTCGTGCTTGGA 60.13 209 R ATCCTGGAAAACATGGCTTG 59.93 CitNCED NM_001288935.1 F ATGGCGGCAGCAACTACTAC 60.30 199 R CTGCAGGTGATGGAGGGTAT 59.95 CitABA2 NM_001288867.1 F GGCCAAAGTGCTACAAGCTC 60.02 206 R TGACAGACCTGCTGACCAAG 60.02 CitAAO3 XM_006487736.2 F TGCCAGATGAAGACAACTGC 59.99 210 R CTGGGCGGCATAACTTGTAT 59.98 CitEF-1α b AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box b XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 b XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND b XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on the literatures (Itoh and Izawa, 2011; Lahey et al., 2004; Quecini et al., 2007) and recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b.

Abbreviations CitZEP: zeaxanthin epoxidase CitVDE: violaxanthin de-epoxidase CitNSY: neoxanthin synthase CitNCED: 9-cis-epoxycarotenoid dioxygenase 3 CitABA2: short-chain alcohol dehydrogenase CitAAO3: abscisic aldehyde oxidase CitEF-1α: Citrus sinensis elongation factor-1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (also known as GAPDH) CitSAND: Citrus sinensis SAND family protein

217

Table B-4. Primer used for gene expression analysis of salicylates biosynthetic genes by real- time RT-PCR a. Primer TM Amplicon size Gene Accession ID (Forward and Reverse) (°C) (bp) CitCS XM_006485798.2 F ACTGGAACACCCATCCATGT 60.10 191 R ACAGCTCCTGGTGCAACTCT 60.06 CitCM2 XM_006483415.2 F GCGAAAAGTCCCCACTAACA 60.11 202 R CTTCCTCTGGGCTGAATGTC 59.80 CitCM3 XM_006482655.2 F GGAGCTGATCCCGTTTACAA 60.07 199 R CTGAAGCACCGTGTAAGCAC 59.51 CitADT1 XM_006467360.2 F CACTCCTGTTGAGGACGACA 59.86 197 R CACCTGGTAAGCCCTGGTAA 59.99 CitTAT XM_006469841.1 F GGTCAATTGTGCCTGTCCTT 59.97 199 R TCGAGGATTTGAGGAACTGC 60.34 CitAST-1 XM_006476023.2 F GGTTGAGAGCCAGCTGAAAC 60.00 196 R AGGTGGCAATTCGATCAGTC 60.08 CitAST-2 XM_006476024.2 F CTCAGCAACTGATCGCAGAC 59.73 200 R CCGGACTTGGATCCTTGTTA 59.93 CitPAL XM_006481431.2 F GGGGATCTGGTTCCTCTTTC 59.87 198 R CATAGAAGCCAGGCCAGAAC 59.84 CitAAT1 NM_001288910.1 F CACCTTGCCCGTATTTGAAC 60.37 195 R CACGTGCCATGTCCTCTATG 60.14 CitKAT XM_006489736.1 F GAAGGAGCAAGACCAAGCAG 60.13 200 R GCTTCAACTTCGCCAACTCT 59.62 CitICS2 XM_006476586.2 F TAGCGCGTAGCAGCAGAGTA 60.08 208 R CTACCACGGGTTCCAGCTAA 60.12 CitEF-1α b AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box b XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 b XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND b XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on the literatures (Itoh and Izawa, 2011; Lahey et al., 2004; Quecini et al., 2007) and recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b. Abbreviations CitCM3: chorismate mutase 3 CitCM2: chorismate mutase 2 CitADT1: Arogenate dehydratase/prephenate dehydratase 1, chloroplastic CitTAT: tyrosine aminotransferase CitAST-1: aspartate aminotransferase, cytoplasmic-like CitAST-2: aspartate aminotransferase, chloroplastic-like CitPAL: phenylalanine ammonia-lyase CitAAT1: alcohol acyl transferase CitKAT: 3-ketoacyl-CoA thiolase 2 CitICS2: isochorismate synthase 2 CitEF-1α: Citrus sinensis elongation factor-1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (also known as GAPDH) CitSAND: Citrus sinensis SAND family protein

218

Table B-5. Primer used for gene expression analysis of auxins biosynthetic genes by real-time RT-PCR a. Primer TM Amplicon size Gene Accession ID (Forward and Reverse) (°C) (bp) CitASA1 XM_015532734.1 F CTCCACGATTACGGGTGAGT 59.99 200 R CCAGGGCAATGTCCATATCT 59.77 CitASA2 XM_006469235.2 F CATTGGAGAGGCTTTTGGAG 59.81 197 R CTGTAACTTCCAGCGCATCA 60.01 CitTS XM_006482255.1 F GCAGATGGAGGCTGTAGGAG 59.97 201 R CCTGCGGTATCACCAAAATC 60.33 CitTSA XM_006470948.2 F TTTACAGGTCCCACCACTCC 59.82 212 R ACTTGTTGCACATGCTCAGG 59.90 CitTSB XM_006493882.2 F ACATCGAATTCCTCGCAGTC 60.23 204 R TAGCGTCTCAGGGACGAACT 60.01 CitTAA2 XM_015529685.1 F TGAGAATGGCAGTGCAAAAG 59.99 207 R TCGGACTAAACCCAAAGTGC 60.11 CitTAA4 XM_006473060.2 F CCCCTGCTGATGAAGAACTC 59.80 202 R CCTCCGTCCTCAAGCACTAC 59.87 CitTDC1 XM_006479363.2 F GCTCAGTGCTGGTCTCAACA 60.19 203 R CCTTATCACGAGCAGCCAAT 60.24 CitYUC2 XM_006466708.2 F CTGGCCCTGTAATTGTTGGT 59.85 194 R ACGAGGGAATGGCACATAAG 59.96 CitYUC8 XM_006480095.2 F CTACAGGGTACCGCAGCAAT 60.15 202 R TCTTTCCAGACCTTGCCAAT 59.67 CitNIT4 XM_006487697.2 F GTTCTGGCAGGACCCAACTA 60.11 200 R CACAGGCCACCTTCAGTTTT 60.15 CitEF-1α b AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box b XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 b XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND b XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on the literatures (Itoh and Izawa, 2011; Lahey et al., 2004; Quecini et al., 2007) and recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b. Abbreviations: CitCS: chorismate synthase CitASA1: anthranilate synthase alpha subunit 1 CitASA2: anthranilate synthase beta subunit 2 CitTS: tryptophan synthase-like CitTSA: tryptophan synthase alpha chain, chloroplastic-like CitTSB: tryptophan synthase beta chain 1, chloroplastic-like CitTAA2: tryptophan aminotransferase-related protein 2-like CitTAA4: tryptophan aminotransferase-related protein 4-like CitTDC1: tyrosine decarboxylase1 CitYUC2: indole-3-pyruvate monooxygenase YUCCA2 CitYUC8: indole-3-pyruvate monooxygenase YUCCA8 CitNIT4: bifunctional nitrilase/nitrile hydratase NIT4A-like CitEF-1α: Citrus sinensis elongation factor-1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (also known as GAPDH) CitSAND: Citrus sinensis SAND family protein

219

APPENDIX C SUPPLEMENTARY MATERIALS FOR CHAPTER 4

“One target, two mechanisms: The impact of Candidatus Liberibacter asiaticus and its vector, Diaphorina citri on citrus leaf pigments”

Table C-1. Primer used for gene expression analysis of carotenoids-biosynthetic enzymes by real-time RT-PCR a. Primer TM Product size Gene Accession ID (Forward and Reverse) (˚C) (bp) CitPYS -1 DQ235260.1 F ATGGGCATAGCACCTGACTC 60.10 200 R ATGGTCACCTCTCCAGCAAA 60.66 CitPYS -2 AB114656.1 F GGCATAGCACCTGACTCACA 59.86 198 R AATGGTCACCTCTCCAGCAA 60.66 CitPYS -3 AY669084.1 F TCGACATTCAGCCATTCAGA 60.35 207 R CAATCCCTAGTGCCAATGCT 60.10 CitPDS -1 AJ319761.1 F GTCAAAACGCCAAGGTCTGT 60.16 197 R GCAGCAAGCAGCACATAGTC 59.78 CitPDS -2 AB114657.1 F GTTCTTCCAGCTCCGCTAAA 59.59 199 R CCTCTGTCGTCACTCGATCA 59.98 CitPDS -3 AY669082.1 F CTGCTGATCAGAGCAAAGCA 60.44 191 R CCCTGACAAAACAGCACCTT 60.15 CitPDS -4 DQ235261.1 F GGACGGGAACTGGTATGAGA 59.93 206 R TGGCCAATATCCCATTTAGC 59.76 CitZDS -1 AJ319762.1 F ACAGAGAAGGGCAAGGTTCA 59.84 199 R TCTTTACCAGGTCCCTCACG 60.10 CitZDS -2 AB114658.1 F GATCCTGATGGAGCCTTGAA 60.16 202 R CCTCGGTCTTAGTCGCAAAC 59.88 CitZDS -3 AY669083.1 F GGGCAAGGTTCATTACTCCA 59.93 198 R GGAGGGGTTTTTACCAGGTC 59.67 CitLCYe -1 AY533827.1 F GGATATTGAGGGCATCAGGA 59.85 196 R CATAGTTGCTCCCGTTGGAT 59.96 CitLCYe -2 AF450280.1 F GGTCCCAAAGTTTCTGTCCA 59.94 207 R CGATGCCAAACAAGTTTCCT 60.11 CitLCYe -3 AB114663.1 F GTGGAGGTTGAGGTGGAAAA 59.94 183 R ACCATCTTTCGATGCCAAAC 59.94 CitLCYe -4 AY552466.1 F TGATTGGTCGTGCTTATGGA 60.07 203 R TCCAATAGCTTCCCTGATGC 60.18 CitLCYb AY094582.1 F CCAGGAAAGAATGGTGGCTA 60.07 197 R TAGGAGCCGCAGCTAAAGTC 59.75 CitCHYb -1 DQ228870.1 F AGCCCTTCTGTCTCCTCACA 59.99 199 R TCCTCGTCCGTGAAAGTCTC 55.00 CitCHYb -2 AB114661.1 F TCTCTCTGTTGGTGCTGCTG 60.33 203 R CAAGGCCTTTGTGGAAGAAG 59.85 CitCHYb -3 AY533828.1 F AAGCTCTGTGGCATGCTTCT 60.16 193 R AACACCGTAATGCCAAGTCC 59.86 CitCHYb -4 AY623047.1 F TGTTCTCTCTGCTGGTGCTG 60.33 201 R CCTTTGTGGAAGAAGCCAAA 60.22 CitZEP -1 AB548572.1 F GCCGTTGTGCTTCTAGGTTC 59.88 203 R CGATCACCTTAACCCGAAAA 59.93

220

Table C-1. Continued Gene Accession ID Primer TM Product size (Forward and Reverse) (˚C) (bp) CitZEP -2 AB548573.1 F GTGATGGGAACTCCTCCAAA 59.90 202 R GTGCTGTGCTCGCTACTCTG 59.95 CitZEP -3 AF437874.1 F AAGGAACCAGCAGGTGGAGT 61.08 195 R CGAGTCCCCAAGCAAAGTAA 60.24 CitZEP -4 AB114662.1 F CATTTCACAAGGAACCAGCA 59.69 203 R CGAGTCCCCAAGCAAAGTAA 60.24 CitVDE NM_001288881.1 F GGGAATTTCCTGTCCCTGAT 60.13 203 R GGTGAAAAAGCCACCATCTG 60.50 CitCCSb AF169241.1 F TACTCCGATTCTGGGAATGC 60.04 199 R TCTGGCCGGTCTTGTAACTC 60.25 CitNSY HM036683.1 F TACCGTATGTCGTGCTTGGA 60.13 209 R ATCCTGGAAAACATGGCTTG 59.93 CitNCED JN794601.1 F ATGGCGGCAGCAACTACTAC 60.30 199 R CTGCAGGTGATGGAGGGTAT 59.95 CitABA2 HM036684.1 F GGCCAAAGTGCTACAAGCTC 60.02 206 R TGACAGACCTGCTGACCAAG 60.02 CitAAO3 HM036685.1 F GGAAGATAACAGCCCTGCAA 60.21 197 R TGACCCCTGTACCTCTCCAG 60.10 CitEF1c AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box c XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 c XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND c XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b CCS gene has been renamed LCYb2 (chromoplast-specific lycopene cyclase beta) by Alquezar et al. (2009) c Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b. Abbreviations CitPYS: Phytoene synthase CitPDS: Phytoene desaturase CitZDS: ζ-Carotene desaturase CitLCYe: Lycopene ε-cyclase CitLCYb: Lycopene β-cyclase CitCHYb: Carotenoid hydroxylase β-ring CitZEP: Zeaxanthin epoxidase CitVDE: Violaxanthin de-epoxidase CitCCS: Capsanthin/capsorubin synthase CitNSY: Neoxanthin synthase CitNCED: Putative 9-cis-epoxycarotenoid dioxygenase 3 CitABA2: Short-chain alcohol dehydrogenase CitAAO3: Abscisic aldehyde oxidase CitEF1: Citrus sinensis elongation factor 1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic CitSAND: Citrus sinensis SAND family protein

221

Table C-2. Primer used for gene expression analysis of chlorophylls-biosynthetic enzymes by real-time RT-PCR a. Primer TM Product size Gene Accession ID (Forward and Reverse) (˚C) (bp) CitGluTR XM_006472322.1 F CACCTGTTGAGATGCGAGAA 59.98 202 R GGGATCCCACTTGTCTTTGA 59.90 CitGSAT XM_006493185.1 F GCTGGATCCTCTCGCTGTAG 60.12 200 R CACATGTGTGAGCCCTTGAC 60.16 CitALA XM_006472731.1 F CGACGAAGAAGCTTGGAATC 59.96 194 R TGTTTCCTGGAAGGATGCTC 60.20 CitPPO XM_006469957.1 F GCAGCACCCTCTGACTTCTC 60.14 200 R CCCTCCAGCTCTTTCATCAG 59.94 CitPPO1 XM_006492368.1 F TACCCCTCAAACTTCGATGC 60.07 205 R CGATCTCTAGCCTCGGTGAC 59.97 CitDVR XM_006489088.1 F TAGGGGGTCAGGTTGAGTTG 59.96 200 R CTCCCCTTGCTCTAATGGTG 59.69 CitPOR XM_006464654.1 F ACCCATCAAAGCGTCTCATC 60.08 198 R TGTTGCAGACTTTGCTGTCC 60.03 CitChlG XM_006481001.1 F TGCCACGTTTCCATACAAAA 59.97 204 R GAACTGAAGCGAAGGTGGAG 59.99 CitCAO XM_006472723.1 F TTTTGCACCTGTGCTCAAAC 59.89 197 R TCTCCAAAGCGTCTCTCCAT 59.95 CitNOL XM_006485465.1 F TGATGGAGCAGGTTCTGATG 59.79 200 R TGGCCTGCTTTGTAGTAGCA 59.63 CitNYC1 -1 XM_006475562.1 F GACGAGGACGTTGGTTTGAT 59.97 199 R GTGTTGCTACCTGTGCTGGA 59.90 CitNYC1 -2 XM_006475626.1 F TCTCTGCACTCGTGAGGCTA 59.88 198 R GCTGTATGCACCCCAACTTT 60.00 CitChlase -1 NM_001288890.1 F GGCCACACTTCCGGTATTTA 59.82 206 R GGGACGCTATGTGGTCAAAG 60.52 CitChlase -2 AF160869.1 F CACCTGAAGGAGCAAACCAT 60.11 206 R CACCACAATCCCACTCACAC 59.85 CitChlase1 -1 XM_006494861.1 F GAACTCCCGGAAAATGTTGA 59.91 198 R GAGAATCGGGGGTTCAAGTT 60.31 CitChlase1 -2 XM_006478070.1 F CCGTCTCCGTTGAAGCTAAG 60.01 206 R GCTTGTGTTGCTGAGAGCAG 59.93 CitChlase2 XM_006489380.1 F ACAAGCTCCACTCCACTTCC 59.30 200 R TCTGGTCCAGCCACATTGTA 60.11 CitEF1b AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box b XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 b XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND b XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b.

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Abbreviations CitGluTR: Glutamyl-tRNA reductase 1, chloroplastic-like CitGSAT: Glutamate-1-semialdehyde 2,1-aminomutase, chloroplastic-like CitALA: δ-Aminolevulinic acid dehydratase 1, chloroplastic-like CitPPO: Protoporphyrinogen oxidase, chloroplastic/mitochondrial-like CitPPO1: Protoporphyrinogen oxidase 1, chloroplastic-like CitDVR: Divinyl chlorophyllide a 8-vinyl-reductase, chloroplastic-like CitPOR: Protochlorophyllide reductase, chloroplastic-like CitChlG : Chlorophyll synthase, chloroplastic-like CitCAO: Chlorophyllide a oxygenase, chloroplastic-like CitNYC1: Chlorophyll(ide) b reductase -NON-YELLOW COLORING 1 (NYC1), chloroplastic-like CitNOL: Chlorophyll(ide) b reductase -NYC1-Like (NOL), chloroplastic-like CitChlase: chloroplast chlorophyllase CitChlase1: chlorophyllase-1, chloroplastic-like CitChlase2: chlorophyllase-2, chloroplastic-like CitEF1: Citrus sinensis elongation factor 1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic CitSAND: Citrus sinensis SAND family protein

223

APPENDIX D SUPPLEMENTARY MATERIALS FOR CHAPTER 5

“Metabolomic response to Huanglongbing: Role of carboxylic compounds in Citrus sinensis response to Candidatus Liberibacter asiaticus and its vector, Diaphorina citri”

Table D-1. Identification and the quantification equations of different carboxylic compounds detected in Valencia sweet orange (C. sinensis) leaves in full-scan GC-MS. Compounds RT a LRI b Constituent Ion m/z (relative abundance) c Quantification equation R2 Amino acids Glycine 7.50 1116 59(80), 83(30), 88(100) y = 181042 x + 127989 0.9992 L-Alanine 7.50 1116 59(80), 88(95), 102(100) y = 529868 x + 322672 0.9972 L-Valine 9.61 1286 98(30), 115(25), 131(100) y = 36995 x + 7943.3 0.9987 L-Leucine 10.80 1382 88(100), 102(25), 144(96) y = 495484 x + 483403 0.9986 γ-Aminobutyric acid 10.97 1396 88(83), 102(100), 112(50) y = 9038.9 x + 12762 0.9993 L-Isoleucine 10.98 1397 88(83), 115(63), 144(100) y = 533209 x + 206553 0.9950 L-Threonine 11.09 1406 59(92), 100(20), 115(100) y = 389691 x - 180682 0.9918 L-Proline 11.43 1433 59(30), 82(24), 128(100) y = 650765 x + 650546 0.9990 L-Asparagine 11.52 1440 56(92), 59(55), 127(100) y = 107492 x + 77695 0.9941 L-Aspartic acid 12.43 1514 118(37), 128(55), 160(100) y = 276673 x + 673870 0.9928 L-Pyroglutamic acid 13.06 1564 57(92), 191(100), 206(12) y = 10778 x + 19288 0.9987 L-Serine 13.31 1584 59(72), 69(20), 100(100) y = 33830 x + 56918 0.9976 L-Glutamine 13.84 1627 69(30), 88(90), 141(100) y = 34550 x - 68068 0.9825 L-Glutamic acid 13.96 1637 114(100),142(70),174(96) y = 193365 x + 172011 0.9990 L-Methionine 14.12 1650 115(100), 147(70) y = 298088 x + 544221 0.9941 L-Cysteine 15.15 1733 132(75), 146(60), 176(90), 192(100) y = 57203 x + 60274 0.9988 L-Phenylalanine 15.43 1755 91(97), 146(50), 162(100) y = 329918 x + 232658 0.9933 Tyramine 18.35 1991 88(100), 121(30), 134(27), 178(50) y = 303393 x + 271674 0.9981 L-Lysine 18.58 2009 88(30), 101(20), 142(100) y = 203579 x + 596101 0.9884 L-Histidine 19.13 2054 140(50), 210(92), 226(30) y = 6937.8 x + 11350 0.9938 L-Tyrosine 20.12 2133 121(100), 165(30), 236(44) y = 420242 x + 545515 0.9972 L-Tryptophan 21.76 2266 77(15), 130(100), 276(10) y = 457280 x + 353415 0.9994 Fatty acids Palmitic acid (C16:0) 17.74 1942 74(100), 87(82), 270(20) y = 5789079 x - 102256 0.9891 α-Linolenic acid (C18:3) 19.31 2068 55(76), 79(100), 292(9) y = 5537.9 x + 8820.2 0.9993 Linoleic acid (C18:2) 19.36 2072 67(100), 81(97), 294(10) y = 4697164 x + 4303901 0.9991 Oleic acid (C18:1) 19.43 2078 55(100), 69(80), 296(8) y = 5284226 x + 11133454 0.9892 Stearic acid (C18:0) 19.67 2097 74(100), 87(80), 298(12) y = 6184424 x + 6765060 0.9910

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Table D-1. Continued

Compounds RT a LRI b Constituent Ion m/z (relative abundance) c Quantification equation R2

Organic acids Benzoic acid 8.66 1210 77(51), 105(100), 136(30) y = 181678 x + 92054 0.9996 Fumaric acid 9.19 1252 59(38), 85(46), 113(100), 144(10) y = 1904.2 x + 1988.2 0.9990 Succinic acid 9.29 1260 59(70), 113(41), 115(100) y = 13301 x + 6250.5 0.9995 Malic acid 11.57 1444 59(100), 75(70), 117(44), 188(10) y = 180476171 x + 1641576 0.9997 Quinic acid 12.13 1489 59(100), 125(40), 153(90), 184(67) y = 70667 x + 130546 0.9878 Citric acid 12.60 1527 59(40), 101(80), 143(100), 175(20) y = 647415 x + 2E+06 0.9905 Salicylic acid 13.76 1621 77(15), 107(12), 135(100), 210(18) y = 780.94 x + 656.73 0.9993 t-Jasmonic acid 14.45 1676 82 (27), 83 (100), 153 (25), 156 (33) y = 15750 x + 47512 0.9970 Ferulic acid 17.95 1958 59(100), 191(78), 222(68), 266(66) y = 10742 x + 11980 0.9996 a RT: Retention time. b LRI: Linear retention index, was calculated using a calibration curve generated by injecting a mixture of alkanes (C12–C26) on a ZB-5MS capillary GC column (Phenomenex, Torrance, CA, USA), under the same chromatographic conditions as samples, equation was LRI = (80.6 × RT) + 511.7, R² = 0.9968. c The constituent Ion (m/z) were obtained from the mass spectra of authentic standards.

225

Table D-2. Primer used for gene expression analysis of Jasmonic acid, salicylic acid, and proline-glutamine pathways by real-time RT-PCR*. Primer TM Product Gene Accession ID (Forward and Reverse) (˚C) size (bp) CitFAD -1 a XM_006480990.1 F CAGATCCCGCATTACCACTT 59.96 203 R GAAGAGCCGTTAAGCTGTGG 60.02 CitFAD -2 a XM_006488479.1 F TGGGGTTGTTGAGAAAGGAG 60.08 200 R GAGGCCAAAAGAACCAAGTG 59.71 CitLOX1.5 -1 a XM_006471965.1 F CACGGCCTTCGTTTACTGAT 60.13 200 R CAGGGCTCGTCTTTCTTGTC 59.99 CitLOX1.5 -2 a XM_006471966.1 F GGGGTCACGTCATAAGTGCT 60.00 204 R CGGAACTCCAATGTCCTCAT 59.93 CitLOX1.5 -3 a XM_006489302.1 F CCTCCTTGGTGTATCCCTCA 59.92 203 R CAGCCCCAACTCTGTTCTTC 59.84 CitLOX1.5 -4 a XM_006492157.1 F TTGAGGGGAGATGGTATTGG 59.74 197 R ATCCAAGCCAGGTCATTGTC 59.93 CitLOX1.5 -5 a XM_006492158.1 F TGAGGGGAGATGGTATTGGA 60.27 196 R ATCCAAGCCAGGTCATTGTC 59.93 CitLOX2.1 -1 a XM_006494208.1 F GTATGGGTCCCGCACTGTAT 59.70 199 R CTGGTGATAGCCCGAATCAT 59.92 CitLOX2.1 -2 a XM_006494210.1 F GAAGAGCTCCGAAGTTGGTG 59.99 197 R GGCCTGTTAGGGAAATAGCC 59.93 CitLOX2.1 -3 a XM_006494223.1 F CTTCCCGGATTTGTTGAAGA 60.04 198 R GATTTTTGGGTCGAGTGAGC 59.68 CitLOX2.1 -4 a XM_006494224.1 F CGGGATCAGAGAAAACAACC 59.53 202 R TGACGTACTCCACGTCCATC 59.55 CitLOX2.1 -5 a XM_006494209.1 F AATTGGAGGCTCGATGACTG 60.22 197 R GAGGCCGAGTTAGCTCAATG 59.98 CitLOX2.1 -6 a XM_006494211.1 F CTGGATACGCTGTCGACTCA 60.01 207 R CAAGAGCTCATATGGCACGA 59.97 CitLOX3.1 a XM_006465842.1 F GACGAAAATGACCCCGAGTA 59.93 199 R ATGCCTCGGTTATCTCACCA 60.48 CitLOX6 a XM_006483993.1 F TGGCTGTCCAAGACACTCTG 60.02 198 R CAGCACCACATCTGCCTTTA 59.86 CitAOS -1 AY243478.1 F CACGTGCTTCAATTCATTCG 60.26 200 R TACGCAGCACTTCGTACACC 59.93 CitAOS -2 a XM_006473347.1 F GTTTCAGCTCGCTCCGTTAC 60.02 199 R GAGGTTGTGACACGCTTCCT 60.31 CitAOS -3 a XM_006479287.1 F CATGCCTCCTGGTCCTTTTA 60.07 199 R AGACGAATGTTTGGGCTCAG 60.25 CitAOC3 a XM_006484352.1 F CCGGCAATTCTGAAGCTAAG 59.97 205 R TGTGACCGTAGTCACCGAAG 59.74 CitAOC4 -1 a XM_006495410.1 F GCGAGTGGGAATTACAGCAG 60.80 201 R TTAACCTGCCCACTCACTCC 60.11 CitAOC4 -2 a XM_006482231.1 F CTGGAGACCTGCAAAAGAGG 59.98 212 R CCCATACACTCCCTCGAAGA 60.07

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Table D-2. Continued Primer TM Product Gene Accession ID (Forward and Reverse) (˚C) size (bp) CitAOC4 -3 a XM_006482230.1 F AAGCGAGTGGGAATTACAGC 59.34 203 R TTAACCTGCCCACTCACTCC 60.11 CitOPR3 a XM_006475468.1 F ATGGTGCTGATTTGGTAGCC 59.96 200 R ACCCACTCAAAGGCGTGATA 60.52 CitPAL -1 a XM_006481431.1 F GGGGATCTGGTTCCTCTTTC 59.87 198 R CATAGAAGCCAGGCCAGAAC 59.84 CitPAL -2 a XM_006481430.1 F AGGGGATCTGGTTCCTCTGT 59.93 199 R CATAGAAGCCAGGCCAGAAC 59.84 CitPAL -3 a XM_006488000.1 F TGTTCCGAGCTCCAGTTTCT 59.99 198 R ATTCTCCTCCAAGTGCCTCA 59.80 CitPAL -4 a XM_006485585.1 F GACCTGGTCCCACTCTCGTA 60.11 200 R GTGGCAGCTAAACCAGAACC 59.74 CitICS -1 a XM_006476586.1 F TAGCGCGTAGCAGCAGAGTA 60.08 208 R CTACCACGGGTTCCAGCTAA 60.12 CitICS -2 a XM_006476587.1 F AAATCCAACCCACCTCCATT 60.42 200 R TTGTGGGTGACTGAGCTTTG 59.87 CitICS -3 a XM_006476588.1 F TGGCTTCTCTTCACCCAAGT 59.84 198 R CGGCATATATCAATGCACCA 60.32 CitProDH a XM_006482264.1 F TTGCAGGGATTTCTCCAAAC 60.05 200 R CTGCAATCCGAGAAAAGAGG 59.95 CitP5CDH -1 a b XM_006476581.1 F TGCCAAAGGTCTCCAATTTC 60.05 205 R GGACCATAAGGCCAACGATA 59.78 CitP5CDH -2 a b XM_006476582.1 F CTCGGCGAGGTTCAAGTTAC 59.88 201 R CGCACCCATCAACTGAAGTA 59.72 CitLHT1 -1 a XM_006469921.1 F TTCTGTCCACAAGGGAAAGC 60.23 202 R GACAACTCCCCTCCACATTG 60.36 CitLHT1 -2 a XM_006469922.1 F CTTCAGTTCGCCCCTGTCTA 60.39 202 R CCATGGCAGTAACATTGTGG 59.84 CitLHT1 -3 a XM_006476924.1 F GTCTCCCGTATGCCATGTCT 59.96 210 R CCAACAGTTGCTGGGGTACT 60.03 CitLHT1 -4 a XM_006469920.1 F TTGAAGTCGGTGTGTGCATT 60.16 200 R CATAACTGCAGCTGCCAAAG 59.63 CitEF-1α c AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CitF-box c XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CitGAPC1 c XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CitSAND c XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93

* The listed genes were assembled based on recently available data in national center for biotechnology information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). a CitP5CDH also known as ALDH12A1 in Arabidopsis. b Predicted gene based on recent available data in NCBI (http://www.ncbi.nlm.nih.gov/gene/) c Genes have been used as reference genes for data normalization according to Mafra et al., 2012; Wei et al., 2014a and Wei et al., 2014b.

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Abbreviations CitFAD: ω-3 Fatty acid desaturase, chloroplastic-like CitLOX1.5: Probable linoleate 9S-lipoxygenase 5-like CitLOX3.1: Linoleate 13S-lipoxygenase 3-1, chloroplastic-like CitLOX6: Lipoxygenase 6, chloroplastic-like CitLOX2.1: Linoleate 13S-lipoxygenase 2-1, chloroplastic-like CitAOS: Allene oxide synthase CitAOC3: Allene oxide cyclase 3, chloroplastic-like CitAOC4: Allene oxide cyclase 4, chloroplastic-like CitOPR3: 12-Oxophytodienoate reductase 3-like CitPAL: Phenylalanine ammonia-lyase-like CitProDH: Proline dehydrogenase 1, mitochondrial-like CitP5CDH: δ-1-Pyrroline-5-carboxylate dehydrogenase 12A1, mitochondrial-like CitLHT1: Lysine histidine transporter 1-like CitICS: Isochorismate synthase, chloroplastic-like CitEF-1α: Citrus sinensis elongation factor-1 alpha CitF-box: Citrus sinensis F-box/kelch-repeat protein At5g15710 CitGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (aka GAPDH) CitSAND: Citrus sinensis SAND family protein

228

APPENDIX E SUPPLEMENTARY MATERIALS FOR CHAPTER 6

“Candidatus Liberibacter asiaticus and its vector, Diaphorina citri, augments the TCA cycle of their host via the GABA shunt and polyamines pathway”

Table E-1. Identification of different non-proteinogenic amino acids (NPAAs), polyamines (PAs), TCA-associated compounds and some proteinogenic amino acids (PAAs) detected in Valencia sweet orange (C. sinensis) leaves using GC-MS.

Standard RT a LRI b Constituent Ion m/z (relative abundance) c

NPAAs and PAs compounds α-amino butyric acid d 10.20 1333.82 59 (50) 72 (30) 116(100) 117 (28) 146(15) β-aAlanine d 10.35 1345.91 88(70) 101(100) 102(30) 130(35) 161(15) γ-amino butyric acid 12.25 1407.97 88(83) 102(100) 112(50) 144(20) 175(10)

L-Pyroglutamic acid 12.60 1571.59 57(92) 115(15) 128(11) 191(100) 206(12) O-acetyl serine 14.52 1594.16 100 (100) 146(11) 159(11) 176(20) - N-acetyl cysteine d 16.28 1744.88 88(50) 117(22) 134(40) 176(100) 235(5) Putrescine 16.60 1775.51 88(100) 89(18) 117(18) 128(35) 172(27) ρ-Aminobenzoic acid 17.93 1871.42 122(25) 134(30) 146(72) 178(80) 209(100) Ornithine 18.92 1994.74 115(22) 128(100) 129(15) 198(20) 230(25) Tyramine 19.74 2036.65 88(100) 121(40) 134(27) 178(60) 253(15) Synephrine 21.29 2131.76 88(67) 102(100) 103(100) 135(15) 181(55) Octopamine 21.45 2178.51 89(43) 09(32) 135(10) 181(100) 194(34)

TCA-associated compounds Fumaric acid 9.19 1251.37 59(38) 85(46) 113(100) 144(10) - Succinic acid 9.29 1261.28 59(70) 113(41) 115(100) - - 2-Ketoglutaric acid 10.95 1297.55 55(50) 59(45) 87(20) 115(100) 130(5) Citric acid 12.60 1527.26 59(40) 101(80) 143(100) 175(20) -

PAAs involved in NPAAs and PAs pathways L-Proline 11.43 1438.60 59(30) 82(24) 128(100) - - L-Serine 13.31 1583.68 59(72) 69(20) 100(100) - - L-Glutamine 13.84 1623.17 69(30) 88(90) 141(100) - - L-Glutamic acid 13.96 1647.35 114(100) 142(70) 174(96) - - L-Cysteine 15.15 1736.82 132(75) 146(60) 176(90) 192(100) - L-Tyrosine 20.12 2133.37 121(100) 165(30) 236(44) - - a RT: Retention time. b LRI: Linear retention index, was calculated using a calibration curve generated by injecting a mixture of alkanes (C12–C26) on a ZB-5MS capillary GC column (Phenomenex, Torrance, CA, USA), under the same chromatographic conditions as samples, equation was LRI=(80.6×RT) +511.7, R² = 0.9968. c The constituent Ion (m/z) were obtained from mass spectra of authentic standards. d Compounds not detected in citrus leaves.

229

Table E-2. Sequences producing significant alignments with Bidirectional amino acid transporter 1 of Arabidopsis thaliana (NP_565254.1; 516 aa; aka GABA permease) and used to create Figure E-1 and the phylogenetic tree in Figure E-2 a. NCBI Max Total Query E Description Ident aa Accession ID score score cover value XP_006468761.1 b PREDICTED: amino-acid permease BAT1-like isoform X1 [C. sinensis] 823 823 97% 0.0 81% 521 XP_006469954.1 c PREDICTED: amino-acid permease BAT1 [C.s sinensis] 781 781 93% 0.0 81% 482 XP_006468762.1 PREDICTED: amino-acid permease BAT1-like isoform X2 [C. sinensis] 642 642 75% 0.0 82% 419 XP_006472841.2 PREDICTED: amino-acid permease BAT1-like [C. sinensis] 410 410 97% 3e-138 42% 535 KDO57518.1 Hypothetical protein CISIN_1g010352mg [C. sinensis] 404 404 97% 5e-136 42% 512 KDO57519.1 Hypothetical protein CISIN_1g010352mg [C. sinensis] 345 345 88% 1e-113 41% 478 KDO57520.1 Hypothetical protein CISIN_1g010352mg [C. sinensis] 272 272 72% 3e-86 40% 394 KDO57522.1 Hypothetical protein CISIN_1g010352mg [C. sinensis] 230 230 59% 3e-71 41% 317 a Bidirectional amino acid transporter 1 of Arabidopsis thaliana (NP_565254.1; 516 aa; aka GABA permease) has been matched with 8 genes of Citrus sinensis using the protein-protein BLAST (BLASTP 2.8.0+) (Altschul et al. 1997, 2005), based on recent available data in GenBank, National Center for Biotechnology Information website (NCBI, https://www.ncbi.nlm.nih.gov/protein/). b PREDICTED: amino-acid permease BAT1-like isoform X1 [Citrus sinensis] has been matched as unnamed protein product (Cs2g13200.1) using the protein-protein BLAST tool (BLASTP) (Altschul et al. 1997, 2005), based on recently available data of C. sinensis cv. Valencia v2.0 genome, chromosome level HZAU assembly (Xu et al. 2013), available on the Citrus Genome Database website (https://www.citrusgenomedb.org/organism/Citrus/sinensis). Identity= 521/521 (100%); Positive= 521/521 (100%); Query Matches 1 to 521; Hit Matches = 1 to 521.

C PREDICTED: amino-acid permease BAT1 [Citrus sinensis] has been matched as unnamed protein product (Cs2g24220.1) using the protein-protein BLAST tool (BLASTP) (Altschul et al. 1997, 2005), based on recently available data of C. sinensis cv. Valencia v2.0 genome from chromosome level HZAU assembly (Xu et al. 2013), available on the Citrus Genome Database website (https://www.citrusgenomedb.org/organism/Citrus/sinensis). Identity= 482/482 (100%); Positive= 482/482 (100%); Query Matches 1 to 482; Hit Matches = 1 to 482.

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Table E-3. List of sequences used in Figure E-3 a.

Accession ID Description Species Family aa

NP_565254.1 Bidirectional amino acid transporter 1 Arabidopsis thaliana Brassicaceae 516 XP_013693273.1 Amino-acid permease BAT1 Brassica napus Brassicaceae 517 XP_021912207.1 Amino-acid permease BAT1 isoform X3 Carica papaya Caricaceae 525 XP_006448382.1 Amino-acid permease BAT1 Citrus clementina Rutaceae 521 XP_006468761.1 PREDICTED: Amino-acid permease BAT1-like isoform X1 Citrus sinensis Rutaceae 521 XP_003536664.1 PREDICTED: Amino-acid permease BAT1 homolog Glycine max Fabaceae 520 XP_016482246.1 PREDICTED: Amino-acid permease BAT1 homolog Nicotiana tabacum Solanaceae 518 XP_002315914.2 Amino-acid permease BAT1 homolog Populus trichocarpa Salicaceae 518 XP_017970990.1 PREDICTED: Amino-acid permease BAT1 isoform X2 Theobroma cacao Malvaceae 525 XP_010663487.1 PREDICTED: Amino-acid permease BAT1 homolog isoform X2 Vitis vinifera Vitaceae 522 a The listed genes were assembled randomly based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, https://www.ncbi.nlm.nih.gov/protein/).

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Table E-4. Primer used for gene expression analysis of GABA shunt and polyamines biosynthetic enzymes by real-time RT-PCR a. Primer TM Product size Gene Accession ID (Forward and Reverse) (˚C) (bp) CsGABP XM_006468698.3 F TTCATCCCCGGACCTTTCAA 58.93 197 R CGAGCACTGAAGATCCAAGC 58.99 CsGABA-T3 XM_006481305.2 F CTCCTGAATGGGGGATAGGT 60.15 196 R TGCTGGGACTTGAGTTCCTT 59.84 CsGAD NM_001288909.1 F ATAGCCCGACTGTTCAATGC 60.10 199 R ATTTCTCCCAGCAGACCTGA 59.80 CsGAD5 XM_006478039.2 F CCTTGACGGGAGAATTTGAG 59.66 200 R GCCGTACTTGTGACCACTGA 59.75 CsGDH1 XM_006479045.2 F CTTTGAGTGGGTGCAGAACA 59.87 203 R CTCAAGCTTCCCAACCTCTG 59.98 CsGDH2 XM_006477017.2 F CTCACCAGCAGTTGTTACCG 59.36 198 R CCAAAACCCTGGATAGCAAA 59.93 CsSSADH XM_006493686.2 F CAACGTACATGGCGTGTCTC 60.18 200 R CTGGCCCATCATTTTCTGTT 59.93 CsOXP1 XM_006478626.2 F ATCCCTCCAGGCTCATTTCT 60.04 193 R CACTTCCACCTCCGATTGTT 59.97 CsGS XM_006490447.2 F GCTCAACCCATGCGTATCTT 60.10 203 R CGAACCAGAAGCTCAAGGAC 59.99 CsG5K XM_006483017.2 F ACGGTAACCAGACAGCAACC 60.04 199 R CCAGGTCTCTTGCTCCAATC 59.80 Csγ-GT1-like XM_006464249.2 F GTGGCTCCAACAAACACAGA 59.73 198 R GCATAAAGGATCCTCCACCA 59.89 Csγ-GT3 XM_006475300.2 F TGGAGTTCCCGGTGAGATAG 60.07 201 R CCATTTGGTGCAAACACTTG 60.00 Csγ-GT3-like XM_006475299.2 F TGGAGGACTCTGTTCCAACC 60.09 195 R CAGGCTCTGAGCAAGCTTTT 59.90 Csγ-GCT -1 XM_006478365.2 F ACTACGAGAGGCTCCCCATT 60.10 199 R TCGATTGCCACGTACTCTTG 59.86 Csγ-GCT -2 XM_006484538.2 F CAGCTTTATCGATCGCTTCC 59.94 196 R GGATCAGGTTGTGGTTCGAG 60.51 Csγ-GCL b XM_006476514.1 F CGGAGGATGCTGTTGTTGTA 59.72 203 R CTCCCAATCGAACCTCTCAG 59.80 CsQPCT c XM_006490569.2 F GCGTTCTTCAGTTCGGAGAG 60.13 207 R CCCCAACCATCTTTCATCTG 60.31 CsPCP1 d XM_006480219.2 F CCATTTTTCCTGCTGATGGT 59.93 202 R GGCACATGAACGAAGAGTGA 59.84 CsTDC1 XM_006479363.2 F GCTCAGTGCTGGTCTCAACA 60.19 203 R CCTTATCACGAGCAGCCAAT 60.24 CsADC XM_006487236.2 F GTCCCTTCAGTCAGCCTTTG 59.84 194 R TGCACAAGCAACTCATAGCC 60.02 CsASL XM_006472396.2 F TGAGCCAAAGCACAAGACTG 60.18 205 R GTCGCTGATCAAACCCTGTT 60.12 CsASS XM_006476944.2 F AGTCTCGGGAATCCCTGTTT 59.93 204 R AAGGACTCAAGCTCCTGCAC 59.60

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Table E-4. Continued Primer TM Product size Gene Accession ID (Forward and Reverse) (˚C) (bp) CsOTC e XM_006473470.2 F GTGACGCTGCTCGTGTTCTA 60.21 201 R CAACCTTGGTTCCTTCCAGA 60.08 CsProDH XM_006482264.1 F TTGCAGGGATTTCTCCAAAC 60.05 200 R CTGCAATCCGAGAAAAGAGG 59.95 CsP5CDH XM_006476581.1 F TGCCAAAGGTCTCCAATTTC 60.05 205 R GGACCATAAGGCCAACGATA 59.78 CsDAO XM_006492160.2 F ACCTCGTTCTTGGGAGTAGC 59.10 179 R ATCGGGCATATAAGGACGCA 59.03 CsODC XM_006492113.2 F CTTACTACGCCGTCAAGTGC 59.01 196 R TTGACTCCAACACTTGCAGC 58.98 CsPAO XM_006482854.1 F AGTGGCAAGCTTGGAATTCC 58.74 199 R ACATTCTTGACACCGTTGCC 59.05 CsSPDS XM_015534077.1 F TCCCGCTCTCATTCCTTTGT 59.02 187 R CCCGCTGAACCATTCTTGTT 58.75 CsPABA synthase f XM_006485802.2 F CGAGGATCCACACCAGAAGA 58.81 187 R CCATGGTGTGAACTGTTGCA 58.97 CsSAT1 XM_006474855.2 F AAGAGACCCTGCGTGCATAA 59.39 198 R AACAGTAACCCACGTCCGAT 59.03 CsSAT5 XM_006475346.2 F GAGCTCAGGTACCCATCTCC 58.96 235 R AGAGAGTGGAGAGAAGCGTG 58.83 CsCS XM_006471676.1 F CCAGCTGCCTTGACATTGTT 59.04 216 R AGCAGGGTTCCATCATCTCC 59.16

Reference genes CsEF1 g AY498567.1 F GGAAGTTCGAGACCACCAAG 59.70 202 R ACACCAAGGGTGAAAGCAAG 60.15 CsF-box g XM_006482390.1 F ACTTGACAGATGGGCTGTCC 60.12 197 R CAGCAACCAAATACCCGTCT 59.99 CsGAPC1 g XM_006483974.2 F ACTCCAGAGGGATGATGTGG 59.92 200 R ATGGGATCTCCTCTGGGTTC 60.28 CsSAND g XM_006488024.2 F GCATCAGCTGCACAGAAGAG 59.89 204 R GGAATGTAGCTGGGTTCCAA 59.93 a The listed genes were assembled based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). b γ-Glutamylcysteine synthetase (γ-GCS) has been matched as PREDICTED: Citrus sinensis glutamate-cysteine ligase, chloroplastic (CsGCL) using the protein-protein BLAST, based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). c Glutaminyl cyclase (QC) has been matched as PREDICTED: Citrus sinensis glutaminyl-peptide cyclotransferase (CsQPCT) using the protein-protein BLAST, based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). d Pyroglutamyl-peptidase (PGP) has been matched as PREDICTED: Citrus sinensis pyrrolidone-carboxylate peptidase 1 (CsPCP1) using the protein-protein BLAST, based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/).

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e Ornithine transcarbamylase (OTC) has been matched as PREDICTED: Citrus sinensis ornithine carbamoyltransferase, chloroplastic (CsOTC) using the protein-protein BLAST, based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). f Para-aminobenzoic acid synthase (PABA synthase) has been matched as PREDICTED: Citrus sinensis aminodeoxychorismate synthase, chloroplastic (CsADC synthase) using the protein-protein BLAST, based on recently available data in GenBank National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov/gene/). g Genes have been used as a reference/housekeeping genes for data normalization according to (Mafra et al. 2012; Wei et al. 2014).

Abbreviations CsGABP: GABA permease (aka PREDICTED: amino-acid permease BAT1-like isoform X1 [C. sinensis]) CsGABA-T3: PREDICTED: Citrus sinensis gamma-aminobutyrate transaminase 3 CsGAD: Citrus sinensis glutamate decarboxylase-like CsGAD5: PREDICTED: Citrus sinensis glutamate decarboxylase 5-like CsGDH1: PREDICTED: Citrus sinensis glutamate dehydrogenase 1 CsGDH2: PREDICTED: Citrus sinensis glutamate dehydrogenase 2 CsSSADH: PREDICTED: Citrus sinensis succinate-semialdehyde dehydrogenase, mitochondrial CsOXP1: PREDICTED: Citrus sinensis 5-oxoprolinase CsGS: PREDICTED: Citrus sinensis glutamate synthase [NADH], amyloplastic CsG5K: PREDICTED: Citrus sinensis glutamate 5-kinase Csγ-GT1-like: PREDICTED: Citrus sinensis gamma-glutamyltranspeptidase 1-like Csγ-GT3: PREDICTED: Citrus sinensis gamma-glutamyltranspeptidase 3 Csγ-GT3-like: PREDICTED: Citrus sinensis gamma-glutamyltranspeptidase 3-like Csγ-GCT: PREDICTED: Citrus sinensis putative gamma-glutamylcyclotransferase Csγ-GCL: PREDICTED: Citrus sinensis glutamate-cysteine ligase, chloroplastic CsQPCT: PREDICTED: Citrus sinensis glutaminyl-peptide cyclotransferase CsPCP1: PREDICTED: Citrus sinensis pyrrolidone-carboxylate peptidase 1 CsTDC1: PREDICTED: Citrus sinensis tyrosine decarboxylase 1 CsADC: PREDICTED: Citrus sinensis arginine decarboxylase-like CsASL: PREDICTED: Citrus sinensis argininosuccinate lyase, chloroplastic CsASA: PREDICTED: Citrus sinensis argininosuccinate synthase, chloroplastic CsOTC: PREDICTED: Citrus sinensis ornithine carbamoyltransferase, chloroplastic CsDAO: PREDICTED: Citrus sinensis probable D-amino acid oxidase PA4548 CsODC: PREDICTED: Citrus sinensis ornithine decarboxylase-like CsPAO: PREDICTED: Citrus sinensis polyamine oxidase 1 CsSPDS: PREDICTED: Citrus sinensis spermine synthase CsPABA synthase: PREDICTED: Citrus sinensis aminodeoxychorismate synthase, chloroplastic CsSAT1: PREDICTED: Citrus sinensis serine acetyltransferase 1, chloroplastic-like CsSAT5: PREDICTED: Citrus sinensis serine acetyltransferase 5 CsCS: PREDICTED: Citrus sinensis cysteine synthase CsEF-1α: Citrus sinensis elongation factor-1 alpha CsF-box: Citrus sinensis F-box/kelch-repeat protein CsGAPC1: Citrus sinensis glyceraldehyde-3-phosphate dehydrogenase, cytosolic (aka GAPDH) CsSAND: Citrus sinensis SAND family protein

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Figure E-1. Multiple sequence alignment of bidirectional amino acid transporter 1 (AtBAT1) of A. thaliana (NP_565254.1; aka AtGABP) and its matched sequences of Valencia sweet orange (C. sinensis). AtGABP has been matched with 8 genes of C. sinensis (see Table E-2) using the protein-protein BLAST (BLASTP 2.8.0+) (Altschul et al. 1997, 2005), based on recently available data in GenBank, National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov/protein/). Conserved amino acids are indicated with black shading and those with high similarity score are in gray. The conserved domains of AtGABP are marked by red and blue lines for AA permease subfamily and AA/polyamines transporter I, respectively. Whiskers reflect the start and the end of each domain. Numbers before and after whiskers denote amino acid residue number for the start and end, respectively. The full list of genes, names, and accession numbers are available in supplementary Table E-2.

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Figure E-2. Evolutionary relationships using an unrooted tree of protein sequences of bidirectional amino acid transporter 1 (AtBAT1) of A. thaliana (NP_565254.1; aka AtGABP) and its matched sequences of Valencia sweet orange (C. sinensis). AtGABP was matched with 8 genes of C. sinensis (see Table E-2) using the protein-protein BLAST (BLASTP 2.8.0+) (Altschul et al. 1997, 2005), based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, https://www.ncbi.nlm.nih.gov/protein/). The evolutionary history was inferred using the Neighbor-Joining method (Saitou and Nei 1987). The optimal tree with the sum of branch length = 1.19 is shown. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method (Zuckerkandl and Pauling 1965) and are in the units of the number of amino acid substitutions per site. The analysis involved 9 amino acid sequences. All positions containing gaps and missing data were eliminated. There was a total of 207 positions in the final dataset. Evolutionary analyses and the joint tree were conducted in MEGA7 software (Kumar et al. 2016) using the neighbor‐joining method. The bootstrap consensus tree inferred from 1000 tests at each branch (Felsenstein 1985). The AtGABP (NP_565254.1) is marked by a black circle, while the predicted amino- acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP) is marked with a black square. The full list of genes, names, and accession numbers are available in supplementary Table E-2.

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Figure E-3. Multiple sequence alignment of the predicted amino-acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP) and the GABP (aka BAT1) protein sequences from various plants species. The used plant species were C. sinensis, C. clementina, A. thaliana, Brassica napus, Carica papaya, Glycine max, Nicotiana tabacum, Populus trichocarpa, Theobroma cacao, and Vitis vinifera. The genes used were assembled randomly based on recently available data in GenBank, National Center for Biotechnology Information website (NCBI, https://www.ncbi.nlm.nih.gov/protein/). Conserved amino acids are indicated with black shading and those with high similarity score are in gray. The conserved domains of AtGABP are marked by red and blue lines for AA permease subfamily and AA/polyamines transporter I, respectively. Whiskers reflect the start and the end of each domain. Numbers before and after whiskers denote amino acid residue number for the start and end, respectively. The full list of genes, names, and accession numbers are available in supplementary Table E-3.

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Figure E-4. In silico analysis of the predicted amino-acid permease BAT1-like isoform X1 of C. sinensis (XP_006468761.1; aka CsGABP). (A) Predicted topology of CsGABP. Numbers inside the transmembrane (TM) domains (blue rectangle) denote amino acid residues. The predicted topology of TM helices has been predicted the protein homology/analogy recognition engine [Phyre2 web portal-version 2.0] (http://www.sbg.bio.ic.ac.uk/~phyre2/html/page.cgi?id=index) (Kelley et al. 2015). (B) The predicted normalized B-factor by ResQ associated with the predicted three- dimensional (3D) secondary structure model of CsGABP (XP_006468761.1) using I- TASSER server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) (Roy et al. 2012; Yang and Zhang 2015). (C and D) Predicted mRNA hairpin structure of CsGABP (minimum free energy (MFE) secondary structure and Centroid secondary structure, respectively). Colors represent strengths with base pairing probabilities.

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BIOGRAPHICAL SKETCH

Yasser Sobhy Ahmed Nehela was born in Kafr El-Zayat, El-Gharbia, Egypt in 1983. In

June 2004, he received his Bachelor of Science in agricultural sciences with an honors degree

(general field) from Faculty of Agriculture, Tanta University, Egypt. Upon graduation, Yasser was appointed as demonstrator/research assistant in the same institution. He obtained his Master of Agricultural Science in plant pathology on October 2012 from the Department of Agricultural

Botany, Faculty of Agriculture, Tanta University, Egypt where he enjoyed his research time in the lab and field. His M.Sc. thesis entitled “Effect of Some Agricultural Practices on Rice Blast

Infection of Some Egyptian Rice Cultivars”.

Early in 2013, Yasser was appointed as an assistant lecturer in the same faculty where he was admitted as a Ph.D. student in the Department of Agricultural Botany, Faculty of

Agriculture, Tanta University, Egypt. In 2014, Yasser was awarded a scholarship for two-year through the joint supervision program from the Cultural Affairs and Missions Sector, Ministry of

Higher Education, Egypt. He joined the plant-pathogen-vector interactions lab (Killiny lab,

CREC, IFAS, UF, Lake Alfred) on March 12th, 2014 as an exchange student/visitor. During this period, he participated on various lab studies, research projects and got more experience in many important techniques, including analytical chemistry techniques (GC-MS, HPLC, and TLC); metabolomic techniques; proteomic techniques; molecular biology (DNA-, RNA extraction,

PCR and RT-PCR techniques); electrophoresis techniques and gene expression; experimental designs and statistical analysis.

In May 2016, and based on his competitive application, Yasser has been recruited, and

Dr. Nabil Killiny - associate professor, Department of Plant Pathology, CREC-IFAS-UF, accepted him as a Ph.D. student. Officially, he started as a formal Ph.D. student in the

Department of Plant Pathology at the University of Florida in the Summer semester 2016, on

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May 9th, 2016. The research project of his Ph.D. focused on “The interactions among citrus plants, the bacterial pathogen Candidatus Liberibacter asiaticus and its insect vector, Asian citrus psyllid, Diaphorina citri at the metabolic level”. Mainly, he used integrative metabolomics and transcriptomics to understand the citrus response(s) against Huanglongbing (aka citrus greening).

After a steep learning curve and many failures, over the course of his graduate research, Mr.

Nehela ended up publishing more than ten peer-reviewed articles and co-authored several conference abstracts. He received his Doctor of Philosophy degree from the Department of Plant

Pathology at the University of Florida in the Fall of 2018.

Upon graduation, Mr. Nehela will continue to work in Killiny lab as a post-doctoral research associate to gain more experience in the area of plant-pathogen-vector interactions.

Later, he plans to return back to Egypt to fulfill an appointed position as an assistant professor of plant pathology in the Department of Agricultural Botany, Faculty of Agriculture, Tanta

University. He will teach the plant pathology courses to undergraduate and graduate students, supervise master and doctorate students, and conduct research hoping to apply what he has learned to improve the citrus industry in Egypt.

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