Chemical Genomic Analyses of Plant-Pathogen

Interactions

by

Karl Johannes Schreiber

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Department of Cell and Systems Biology

University of Toronto

© Copyright by Karl Johannes Schreiber 2011 Chemical Genomic Analyses of Plant-Pathogen Interactions

Karl Johannes Schreiber

Doctor of Philosophy

Department of Cell and Systems Biology University of Toronto

2011

Abstract

The recently-emerged field of chemical genomics is centered on the use of small molecules to perturb biological systems as a means of investigating their function. In order to employ this approach for the study of plant-pathogen interactions, I established an assay in which Arabidopsis thaliana seedlings are grown in liquid media in 96-well plates. Inoculation of these seedlings with a virulent strain of the bacterial phytopathogen Pseudomonas syringae resulted in macroscopic bleaching of the cotyledons of these seedlings. This symptom was used as the basis for high- throughput chemical genomic screens aimed at identifying small molecules that protect

Arabidopsis seedlings from infection. One of the first chemicals identified through this screen was the sulfanilamide compound sulfamethoxazole (Smex). This compound was later shown to also reduce the susceptibility of both Arabidopsis and wheat to infection by the fungal pathogen Fusarium graminearum, suggesting a broad spectrum of activity. More detailed investigations of Smex indicated that the protective activity of this compound did not derive from antimicrobial effects, and that this activity was not executed through common defence-related signalling pathways. The folate biosynthetic pathway enzyme dihydropteroate synthase is a known target of sulfanilamides, and it does appear to contribute to Smex-induced disease resistance, albeit in a folate-independent manner. In order to identify downstream mediators of

ii Smex activity, I initiated two forward genetic screens intended to recover mutants with altered sensitivity to Smex in a seedling growth assay. Interestingly, while these screens yielded mutants with striking Smex sensitivity phenotypes, disease resistance phenotypes were not altered. Gene expression profiling of Arabidopsis tissues treated with Smex prior to bacterial inoculation suggested that this compound generally affects lipid signalling. Altogether, it is evident that Smex elicits a complex set of responses in

Arabidopsis with apparently non-overlapping phenotypic outputs.

iii Acknowledgements

Individual success is rarely the result of solitary effort, and I am grateful to a large number of people for their many contributions to my work and life in Toronto. Firstly, I am immensely appreciative of my supervisor, Dr. Darrell Desveaux, for his guidance and support throughout the last five years. His constant supply of new ideas and boundless enthusiasm for science not only made the lab an exciting place to work, but also helped capture my imagination to think about what is possible in scientific research. His patience, optimism, and willingness to chat were also greatly valued. I also feel very fortunate to have had a tremendous group of people with whom to work. I thank the “original” lab members Mike Wilton, Corinna Felsensteiner, and Dr. Jennifer Lewis for their support, advice, and companionship, as well as newer members Christine Cao, Timothy Lo, Brenden Hurley, Amy Lee, and Sol Nievas for further enriching the lab environment. I also had the priviledge of supervising several excellent undergraduate students, including Shuyi Jin, Masany Jung, James Peek, Shu Hiu, Norrapat Shih, Melissa Cheung, Ming Lin, Eric Fich, David Ye, Allen Jian, and Argishti Baghdasarian. I thank the members of the Guttman lab for their helpful discussions at lab meetings, and the members of the Yoshioka lab for being such entertaining and hospitable neighbours. Thanks also go out to Michael Stokes for sharing resources and ideas for working with sulfanilamide compounds. I would like to acknowledge the members of my supervisory committee, Drs. David Guttman and Nick Provart, for providing valuable input and direction for my projects. I also thank Drs. Peter McCourt, Charles Deprés, Keiko Yoshioka, and Thomas Eulgem for serving as additional members of various examination committees. Finally, I extend my deepest gratitude to my family for their patience, support, and encouragement. I appreciate their efforts to try to understand what it is that I do, and their enduring support for all of my pursuits. They are a key source of inspiration, balance, and perspective, and have laid the foundation for any success that I have had.

iv Table of Contents

Abstract ii

Acknowledgements iv

List of Tables ix

List of Figures xi

List of Appendices xiv

Abbreviations xv

Chapter 1 - General Introduction 1

Abstract 2

Introduction 3

Known Inducers of Plant Disease Resistance 5

Small Molecules (<500 Da) 5

Large Molecules (>500 Da) 26

Microbe-Associated Molecular Patterns 29

High-Throughput Chemical Genetics in Plant Pathology 37

Design of a High-Throughput Screen 39

Characterization of Hits 42

Target Identification 43

General Issues for Induced Disease Resistance in Agriculture 45

Conclusions and Future Pespectives 47

Thesis Overview 49

Chapter 2 - A High-Throughput Chemical Screen for Resistance to

Pseudomonas syringae in Arabidopsis 50

Abstract 51

v Introduction 52

Results and Discussion 54

Establishment of a high-throughput Arabidopsis-P. syringae

pathogenicity assay 54

Chemical screening 64

Conclusions 78

Experimental Procedures 79

Plant materials and bacterial strains 79

Arabidopsis-Pseudomonas syringae 96-well plate pathogenicity

assay 80

Chemical screening 80

Microscopy 81

Bacterial growth inhibition assays 82

Soil-grown plant inoculations and bacterial quantitation 82

Acknowledgements 83

Chapter 3 - Found in Translation: High-Throughput Chemical Screening in Arabidopsis thaliana Identifies Small Molecules that Reduce Fusarium

Head Blight Disease in Wheat 84

Abstract 85

Introduction 86

Results 88

Characterization of the Arabidopsis-F. graminearum pathosystem

in liquid media 88

Chemical screening 93

Experimental translation from Arabidopsis to wheat 93 vi Discussion 99

Conclusions 106

Experimental Procedures 107

Fungal strains and inoculum preparation 107

Arabidopsis-Fusarium graminearum 96-well plate pathogenicity

assay 108

Chemical screening 109

Wheat cultivation and pathogenicity assays 110

Acknowledgements 111

Chapter 4 - Characterization of the Activity of Sulfamethoxazole in

Arabidopsis 112

Abstract 113

Introduction 114

Results 118

Impact of Smex on bacterial growth and virulence 118

Analysis of candidate Smex targets 120

Forward genetic screens for altered responses to Smex 126

Mutants with reduced sensitivity to Smex 129

Mutants with enhanced sensitivity to Smex 136

Transcriptional profiling of Smex activity in Arabidopsis 139

Discussion 147

Conclusions 156

Experimental Procedures 157

Plant materials and bacterial strains 157

Genotypic screening of Arabidopsis T-DNA insertion lines 158 vii Arabidopsis-Pseudomonas syringae 96-well plate pathogenicity

assay 159

Genetic mapping by whole-genome sequencing 160

Transcriptional analyses 161

Chapter 5 - General Discussion 162

Discussion 163

Future Directions 166

Conclusions 170

References 171

Copyright Acknowledgements 318

viii List of Tables

Table 1-1: Small molecules (<500 Da) known to induce disease resistance in

plants 6

Table 1-2: Large molecules (>500 Da) known to induce disease resistance in

plants 27

Table 3-1: Summary of data from evaluations of potential antagonistic or

defence priming activities for gramine, sulfamethoxazole (Smex),

or sulfanilamide (Snil) on wheat heads challenged with Fusarium

graminearum 98

Table 3-2: Incidence of infection in wheat heads sprayed with either gramine

or sulfamethoxazole (Smex) prior to spray inoculation with Fusarium

graminearum 101

Table 3-3: Extent of infection in wheat heads sprayed with either gramine or

sulfamethoxazole (Smex) prior to spray inoculation with Fusarium

graminearum 102

Table 4-1: Phytotoxin sensitivity of wildtype Arabidopsis and a mutant that

exhibits enhanced sensitivity to sulfamethoxazole (ESS 3-10) 138

Table 4-2: Arabidopsis genes upregulated by at least five-fold in plants treated

with sulfamethoxazole versus DMSO prior to bacterial infection 141

Table 4-3: Arabidopsis genes downregulated by at least five-fold in plants

treated with sulfamethoxazole versus DMSO prior to bacterial

infection 142

ix Table 4-4: Comparison of gene expression data from a sulfamethoxazole

priming experiment with transcriptional profiles from Arabidopsis

tissues exposed to defence-associated molecules or pathogen

infection 143

Table 4-5: Enrichment of Gene Ontology (GO) annotations in Arabidopsis

microarray data from a sulfamethoxazole priming experiment 144

Table 4-6: Primers used in this study 159

x List of Figures

Figure 1-1: Structural similarities among small molecules known to induce disease

resistance in plants 11

Figure 2-1: Phenotype of Arabidopsis seedlings inoculated with Pto DC3000

in liquid media 55

Figure 2-2: Phenotypes of Arabidopsis seedlings inoculated with various

strains of P. syringae in liquid media 58

Figure 2-3: Characterization of the Arabidopsis-Pseudomonas syringae

pathosystem using known inducers of plant defence responses 62

Figure 2-4: Sample results obtained from 96-well plates used for chemical

screening 65

Figure 2-5: Protective effects of sulfanilamides identified by chemical screening

on Arabidopsis seedlings inoculated with Pto DC3000 67

Figure 2-6: Preliminary dose-response evaluation of sulfanilamide compounds 69

Figure 2-7: Evaluation of potential antimicrobial activity of sulfanilamide

compounds 71

Figure 2-8: Examination of potential interference with type III secretion in

P. syringae by sulfamethoxazole (Smex) 72

Figure 2-9: Assessment of potential general effects of sulfamethoxazole

(Smex) on Pto DC3000 virulence on Arabidopsis 74

Figure 2-10: Protective effects of sulfanilamides identified by chemical

screening on three-week-old, soil-grown Arabidopsis plants

inoculated with Pto DC3000 75

xi Figure 2-11: Effect of spraying sulfamethoxazole (Smex) on plants prior to

inoculation with Pto DC3000 by dipping 76

Figure 2-12: Effect of spraying sulfamethoxazole (Smex) on plants prior to

inoculation with Pto DC3000 by pressure infiltration 77

Figure 3-1: Phenotype of Arabidopsis seedlings inoculated with

F. graminearum in liquid media 89

Figure 3-2: The Arabidopsis-F. graminearum interaction can be attenuated

by exogenous application of small molecules or by genetically

altering host defence responses 92

Figure 3-3: Identification of novel small molecules that protect Arabidopsis

seedlings from infection by F. graminearum 94

Figure 3-4: Activity of gramine and sulfamethoxazole in the wheat-

F. graminearum pathosystem as evaluated using single spikelet

treatment/inoculation approaches 96

Figure 3-5: Activity of gramine and sulfamethoxazole in the wheat-

F. graminearum pathosystem as evaluated using a spray

treatment/inoculation approach 100

Figure 4-1: Overview of tetrahydrofolate (THF) biosynthesis in Arabidopsis 115

Figure 4-2: Growth of Pseudomonas syringae pv. tomato DC3000

(Pto DC3000) in media containing sulfamethoxazole (Smex) 119

Figure 4-3: Relationship between the enzyme dihydropteroate synthase

(HPPK/DHPS) and sulfamethoxazole (Smex)-induced disease

resistance in Arabidopsis 121

Figure 4-4: Relationship between folate biosynthesis and sulfamethoxazole

(Smex)-induced disease resistance in Arabidopsis 123 xii Figure 4-5: Activity of sulfamethoxazole (Smex) in Arabidopsis mutants that

affect defence-related signalling pathways 127

Figure 4-6: Growth phenotypes of Arabidopsis seedlings germinated on

media containing sulfamethoxazole (Smex) 129

Figure 4-7: Structure-activity relationships for various sulfanilamide

compounds 131

Figure 4-8: Activity of sulfamethoxazole (Smex) in Arabidopsis oxp1-1

T-DNA disruptants 134

Figure 4-9: Phenotypes associated with an “enhanced sensitivity to

sulfamethoxazole (Smex)” mutant (ESS 3-10) 137

Figure 4-10: Influence of jasmonate (JA) signalling on disease resistance

in Arabidopsis 146

xiii List of Appendices

Appendix 1: Evaluations of Pathogen Resistance Phenotypes in Arabidopsis

Seedlings Grown in Liquid Media 209

Appendix 2: Identification of Small Molecules that Modulate the Interaction

Between Arabidopsis and Pseudomonas syringae 211

Appendix 3: Identification of Small Molecules that Modulate the Interaction

Between Arabidopsis and Fusarium graminearum 233

Appendix 4: Transcriptional Response of Liquid-Grown Arabidopsis Seedlings

to Sulfamethoxazole 236

Appendix 5: Transcriptional Response of Plants Treated with

Sulfamethoxazole Prior to Bacterial Inoculation 244

Appendix 6: Summary of Results from a Forward Genetic Screen Intended

to Identify Novel Virulence Determinants in Pseudomonas

syringae pv. maculicola ES4326 253

Appendix 7: Summary of Results from a Forward Genetic Screen Intended

to Identify Negative Regulators of Flagellar Motility in

Pseudomonas syringae pv. maculicola ES4326 Grown Under

Type III Secretion System-Inducing Conditions 258

Appendix 8: AlgW Regulates Multiple Pseudomonas syringae Virulence

Strategies 262

xiv Abbreviations

ABA - abscisic acid

BABA - β-aminobutyric acid

BTH - benzo(1,2,3)thiadiazole-7-carbothioic acid S-methyl ester

CA - carbonic anhydrase cfu - colony-forming units

DHF - dihydrofolate

DHPS - dihydropteroate synthase

DMSO - dimethyl sulfoxide

DON - deoxynivalenol dpi - days post-inoculation

ESS - enhanced sensitivity to sulfamethoxazole

ET - ethylene

FLS2 - FLAGELLIN-SENSITIVE 2

GUS - β-glucuronidase hpi - hours post-inoculation

HPPK - hydroxymethyldiopterin pyrophosphokinase

HR - hypersensitive response

INA - 2,6-dichloroisonicotinic acid

JA - jasmonic acid

NPR1 - NONEXPRESSOR OF PATHOGENESIS-RELATED PROTEIN GENES1

OXP1 - OXOPROLINASE1

PABA - p-aminobenzoic acid

xv PAMP - pathogen-associated molecular pattern

Pma ES4326 - Pseudomonas syringae pv. maculicola ES4326

Pto DC3000 - Pseudomonas syringae pv. tomato DC3000

PR - pathogenesis-related

RSS - reduced sensitivity to sulfamethoxazole

ROS - reactive oxygen species

SA - salicylic acid

SABP - salicylic acid-binding protein

SAR - systemic acquired resistance

Sdiz - sulfadiazine

Smex - sulfamethoxazole

Snil - sulfanilamide

Spyr - sulfapyridine

TTSS - type III secretion system

xvi

Chapter 1

General Introduction

Modified from:

Message in a bottle: Chemical biology of induced disease resistance in plants

Karl J. Schreiber and Darrell Desveaux (2008)

Plant Pathology Journal 24, 245-268

Author contributions: K.J.S. wrote the manuscript, with input and direction from D.D.

1 Abstract

The outcome of plant-pathogen interactions is influenced significantly by endogenous small molecules that coordinate plant defence responses. There is currently tremendous scientific and commercial interest in identifying chemicals whose exogenous application activates plant defences and affords protection from pathogen infection. In this review, we provide a survey of compounds known to induce disease resistance in plants, with particular emphasis on how each compound was originally identified, its putative or demonstrated mechanism of defence induction, and the known biological target(s) of each chemical. Larger polymeric structures and peptides/proteins are also discussed in this context. The quest for novel defence- inducing molecules would be aided by the capability for high-throughput analysis of candidate compounds, and we describe some issues associated with the development of these types of screens. Subsequent characterization of hits can be a formidable challenge, especially in terms of identifying chemical targets in plant cells. A variety of powerful molecular tools are available for this characterization, not only to provide insight into methods of plant defence activation, but also to probe fundamental biological processes. Furthermore, these investigations can reveal molecules with significant commercial potential as crop protectants, although a number of factors must be considered for this potential to be realized. By highlighting recent progress in the application of chemical biology techniques for the modulation of plant-pathogen interactions, we provide some perspective on the exciting opportunities for future progress in this field of research.

2 Introduction

When faced with pathogen attack, plants do not have the option to physically escape. Instead, all threats must be confronted and effectively mitigated using the plant’s available resources. The coordination of these defensive resources involves a number of small molecules with various physiological activities. Salicylic acid (SA) is a key regulator of plant defence that primarily mediates responses to biotrophic pathogens (Thomma et al., 1998; Glazebrook, 2005). The detection of an invading pathogen by host resistance (R) proteins initiates a cascade of events that culminate in programmed cell death at the site of infection, known as the hypersensitive response

(HR). This cell death response is facilitated by local accumulations of nitric oxide and reactive oxygen species (ROS) as well as SA. Following the HR, uninfected tissues become more resistant to subsequent pathogen infections. This systemic acquired resistance (SAR) is SA-dependent and provides protection from attacks by a broad range of pathogens (Gaffney et al., 1993; Ryals et al., 1996). When plants encounter necrotrophic pathogens, their responses generally rely on jasmonic acid (JA) and ethylene (ET) signalling. Both JA and ET are also implicated in the control of induced systemic resistance (ISR), which is stimulated by the infection of plant roots with certain strains of nonpathogenic plant growth-promoting rhizobacteria (van Loon et al., 1998).

Recently, additional molecules have been found to modulate disease resistance, including abscisic acid, brassinosteroids, gibberellin, cytokinin, and auxin (Nakashita et al., 2003a; Mauch-Mani and Mauch, 2005; Navarro et al., 2006; Robert-Seilaniantz et al., 2007; Wang et al., 2007). There is significant cross-talk among these signalling molecules which helps coordinate responses appropriate for the invading pathogen

(Robert-Seilaniantz et al., 2007; Spoel and Dong, 2008). 3 Given the diversity of endogenous molecules known to influence plant disease resistance, there is considerable interest in the activation or enhancement of these immune responses by the exogenous application of chemicals. Indeed, White (1979) noted that treatment of tobacco (Nicotiana tabacum cv. Xanthi-nc) with SA significantly reduced its susceptibility to infection by tobacco mosaic virus (TMV). Similarly, applications of JA or ET can induce resistance to pathogens such as Botrytis cinerea and Erysiphe graminis (Schweizer et al., 1993; Diaz et al., 2002). There are, however, critical limitations on the widespread use of these specific compounds in a field or greenhouse setting. For example, at the concentrations required to induce resistance,

SA displays phytotoxicity in some plant species (Friedrich et al., 1996). As a gas, large-scale application of ET is impractical. Some of these endogenous signals may also only have transient activity due to their conversion to biologically inactive conjugates for storage (Chen et al., 1995). The search for novel chemicals for the induction of disease resistance was initiated in part to address these technical issues, while at the same time generating additional tools for probing the signalling pathways that control resistance. Here, we summarize the current products of this research, both in terms of historical background and subsequent mechanistic characterization. We focus only on those molecules that, when applied as a single, purified entity, result in a measurable, significant increase in resistance to a given pathogen. We exclude those compounds that have only been demonstrated to activate a specific marker of plant defence, as well as those with direct antimicrobial activity. In addition, we have not sought to exhaustively catalogue all of the plant-pathogen combinations whose interaction is influenced by a given chemical, but rather provide examples that illustrate this activity. This review was prompted in part by the emergence of new, high- throughput approaches for the study of host-pathogen interactions and their modulation 4 by exogenously-applied molecules. As such, we discuss some of the issues associated with high-throughput screening for novel inducers of defence, particularly with regards to defining the goals and setup of a screen, as well as the extensive downstream analyses required to characterize the activity of a molecule of interest.

Known Inducers of Plant Disease Resistance

Small Molecules (<500 Da)

Synthetic/Inorganic Compounds

The established role of SA in modulating disease resistance made this molecule a popular starting point for testing structural derivatives. One such compound, 2,6- dichloroisonicotinic acid (INA), was identified in an industrial screening program (Ciba-

Geigy AG, now Novartis) as capable of inducing resistance to anthracnose disease

(Colletotrichum lagenarium) in cucumber and TMV in tobacco (Table 1-1 and Figure 1-

1; Metraux et al., 1991; Ward et al., 1991). This chemical is both structurally and functionally similar to SA, as both compounds induce the expression of similar sets of pathogenesis-related (PR) proteins concomitant with the development of SAR (Ward et al., 1991; Uknes et al., 1992). Further, both bind to and inhibit the ROS scavenging enzymes catalase (salicylic acid-binding protein, SABP) and ascorbate peroxidase

(Conrath et al., 1995; Durner and Klessig, 1995). Modulation of ROS levels appears to be a key aspect of SA/INA activity, because co-application of INA and an antioxidant blocked the induction of PR gene expression. Notably, however, INA does not induce

5 Table 1-1: Small molecules (<500 Da) known to induce disease resistance in plants

Original Source - Name Structure Molecules Screened Reference

OH Salicylic acid (SA) Specifically tested White, 1979

COOH

O OH Metraux et al., 2,6-dichloroisonicotinic SA analogues 1991; Ward et acid (INA) al., 1991

6 Cl N Cl O S Benzo-1,2,3-thiadiazole-7- Friedrich et al., Benzothiadiazole carbothioic acid S-methyl S 1996; Schurter derivatives ester (BTH) N et al., 1987 N

3,4-dichloro-N-(2- O Tsubata et al., Benzothiadiazole cyanophenyl)-1,2-thiazole- N 2006; Yasuda et N H derivatives 5-carboxamide (tiadinil) al., 2004 N S Cl O Yasuda et al., SV-03 OH (Tiadinil metabolite) N 2006 N S Cl 3-chloro-1-methyl-1H- O Pyrazolecarboxylic acid Nakashita et al., pyrazole-5-carboxylic acid N N OH derivatives 2003b (CMPA)

H O N CN N-cyanomethyl-2- Yoshida et al., Cyanoalkylisonicotinamide chloroisonicotinamide 1987; Yoshida et derivatives (NCI) al., 1990 Cl N

Benzothiadiazole Watanabe et al., Probenazole (PBZ) O S derivatives 1977 O N O

Yoshioka et al., Benzisothiazole (BIT) (Probenazole metabolite) O 2001 S O N O H O OH

3,5-dichloroanthranilic acid Knoth et al., NH2 Small molecule libraries

7 (DCA) 2009

Cl Cl O O Adipic acid derivatives NH X Adipic acid derivatives Flors et al., 2003

O O

H2N S NH Arabidopsis-bioactive Schreiber et al., Sulfamethoxazole O N O compounds 2008 (Chapter 2)

Potassium and phosphate Gottstein and Phosphates XPO 4 salts Kuc, 1989 O HO Chemical extracts from Doubrava et al., Oxalates X+ - O spinach and rhubarb 1988 O

O

O OH

Ethylenediaminetetraacetic N OH Specifically tested as a Walters and acid HO N calcium chelator Murray, 1992 HO O

O reviewed in Silicon Si, H SiO - 4 4 Epstein, 1994 Ghoshroy et al., Cadmium Cd Specifically tested 1998 β-aminobutyric acid NH2 O Variant amino acids Papavizas, 1964 (BABA) OH O N NH

8 N N O Collection of plant Emmanouil and Riboflavin (Vitamin B2) HO metabolites Wood, 1981

HO OH

OH O Menadione sodium SO3Na Borges et al., bisulfite (Vitamin K Specifically tested 3 2003 addition compound) O NH2

N N+ S Compounds shown to Malamy et al., Thiamine (Vitamin B ) induce PR-1 gene 1 N 1996 expression

OH

OH OH HO O OH Reignault et al., Trehalose O O Natural product collection HO OH 2001

OH OH OH OH Prithiviraj et al., Catechin OH Specifically tested HO O 2007

OH

H Chemical extract from the N NH2 Yamakawa et Spermine H2N N intercellular fluid of TMV- H al., 1998 infected tobacco leaves OH

9 O OH Chemical extract from Cholic acid Koga et al., 2006 human feces

HO OH O 3-acetonyl-3- HO Chemical extract from Li et al., 2008 hydroxyoxindole (AHO) Strobilanthes cusia O N H

Cutin monomers O Collection of cutin Schweizer et al, (16-hydroxypalmitic acid HO OH monomers 1996 shown)b

Laquitane et al., Ergosterol Specifically tested 2006

HO

O H N O Growth media from N N O H H cultures of Pseudomonas Waspi et al., Syringolin O OH NH syringae pv. syringae 1998 HN strain B 301D-R

O

Growth media from N-alkylated benzylamine Ongena et al., cultures of Pseudomonas derivatives N+ 2005 putida BTP1 10

O OH O Selected mutants of Iavicoli et al., 2,4-diacetylphloroglucinol Pseudomonas fluorescens 2003 CHA0 (i.e. genetic screen) HO OH

OH Volatiles from Bacillus 2R, 3R-butanediol subtilis GB03 and Bacillus Ryu et al., 2004

OH amyloliquefaciens IN937a

aRefers to initial observations of induced disease resistance in plants.

bNote: some microbial fatty acids also induce disease resistance (see text).

Figure 1-1: Structural similarities among small molecules known to induce disease resistance in plants. The structures listed in Table 1-1 were clustered using the

ChemMine online structural analysis workbench (http://chemmine.ucr.edu; Girke et al.,

2005). Individual elements such as silicon and cadmium were excluded from the analysis.

11 SA accumulation, and INA still confers resistance upon both tobacco and Arabidopsis plants expressing the nahG gene, which encodes a bacterial salicylate hydroxylase that degrades salicylic acid to biologically inactive catechol (Delaney et al., 1994; Vernooij et al., 1995). This indicates that INA acts downstream of SA accumulation to induce disease resistance.

Further screening led to the identification of additional compounds that, although more structurally diverse, still mimicked SA function. In a screen of various benzothiadiazole derivatives, benzo-1,2,3-thiadiazole-7-carbothioic acid S-methyl ester

(BTH, acibenzolar-S-methyl) emerged as a strong inducer of SAR in numerous plant- pathogen combinations, with much lower phytotoxicity than either SA or INA (Schurter et al., 1987; Friedrich et al., 1996). Like SA, BTH inactivated catalase, ascorbate peroxidase, and a mitochondrial NADH:ubiquinone oxidoreductase (Wendehenne et al., 1998; van der Merwe and Dubery, 2006). Treatment of barley (Hordeum vulgare

L.) with BTH did not immediately induce ROS production, but conditioned the plants for a faster and stronger response upon infection with the powdery mildew fungus

Blumeria graminis (Faoro et al., 2008). This potentiated, or “primed” (Conrath et al.,

2006) response included a more intense HR-associated oxidative burst and more extensive formation of cell wall appositions (papillae), coupled with greater accumulation of phenolic compounds at sites of attempted fungal penetration (Faoro et al., 2008). The activity of BTH varies between different pathosystems, though, as BTH- induced resistance of bean (Phaeseolus vulgaris) to the rust fungus Uromyces appendiculatus involves an oxidative burst but no HR-related cell death (Iriti and Faoro,

2003). With regards to SA signalling, BTH acts downstream of SA accumulation

(Friedrich et al., 1996) and may contribute to the establishment of SAR through an interaction with SABP2, a methyl salicylate esterase that is critical for the perception of 12 defence-inducing signals in systemic tissues (Du and Klessig, 1997; Forouhar et al.,

2005; Park et al., 2007).

A number of other SAR inducers also act downstream of SA accumulation, although their activity has been less thoroughly characterized. Based on the efficacy of

BTH, a screen of variant benzothiadiazole structures was conducted at Nihon Nohyaku

Co., Ltd. (Japan) on the rice (Oryza sativa)-rice blast (Magnaporthe grisea) pathosystem. This screen yielded 3,4-dichloro-N-(2-cyanophenyl)-1,2-thiazole-5- carboxamide (tiadinil, TDL), which has activity not only against fungal pathogens of rice but also bacterial and viral pathogens of tobacco (Yasuda et al., 2004; Tsubata et al.,

2006). A metabolite of TDL, termed SV-03, was subsequently found to be equally effective in the stimulation of disease resistance (Yasuda et al., 2006). In a different screen, 3-chloro-1-methyl-1H-pyrazole-5-carboxylic acid (CMPA) was identified from a survey of pyrazolecarboxylic acid derivatives as capable of protecting rice from infection by rice blast (Pyricuraria oryzae) and bacterial blight (Xanthomonas oryzae pv. oryzae) (Nakashita et al., 2003b; Nishioka et al., 2005). The resistance of tobacco to

Pseudomonas syringae pv. tabaci and Oidium sp. was also enhanced by treatment with CMPA (Yasuda et al., 2003). Finally, among several cyanoalkylisonicotinamide structures screened for their ability to control M. grisea infection, N-cyanomethyl-2- chloroisonicotinamide (NCI) was especially effective (Yoshida et al., 1987; Yoshida et al., 1990). This compound also reduced the growth of a virulent strain of P. syringae on Arabidopsis, as well as TMV, P. syringae pv. tabaci, and O. lycopersici on tobacco

(Nakashita et al., 2003a; Yasuda et al., 2003). Yasuda (2007) noted that TDL, SV-03,

CMPA, and NCI all induced the expression of the same set of PR genes, all acted independently of SA accumulation and JA/ET perception, and all required the SA signalling regulatory protein NONEXPRESSOR OF PR GENES1 (NPR1). Evidently, it 13 is possible to stimulate the pathway between SA production and NPR1 activity with a variety of different chemical structures, although the cellular ligand(s) for each compound remain to be identified.

Other compounds are also closely tied to SA signalling, but at different points in the pathway. Researchers at Meiji Seika Kaisha, Ltd. (Japan) also drew inspiration from BTH as a starting point for screening benzothiadiazole derivatives for novel inducers of resistance. This investigation produced 3-allyloxy-1,2-benzothiazole 1,1- dioxide, which has been widely used under the name probenazole for the control of M. grisea in rice (Watanabe et al., 1977). Probenazole and its metabolite 1,2- benzisothiazole-1,1-dioxide (BIT, saccharin) both stimulated the expression of PR genes and the development of SAR against a range of pathogens (Yoshioka et al.,

2001; Nakashita et al., 2002). In contrast to the compounds discussed above, however, probenazole and BIT do induce SA accumulation, they do not bind either catalase or SABP2, and their ability to confer SAR is blocked in plants expressing the nahG gene. Efforts to understand the mechanism of probenazole-induced resistance resulted in the isolation of a probenazole-responsive gene termed PBZ1 (Midoh and

Iwata, 1996). Interestingly, PBZ1 is also induced by NCI, but not BIT, indicating that the induced resistance is not necessarily PBZ1-dependent (Nakashita et al., 2001).

The lack of PBZ1 induction by SA also suggests that probenazole does not function by exclusively stimulating SA accumulation. The sequence of PBZ1 shows some similarity to that of PR-10 (Midoh and Iwata, 1996), which may be a ribonuclease

(Bantignies et al., 2000). Kim et al. (2008a) observed the accumulation of PBZ1 in tissues undergoing programmed cell death, although the exact function of PBZ1 in this context remains to be fully elucidated. Additional probenazole-induced genes include phenylalanine ammonia lyase (PAL) and caffeic acid 3-O-methyltransferase, which 14 may be responsible for the production of flavonoid-type phytoalexins and/or lignin or, in the case of PAL, SA biosynthesis (Lin et al., 2008).

More recently, high-throughput chemical screens have yielded molecules that provide additional insight into SA signalling. From a group of Arabidopsis genes previously characterized as exhibiting a “late/sustained upregulation in response to

Hyaloperonospora parasitica (now Hyaloperonospora arabidopsidis)” (LURP), Knoth et al. (2009) designed a reporter construct composed of the promoter of LURP member

CaBP22 fused to the β-glucuronidase (GUS) coding sequence. Using transgenic

Arabidopsis seedlings grown in liquid media, they demonstrated that this reporter was responsive to H. arabidopsidis infection as well as SA treatment. This reporter line was subsequently used to screen 42,000 compounds for inducers of GUS gene expression.

This screen yielded a number of SA analogues, including 3,5-dichloroanthranilic acid

(DCA), which is structurally similar to INA. In contrast to the long-lasting disease resistance induced by INA, however, DCA conferred a more transient type of resistance to H. arabidopsidis. In addition, while INA functions in an NPR1-dependent manner, the activity of DCA was only partially dependent on NPR1. The incomplete overlap of gene expression profiles from DCA- and INA-treated seedlings further reinforced these functional differences. Overall, DCA should provide another tool for probing the apparent complexity of SA-associated signalling pathways.

Beyond SA and its analogues, some compounds have been discovered as part of a search for bioactive synthetic molecules with general effects on plant metabolism.

Flors et al. (2001) hypothesized that synthetic growth regulators may enhance disease resistance by delaying senescence and stimulating biosynthetic pathways with potential defence-related end-products. This was tested by synthesizing derivatives of adipic acid, a six-carbon dicarboxylic acid, and screening for compounds that reduced the 15 growth of Phytophthora citrophthora, Phytophthora capsici, or Alternaria solani on tomato (Solanum lycopersicum L.) or pepper (Capsicum annuum L.). While many compounds were most effective when used as a mixture, three novel amide derivatives of adipic acid provided significant protection when used on their own (Flors et al., 2001;

Flors et al., 2003a; Flors et al., 2003b). These compounds stimulated plant growth, increased total protein content, reduced protease activity, increased photosynthetic rate, and improved water use efficiency, indicative of an overall antisenescence effect.

The chemicals also upregulated PAL and chalcone isomerase (CHI) activities for increased output of phenylpropanoids and flavanones potentially bound for isoflavonoid phytoalexins. No direct antimicrobial activity was observed for the three compounds.

In some cases, even molecules with ostensible antibiotic activity can specifically stimulate plant defence responses. A collection of compounds known to be bioactive in

Arabidopsis was screened to identify chemicals that protect Arabidopsis seedlings from infection by P. syringae (Chapter 2). A group of sulfanilamide compounds was identified that provided varying levels of protection, with sulfamethoxazole (Smex) being the most effective. At the concentration used for screening, this compound did not directly inhibit bacterial growth. Analysis of various Arabidopsis signalling mutants indicated that Smex-mediated protection is manifested independently of SA, JA, ET, and ABA signalling, and does not require an oxidative burst. Both the physical target of

Smex and its mechanism of activity are currently unknown.

Inorganic compounds can also be applied to enhance disease resistance in plants. Gottstein and Kuc (1989) first noted that phosphate salts induced systemic resistance to anthracnose in cucumber. The activation of broad-spectrum, systemic disease resistance by phosphates has since been observed in several other plant species (Reignault and Walters, 2007). This activity may involve the sequestration of 16 calcium ions, which could disrupt the cell wall and cause the release of defence- inducing cell wall fragments (Gottstein and Kuc, 1989). Notably, Ca2+-binding organic acids such as oxalates and ethylenediaminetetraacetic acid also induced resistance to anthracnose in cucumber (Doubrava et al., 1988; Walters and Murray, 1992). Tissues treated with phosphates also exhibited ROS production, cell death, and both local and systemic accumulations of SA (Orober et al., 2002). In addition, phosphates stimulated increases in the activity of PAL, peroxidase, and lipoxygenase enzymes, which could contribute to cell wall reinforcement and further defence induction (Mitchell and

Walters, 2004).

Although it is the second most abundant element in soils, silicon has long been known to alleviate biotic stress in plants (reviewed in Epstein, 1994). Diogo and Wydra

(2007) suggested that pathogen spread was inhibited by silicon-induced modifications to pectic polysaccharides that help maintain cell wall integrity. Indeed, silicon treatment upregulated the activity of PAL, polyphenol oxidase, and peroxidase enzymes, all of which could influence cell wall structure (Qin and Tian, 2005). Transcriptomic analysis of silicon-treated Arabidopsis plants revealed that, while this element had essentially no effect on plants in the absence of pathogen infection, it dramatically enhanced host defence responses upon perception of a fungal invader (Fauteux et al., 2006).

Various metal ions are also capable of inducing both defence gene expression and resistance to pathogen infection (Sinha and Giri, 1979; Asselin et al., 1985; White et al., 1986). A mechanism of action has not been elucidated for most of these ions, but frequently, a direct antimicrobial effect at some level cannot be excluded

(Poschenrieder et al., 2006). On the other hand, non-toxic concentrations of cadmium eliminated the disease symptoms caused by turnip vein clearing virus, apparently by interfering with systemic viral movement in a SA-independent manner (Citovsky et al., 17 1998; Ghoshroy et al., 1998). When applied as a seed treatment, this metal also protected wheat seedlings from infection by Fusarium oxysporum (Mittra et al., 2004), in the absence of direct antifungal activity.

Inducers from Biotic Sources

Amino acids and β-aminobutryic acid

In consideration of the selective pressures placed on plants for the evolution of effective defence mechanisms, the vast pool of naturally produced compounds seems to be an obvious source for molecules that influence disease resistance. One of the first “natural products” with such demonstrated activity was phenylalanine, which significantly reduced the susceptibility of apple leaves to infection by the fungal pathogen Venturia inequalis (Kuc et al., 1957). This finding fuelled a period of extensive investigation into the relationship between amino acids and disease resistance in which a variety of structures were tested in several different pathosystems

(van Andel, 1966). The modes of action for these compounds were not fully ascertained, but it was evident that most amino acids did not have antimicrobial activity at the concentrations required for activation of plant defence responses. While the potential use of amino acids as prophylactic plant protectants has been revisited occasionally (Sinha and Giri, 1979; Emmanouil and Wood, 1981; Asselin et al., 1985), mechanistic explanations for this activity are mostly still lacking.

One notable exception to this situation is the nonprotein amino acid β- aminobutyric acid (BABA), which has provided tremendous insight into defence-related signalling pathways in plants. As the relevance of common amino acids to plant 18 defence was becoming apparent, Papavizas (1964) identified BABA from a set of variant amino acid structures as a compound that significantly reduced the severity of root rot on peas (Pisum sativum) caused by the fungal pathogen Aphanomyces euteiches. The efficacy of BABA as an inducer of disease resistance was subsequently demonstrated in numerous plant-pathogen combinations (Cohen, 2002).

Importantly, this activity occurs in the absence of direct antimicrobial effects. The signalling pathways required for BABA-induced resistance (BABA-IR) seem to vary for different types of pathogens. In Arabidopsis, the resistance induced against P. syringae and B. cinerea is SA-dependent but JA and ET-independent, while resistance to the oomycete Hyaloperonospora arabidopsidis is independent of all three pathways

(Zimmerli et al., 2000; Zimmerli et al., 2001). BABA does not directly activate defence responses, but rather primes the plant to respond more rapidly after pathogen attack, as demonstrated by the enhanced PR-1 gene induction following P. syringae infection, and the earlier and greater callose deposition upon infection of BABA-treated

Arabidopsis with the necrotrophic pathogens Alternaria brassicicola and

Plectosphaerella cucumerina (Ton and Mauch-Mani, 2004). Inhibition of callose formation by 2-deoxy-D-glucose eliminated BABA-IR to A. brassicicola. Interestingly, treatment with abscisic acid (ABA) mimics the response to BABA, both in terms of primed callose accumulation and subsequent resistance to A. brassicicola and P. cucumerina. Furthermore, BABA-IR to P. cucumerina is blocked in the ABA biosynthetic mutant aba1-5, the ABA-insensitive mutant abi4-1, and the callose synthase mutant pmr4-1.

The connection between callose, ABA, and BABA was addressed through more detailed genetic studies. High concentrations of BABA induce sterility in Arabidopsis

(Jakab et al., 2001), which allowed the identification of IBS (impaired in BABA-induced 19 sterility) lines from a T-DNA insertion collection (Ton et al., 2005). One of the products of this screen was IBS3, which encodes a zeaxanthin epoxidase with an important role in ABA biosynthesis. The ibs3 mutant displayed reduced BABA-IR to H. parasitica coincident with deficiencies in priming for callose deposition and ABA-inducible gene expression. Disruption of IBS2, a polyphosphoinositide phosphatase, also reduced primed callose deposition, but only compromised BABA-IR to salt stress. Another mutant, ibs1, affected BABA-IR against H. parasitica and P. syringae, although the susceptibility of untreated plants was not altered. IBS1 encodes a cyclin-dependent kinase that influences the SA-dependent component of BABA priming. These results suggest that BABA activity against different pathogens and stresses may be mediated by multiple pathways. Indeed, the callose-deficient pmr4-1 mutant is compromised for

BABA-IR against A. brassicicola but not P. syringae (Flors et al., 2008). This mutant is actually more resistant to P. syringae, owing to the negative crosstalk between callose synthesis and SA signalling (Nishimura et al., 2003). Treatment with BABA further enhances resistance to P. syringae (Flors et al., 2008). A. brassicicola downregulates

ABA accumulation in Arabidopsis, which does not occur in BABA-treated plants. In this case, BABA appears to confer resistance by sensitizing tissues for ABA perception and priming callose deposition at some point upstream of PMR4.

Vitamins

As critical components of many physiological processes, vitamins may also influence the outcome of plant-pathogen interactions. Emmanouil and Wood (1981) observed that treating the leaves of pepper, tomato, or eggplant with riboflavin (vitamin

B2) prior to inoculation of roots with Verticillium dahliae significantly reduced the fungal 20 load and overall disease symptoms of these plants. Riboflavin was later shown to protect various hosts from viral, bacterial, fungal, and oomycete pathogens, with little or no phytotoxicity (Aver'yanov et al., 2000; Dong and Beer, 2000; Pushpalatha et al.,

2007). This systemic induced resistance required protein kinase signalling and a functional NPR1 gene, but did not depend on SA accumulation. As a cofactor of enzyme flavoproteins, riboflavin may influence plant defence responses by catalyzing the production or metabolism of ROS. The accumulation of active oxygen molecules may also underlie the activity of menadione (vitamin K3), which was first studied as a plant growth regulator (Rao et al., 1985). The water-soluble addition compound menadione sodium bisulphite (MSB) showed strong activity against Fusarium oxysporum on banana and Leptosphaeria maculans on Brassica napus (Borges et al.,

2003; Borges et al., 2004). Menadione is a naphthoquinone that functions as an electron carrier in the plasma membrane (Oldenburg et al., 2008). It is possible that exogenous menadione increases the pool of naphthoquinone, leading to an accumulation of superoxide ions and H2O2 that could stimulate plant defence responses (Borges et al., 2003).

Another recently characterized vitamin with resistance-inducing activity is thiamine (vitamin B1). Some early experiments demonstrated that thiamine can activate PR-1 gene expression in tobacco (Asselin et al., 1985) and stimulate resistance to TMV in a SA-dependent manner (Malamy et al., 1996). Subsequent investigations indicated that the resistance induced by thiamine is systemic, broad- spectrum, and long-lasting (Ahn et al., 2005). In Arabidopsis, thiamine primes the pathogen-induced expression of PR-1 and PAL as well as callose deposition and an oxidative burst associated with the HR (Ahn et al., 2007). All of these responses were abolished when catalase, a H2O2 scavenger, was co-infiltrated with a virulent bacterial 21 pathogen, thus indicating the key role of ROS in the activity of thiamine. The primed response was also found to be independent of ABA, JA, and ET signalling, but required both SA accumulation and a functional NPR1 gene. Finally, thiamine primes the expression of a Ca2+-dependent protein kinase gene, suggesting that this compound acts upstream of Ca2+ signalling to activate a set of responses mediated by the SA pathway (Ahn et al., 2005).

Sugars

A number of sugars have also demonstrated a capability for plant defence induction. A screen of various sugars revealed that cellobiose, mannose, arabinose, and sucrose significantly reduced the colonization of pepper and eggplant leaves by V. dahliae (Emmanouil and Wood, 1981). Trehalose, previously shown to be important for plant responses to abiotic stress (Drennan et al., 1993), protected wheat from infection by the powdery mildew fungus B. graminis (Reignault et al., 2001). Tissues treated with trehalose exhibited enhanced papillae formation at sites of attempted fungal penetration, increased expression of the phenlypropanoid pathway enzymes PAL and peroxidase, as well as accumulations of H2O2 and phenolic compounds (Reignault et al., 2001; Renard-Merlier et al., 2007).

Catechin

The observation that high concentrations of the allelochemical catechin stimulated extensive ROS production and cell death in plants (Bais et al., 2003) spurred an investigation into the contribution of this molecule to plant defence 22 responses. Intriguingly, lower concentrations of (±)-catechin stimulated growth in

Arabidopsis and reduced its susceptibility to infection by a virulent strain of P. syringae

(Prithiviraj et al., 2007). This level of exposure resulted in moderate accumulations of

ROS, significant callose deposition in leaves, and the SA/NPR1-dependent induction of

PR-1. Overall, these findings illustrate the phenomenon of hormesis, in which sublethal concentrations of a toxin actually promote the growth and survival of an organism

(Calabrese and Baldwin, 2003).

Polyamines

Although there is strong evidence that polyamines are associated with plant defence responses (Walters, 2003), they have only received brief attention as potential exogenous inducers of disease resistance. Polyamines are known to accumulate in necrotic lesions during the HR (Torrigiani et al., 1997) and in intercellular spaces of

TMV-infected tissue (Yamakawa et al., 1998). Treatment of tobacco plants with the polyamine spermine induced the expression of several PR genes and resulted in significantly reduced lesion sizes in leaves inoculated with TMV. Spermine did not induce SA accumulation, nor did SA increase spermine levels. The activity of polyamines in the context of defence remains to be fully characterized, but these compounds could be components of the programmed cell death signalling machinery that facilitate the accumulation of ROS and other defence-related molecules (Walters,

2003; Kusano et al., 2008).

23 Cholic Acid

Based on observations that the application of manure-based fertilizers can suppress disease in plants (Zinati, 2005), Koga et al. (2006) postulated that compounds present in animal feces would be capable of inducing defence responses in plants. To test this theory, fractions from a chemical extract of human feces were applied to rice leaves, followed by assessments of phytoalexin accumulation. Cholic acid, a primary bile acid in animals, was identified as a strong inducer of phytocassane phytoalexins. This acid was subsequently shown to increase the resistance of rice to infection by M. grisea through a cell death-associated response. There appeared to be significant specificity in the activity of cholic acid, because no other bile acid derivatives elicited this response with the same strength as cholic acid, and other known microbial elicitors induced the accumulation of different combinations of phytoalexins (Shimizu et al., 2008). The mechanism of cholic acid-induced resistance in plants in unclear, and while natural ligands of other bile acids have been identified in animals, a receptor for cholic acid has yet to be identified.

3-Acetonyl-3-hydroxyindole

Some resistance-inducing compounds have been isolated from surveys of non- agricultural plants. By screening chemical extracts from the ornamental Strobilanthes cusia for the induction of resistance to TMV in tobacco, Li et al. (2008) identified and purified the bioactive compound 3-acetonyl-3-hydroxyindole (AHO). This indole-type compound is a derivative of isatin, an auxin precursor (Applewhite et al., 1994). In addition to TMV, AHO protects tobacco from infection by the powdery mildew fungus 24 Erysiphe cichoracearum (Li et al., 2008). The mode of action of AHO remains to be fully characterized, but this chemical is known to induce PR-1 gene expression, PAL activity, and resistance to TMV in a SA-dependent manner. Furthermore, AHO induces

SA accumulation as well as the expression of other proteins associated with SA signalling, such as mitogen-activated protein kinases (MAPKs) and SA-induced protein kinases.

Cutin

In some cases, plant-derived defence elicitors are liberated as a consequence of pathogen invasion. Upon contact with leaf tissue, many phytopathogenic fungi produce an exudate that contains cutinase enzymes (Schafer, 1993). The activity of these enzymes releases cutin monomers from the plant cuticle which, if perceived by the host plant, could betray the presence of an invading pathogen. With this in mind, a variety of cutin monomers were tested on barley for their effectiveness in eliciting resistance to the powdery mildew fungus Erysiphe graminis (Schweizer et al., 1996). A number of monomers provided partial protection from infection and also displayed activity against

M. grisea on rice. Later studies indicated that cutin monomers stimulate ROS production (Kauss et al., 1999) and induce the expression of lipid transfer proteins

(LTPs) (Kim et al., 2008b). A cutin receptor has yet to be identified, but it is possible that cutin monomers may be perceived by affecting membrane structure and/or certain membrane-associated proteins (Douliez, 2004). Transduction of a cutin-induced signal may involve LTPs, some of which are known to be involved in long-distance signalling for the establishment of SAR (Maldonado et al., 2002). This mechanism is, however, purely speculative. 25 Large Molecules (>500 Da)

Polyacrylic Acid

There are significant parallels between the immune systems of plants and animals (Nurnberger et al., 2004; Iriti and Faoro, 2007) which may be exploited for the discovery of plant defence-inducing compounds. Given that certain synthetic polyanions stimulate the production of antiviral interferons (De Clercq et al., 1970),

Gianinazzi and Kassanis (1974) hypothesized that these compounds might also induce virus resistance in plants. Of various polymers tested, only polyacrylic acid (PA) was capable of enhancing resistance to TMV and tobacco necrosis virus in tobacco (Table

1-2). Resistance was not induced by polyacrylamide which, notably, did not stimulate interferon production in animal cells (De Clercq et al., 1970). Later studies indicated that small PA polymers (1,500 – 2,000 Da) also provided effective protection against

Colletotrichum lagenarium in cucumber, pelargonium leaf curl virus in Datura stramonium, as well as P. syringae pv. porri and tobacco ringspot virus in tobacco

(Mills and Wood, 1984; Ahl et al., 1985). In all cases, PA did not exhibit antimicrobial activity. With regards to the characterization of PA activity, analyses of crosses between different Nicotiana species revealed that PA responsiveness was inherited as a dominant trait distinct from the N gene, which encodes an R protein that determines

TMV resistance (Dumas et al., 1985). PA stimulates the production of SA, and PA- induced resistance to TMV is blocked in nahG plants and at high temperature (Malamy et al., 1996). While PA has been tested in other pathosystems (Ortega-Ortiz et al.,

2003), further mechanistic characterization has not been published.

26 Table 1-2: Large molecules (>500 Da) known to induce disease resistance in plants

Name Referencea

Gianinazzi and Kassanis, Polyacrylic acid 1974

Plant-derived oligosaccharides Oligogalacturonides Aziz et al., 2004 Cellodextrins Aziz et al., 2007 Galactoglucomannan-derived oligosaccharides Slovakova et al., 2000

Plant proteins Lipid transfer protein 1 - jasmonic acid complex Buhot et al., 2004

Microbe-associated molecular patterns Chitin/chitosan Hadwiger, 1979 Glucans Hodgson, 1969 Lipids Cohen et al., 1991 Lipopolysaccharide Graham et al., 1977 Peptides/Proteins flg22 (flagellin) Zipfel et al., 2004 elf18 (elongation factor Tu) Kunze et al., 2004 elicitins Bonnet et al., 1996 cellulose-binding elicitor lectin Gaulin et al., 2006 harpin Dong et al., 1999 peptaibols Kim et al., 2000 Sm1 (small protein 1) Djonovic et al., 2006 Epl1 Vargas et al., 2008 aRefers to initial observations of induced disease resistance in plants

27 Plant-derived oligosaccharides

The elicitation of plant defence responses by oligosaccharides is well- established (Shibuya and Minami, 2001). Hahn et al. (1981) first identified

“endogenous elicitors” as oligosaccharides from soybean, tobacco, sycamore, and wheat cell walls that induced the accumulation of phytoalexins. Aziz et al. (2004) specifically studied α-1,4-oligogalacturonides (OGA) as candidate plant protectants, and demonstrated that these molecules do increase the resistance of grapevine to B. cinerea infection. In treated leaves, OGA triggered the production of H2O2 and induced the expression of several defence-related genes including some PR genes. The induced resistance response was impaired in the presence of diphenylene iodonium, which is an inhibitor of NADPH oxidase, and the protein kinase inhibitor K252a, thus highlighting the importance of both the oxidative burst and protein phosphorylation for the protective effect. In Arabidopsis, OGA-induced resistance to B. cinerea is mediated by mechanisms independent of SA, JA, and ET signalling (Ferrari et al., 2007).

Cellodextrins, which are water-soluble derivatives of cellulose (β-1,4-linked glucoside residues), also protect grapevine from B. cinerea (Aziz et al., 2007). Like OGA, cellodextrins stimulate an oxidative burst and induce a similar set of defence-related genes, although the dynamics of these responses differ between the two stimuli, suggesting that they may be differentially perceived. Finally, oligosaccharides derived from galactoglucomannan significantly reduce the severity of disease symptoms caused by tobacco necrosis virus on cucumber (Slovakova et al., 2000). This response was accompanied by the accumulation of peroxidase enzymes and PR proteins.

28 Plant proteins

It is evident that there are a vast number of endogenous proteins involved in the mediation of plant defence responses, but the activity of exogenously-applied proteins is largely unexplored. One fascinating exception is the tobacco lipid transfer protein

LTP1 which, in a complex with JA, enhances the systemic resistance of tobacco to H. arabidopsidis (Buhot et al., 2004). Treatment of plants with LTP1 or JA alone did not induce resistance. As another example, AtPep1 is an endogenous Arabidopsis peptide that may be part of a positive feedback loop for innate immune signalling (Huffaker and

Ryan, 2007). Although the efficacy of exogenous AtPep1 treatment was not tested, ectopic expression of an AtPep1 propeptide in Arabidopsis provided significant protection from infection by Pythium irregulare (Huffaker et al., 2006).

Microbe-Associated Molecular Patterns

Over the course of an attempted infection, pathogens are in extremely close association with their hosts. This proximity provides the opportunity for pathogens to manipulate host metabolism for the release of nutrients, but at the same time brings the invader within range of the plant’s surveillance system. This system can perceive a wide variety of microbe-associated molecular patterns (MAMPs, also known as pathogen-associated molecular patterns or PAMPs), which are highly conserved structures that are essential for microbial fitness yet absent from potential hosts

(Nurnberger et al., 2004). These features provide an evolutionarily stable mechanism for the detection of “nonself” molecules by pattern recognition receptor (PRR) proteins.

The recognition of MAMPs activates a basal immune response that generally includes 29 MAP kinase signaling, callose deposition for cell wall reinforcement, ROS production, and the expression of defence-related genes (Chisholm et al., 2006; Nurnberger et al.,

2004). We discuss MAMPs in a separate section to illustrate the diversity and overall preponderance of potential defence-inducing molecules that are presented by microbes themselves, both pathogenic and nonpathogenic.

Chitin/Chitosan

Fungal cell walls often contain chitin, a β-1,4-linked N-acetylglucosamine polymer, and its deacetylated derivative chitosan. The elicitor activity of chitosan was first demonstrated in a screen of fungal cell wall components that were assayed for their ability to induce phytoalexin accumulation in pea pods and induce resistance to the fungal pathogen Fusarium solani (Hadwiger, 1979). Chitosan does exhibit some antifungal activity (Hadwiger and Beckman, 1980), but also stimulates several defence responses in plants, including production of PR proteins (Agrawal et al., 2002), lignification (Barber et al., 1989), increased lipoxygenase activity, and upregulation of

PAL (Trotel-Aziz et al., 2006). Chitin and chitosan are known to associate with plasma membranes (Baureithel et al., 1994), and a chitin-binding protein (CE-BiP) was recently identified in rice (Kaku et al., 2006). This protein contains two extracellular Lysin Motif

(LysM) domains and a transmembrane region, but lacks an obvious intracellular domain for signal transduction. Chitin-responsiveness assays were conducted on

Arabidopsis lines with T-DNA insertions in CE-BiP-related sequences, yielding a receptor-like kinase (CERK1/LysM1 RLK) whose knockout completely abolished chitin- induced responses (Miya et al., 2007; Wan et al., 2008). These knockouts also displayed increased susceptibility to A. brassicicola and Erysiphe cichoracearum, but 30 not P. syringae, illustrating the importance of chitin perception to resistance against fungal pathogens.

Glucans

Another group of oligosaccharides, the glucans (D-glucose polymers), can also activate plant immune responses. This was first observed with a β-1,3-linked D-glucan from P. infestans, which strongly inhibited the development of lesions in tobacco tissues inoculated with various viruses (Hodgson et al., 1969; Singh et al., 1970). It is interesting to note that tobacco was also protected from the soft rot pathogen Erwinia carotovora by laminarin, a linear β-1,3 glucan from the marine brown alga Laminaria digitata (Klarzynski et al., 2000). Laminarin also reduced the growth of B. cinerea and

Plasmopara viticola on grapevine leaves (Aziz et al., 2003). Host perception of laminarin induced multiple responses, including ion fluxes, an oxidative burst, activation of a MAPK cascade, callose deposition, phytoalexin production, and the expression of

PR genes (Aziz et al., 2003; Daxberger et al., 2007; Trouvelot et al., 2008). In both

Arabidopsis and tobacco, sulfated laminarin (PS3) provided greater local protection from TMV infection than did laminarin, and these glucans acted synergistically when used in combination (Menard et al., 2004; Menard et al., 2005). Notably, PS3 induced

SA accumulation and PR-1 expression, while laminarin did not. In terms of a mechanism of action, glucan-binding proteins (GBP) have previously been identified

(Mithofer et al., 1996; Umemoto et al., 1997). These proteins are composed of two domains, one with glucan binding activity, and the other showing similarity to fungal glucan endoglucosidase enzymes (Fliegmann et al., 2004). This structural arrangement would facilitate the release of elicitor molecules in close proximity to the 31 elicitor binding site for efficient MAMP detection. The GBP is likely part of a larger receptor complex, because GBP alone is essential but not sufficient for the glucan response.

Lipids

As a group, lipids are ubiquitous entities with diverse structural and biochemical roles. When applied exogenously to plants, certain lipids induce the accumulation of phytoalexins (Bostock et al., 1981). The induction of resistance was demonstrated by

Cohen et al. (1991), who noted a significant reduction in the symptoms of P. infestans infection on potato leaves sprayed with eicosapentanoic acid (EPA) or arachidonic acid

(AA). Pre-treatment of pearl millet seeds with EPA, AA, or docosahexanoic acid protected plants from the downy mildew pathogen Sclerospora graminicola, even at later developmental stages (Amruthesh et al., 2005). In addition to fatty acids, sphingolipids such as ceramides and cerebrosides induce resistance in a variety of plant-pathogen combinations (Koga et al., 1998; Deepak et al., 2003; Umemura et al.,

2004). These compounds stimulate ROS production, and there is some evidence that the intracellular balance between ceramides and their phosphorylated derivatives modulates programmed cell death in plants (Liang et al., 2003).

Ergosterol/Syringolin

Aside from fatty acids, a limited number of small molecule elicitors are derived from pathogens. Ergosterol is a component of fungal cell membranes that triggers

ROS production, ion fluxes, and phytoalexin accumulation in plants (Kasparovsky et al., 32 2003). Grape plantlets treated with ergosterol exhibited large reductions in the symptoms of disease caused by B. cinerea (Laquitaine et al., 2006). Another elicitor, syringolin, was isolated from P. syringae pv. syringae and characterized as a small peptide containing non-protein amino acids and an unusual ring structure (Waspi et al.,

1998). The virulence function of syringolin was recently found to involve inhibition of the host proteasome as a means of suppressing defence responses (Groll et al., 2008).

In plants that are nonhosts for P. syringae, however, purified syringolin induced resistance to the fungal pathogens B. graminis and Pyricularia oryzae (Waspi et al.,

1998; Waspi et al., 2001). In addition to a protective effect, syringolin also displayed curative activity in eliminating fungal populations from previously inoculated tissues.

This dramatic efficacy was not due to antifungal activity, but was associated with the induction of cell death and sustained accumulation of PR proteins.

Rhizobacteria-derived small molecules

Bacteria in the rhizosphere produce a variety of signals that stimulate ISR in the host plant. Characterization of the media in which Pseudomonas putida BTP1 was cultured revealed that an N-alkylated benzylamine derivative from this organism conferred systemic resistance to B. cinerea in bean plants (Ongena et al., 2005).

Preliminary analyses suggested that this compound induces the production of antifungal phytoalexins in treated plants. Iavicoli et al. (2003) used mutants of

Pseudomonas fluorescens CHA0 to demonstrate that the compound 2,4- diacetylphloroglucinol (DAPG) is important for ISR in Arabidopsis. Interestingly, stimulation of ISR by P. fluorescens is dependent on a functional NPR1 protein as well as JA and ET signaling, while DAPG-induced resistance requires only ET signaling. 33 Finally, the compound 2R, 3R-butanediol was isolated from a blend of volatiles collected from two rhizobacterial Bacillus species and shown to induce resistance to

Erwinia carotovora subsp. carotovora SCC1 in Arabidopsis (Ryu et al., 2004). This chemical was also recovered from Pseudomonas chlororaphis O6 in a screen for resistance-inducing volatiles using tobacco as a host (Han et al., 2006). The protection provided by 2R, 3R-butanediol is specific to this stereoisomer and is dependent on ET signaling.

Lipopolysaccharide

One MAMP that is specific to Gram-negative bacteria is the cell wall component lipopolysaccharide (LPS). A screen of Pseudomonas solanacearum cell fractions revealed that purified LPS conferred resistance to tobacco against P. solanacearum infection (Graham et al., 1977). Treatment with LPS may prime plants for a more rapid response to pathogen infection, as shown with Xanthomonas axonopodis on pepper plants, where the induced responses included PR gene expression and accumulation of phenolic compounds (Newman et al., 2002). In dicots, LPS prevents HR-associated programmed cell death during pathogen challenge, but appears to induce cell death in monocots even in the absence of a pathogen (Newman et al., 2000; Desaki et al.,

2006). The functional significance of this difference remains to be clarified. With regards to LPS perception, the LPS receptor in animal cells comprises a plasma membrane-bound, multiprotein complex that is endocytosed upon binding LPS

(Husebye et al., 2006; Miyake, 2006). Exogenous LPS binds to the plant cell wall and is internalized in a manner suggestive of receptor-mediated endocytosis (Gross et al.,

2005), but no proteins with significant sequence similarity to the components of the 34 LPS receptor are found in Arabidopsis (Newman et al., 2007). Interestingly, plants do possess receptors such as the R protein RPS4 which are structurally homologous to an intracellular LPS receptor found in mammals (Inohara and Nunez, 2003). Overall, though, the machinery of LPS detection and signalling in plants remains undefined.

Peptides/Proteins

A large number of MAMPs are peptides, regions of proteins not only associated with pathogen virulence, but also with general metabolism. Two of the most well- characterized MAMPs are located within the bacterial flagellin protein (flg22) and the translational elongation factor-Tu (elf18) (Felix et al., 1999; Kunze et al., 2004).

Infiltration of either peptide into the leaves of Arabidopsis plants greatly reduced their susceptibility to subsequent infection by a virulent strain of P. syringae (Kunze et al.,

2004; Zipfel et al., 2004). Both peptides are perceived by receptor-like kinase proteins that initiate a MAPK cascade leading to ROS production and callose accumulation

(Gómez-Gómez and Boller, 2000; Nurnberger et al., 2004; Zipfel et al., 2006).

Elicitins are small (98 amino acids, ~10 kDa) proteins secreted by Phytophthora and Pythium spp. that activate a broad-spectrum, systemic resistance response when applied to plants (Bonnet et al., 1996; Capasso et al., 1999; Benhamou et al., 2001;

Baillieul et al., 2003). This response may include the induction of ion fluxes, callose deposition, and accumulation of a calcium pectate gel in the intercellular spaces of parenchyma cells (Lherminier et al., 2003). Upstream of these responses, elicitins bind sterols, acting as a type of LTP (Osman et al., 2001). Buhot et al. (2001) identified a plasma membrane receptor whose binding to a plant LTP can be competed out by elicitin, suggesting a possible elicitin receptor. 35 Another Phytophthora protein, a cellulose-binding elicitor lectin (CBEL), was shown to protect tobacco from infection by a virulent strain of H. arabidopsidis (Gaulin et al., 2006). The ability of this 34 kDa protein to elicit necrosis and expression of defence-related genes in plants depends on two cellulose-binding domains within

CBEL (Villaba-Mateos et al., 1997).

Originally identified in Erwinia amylovora, harpins are acidic, glycine-rich, heat- stable proteins that induce a HR in many plants (Wei et al., 1992). Exogenously applied harpin induces resistance in numerous pathosystems (Reignault and Walters,

2007). In Arabidopsis, harpin-induced resistance to H. arabidopsidis and P. syringae is

SA- and NPR1-dependent, but JA- and ET-independent (Dong et al., 1999). A harpin receptor is not known, but expression profiling of harpin-treated tobacco cell suspensions identified a harpin-responsive receptor-like kinase gene that may play a role in harpin perception (Sasabe et al., 2007).

In many fungi, non-ribosomal peptide synthetases generate peptaibols, short

(≤20 amino acids) peptides which frequently contain α-amino isobutyric moieties and modified termini (Grigoriev et al., 2003). Although generally characterized as antibiotics (Szekeres et al., 2005), peptaibols can also induce resistance in plants independently of this activity. A 19-mer peptaibol from Apiocrea chrosospermin conferred resistance to TMV in tobacco (Kim et al., 2000), while Trichoderma virens produces an 18-mer peptaibol that significantly reduced the growth of P. syringae on cucumber seedlings (Viterbo et al., 2007). This systemic resistance response involved the induction of defence-related genes such as hydroperoxide lyase, PAL, and peroxidase, although the mechanism of activation remains unknown.

T. virens also produces Sm1 (small protein 1), a 12.6 kDa protein that belongs to the ceratoplatanin family (Djonovic et al., 2006). Sm1 triggers an oxidative burst but 36 not cell death, and the treatment of cotton cotyledons with this protein provides significant protection from infection by a Colletotrichum sp. pathogen. An Sm1 homologue from T. atroviride, Epl1, induces systemic resistance to Colletotrichum graminicola in maize (Vargas et al., 2008).

Finally, it is worth noting the peptides and peptide-associated MAMPs that stimulate plant defence responses, but have not yet been shown to induce disease resistance when applied exogenously. These include peptidoglycan (Gust et al., 2007),

Pep-13 from a transglutaminase (Brunner et al., 2002), cold-shock protein (Felix and

Boller, 2003), xylanase (Ron and Avni, 2004), invertase (Basse et al., 1993), and necrosis-inducing peptides (Fellbrich et al., 2002; Qutob et al., 2006). Interestingly, ectopic expression of a yeast invertase in tobacco significantly reduced its susceptibility to potato virus Y (Herbers et al., 1996). Given the induction of resistance by a significant number of MAMPs, the molecules listed above would be prime candidates for testing exogenously in a model pathosystem.

High-Throughput Chemical Genetics in Plant Pathology

In a very general sense, the quest for novel sources of enhanced disease resistance in plants relies heavily on chemical and/or genetic variation. Classically, the genes responsible for pathogen defence have been interrogated in genetically variable populations of plants generated by techniques such as chemical mutagenesis, transposon insertion (for gene disruption and/or activation), fast neutron bombardment, and ion irradiation (Li et al., 2001; Alonso et al., 2003; Shikazono et al., 2005; Waugh et al., 2006). A relatively new approach is that of chemical genetics (or chemical genomics), in which small molecules are used as biological perturbants to modulate a 37 phenotype of interest (Stockwell, 2000). This strategy offers a number of advantages, including the capability to reversibly modulate phenotypes in a dose-dependent manner and the potential for influencing the activity of structurally similar, functionally redundant protein families (Stockwell, 2004; Kawasumi and Nghiem, 2007; Smolinska et al.,

2008). As with classical genetics, there are two main approaches to screening small molecules. Forward chemical genetics involves screening through collections of small molecules and identifying those that cause a specific phenotype in the test population, eventually working towards identifying the biological ligand of that chemical. In contrast, reverse chemical genetic approaches endeavour to identify chemical ligands of a specific biological target, followed by analyses of the phenotype induced by those small molecules at the organismal level. It should be evident from this review that there is a long history of forward chemical genetic screening for inducers of disease resistance, although most of these studies have only evaluated small sets of selected compounds. Many “modern” forward chemical genetic screens utilize large numbers of compounds in an effort to modulate as many targets as possible, akin to the saturation of a classical genetic screen. Extensive small molecule collections are commercially available for such genome-wide surveys, and many of these libraries have been assembled from compounds with “drug-like” properties to maximize their potential biological activity (Baurin et al., 2004). The capability to screen such large numbers of chemicals depends on the development of a high-throughput pathology assay, which in turn requires the consideration of several important issues.

38 Design of a High-Throughput Screen

The experimental design of a high-throughput assay is strongly influenced by the objective of the screen. If the goal is to modify a specific plant signalling pathway, then the phenotype used for identifying positive results (hits) could be the expression of a certain reporter gene or the accumulation of a specific protein. For example, the ability of various chemicals to induce the expression of specific PR proteins has been surveyed in the past (Asselin et al., 1985). More recent screens have employed a β- glucuronidase reporter gene fused to the promoters of MAMP- or infection-responsive genes in order to identify small molecules that either activate or inhibit specific defence responses (Serrano et al. 2007; Knoth et al., 2009). In this case, expression of the reporter gene can be monitored either histochemically or by quantitative fluorimetry.

This type of screen can yield valuable insight into the signalling pathways that coordinate defence responses, but it may also identify compounds that do not necessarily have an immediate function in disease resistance. In order to incorporate all pathways leading to effective disease resistance, it may be more appropriate to assess the general phenotype of a whole organism. This approach has been successfully adopted to identify antifungal compounds in the Caenorhabditis elegans-

Candida albicans pathosystem (Breger et al., 2007), and presumably could be extended to bacterial pathogens as well (Aballay and Ausubel, 2002). In addition, a number of other well-characterized hosts are amenable to studies of chemical interference with microbial pathogenesis (Mylonakis et al., 2007). In most cases, the phenotypic endpoint is the death or survival of the host, although assessments of microbial proliferation can supplement these observations.

39 For screening disease resistance in plants, defining the phenotype to be evaluated is of fundamental importance. If the screen is intended to generate a commercial crop protectant, then major consideration should be given to the most economically relevant characteristics such as yield and crop quality. On the other hand, high-throughput analyses prioritize economy of time and space, and the maintenance of vast populations of plants over their entire growing season is generally impractical. As such, the main challenge for this type of screen involves defining a phenotype that will serve as an accurate surrogate for final yield/product quality. This is not a trivial task because, although pathogen infection and yield loss are correlated in a general sense, the connection between disease symptoms and yield can be more difficult to establish (Gaunt, 1995). Complications arise from the variety of factors that contribute to yield as well as the many epidemiological variables that influence disease progression. As such, single assessments of disease symptoms may provide insufficient predictive power for estimates of yield, especially if made at a relatively early developmental stage. In the end, a practical compromise may be to select an obvious infection phenotype for a primary screen, and subsequently assess yield benefits in a secondary screen. We have developed a high-throughput assay in which

Arabidopsis seedlings are grown in liquid media in 96-well plates (Chapter 2).

Inoculation of seedlings with virulent P. syringae results in the eventual bleaching of cotyledons, while cotyledons remain green in the presence of non-virulent strains.

Furthermore, molecules known to induce defence in Arabidopsis, such as SA and the flg22 peptide, also protect seedlings from bleaching. This phenotype is closely associated with the level of bacterial growth within seedling tissues. For screening purposes, cotyledonary bleaching is a relatively straightforward phenotype to evaluate, and is sensitive enough that compounds that confer partial protection from infection can 40 be identified. We have not yet verified the correlation between bleaching and yield, but importantly, compounds that prevent bleaching in seedlings also significantly reduce bacterial growth in adult Arabidopsis plants.

The diversity of structures and potential activities of small molecules implies that compromises may need to be made in other aspects of the screen. Ideally, every compound would be tested at multiple concentrations to generate a dose-response curve for the screening phenotype. For libraries containing thousands of chemicals, this approach would necessitate significant automation of the screening process and the capacity for analyzing massive amounts of data. Where such resources are not available, one or two concentrations (usually in the low micromolar range) can be tested with the acceptance of a certain rate of false negatives. The timing of chemical application and pathogen inoculation is another variable to consider. The activation or priming of plant defence may require some amount of time before plants are “ready” to combat infection (Gianinazzi and Kassanis, 1974; Conrath et al., 2006). As an example, SA and SA analogues induce PR gene expression within four to twelve hours of treatment, concomitant with the induction of disease resistance (Ward et al., 1991;

Lawton et al., 1996; Lebel et al., 1998) Screening at multiple time-points after chemical treatment would be the most comprehensive approach in order to identify the optimal priming time. Finally, the manner in which chemicals are applied will influence the output of the screen. In this review, we have described screens that introduced compounds through seed soaking, soil drenches, supplementation of growth media, foliar sprays, and direct infiltration of tissues. While it may be desirable to screen compounds in a context similar to what occurs in the field, logistics and practicality may limit the screen to a particular plant developmental stage or specific growth conditions that in turn dictate the use of a different approach. Again, compounds yielding positive 41 results in the primary screen could be analyzed in secondary screens that more closely mimic field conditions.

Having determined the inputs for a screen, it is also necessary to consider the output of this experiment. If the screen is based on the expression of a reporter gene, quantification of the reporter should be relatively straightforward. For a phenotype- based pathosystem screen, a chemical that induces resistance to infection would confer a phenotype that deviates significantly from an untreated control. The results of this type of screen are less simple to interpret, as hits will be defined by an arbitrary threshold of what constitutes a “significant” difference in the form of protection from pathogen infection. The reproducibility of results will strongly influence where this threshold can be set.

Characterization of Hits

Once hits are identified in a screen, numerous analyses can be performed in order to understand the mechanism of action of these chemicals. Alterations of pathosystem behaviour can arise from chemically-induced effects on either the plant or the pathogen (or possibly both), so it is important to first differentiate where a compound is acting. Direct antimicrobial activity can be assessed by a simple growth assay, although this may be difficult for some biotrophic fungi and oomycetes. In the absence of antimicrobial effects, a compound may be affecting some aspect of pathogen virulence. Interference with the secretion of virulence effector proteins could be evaluated in media that normally stimulate effector production, or by co-infiltrating plants with the compound and an avirulent pathogen that normally triggers an effector- dependent hypersensitive response HR. Microscopic analysis may reveal chemically- 42 induced effects on pathogen motility, or morphological changes such as reduced germ tube or appresorium formation (Geissler and Katekar, 1983; Pontzen and Scheinpflug,

1989; Oh and Lee, 2000).

On the other side of the pathosystem, the chemical of interest may be inducing a response in the plant. The entry of pathogens into host tissues could be blocked if the compound stimulated the closure of stomata, which could be ascertained microscopically. If pathogen entry is unaffected, then resistance may arise from the stimulation of active plant defence mechanisms. Here, analyses could focus on the expression of PR and other defence-related genes, ROS production, and callose deposition. The dependence of chemically-induced resistance, and possibly specific defence responses, on certain signalling pathways can also be determined. A large number of Arabidopsis mutants have been identified that disrupt signalling mediated by specific molecules (Kazan and Schenk, 2007; Robert-Seilaniantz et al., 2007). While these mutants can provide valuable information on the pathways being manipulated by a defence-inducing chemical, they usually cannot reveal direct molecular targets. The assembly of a more precise functional picture requires the identification of cellular target(s) that is (are) directly affected by the chemical.

Target Identification

Several different tools are available to assist in the search for biological ligands of small molecules, generally assumed to be proteins. A biochemical approach may be taken, in which the compound of interest is covalently linked to a solid substrate for affinity purification of interacting proteins from a crude cell extract (Zheng et al., 2004).

This requires the introduction of a reactive linker into the chemical, which must then be 43 retested and possibly redesigned to ensure that the modification does not interfere with the compound’s activity. The development of tagged libraries eliminates the need for these structure-activity optimization steps (Inverarity and Hulme, 2007; Kim and Chang,

2007), but most available libraries do not have this feature. Overall, affinity purification can demonstrate physical associations with potential physiological relevance, but the technique often suffers from the recovery of background contaminants, especially when the affinity of the chemical for its protein ligand is low (Zheng et al., 2004).

An alternative approach for target identification is based on genetic analyses.

Assuming that the chemical of interest inhibits the activity of its protein ligand, then inactivation of the corresponding gene should phenocopy the effects of the chemical. If the chemical is phytotoxic at some concentration, loss-of-function mutants could be obtained from a mutagenized population of plants that is screened for insensitivity to the compound. These mutants would be expected to show enhanced resistance to pathogen infection even in the absence of the compound. Even if the chemical actually stimulates rather than inhibits protein activity, these mutants remain informative as susceptible hosts whose infection cannot be prevented by the selected small molecule.

It is important to note that the mutated genes identified in either scenario may not encode actual ligands, but rather a downstream signalling component or a protein that contributes to the stability, uptake, or activity of the chemical (Dai et al., 2005; Zhao et al., 2007). Nonetheless, this approach has proven extremely useful in characterizing the activity of compounds such as BABA and the herbicide DAS734 (Ton et al., 2005;

Walsh et al., 2007). Another genetic approach could utilize analyses of gene expression in chemically-treated versus untreated plants to indicate the global transcriptional response to the chemical. The inclusion of transcriptomic data from infected plants would further enhance this analysis by identifying genes whose 44 expression is altered in opposite directions in treated versus infected plants. Again, a chemical target may not be made immediately apparent through this exercise, but the metabolic pathways and processes influenced by the compound will be clarified. Some more specific tools are available in other model organisms such as yeast, where large collections of hetero- and homozygous deletion mutants can be screened for increased sensitivity to a chemical (Giaever et al., 1999; Parsons et al., 2004). This avoids the task of mapping mutations in plants, but relies on the assumption that an orthologue of the plant target exists in yeast. The cumulative output of these approaches may be a small list of candidate targets which must be verified by additional biochemical and genetic tests. Overall, target identification is not a trivial task, and protein ligands are known for only a few of the small molecules described in this review: SA, INA, and

BTH. These molecules interact with multiple SA-binding proteins that each influence specific aspects of SA signalling (Vlot et al., 2009), thus cautioning that identification of a single target may not provide a complete picture of the mechanism of action of a given chemical.

General Issues for Induced Disease Resistance in Agriculture

The successful application of crop protectants in a field setting depends on an additional set of factors. While the vast majority of small molecules found in libraries have been pre-selected for drug-like qualities, many natural products do not meet these criteria. A hydrophilic molecule like trehalose, for example, cannot easily penetrate the cuticle of plant leaves, thus requiring relatively high concentrations in order to have an effect on disease resistance (Reignault et al., 2001). Some of these natural products can be chemically modified to enhance their activity, as demonstrated by the efficacy of 45 sulfated laminarins over their unmodified form (Menard et al., 2004). Other molecules, such as heavy metals, may display strong activity, but are ecologically unsafe for wide release into the environment.

In the transition of candidate compounds from the laboratory to the field, efficacy is certainly a central concern. Environment, plant genotype, and plant nutrition can dramatically affect the induction of disease resistance (Walters et al., 2005), and an ideal chemical should maintain its efficacy in plants cultivated under a range of growth conditions. Since agricultural equipment is often not perfectly calibrated, chemical activity should be relatively consistent within a certain margin of application error, especially for hormetic phytotoxins. Beyond agronomic practicality, defence-inducing compounds must ultimately be economically feasible options for crop protection, minimizing yield losses to an extent that would be judged favourably in cost-benefit analyses.

The costs and benefits of induced disease resistance should also be weighed at a biological level. The activation of plant defence machinery requires a reallocation of some resources, possibly to the detriment of processes such as seed production (Heil and Baldwin, 2002). In the presence of pathogen infection, this response provides a net benefit to plant fitness, but may be more punitive when pathogens are absent. This is vividly illustrated by the stunted phenotype of mutants that constitutively express defence-related genes (Bowling et al., 1994). Chemical induction of plant defences provides some temporal control over the deployment of resources, but there still may be fitness costs in the absence of significant infection (Heil et al., 2000; Cipollini, 2002).

As such, chemicals that prime plant defences may provide the greatest overall fitness benefit (van Hulten et al., 2006). As an aside, Kover and Schaal (2002) observed that different ecotypes of Arabidopsis varied in the impact of bacterial infection on seed 46 yield. This was attributed to variations in “tolerance” of infection, as a phenomenon separate from R gene-mediated resistance mechanisms. While virtually unexplored as a factor affecting fitness, the influence of small molecules on tolerance could be another mechanism for the prevention of disease-related yield losses.

Conclusions and Future Perspectives

In this review, we have described a structurally diverse array of molecules that are capable of inducing disease resistance in plants, likely through equally diverse mechanisms. A vast amount of chemical space remains to be explored, and high- throughput assays will feature prominently in this exploration. The design of such assays is not trivial, but it should be centered on a salient infection phenotype that is dependent on pathogen virulence and reversible by known inducers of plant defence.

The identification of hits in this assay is only the beginning of a long path of discovery with regards to a molecule’s biological target and mechanism of action.

Advances in this field have been, and will continue to be, driven by the introduction of additional analytical tools and resources. The activity of compounds in different ecotypes or cultivars can reveal pharmacogenomic variation, which not only provides another avenue for target identification, but also generates valuable data on the structural aspects that influence protein-ligand interactions (Zhao et al., 2007).

Future screens may also move beyond small molecules to include searches for bioactive peptides. An immense number of possible sequences exist even for small peptides, and the introduction of modifications such as glycosylation or phosphorylation would expand this number further. The commercial release of Messenger® (Eden

Bioscience Corp., USA; Jones, 2001), a formulation of harpin protein, illustrates the 47 utility of proteinaceous elicitors as crop protectants. Overall, plants are amazingly well- equipped to combat pathogen attacks, but would be assisted by a message to prepare their defences in advance of these assaults. Chemicals and other molecules can deliver that message, working with the plant’s own defensive resources to generate an effective resistance response.

48 Thesis Overview

The initial objective of this thesis project was to develop an assay for high- throughput analyses of plant-pathogen interactions conducive to forward chemical genomic screens. I first established this assay with the Arabidopsis-Pseudomonas syringae pathosystem, characterized infection phenotypes in detail, and demonstrated the suitability of this setup for chemical screening (Chapter 2 and Appendix 1). The assay was later extended to the Arabidopsis-Fusarium graminearum pathosystem, whose characterization is described in Chapter 3. With these tools in place, I was able to address a second objective focused on the identification of small molecules that protect Arabidopsis seedlings from pathogen infection. Chemical libraries were screened against both of these pathosystems, as summarized in Appendices 2 and 3.

Interestingly, the compound sulfamethoxazole (Smex) reduced the susceptibility of

Arabidopsis seedlings to both P. syringae and F. graminearum (Chapters 2 and 3).

Subsequent efforts to characterize the activity of Smex in Arabidopsis are described in

Chapter 4, with supplementary data provided in Appendices 4 and 5.

In parallel to chemical genomic investigations of host resistance, I also performed forward genetic screens in P. syringae. Transposon disruptants of P. syringae pv. maculicola ES4326 were screened either for reduced virulence in the liquid assay (Appendix 6) or for a failure to downregulate flagellar motility under conditions that induce P. syringae virulence mechanisms (Appendix 7). One of the disruptants identified in the motility screen also exhibited impaired virulence, and the further characterization of this diruptant is described in Appendix 8.

49

Chapter 2 A High-Throughput Chemical Screen for Resistance to Pseudomonas syringae in Arabidopsis

Previously published as: A high-throughput chemical screen for resistance to Pseudomonas syringae in Arabidopsis Karl J. Schreiber, Wenzislava Ckurshumova, James Peek, and Darrell Desveaux (2008) Plant Journal 54, 522-531

Author contributions: K.J.S. performed most of the experiments and wrote the manuscript with input and direction from D.D. W.C. performed some of the microscopy to characterize the Arabidopsis thaliana-Pseudomonas syringae pathosystem and J.P. assisted with chemical screening.

50 Abstract

The study of plant pathogenesis and the development of effective treatments to protect plants from diseases could be greatly facilitated by a high-throughput pathosystem to evaluate small molecule libraries for inhibitors of pathogen virulence.

The interaction between the Gram-negative bacterium Pseudomonas syringae and

Arabidopsis thaliana is a model for plant pathogenesis. However, a robust high- throughput assay to score the outcome of this interaction is currently lacking. We demonstrate that Arabidopsis seedlings incubated with P. syringae in liquid culture display a macroscopically visible “bleaching” symptom within five days of infection.

Bleaching is associated with a loss of chlorophyll from cotyledonary tissues and is correlated with bacterial virulence. Gene-for-gene resistance is absent in the liquid environment, possibly due to suppression of the hypersensitive response under these conditions. Importantly, bleaching can be prevented by treating seedlings with known inducers of plant defence such as salicylic acid (SA) or a basal defence-inducing peptide of bacterial flagellin (flg22) prior to inoculation. Based on these observations, we have devised a high-throughput liquid assay using standard 96-well plates to investigate the P. syringae-Arabidopsis interaction. An initial screen of small molecules active on Arabidopsis revealed a family of sulfanilamide compounds that afford protection against the bleaching symptom. The most active compound, sulfamethoxazole, also reduced in planta bacterial growth when applied to mature soil- grown plants. The whole-organism liquid assay provides a novel approach to probe chemical libraries in a high-throughput manner for compounds that reduce bacterial virulence in plants.

51 Introduction

The interaction of pathogenic organisms with their hosts involves a number of dynamic and complex molecular events. A model for the study of plant-pathogen interactions is found in Arabidopsis thaliana and the Gram-negative bacterium

Pseudomonas syringae. This pathogen generally enters host tissues through openings such as wounds or stomata and multiplies in the apoplast (Underwood et al., 2007).

Infection of Arabidopsis by P. syringae invokes a two-branched innate immune system

(Jones and Dangl, 2006). In one branch, host cell receptors detect conserved pathogen-associated molecular patterns (PAMPs) such as flagellin and subsequently activate a basal defence program (Zipfel et al., 2004). Effector proteins delivered by the bacterial type III secretion system (TTSS) can suppress these basal responses to facilitate infection (Nomura et al., 2005). In the second branch of plant innate immunity, host resistance (R) proteins can perceive these pathogen-induced perturbations and counteract with a programmed cell death, or hypersensitive response (HR) (Dangl and

Jones, 2001). In turn, certain type III effectors can subsequently block R gene- mediated defences and restore bacterial virulence (Jamir et al., 2004; Kim et al., 2005).

While many aspects of the battle between pathogen virulence and host resistance have been studied in this system, it is evident that a great deal is still unknown.

Chemical genetics aimed at identifying small bioactive molecules provides a powerful method to probe biological systems with numerous advantages over classical forward genetic screening (Stockwell, 2004). Whole-organism, high-throughput pathosystems enable the screening of large libraries of chemical compounds for small molecules that alter pathogen virulence (Breger et al., 2007). An important advantage of whole-organism screens is that host, pathogen, and antimicrobial compound can be 52 simultaneously interrogated (Mylonakis et al., 2007). Such a system for plant pathogenesis could significantly accelerate the identification of small molecules that afford plants protection against disease. For plant-pathogen interactions, large-scale studies are currently limited by the time and space required for plant growth as well as the lack of a facile yet robust method to apply small molecules and pathogens to plants and monitor the infection process in a high-throughput manner.

In this study, we describe a rapid, high-throughput system for the study of

Arabidopsis-P. syringae interactions performed in standard 96-well plates. The plants are grown in liquid facilitating the uniform application of chemicals from small molecule libraries, similar to the system recently developed to identify small molecules that interfere with cellulysin- or flg22-activated gene expression in Arabidopsis (Serrano et al., 2007). Using this pathosystem, we have initiated a chemical screen for small molecules that modulate the susceptibility of Arabidopsis to infection by P. syringae.

Since the assay monitors for healthy plants, compounds that are harmful to the host are selected against. We have also designed a set of downstream analyses to broadly characterize what aspect of the interaction is affected by a given compound. This system will be a valuable addition to the collection of whole-organism model pathosystems already in use for high-throughput analyses (Mylonakis et al., 2007). The screen’s agriculturally relevant endpoint of protecting seedlings from infection promises to identify compounds that can be used for the development of effective treatments to control plant diseases and potentially influence bacterial pathogenesis in general.

53 Results and Discussion

Establishment of a high-throughput Arabidopsis-P. syringae pathogenicity assay

One of the challenges of interrogating plant-pathogen interactions is the capability to do so in a high-throughput manner. In response to this, we have developed a liquid assay with which to rapidly assess a large number of conditions that may affect the infection of Arabidopsis seedlings by P. syringae. Initially, it was necessary to characterize the infection phenotype in this environment. In the liquid format, the cotyledons of Arabidopsis (Col-0) seedlings inoculated with a virulent strain of P. syringae become bleached over a period of four to five days post-inoculation

(Figure 2-1A-F). This bleaching is reminiscent of the chlorosis that develops on the rosette leaves of mature plants following infection with P. syringae pv. tomato DC3000

(Pto DC3000; Whalen et al., 1991; Frye and Innes, 1998), and can also be observed on the true leaves of larger seedlings inoculated with virulent P. syringae strains in liquid media (Bais et al., 2005). Macroscopic bleaching became visible after three days but was most evident after four days. By five days, essentially 100% of the seedlings were bleached. Bleaching was also visualized as the loss of chlorophyll fluorescence which was apparent microscopically at two days post-infection (Figure 2-1G-L). The loss of fluorescence consistently begins within the distal secondary vein loop (Figure 2-1S) and eventually includes the entire cotyledon by four days post-infection. Inoculation with Pto DC3000 expressing green fluorescent protein (Pto DC3000 + GFP) revealed that bacteria accumulate on the surface of cotyledons over time (Figure 2-1M-R). More importantly, the number of bacteria in the intercellular spaces of cotyledonary mesophyll tissue also increased over the same timeframe (Figure 2-1M-R inset; Figure 54

55 Figure 2-1: Phenotype of Arabidopsis seedlings inoculated with Pto DC3000 in liquid media.

(A-F) Brightfield microscopy of wholemount seedlings, illustrating the bleaching phenotype used in the screen. Timescale is given in hours post-inoculation (hpi).

Insets show a representative cotyledon. Scale bars indicate 1 mm.

(G-L) Progression of chlorophyll degradation in infected cotyledons. Red, chlorophyll fluorescence. Nearly complete chlorophyll loss in (K), (L). Lower left: fraction of cotyledons showing pattern almost identical to the image provided. Scale bars indicate

500 µm.

(M-R) Fluorescence microscopy of seedlings. Green, Pto DC3000+GFP; red, chlorophyll fluorescence. Lower right: fraction of seedlings showing pattern almost identical to the image provided. Insets show a representative view of bacteria found in intercellular spaces of cotyledon mesophyll tissue within the distal secondary vein loops; see also (s). Scale bars indicate 1 mm, insets 125 µm.

(S) “i” and “ii” indicate the distal secondary loops where mesophyll pictures were taken.

(T) Intercellular counts of fluorescent spots / mm² counted from mesophyll pictures of seedlings inoculated with Pto DC3000+GFP. “n” indicates the number of mesophyll pictures counted in one experiment. Error bars represent the standard deviation from the mean of each set of “n” mesophyll pictures. The experiment was repeated twice with similar results.

(U) Quantitation of Pto DC3000 population growth within seedlings (bars) and in the surrounding liquid media (solid line). Seedlings were surface-sterilized prior to analysis. Day 0 samples were collected at two hours post-inoculation. Error bars represent the standard deviation from the mean of five samples.

56 2-1T). The results of this visual analysis were corroborated by quantitation of bacterial populations in surface-sterilized seedlings (See Experimental Procedures; Figure 2-

1U). Significant levels of bacteria are recovered from surface-sterilized seedlings two hours post-inoculation (Day 0) suggesting that bacteria have already entered the plant tissue in this short period of time. However, we cannot rule out the possibility that some surface-localized bacteria that resisted the surface sterilization procedure may contribute to this initial count. Bacterial abundance increases 1,000- to 10,000-fold over a four-day period and appears to be maximal at four days post-inoculation, after which weakening/collapse of the tissue is associated with a loss of bacteria and thus lower counts (data not shown). While the abundance of Pto DC3000 is correlated with the bleaching of cotyledons, we sought to determine whether this phenotype was a consequence of bacterial virulence.

Arabidopsis seedlings in liquid media were inoculated with either Pto DC3000,

P. syringae pv. maculicola ES4326 (Pma ES4326), P. syringae pv. phaseolicola 1448A

(Pph 1448A), or the hrcC mutant of Pto DC3000 (Pto DC3000 hrcC). Like Pto DC3000,

Pma ES4326 is virulent on Arabidopsis (Davis et al., 1991), and also caused the bleaching of infected cotyledons over four to five days (Figure 2-2). Pph 1448A is a non-host pathogen of Arabidopsis, while Pto DC3000 hrcC lacks a functional type III secretion system such that virulence effector proteins cannot be injected into host cells

(Yuan and He, 1996). Importantly, the cotyledons of seedlings inoculated with these strains remained green, even beyond seven days post-inoculation. Furthermore, Pto

DC3000 and Pma ES4326 multiplied to 1 x 106 cfu within seedling tissues whereas

Pph 1448A and Pto DC3000 hrcC were nearly 100-fold less abundant at three days post-inoculation (Figure 2-2I). Overall, the bleaching phenotype is dependent on the

57

58 Figure 2-2: Phenotypes of Arabidopsis seedlings inoculated with various strains of P. syringae in liquid media.

Seedlings were inoculated with Pto DC3000 expressing GFP (“DC3000+GFP”), P. syringae pv. maculicola ES4326 (“ES4326” – virulent on Arabidopsis), P. syringae pv. phaseolicola 1448A (“1448A” – a non-host strain on Arabidopsis), or Pto DC3000 hrcC

(“DC3000 hrcC” – a type III secretion-deficient Pto DC3000 mutant).

(A-D) Brightfield microscopy of wholemount seedlings four days post-inoculation, illustrating the bleaching phenotype used in the screen. Insets show a representative cotyledon. Lower left: fraction of seedlings showing pattern almost identical to the image provided. Scale bars indicate 1 mm.

(E-H) Chlorophyll fluorescence of cotyledons at four days post-inoculation. Lower left: fraction of seedlings nearly identical to the image provided. Scale bars indicate 500µm.

(I) Quantitation of bacterial populations within seedlings (bars) and in the surrounding liquid media (lines) following inoculation with various strains of P. syringae. Error bars represent the standard deviation from the mean of five samples. Asterisks indicate bacterial populations within seedlings significantly different from Pto DC3000 as determined by a Student’s t-test (α=0.05).

59 type III secretion system of P. syringae, and is associated with significant growth of bacterial populations within seedling tissues.

To further characterize this pathosystem we examined whether gene-for-gene- mediated resistance could be monitored. Arabidopsis seedlings inoculated with Pto

DC3000 expressing the avirulence genes AvrRpt2, AvrRpm1, or AvrB did not display an observable hypersensitive response (HR) as observed in adult soil-grown plants and exhibited bleaching over the same timeframe as seedlings inoculated with Pto DC3000 lacking the avirulence proteins. Furthermore, the growth of Pto DC3000 expressing these avirulence genes was not significantly reduced relative to virulent Pto DC3000

(Appendix 1). This suggests that gene-for-gene resistance and the corresponding HR are not manifested in seedlings grown in liquid media. This is not altogether unexpected, given that the maintenance of soil-grown plants under conditions of high humidity or low oxygen can delay or entirely suppress the HR normally associated with gene-for-gene resistance responses (Hammond-Kosack et al., 1996; Mittler et al.,

1996; Wang et al., 2005). Furthermore, enhanced resistance was not observed in the

Arabidopsis mutants constitutive expressor of pathogenesis-related (PR) genes 22

(cpr22), cpr1, cpr5 or the “defence, no death” mutant (dnd1) (Appendix 1). Features shared by these mutants include elevated levels of salicylic acid (SA), constitutive expression of one or more PR genes, and enhanced disease resistance. While cpr5 and cpr22 are lesion-mimic mutants, spontaneous cell death occurs only under certain conditions in dnd1 and not at all in cpr1 (Bowling et al., 1994; Yoshioka et al., 2001; Yu et al., 1998; Clough et al., 2000; Kirik et al., 2001). Importantly, however, conditions of high humidity significantly reduced the accumulation of SA and eliminated PR-1 gene expression, spontaneous cell death, and enhanced resistance in cpr22 plants

(Yoshioka et al., 2001; K. Yoshioka, personal communication). A similar phenomenon 60 was also observed for the lesion mimic mutant ssi4 (Zhou et al., 2004). While the molecular mechanisms that underlie humidity-dependent resistance phenotypes are not yet defined, we speculate that continuous immersion in liquid also eliminates the enhanced disease resistance phenotype that characterizes the family of cpr mutants.

In order to assess the amenability of the pathosystem for chemical screening for disease resistance, we evaluated the effects of salicylic acid (SA) and the flg22 peptide, which are known inducers of plant defence. Treatment of seedlings with 25

μM SA prior to inoculation with Pto DC3000 provided protection from bleaching (Figure

2-3A-H) and significantly reduced the bacterial populations within seedlings (Figure 2-

3I). This protective activity was eliminated in the nahG mutant, which expresses a salicylate hydroxylase gene that converts SA to the inactive molecule catechol

(Delaney et al., 1994). The addition of SA provided slight yet significant protection of npr1-1 seedlings (Figure 2-3I). The reduction in bacterial growth, however, was insufficient to prevent the bleaching of the cotyledons (Figure 2-3D). Although npr1-1 mutants lack a key component in the SA signalling pathway (Cao et al., 1994), plant defence responses can be induced by SA in an NPR1-independent manner (Clarke et al., 1998). The NPR1-independent, SA-dependent defences reduce bacterial growth in the liquid pathosystem but are insufficient to prevent bleaching, suggesting that there may be a threshold of bacterial growth at which bleaching occurs. In the absence of

SA, bacterial growth in nahG and npr1-1 seedlings was higher than in Col-0 seedlings at two days post-inoculation, indicating increased susceptibility to pathogen infection

(data not shown). This difference was less evident by the third day after inoculation, possibly due to a plateau in bacterial growth within seedlings. Therefore, salicylic acid- mediated resistance can be induced in the liquid assay and prevents Pto DC3000-

61

62 Figure 2-3: Characterization of the Arabidopsis-Pseudomonas syringae pathosystem using known inducers of plant defence responses.

(A-H) Brightfield and fluorescence microscopy of salicylic acid (SA)-treated seedlings at five days post-inoculation. Various defence-related signalling mutants were treated with either 1% DMSO (“-SA“) or 25 μM SA (“+SA”) prior to inoculation with P. syringae

DC3000 (Pto DC3000) at 1 x 105 cfu/mL. Lower left: fraction of seedlings showing pattern almost identical to the image provided. Scale bars indicate 1 mm for brightfield images and 400 µm for fluorescence images

(I) Quantitation of bacterial populations within seedlings that were treated with SA and inoculated as described for (A-H). Error bars represent the standard deviation from the mean of six samples. Asterisks indicate bacterial populations within seedlings significantly different from DMSO controls as determined by a Student’s t-test (α=0.05).

The experiment was repeated twice with similar results.

(J) Quantitation of Pto DC3000 population growth within flg22-treated seedlings. Prior to inoculation with Pto DC3000 at 1 x 105 cfu/mL, seedlings were treated with 0.1 or 1.0

μM flg22 peptide. An equivalent volume of liquid media was added to the negative control. Error bars represent the standard deviation from the mean of seven samples.

Asterisks indicate bacterial populations within seedlings significantly different from the negative control as determined by a Student’s t-test (α=0.05).

(K-R) Brightfield and fluorescence microscopy of seedlings at five days post- inoculation. Seedlings were treated with flg22 and inoculated as described for (J).

Lower left: fraction of seedlings showing pattern almost identical to the image provided.

Scale bars indicate 1 mm for brightfield images and 400 µm for fluorescence images.

The experiment was repeated once with similar results.

63 induced cotyledon bleaching, demonstrating the suitability of the pathosystem for small molecules that induce plant resistance.

To further characterize the pathosystem, we evaluated the activity of the basal defence-inducing peptide flg22 in the liquid assay. This peptide represents a highly conserved 22-amino-acid sequence from bacterial flagellin that is sufficient to induce basal immune responses in plants that possess the FLS2 receptor (Felix et al., 1999;

Gómez-Gómez et al., 1999). In the liquid assay, treatment of seedlings with either 0.1 or 1 μM flg22 prior to inoculation with Pto DC3000 provided protection from bleaching

(Figure 2-3K-R) and significantly reduced the abundance of this pathogen within seedlings (Figure 2-3J). Bacterial populations in the media surrounding the seedlings were not significantly affected by flg22 treatment (data not shown). Therefore, inducers of basal resistance can also reduce bacterial growth and prevent Pto DC3000-induced bleaching in the liquid assay.

Chemical screening

The liquid assay was developed with the intention of screening for small molecules that can protect Arabidopsis from infection by P. syringae. This protection would be visualized as the prevention of cotyledon bleaching in the presence of a small molecule and the virulent strain of P. syringae, Pto DC3000 (Figure 2-4). We began screening a library of compounds compiled on the basis of their activity on dark-grown

Arabidopsis seedlings (S.R. Cutler, unpublished results). We screened the chemicals in this library at 25 μM in duplicate. Hits were only selected if the compound provided protection from bleaching in both replicates. After screening less than 200 small molecules from the LATCA (Library of Active Compounds in Arabidopsis; S.R. Cutler, 64

Figure 2-4: Sample results obtained from 96-well plates used for chemical screening.

(A) Uninoculated seedlings.

(B) DMSO-treated control seedlings.

(C) A well designated as a non-hit, with all seedlings exhibiting complete bleaching of cotyledons as in (B).

(D) A well designated as a hit, very similar in appearance to the uninoculated control.

All pictures were taken at five days post-inoculation.

65 unpublished) collection, a group of sulfanilamide compounds were identified as providing some amount of protection from cotyledon bleaching in the liquid infection assay (Figure 2-5; see also Appendix 2).

Three compounds were selected for retesting and further analysis: sulfamethoxazole (Smex) and sulfadiazine (Sdiz), both hits in the screen, and sulfapyridine (Spyr), a closely-related compound that was a non-hit (Figure 2-5A).

Seedlings treated with 25 μM Smex prior to inoculation appeared nearly as healthy as uninoculated seedlings, and exhibited minimal chlorophyll loss at four days post- inoculation (Figure 2-5D and I). Sdiz-treated seedlings were not protected to the same degree, but still showed only a small amount of bleaching and chlorophyll loss (Figure

2-5C and H, Figure 2-6). The P. syringae-induced bleaching symptom of Spyr-treated seedlings was slightly delayed but generally similar to DMSO-treated controls by five days post-inoculation (Figure 2-5E and J). This pattern of activity was in line with visual assessments of population numbers for Pto DC3000 + GFP within cotyledonary mesophyll tissue from seedlings treated with different sulfanilamides prior to inoculation

(Figure 2-5Q). Quantitative growth assays also indicated that Smex had the most significant effect on bacterial populations within infected tissues (Figure 2-5R and S).

Interestingly, the amount of bacteria adhering to the surface of each seedling appeared to be very similar amongst all treatments (Figure 2-5L-O). Rudimentary structure- activity analyses indicated that Smex, Sdiz, and Spyr all prevented the bleaching of cotyledons when applied at 100 μM, while no protection was provided below 25 μM

(Figure 2-6). In contrast, sulfanilamide (Snil), the root structure of this family of compounds, did not display protective activity at concentrations up to 100 μM (Figure 2-

5S, Figure 2-6). This suggests that the sulfanilamide R-group is required for significant activity in this assay. 66

67 Figure 2-5: Protective effects of sulfanilamides identified by chemical screening on

Arabidopsis seedlings inoculated with Pto DC3000.

(A) Chemical structures of sulfadiazine (Sdiz), sulfamethoxazole (Smex), sulfapyridine

(Spyr), and the core structure compound sulfanilamide (Snil).

(B-F) Brightfield microscopy of wholemount seedlings four days post-inoculation with

Pto DC3000 in the presence of (B) 1% DMSO; (C) 25 μM Sdiz; (D) 25 μM Smex; (E) 25

μM Spyr; versus (F) uninfected control. Scale bars indicate 1 mm. Insets show a representative cotyledon.

(G-K) Chlorophyll fluorescence of cotyledons treated as in (B-F) at four days post- inoculation with Pto DC3000. Scale bars indicate 500 µm.

(L-P) Visualization of Arabidopsis seedlings treated as in (B-F) infected with Pto

DC3000+GFP. Green, Pto DC3000+GFP; red, chlorophyll fluorescence. Scale bars indicate 1 mm.

(Q) Intercellular counts of fluorescent spots / mm2 counted from mesophyll pictures of seedlings treated with various sulfanilamide compounds at four days post-inoculation with Pto DC3000+GFP. “n” indicates the number of mesophyll pictures counted. Error bars represent the standard deviation from the mean of three independent experiments. Representative images of mesophyll cells at four days post-inoculation are shown below the graph.

(R,S) Quantitation of Pto DC3000 growth within seedlings (bars) and in the surrounding liquid media (lines) when treated with sulfanilamide compounds six hours prior to inoculation. Sulfanilamides were tested at 25 μM (R) and 100 μM (S). Error bars represent the standard deviation from the mean of five samples. Asterisks indicate

68 bacterial populations within seedlings significantly different from DMSO-treated seedlings as determined by a Student’s t-test (α=0.05).

Figure 2-6: Preliminary dose-response evaluation of sulfanilamide compounds.

Five-day-old seedlings were treated with a range of concentrations of sulfamethoxazole

(Smex), sulfadiazine (Sdiz), sulfapyridine (Spyr), or sulfanilamide (Snil) prior to

7 inoculation with 1 x 10 cfu/mL Pto DC3000 (OD600=0.02). Pictures were taken at five days post-inoculation. The reduced visibility of seedlings in some wells is due to dead seedlings sinking to the bottom of the well and thus away from the plane of focus.

69 Since sulfanilamides have been widely used in medical practice as bacteriostatic antibiotics against a range of human bacterial pathogens, we examined if they were preventing cotyledon bleaching by inhibiting P. syringae growth in the liquid assay. As a simple preliminary analysis, an aliquot of the liquid media from each well of the screening plates was removed and plated on solid media in a dilution series to allow an estimation of the bacterial populations remaining in the well. In this assay, the three sulfanilamides did not significantly reduce the number of bacteria in the liquid media relative to a DMSO-treated control (data not shown). For a more quantitative evaluation, we monitored the growth of Pto DC3000 in either minimal or rich media containing a range of sulfanilamide concentrations. All three compounds did not significantly alter bacterial growth at concentrations used for screening (Figure 2-7).

While the source of insensitivity to sulfanilamides was not investigated for Pto DC3000, it is evident that these compounds do not protect seedlings by affecting bacterial growth in the liquid assay.

We investigated other mechanisms by which the sulfanilamides could be protecting the seedlings. One possibility involves chemical interference with some aspect of bacterial virulence such as the type III secretion system. To test for an effect on TTSS function we co-infiltrated the test chemical and Pto DC3000 expressing the avirulence protein AvrRpt2 into Arabidopsis Col-0. AvrRpt2 is translocated into host cells by the TTSS where its recognition by the R protein RPS2 triggers a macroscopically observable HR (Yu et al., 1993). Co-infiltration of this strain with either

25 or 100 μM Smex did not alter the kinetics or physical manifestation of the HR

(Figure 2-8). More general effects on virulence were also examined by incubating Pto

DC3000 in the presence of either 100 μM Smex, 100 μM Snil, or 0.02 % DMSO for six

70

Figure 2-7: Evaluation of potential antimicrobial activity of sulfanilamide compounds.

Cultures of Pto DC3000 were incubated in rich media (A) or minimal media (B) with a range of concentrations of three sulfanilamide compounds. Tetracycline (Tet) was included as a positive control for antimicrobial activity. Bacterial growth was calculated as the change in OD600 over an eight- (A) or thirty-six- (B) hour time period, relative to an untreated control. Error bars represent the standard deviation from the mean of data from three experiments.

71

Figure 2-8: Examination of potential interference with type III secretion in P. syringae by sulfamethoxazole (Smex).

The leaves of four-week-old, soil-grown Arabidopsis plants were inoculated with 10 mM

MgCl2, Pto DC3000, or a strain of Pto DC3000 that expresses the AvrRpt2 avirulence gene (“Pto DC3000 + AvrRpt2”) in the presence or absence of 100 μM Smex. The collapse of inoculated tissues in Pto DC3000 + AvrRpt2-inoculated leaves indicates that the bacteria are able to deliver effector proteins through the type III secretion system. Leaves displaying a macroscopic HR are indicated by an asterisk. Images were taken 16 hours post-inoculation.

72 5 hours prior to inoculation at 1 x 10 cfu/mL (OD600=0.0002). Measurement of bacterial growth over three days indicated that there were no significant differences between Pto

DC3000 pre-incubated with Smex and those bacteria treated with DMSO or Snil

(Figure 2-9). Overall, components of bacterial virulence do not appear to be affected by sulfanilamides.

In the absence of any significant effect on the pathogen, sulfanilamide compounds could be acting upon the plant to enhance its resistance to infection. To examine this possibility, leaves of soil-grown plants were treated with 100 μM Smex 24 hours prior to inoculation with Pto DC3000. In this assay Smex significantly reduced

Pto DC3000 population numbers by 0.75 logs at three days post-inoculation versus

Snil- or DMSO-treated controls (Figure 2-10). Similarly, plants sprayed with 2 mM

Smex six hours prior to either dip inoculation or pressure infiltration with Pto DC3000 exhibited significant reductions in bacterial growth at three days post-inoculation versus

DMSO-treated controls (Figures 2-11 and 2-12). Since PR-1 gene expression is often induced during plant defence responses, we monitored its expression in the liquid assay using plants containing a fusion of the PR-1 promoter and β-glucuronidase

(GUS) ORF sequences. Incubation of these seedlings with 100 μM Smex did not induce PR-1:GUS expression, even after three days of continuous exposure to the compound (data not shown). Therefore, sulfanilamide compounds protect Arabidopsis seedlings from infection in a manner independent of PR-1 expression.

The mechanism of sulfanilamide-induced resistance remains to be determined.

These compounds are structural analogues of p-aminobenzoic acid that competitively inhibit the enzyme dihydropteroate synthase (DHPS), a key step in folate biosynthesis

(McCullough and Maren, 1973). Arabidopsis DHPS enzymes can be inhibited in vitro by sulfanilamides (Prabhu et al., 1997), and the germination of Arabidopsis seeds is 73

Figure 2-9: Assessment of potential general effects of sulfamethoxazole (Smex) on Pto

DC3000 virulence on Arabidopsis.

Bacteria were incubated with 0.02 % DMSO, 100 μM sulfanilamide (Snil), or 100 μM sulfamethoxazole (Smex) for six hours prior to inoculation of plants by pressure infiltration. Error bars represent the standard deviation from the mean of six samples per treatment.

74

Figure 2-10: Protective effects of sulfanilamides identified by chemical screening on three-week-old, soil-grown Arabidopsis plants inoculated with Pto DC3000.

Growth of Pto DC3000 in plants pressure-infiltrated with 0.02% DMSO, 100 μM Smex or 100 μM Snil 24 hours prior to inoculation. Error bars represent the standard deviation from the mean of six samples. Asterisks indicate values significantly different from

DMSO-treated plants as determined by a Student’s t-test (α=0.05). The experiment was repeated twice with similar results.

75

Figure 2-11: Effect of spraying sulfamethoxazole (Smex) on plants prior to inoculation with Pto DC3000 by dipping.

Smex was applied at 1 or 2 mM (0.8 % DMSO as a control) and plants were inoculated six hours after chemical treatment by dipping in a solution of 5 x 108 cfu/mL Pto

DC3000 (OD600=1.0) plus 0.01 % Silwet. Asterisks indicate bacterial populations within plants significantly different from DMSO-treated plants as determined by a Student’s t- test (α=0.05). Error bars represent the standard deviation from the mean of six samples per treatment, taken at three days post-inoculation.

76

Figure 2-12: Effect of spraying sulfamethoxazole (Smex) on plants prior to inoculation with Pto DC3000 by pressure infiltration.

Smex was applied at 2 mM (0.8 % DMSO as a control) and plants were inoculated six hours after chemical treatment by infiltrating a solution of 1 x 105 cfu/mL Pto DC3000

(OD600=0.0002). Error bars represent the standard deviation from the mean of six samples per treatment, taken at three days post-inoculation.

77 inhibited by 4 μM Sdiz (Hadi et al., 2002). In the liquid media format, the lethal dose of the sulfanilamides used in this study was 2 mM or greater (data not shown). This difference is likely due to chemical exposure at different developmental stages, because cytosolic DHPS activity appears to be especially important for germination

(Storozhenko et al., 2007). Another isoform of DHPS is localized to mitochondria

(Neuburger et al., 1996). We speculate that sulfanilamide-induced inhibition of mitochondrial and/or cytosolic DHPSs induces a plant defence signalling pathway that is independent of PR-1 expression. In support of this hypothesis, 25 μM Smex still prevents Pto DC3000-induced bleaching in Arabidopsis seedlings with a mutation in the NPR1 gene, which is critical for PR-1 expression (K.S. and D.D., unpublished results).

Conclusions

In order to screen for small molecules that modulate plant-pathogen interactions, we have developed a 96-well liquid pathosystem suitable for high-throughput chemical screening. This assay can be used to monitor induction of SA-induced resistance and basal resistance but not gene-for-gene resistance or the resistance associated with lesion-mimic mutants. While many chemical screens are centered on a specific process such as the activation of a reporter gene (Armstrong et al., 2005; Serrano et al., 2007), the assay presented is based on a macroscopic bleaching phenotype that is correlated with bacterial virulence. Given that the screen is a whole-organism-based assay, there are several different potential mechanisms through which plant-pathogen interactions could be affected. We have presented a series of experiments for broadly characterizing the modes of action with regards to both the host and pathogen. We 78 anticipate that this whole-organism pathosystem will be an important approach with which to study numerous aspects of plant-pathogen interactions in a high-throughput manner. In addition, the ability to probe small molecule libraries for inhibitors of plant pathogenesis could deliver commercially relevant chemicals for agricultural or horticultural use. Given the commonalties of mammalian- and plant-pathogen virulence strategies and the similar aspects of animal and plant innate immunity, some of these compounds may prove to be more generally applicable for the development of therapeutic compounds (Galan and Collmer, 1999; Ausubel, 2005).

Experimental Procedures

Plant materials and bacterial strains

Seeds for soil-grown plants were placed on moist soil (ProMix BX, Premier

Horticulture Ltd., Dorval, PQ, Canada) amended with 20-20-20 fertilizer, stratified for two days at 4oC, then placed in a growth room with a nine-hour photoperiod and a day/night temperature regime of 22oC/18oC. Unless otherwise specified, experiments were performed with Arabidopsis ecotype Columbia-0. PR-1::uidA (encoding β- glucuronidase) transgenic Arabidopsis seeds as well as nahG, npr1-1, eds16, cpr1, cpr5, cpr22, and dnd1 mutant seeds were obtained from Dr. Keiko Yoshioka and Dr.

Wolfgang Moeder. Pto DC3000 expressing a green fluorescent protein gene was obtained from Dr. Sheng Yang He. Pto DC3000 hrcC was obtained from Dr. Jeff Dangl.

Pma ES4326 was obtained from Dr. David Guttman.

79 Arabidopsis-Pseudomonas syringae 96-well plate pathogenicity assay

For liquid assays, surface-sterilized Arabidopsis thaliana (ecotype Columbia) seeds were distributed into 96-well plates containing 200 μL of liquid media (0.5X

Murashige and Skoog (MS) basal media (SigmaAldrich, Oakville, ON, Canada), 2.5 mM 2-(N-Morpholino)ethanesulfonic acid (MES), pH 5.8 (SigmaAldrich)). Between 5 and 10 seeds were distributed per well using a pipette. After four days of stratification at 4oC, covered plates were placed under continuous light at 22oC in a controlled environment room. Five-day-old seedlings were inoculated with Pto DC3000 at a final

7 concentration of 1 x 10 cfu/mL (OD600=0.02). Covered plates were gently agitated on a Heidolph Titramax 1000 vibrating shaker (VWR, Mississauga, ON, Canada) at 600 rpm under continuous light at 22oC in a controlled environment room. Seedling phenotypes were assessed at five to six days post-inoculation.

To enumerate bacterial populations in inoculated seedlings in the liquid assay, seedlings were removed from the 96-well plate using forceps, placed in a fine mesh sieve and surface sterilized in 70% ethanol for 20 sec. followed by a rinse with water prior to tissue homogenization. Approximately six seedlings were homogenized in 200

μl of 10 mM MgCl2 and bacteria were quantified by serial dilution plating. In addition, the numbers of bacteria in the liquid media of the assay plates were also determined by serial dilution plating.

Chemical screening

The LATCA collection was provided by Dr. Sean Cutler (UC Riverside, CA,

USA) as 2.5 mM stock solutions dissolved in dimethyl sulfoxide (DMSO). These 80 chemicals were screened using five-day-old seedlings grown in liquid culture as described above. Compounds were added to each well at a final concentration of 25

μM, with control wells containing 1% DMSO. Plates were stored in the dark at room temperature for six hours, then inoculated with Pto DC3000 and incubated as described above. Seedling phenotypes were assessed at five to six days post- inoculation. All compounds were screened in duplicate. Experiments using salicylic acid (SigmaAldrich) and flg22 peptide (Sheldon Biotechnology Centre, Montreal, PQ,

Canada) were conducted in the same manner.

Microscopy

Prior to the capture of wholemount images, seedlings were washed briefly with water and arranged on a water-agar plate (0.8% Agar (Bioshop, Burlington, ON,

Canada). A Leica MZFLIII stereomicroscope (Leica Microsystems, Wetzlar, Germany) was used for both brightfield and fluorescent microscopy, the latter utilizing a GFP2 filter (Leica Microsystems). All images were taken with identical exposure times. For the collection of images from intercellular spaces, seedlings were washed vigorously with water and mounted in water on a glass microscope slide. Samples were viewed using an Olympus (Tokyo, Japan) AX-70 microscope equipped with a filter suitable for fluorescence microscopy. Mesophyll layers were selected through optical sectioning with DIC microscopy. All photographs were taken with either a Canon EOSD60 digital camera (Canon Inc., Tokyo, Japan) or a MicroPublisher 3.3 RTV camera (QImaging,

Surrey, BC, Canada). Images were assembled in Adobe Photoshop 5.0 (Adobe

Systems, Mountain View, CA, USA).

81 Bacterial growth inhibition assays

A suspension of Pto DC3000 was prepared in either King’s B (King et al., 1954) or Pseudomonas Minimal Medium (Huynh et al., 1986) at OD600=0.15. Two hundred microlitres of culture was added to each well of a 96-well Nunc optical bottom plate

(VWR) and supplemented with a range of concentrations of sulfadiazine, sulfamethoxazole, sulfapyridine, or tetracycline (SigmaAldrich). DMSO was used as the solvent control for the sulfanilamides and dimethylformamide used for tetracycline.

Plates were incubated with shaking at 30oC. Bacterial growth was monitored using a

BMG Labtech POLARstar OPTIMA plate reader (Fisher Scientific, Markham, ON,

Canada).

Soil-grown plant inoculations and bacterial quantitation

Generally, the leaves of five-week-old Arabidopsis plants were inoculated by pressure infiltration using a syringe without a needle. Inocula were prepared in 10 mM

5 7 MgCl2 at 1 x 10 cfu/mL (OD600=0.0002) for bacterial growth assays or at 5 x 10 cfu/mL (OD600=0.1) for HR experiments. When bacteria were pre-treated with sulfanilamides prior to inoculation, bacterial solutions were prepared in 0.5X MS; 2.5

7 mM MES, pH 5.8 at a concentration of 1 x 10 cfu/mL (OD600=0.02). These suspensions were incubated for six hours with gentle agitation at room temperature in the presence of either 100 μM Snil, 100 μM Smex, or 0.02% DMSO as a control. The

5 bacteria were then diluted to 1 x 10 cfu/mL (OD600=0.0002) in 10 mM MgCl2, without further supplementation of compound, and used to inoculate plants by pressure infiltration. When dipping experiments were performed, the inoculum contained 5 x 108 82 cfu/mL (OD600=1.0) and 0.01% Silwet L-77 surfactant (GE Silicones, West Virginia,

USA). Bacterial growth within inoculated tissues was quantified as described previously (Katagiri et al., 2002).

Acknowledgements

We thank Dr. Sheng Yang He, Michigan State University, Dr. Jeff Dangl,

University of North Carolina Chapel Hill and Dr. David Guttman, University of Toronto for bacterial strains. We thank Dr. Wolfgang Moeder and Dr. Keiko Yoshioka for transgenic seeds. We are grateful to Dr. Daphne Goring for providing growth room space. D.D. is a Canada Research Chair in Plant-Microbe Systems Biology. This work was supported by an NSERC Discovery Grant and an award from the Canadian

Foundation for Innovation to D.D.

83

Chapter 3

Found in Translation: High-Throughput Chemical Screening in

Arabidopsis thaliana Identifies Small Molecules that Reduce

Fusarium Head Blight Disease in Wheat

Previously published as:

Found in translation: High-throughput chemical screening in Arabidopsis thaliana

identifies small molecules that reduce Fusarium head blight disease in wheat

Karl J. Schreiber, Charles G. Nasmith, Ghislaine Allard, Jasbir Singh, Rajagopal

Subramaniam, and Darrell Desveaux (2011)

Molecular Plant-Microbe Interactions 24, 640-648

Author contributions: K.J.S. and C.G.N. are co-authors on this publication. K.J.S. wrote the manuscript with input and direction from all of the other authors. K.J.S. optimized assay conditions, characterized the Arabidopsis-Fusarium graminearum interaction in liquid media, and performed chemical screens. C.G.N. provided analyses of wheat-Fusarium graminearum interactions with support from G.A., J.S., and R.S.

R.S. also provided some Arabidopsis images for the manuscript.

84 Abstract

Despite the tremendous economic impact of cereal crop pathogens such as the fungus Fusarium graminearum, the development of strategies for enhanced crop protection is hampered by complex host genetics and difficulties in performing high- throughput analyses. To bypass these challenges, we have developed an assay in which the interaction between F. graminearum and the model plant Arabidopsis thaliana is monitored in liquid media in 96-well plates. In this assay, fungal infection is associated with the development of dark lesion-like spots on the cotyledons of

Arabidopsis seedlings by four days post-inoculation. These symptoms can be alleviated by the application of known defence-activating small molecules and in previously-described resistant host genetic backgrounds. Based on this infection phenotype, we conducted a small-scale chemical screen to identify small molecules that protect Arabidopsis seedlings from infection by F. graminearum. We identified sulfamethoxazole and the indole alkaloid gramine as compounds with strong protective activity in the liquid assay. Remarkably, these two chemicals also significantly reduced the severity of F. graminearum infection in wheat. As such, the Arabidopsis-based liquid assay represents a biologically relevant surrogate system for high-throughput studies of agriculturally important plant-pathogen interactions.

85 Introduction

The ascomycete fungus Fusarium graminearum (teleomorph Gibberella zeae

(Schw.) Petch) is an economically significant pathogen of cereal crops such as wheat, barley, maize, oats, and rye (Parry et al., 1995). The development of Fusarium head blight disease on these crops generally occurs during warm days and cool nights, particularly in spring when susceptible host plants are flowering. Infection occurs at anthesis, when rain-splashed conidia or airborne ascospores from infected crop debris contact and germinate on floral tissues. Upon invasion of these tissues, the fungus proliferates and spreads to neighbouring spikelets within a spike (Goswami and Kistler,

2004). Subsequent necrosis of infected tissues is associated with reductions in both grain yield and quality. Infection is also accompanied by the in planta accumulation of various tricothecene mycotoxins by F. graminearum, including nivalenol, deoxynivalenol (DON), 3-acetyl deoxynivalenol (3-ADON), and 15-acetyl deoxynivalenol (15-ADON) (Hohn et al., 1998). These toxins inhibit protein translation

(Cundliffe et al., 1974) and represent a serious health issue when present at high concentrations. In terms of resistance to F. graminearum infection, the primary mechanisms involve resistance to initial infection (type I), resistance to fungal spread within an infected spike (type II), and reduced DON accumulation (type III) (Bai and

Shaner, 2004). Presently, a limited number of wheat genotypes are known to confer type II resistance (Anderson et al., 2001; Ban and Suenaga, 2000; Cuthbert et al.,

2006; Van Ginkel et al., 1996), however the molecular events underlying this resistance remain unknown.

The genetic complexity of polyploid cereals presents a considerable challenge for the characterization of resistance to F. graminearum, such that the use of a more 86 genetically tractable host such as Arabidopsis represents an appealing alternative.

Previous investigations of the Arabidopsis-F. graminearum interaction involved a range of inoculation techniques, including pressure infiltration of leaf tissue (Makandar et al.,

2006), point inoculation of wounded siliques (Cuzick et al., 2008), spray inoculation of floral organs (Urban et al., 2002), and wound inoculation of detached leaves (Chen et al., 2006). While reproducible and biologically relevant data can be obtained with these protocols, they are difficult to extend to high-throughput assays. We previously developed an assay in which Arabidopsis seedlings are grown in liquid media in 96-well plates (Chapter 2). We demonstrated that this experimental setup could be used to study the Arabidopsis-Pseudomonas syringae pathosystem with great economy of both time and space. In particular, this assay was amenable to high-throughput chemical screens to identify small molecules that alter the outcome of the Arabidopsis-P. syringae interaction. The chemical genetic approach provides several advantages over classical forward genetic screening (Kawasumi and Nghiem, 2007; Stockwell, 2000), including the capability to perturb biological systems at the proteome level. Importantly, given that the structure of protein families is often more highly conserved than are their primary sequences (Illergård et al., 2009), the activity of a compound in a model system should translate to other systems. Furthermore, many known defence-inducing molecules are active in a broad range of host plants (Chapter 1).

In this study, we characterize the Arabidopsis-F. graminearum interaction in a liquid-based assay. We demonstrate that this interaction can be modulated by the application of chemicals, either to “prime” host defences or to directly inhibit pathogen growth. Based on these phenotypic observations, we initiated a screen to identify small molecules that protect Arabidopsis seedlings from infection by F. graminearum.

Importantly, the protective activity of compounds of interest was subsequently 87 established in wheat. Such translation to a native host of F. graminearum validates the biological relevance of the Arabidopsis screening assay.

Results

Characterization of the Arabidopsis-F. graminearum pathosystem in liquid media

In order to evaluate the Arabidopsis-F. graminearum interaction in a high- throughput manner, we examined this pathosystem using an assay conducted in liquid media in 96-well plates (Chapter 2). In this environment, inoculation of Arabidopsis

(Col-0) seedlings with F. graminearum spores led to a highly reproducible progression of macroscopic disease symptoms (Figure 3-1). In particular, small brown spots were visible on cotyledons within two days post-inoculation (dpi). Over time, these spots increased in both size and number, and by four dpi, any cotyledonary tissues that lacked spots were nearly translucent. Hypocotyls remained relatively unaffected by the fungus, and root tips exhibited a general browning over time. Trypan blue staining revealed numerous sites of cell death in cotyledons at two dpi, especially at the tips of these tissues (Figure 3-1F-J). Notably, localized sites of staining were generally centered at or near stomatal guard cells (Figure 3-1H). As with the macroscopic spotting symptoms, sites of trypan blue staining became more abundant and widespread as time progressed. By four dpi, however, many cotyledons exhibited reduced staining of plant cells, while fungal hyphae were especially prominent, having now completely innervated most cotyledonary tissues (Figure 3-1J). Inoculation of wells with GFP-expressing F. graminearum clearly illustrated the extensive fungal invasion of cotyledons at four dpi (Figure 3-1K, L). By this point, a mass of fungal 88

89 Figure 3-1: Phenotype of Arabidopsis seedlings inoculated with F. graminearum in liquid media.

(A-E) Macroscopic symptom development in infected seedlings. Timescale is given in days post-inoculation (dpi). Scale bars indicate 1 mm.

(F-J) Microscopic phenotypes observed following trypan blue staining. Punctate staining at early time points is generally centered on stomata (inset in H), while proliferating fungal mycelia are also stained at later time points. Scale bars indicate

0.25 mm (20 μm for inset).

(K-L) Growth of GFP-labeled F. graminearum in Arabidopsis cotyledons at four dpi.

Images represent an overhead view of adaxial mesophyll cells (K) and a side view reconstructed from multiple z-stacks (L). Scale bars indicate 10 μm.

(M-N) Influence of deoxynivalenol (DON) production on symptom development in

Arabidopsis. Wells were inoculated with either wildtype F. graminearum (Fg-WT) (M) or a Δtri6 mutant incapable of producing DON (Fg-Δtri6) (N). Images were captured at four dpi. Scale bars indicate 1 mm.

All images are representative of observations from at least three biological replications.

90 mycelia was also evident in inoculated wells (data not shown). Interestingly, a DON- deficient Δtri6 mutant of F. graminearum elicited disease symptoms very similar to those of the wildtype fungus, indicating that DON is dispensable for infection of

Arabidopsis seedlings in liquid media (Figure 3-1M,N).

The infection symptoms depicted in Figure 3-1 could be significantly attenuated by altering host defence responses either genetically or by the application of known defence-inducing molecules. We observed that overexpression of a GOLDEN2-LIKE

(GLK1) gene dramatically reduced fungal infection of Arabidopsis seedlings (Figure 3-

2), as shown previously using soil-grown plants (Savitch et al., 2007). Similarly, disruption of jasmonic acid (JA) signalling in coronatine insensitive 1 (coi1) and jasmonate resistant 1 (jar1) mutants was associated with minimal symptom development following inoculation with F. graminearum (Figure 3-2), also in line with previous observations (Makandar et al., 2010). Exogenous application of the basal defence-eliciting peptide flg22 prior to inoculation also protected seedlings from infection, and this protection was eliminated in seedlings lacking the flg22 receptor

FLAGELLIN-SENSITIVE 2 (FLS2) (Figure 3-2). Finally, when seedlings were pre- treated with the antifungal compound hygromycin, all plant tissues remained relatively green and mycelial growth in the wells was negligible (Figure 3-2). Overall, the phenotypes of the resistant host genotypes and small molecule-treated seedlings were very consistent across both technical and biological replicates. These results indicated that infection of Arabidopsis seedlings in liquid media could be affected by altering host defences and/or pathogen growth.

91

Figure 3-2: The Arabidopsis-F. graminearum interaction can be attenuated by exogenous application of small molecules or by genetically altering host defence responses. In addition to wildtype Arabidopsis (Col-0) (WT), a line overexpressing

GLK1 (GLK1-OE) was examined, as well as coi1 and jar1 mutants. Wildtype seedlings were also treated with 1% DMSO, 25 μM hygromycin (Hyg), or 1 μM flg22 peptide

(WT+flg22) 12 hours prior to inoculation. The flg22 peptide was also tested on fls2 mutants (fls2+flg22). Scale bars indicate 1 mm. All images are representative of observations from at least three biological replications.

92 Chemical screening

Based on the findings summarized in Figure 3-2, we conducted a small-scale screen to identify novel compounds capable of preventing the infection of Arabidopsis seedlings by F. graminearum. In a prior screen, we identified a family of sulfanilamide- based compounds that protected Arabidopsis from infection by P. syringae (Chapter 2).

Sulfamethoxazole (Smex) exhibited the strongest activity, while the sulfanilamide (Snil) core group alone was essentially inactive in the liquid assay (Chapter 2). Remarkably, these observations were recapitulated with F. graminearum (Figure 3-3A). Very little spotting or browning was observed in seedlings pre-treated with 25 μM Smex, and at

50 μM, seedlings were virtually symptom-free. Seedlings pre-treated with Snil, however, were indistinguishable from DMSO-treated controls. We also screened 80 chemicals from a natural product collection and identified the indole alkaloid gramine

(also called donaxine) as having strong protective activity (Figure 3-3B; see also

Appendix 3). Interestingly, this compound did not protect seedlings from infection by P. syringae (data not shown).

Experimental translation from Arabidopsis to wheat

We next investigated if chemicals identified through an Arabidopsis-based screen would exhibit similar activity on wheat, a natural host of F. graminearum. Two chemical treatment regimes were employed, involving either simultaneous application of fungal spores and chemical to a single spikelet (“antagonism”) or chemical pre- treatment of one spikelet followed by inoculation of an adjacent spikelet 24 hours later

93

Figure 3-3: Identification of novel small molecules that protect Arabidopsis seedlings from infection by F. graminearum.

(A) Differential activity of sulfamethoxazole (Smex) and sulfanilamide (Snil) in the liquid assay.

(B) Protection of Arabidopsis seedlings from F. graminearum infection by 50 μM gramine, a compound identified from a collection of natural products.

(C) Chemical structures of Smex, Snil, and gramine.

All images are representative of observations from at least three biological replications.

94 (“priming”). (A spikelet is the structure within which a single grain of wheat will eventually develop.) We subsequently monitored the development of macroscopic disease symptoms over time and measured the accumulation of DON in wheat heads at 21 days post-inoculation. For both methods, inoculated heads pre-/co-treated with

DMSO exhibited extensive discolouration that eventually affected nearly 100% of spikelets (Figure 3-4A, Table 3-1). This phenotype coincided with DON accumulations in excess of 600 ppm. Co-application of 50 μM Smex and F. graminearum significantly reduced the infection to 43% of spikelets and lowered DON concentrations to 20% of that measured in the DMSO control. These reductions were less dramatic for Snil, and only the effect on DON accumulation was statistically significant. Gramine also exhibited weak activity and again, significant reductions were only observed for DON content (42% of control). Priming experiments corroborated the strong activity of

Smex, which reduced spikelet infection by over 50% and DON accumulation by 75%.

Sulfanilamide did not have a significant impact on either measurement. Priming with gramine, however, resulted in the infection of 30% fewer spikelets and close to 75% less DON accumulation. Neither Smex nor gramine significantly inhibited fungal growth in vitro at a concentration of 50 μM (Figure 3-4B) suggesting that these compounds induce defence responses in wheat that hinder F. graminearum infection. Overall, these results demonstrate that the Arabidopsis-F. graminearum pathosystem can be used to identify disease control strategies in wheat.

In addition to directly treating/inoculating single spikelets, we also evaluated the activity of gramine and Smex by spraying the chemicals on wheat heads followed by spray inoculation 24 hours later. When applied at a concentration of 50 μM, neither gramine nor Smex significantly altered the development of F. graminearum infection symptoms (data not shown). Considering that spray treatment likely lowers the 95

96 Figure 3-4: Activity of gramine and sulfamethoxazole in the wheat-F. graminearum pathosystem as evaluated using single spikelet treatment/inoculation approaches.

(A) A single spikelet within each wheat head was either simultaneously treated with chemical and F. graminearum (Fg) conidiospores (“antagonism”) or locally pre-treated with chemical at a single spikelet, then inoculated at an adjacent spikelet 24 hours later

(“priming”). Images were captured at 21 days post-inoculation (dpi) for co-application experiments and 14 dpi for priming experiments. The average percent spikelet infection per head (% Infection) is indicated ± standard deviation. Mean deoxynivalinol

(DON) concentrations were also measured in wheat heads at the above time points and are provided in parts per million (ppm) ± standard deviation. In uninoculated heads, the baseline DON measurement is invariably 0.8 ppm. Asterisks indicate a statistically significant difference between the treatment and the DMSO control in three biological replicates, as determined by Student’s t-tests (α=0.05). Abbreviations: - = uninoculated, + = inoculated, Smex = sulfamethoxazole, Snil = sulfanilamide. The experiment was performed three times with similar results.

(B) Growth of F. graminearum on PDA media supplemented with 50 μM sulfamethoxazole, sulfanilamide, or gramine. Control plates contain 1% DMSO.

Images are representative of observations from at least three biological replications.

97 Table 3-1: Summary of data from evaluations of potential antagonistic or defence priming activities for gramine, sulfamethoxazole (Smex), or sulfanilamide (Snil) on wheat heads challenged with Fusarium graminearum

% Infected Spikeletsa Experimentb Replicate 1% DMSO 50 μM 50 μM Smex 50 μM Snil Gramine

Antagonism 1 100 ± 0 73.6 ± 26.4 46.6 ± 32.9 59.5 ± 23.3

p-valuec - 0.09 0.02 0.02

2 100 ± 0 71.4 ± 25.1 41.2 ± 30.5 56.9 ± 31.6

p-value - 0.04 0.01 0.04

3 97.3 ± 5.9 76.7 ± 40.9 42.9 ± 35.7 54.6 ± 41.9

p-value - 0.32 0.03 0.08

Priming 1 100 ± 0 77.0 ± 11.7 55.8 ± 21.8 79.2 ± 15.2

p-value - 0.01 0.01 0.04

2 100 ± 0 74.2 ± 13.0 53.3 ± 13.9 80.8 ± 9.8

p-value - 0.01 0.002 0.01

3 100 ± 0 70.7 ± 21.8 52.0 ± 28.5 83.8 ± 15.6

p-value - 0.04 0.02 0.08 a Values are indicated as means of observations from five heads ± standard deviation. b See Experimental Procedures for treatment/inoculation protocols c p-values are derived from Student’s t-tests comparing chemical treatments to DMSO.

98 effective dose of chemical that reaches floral tissues, we tested higher concentrations of each compound along with a lower inoculum concentration, as used by Gilbert et al.

(2001). With this method, only a subset of inoculated heads actually became infected, even after several weeks (Figure 3-5). Notably, however, pre-treatment of heads with

250 μM gramine or Smex reduced the number of infected heads by approximately 50% relative to the DMSO control (Figure 3-5, Table 3-2). The spread of disease within these infected heads was also significantly reduced by at least 30% (Figure 3-5, Table

3-3). These results provide a promising indication that both gramine and Smex retain their activity under “real world” conditions.

Discussion

As a small, well-characterized model plant, Arabidopsis has tremendous potential utility as a surrogate for studies of fungal pathology in more genetically complex plant hosts. We examined the interaction between Arabidopsis and F. graminearum in a 96-well assay format as a precursor to more high-throughput analyses. The inoculation of Arabidopsis seedlings in liquid media with F. graminearum macroconidia resulted in the appearance of dark, lesion-like spots on the cotyledons of infected seedlings. Later stages of infection were characterized by extensive spotting and significant loss of tissue integrity. Such apparent necrosis was previously observed after inoculation of wounded siliques (Cuzick et al., 2008) and spray inoculation of floral organs (Urban et al., 2002). Interestingly, similar infection symptoms were observed on detached leaves only when these tissues were wounded prior to inoculation (Chen et al., 2006). In our liquid assay, the proliferation of F. graminearum in intact Arabidopsis cotyledons is likely aided by the continuous contact 99

Figure 3-5: Activity of gramine and sulfamethoxazole in the wheat-F. graminearum pathosystem as evaluated using a spray treatment/inoculation approach. Wheat heads were sprayed with chemicals, then sprayed with a F. graminearum (Fg) spore suspension 24 hours later. At 28 days post-inoculation, the number of wheat heads exhibiting symptoms of F. graminearum infection was recorded (“% Infected Heads”).

Representative images of infected spikelets are shown. The average percent spikelet infection within the infected heads (“% Infected Spikelets”) is indicated ± standard deviation. Asterisks indicate a statistically significant difference between the treatment and the DMSO control, as determined by a Student’s t-test (α=0.05). Abbreviations: - = uninoculated, + = inoculated, Smex = sulfamethoxazole. The experiment was performed twice with similar results (Tables 3-2 and 3-3).

100 Table 3-2: Incidence of infection in wheat heads sprayed with either gramine or sulfamethoxazole (Smex) prior to spray inoculation with Fusarium graminearum

Proportion of Infected Heads (%)a Replicate 1% DMSO 250 μM Gramine 250 μM Smex

1 12/24 (50.0) 6/24 (25.0) 7/24 (29.2) 2 7/21 (33.3) 4/21 (19.0) 4/21 (19.0) a The proportion of infected heads is expressed as the number of wheat heads exhibiting infection symptoms over the total number of heads inoculated. The percentage of infected heads is indicated in parentheses. Chemical treatments and inoculations were performed as described in Experimental Procedures and infection symptoms were assessed at 28 days post-inoculation.

101 Table 3-3: Extent of infection in wheat heads sprayed with either gramine or sulfamethoxazole (Smex) prior to spray inoculation with Fusarium graminearum

% Infected Spikeletsa Replicate 1% DMSO 250 μM Gramine 250 μM Smex

1 100 ± 0 71.3 ± 27.7 54.1 ± 36.14 nb 12 6 7 p-valuec - 0.05 0.005

2 100 ± 0 47.6 ± 19.4 47.3 ± 25.2 n 7 4 4 p-value - 0.012 0.025 a Values are indicated as means ± standard deviation. Chemical treatments and inoculations were performed as described in Experimental Procedures and infection symptoms were assessed at 28 days post-inoculation (dpi). b n = number of observations. Not all heads become infected following spray inoculation, so “n” represents the number of heads from a given treatment group that exhibited symptoms of infection at 28 dpi (see also Table 3-2). c p-values are derived from Student’s t-tests comparing gramine or Smex treatments to DMSO.

102 between host and pathogen under maximally humid conditions, which favour fungal growth. Cotyledons may also be more susceptible to infection than mature Arabidopsis tissues (Aarts et al., 1998).

At the microscopic level, trypan blue staining identified areas of cell death that increased in both size and number over time. Notably, staining was initially localized to guard cells and some neighbouring cells, in agreement with observations by Cuzick et al. (2008). This also provides an important correlate to wheat, in which stomata are key points of entry for F. graminearum (Pritsch et al., 2000). Indeed, Desmond et al.

(2008) noted that inoculation of wheat leaf tissue with F. graminearum induced stomatal H2O2 accumulation and eventual guard cell death at the site of infection. The extent to which these events reflect induced host defence responses versus consequences of necrotrophic pathogenesis remains to be investigated.

One aspect of F. graminearum pathogenesis that appears to differ between

Arabidopsis and wheat is the virulence contribution of the mycotoxin DON. Strains of

F. graminearum lacking DON are significantly less capable of colonizing and spreading within wheat tissues, although virulence on other cereal crops may be unaffected

(Proctor et al., 1995; Jansen et al., 2005; Maier et al., 2006). We noted that the absence of DON did not alter the infection phenotype of Arabidopsis seedlings in liquid media, similar to previous observations from silique inoculation assays (Cuzick et al.,

2008). As such, the liquid assay provides the opportunity to probe mechanisms of disease resistance in a DON-independent manner.

Having noted a salient, reproducible infection phenotype in the liquid assay, we then sought to survey factors that may influence the outcome of the Arabidopsis-F. graminearum interaction. Overexpression of GLK1, a transcriptional activator, was previously shown to enhance the resistance of Arabidopsis to infection by F. 103 graminearum (Savitch et al., 2007). Similar enhancements were demonstrated in coi1 and jar1 mutants (Makandar et al., 2010). Notably, all three of these genotypes were originally assessed by pressure infiltration of leaves from soil-grown adult plants. Our corroboration of the resistance phenotypes in seedlings grown in liquid media thus validates the biological relevance of this Arabidopsis assay.

There are, however, some notable differences in resistance mechanisms against

F. graminearum between Arabidopsis and wheat. Prior observations from the liquid assay indicated that the bacterial flagellin peptide flg22 could protect Arabidopsis seedlings from infection by P. syringae (Chapter 2). We demonstrated similar activity for this peptide against F. graminearum, including a dependence on the FLS2 receptor

(Figure 3-2). A wide range of defence responses are induced by pathogen-associated molecular patterns such as flg22, including callose deposition in cell walls and expression of defence genes (Gómez-Gómez et al., 1999; Jones and Dangl, 2006;

Pitzschke et al., 2009; Schwessinger and Zipfel, 2008). Our results indicate that the elicitation of this basal immune response is an effective strategy for protecting

Arabidopsis from both bacterial and fungal pathogens. However, we were unable to detect significant flg22-induced resistance in wheat (data not shown), suggesting that any responses induced by this peptide are relatively weak and that other pathogen- associated molecular patterns may play a more prominent role in the elicitation of wheat defences. Furthermore, although JA appears to play a negative role in

Arabidopsis resistance against F. graminearum, expression studies suggest that JA may play a positive role in the resistance of wheat against F. graminearum and F. pseudograminearum (Desmond et al., 2006; Li and Yen, 2008). Despite these differences, we have demonstrated that Arabidopsis can be used to identify small molecules that can protect wheat against F. graminearum infection. 104 We also observed effective control of F. graminearum infection in Arabidopsis by the antifungal compound hygromycin. In addition to the absence of infection symptoms on seedlings, very few mycelia were present in the liquid media, contrasting with the profuse mycelial growth in control wells and those containing the resistant Arabidopsis genotypes (data not shown). This illustrates one of the strengths of the liquid assay, in that the simultaneous evaluation of both host and pathogen allows rapid characterization of chemicals in terms of antifungal activity, efficacy of plant protection, and potential phytotoxicity all in the same well.

Further to these advantages, and perhaps most importantly, we have demonstrated that novel compounds identified using an Arabidopsis-based liquid assay exhibit similar protective activity on wheat. The strongest activity was displayed by

Smex, a compound also shown to protect Arabidopsis from infection by P. syringae

(Chapter 2). In the wheat-F. graminearum interaction, the retention of significant activity in the priming experiment suggests that some type of plant defence response is being activated by this compound. It remains to be determined whether Smex-induced resistance against Fusarium employs an SA- and NPR1-independent pathway as it does against P. syringae (Chapter 2). At the same time, Snil significantly reduced the extent of infection only when co-applied with the fungus, indicating that there may be a direct effect on some aspect of fungal virulence that relies solely on the sulfanilamide core group.

The indole alkaloid gramine was also found to reduce the severity of F. graminearum infection in wheat. Although weaker than Smex, gramine reduced DON accumulation in both antagonism and priming experiments. These results suggest that both gramine and Smex influence type II and/or type III resistance against F. graminearum. The spray experiments also indicate that type I resistance may be 105 affected. Such outcomes could arise from the induction of host defences and/or the inhibition of some aspect of fungal virulence. Gramine has long been recognized in barley (Hordeum vulgare L.) as a root-secreted allelochemical (Overland, 1966), but it is also present in leaves and further accumulates in response to abiotic, biotic, and mechanical stresses (Hanson et al., 1983; Hautala and Holopainen, 1995; Matsuo et al., 2001). In addition, exogenously applied gramine was shown to reduce aphid feeding and fecundity on barley (Corcuera, 1993; Zúñiga et al., 1988) and inhibit spore germination by the powdery mildew fungus Erysiphe graminis f.sp. hordei (Wippich and

Wink, 1985). Investigations of gramine toxicity indicate that this compound uncouples electron transport in plant and cyanobacterial thylakoids (Andreo et al., 1984; Foguel and Chaloub, 1993), as well as in mammalian mitochondria (Niemeyer and Roveri,

1984). The mechanism through which gramine reduces susceptibility to F. graminearum infection remains to be determined.

Conclusions

In summary, we have described an assay for high-throughput investigations of the Arabidopsis-F. graminearum pathosystem. Of major significance is our demonstration that information obtained from the genetically tractable Arabidopsis system can be extended to an economically important crop species. The ability to translate screening results not only from a dicot to a monocot, but also from plants at different developmental stages grown in vastly different environments, strongly reinforces the biological relevance of the liquid assay. This also suggests that the liquid assay could potentially be used to study other agriculturally relevant pathogens.

Furthermore, our screening and subsequent translation experiments were performed 106 with compounds at micromolar concentrations, while most commercial fungicides currently registered for use against Fusarium spp. are applied at millimolar concentrations. As such, the liquid assay provides rigorous test conditions conducive to the identification of chemicals with strong activity in the host and/or pathogen. Given recent observations of F. graminearum isolates with resistance to multiple fungicides

(Becher et al., 2010; Chen and Zhou, 2009), the identification of crop protectants with alternative modes of action is an increasingly urgent task. This challenge can be addressed through the development of novel high-throughput assays as we have demonstrated with the Arabidopsis-F. graminearum liquid pathosystem.

Experimental Procedures

Fungal strains and inoculum preparation

Fusarium graminearum Schwabe (teleomorph Giberella zeae (Schw.) Petch) wildtype strain DAOM 233423 was obtained from the Canadian Collection of Fungal

Cultures (CCFC/DAOM), Agriculture and Agri-Food Canada, Ottawa. A Δtri6 strain was generated by homologous recombination, as described by Seong et al. (2009).

The F. graminearum-GFP (Fg-GFP) strain was obtained from Dr. Robert Proctor,

National Center for Agricultural Utilization Research, Agricultural Research Service,

USDA, Peoria, Ill. USA. Fungi were grown on potato dextrose agar (PDA) media for routine culture and analyses. To prepare conidiospores for pathogenicity assays, an approximately 3 mm plug was extracted from a fresh PDA plate culture and transferred to 100 mL of CMC media (Cappellini and Peterson, 1965). Cultures were shaken at

28°C for 3-5 days to generate conidia. Mycelial solids were separated from conidia by 107 passing through four layers of sterile cheesecloth. Conidia were then washed with sterile water twice by centrifugation at 4,000 rpm for 15 minutes at room temperature.

The lightly pelleted conidia were resuspended in sterile water and then stored at 4°C.

Conidia were inspected and counted with a hemocytometer prior to use.

Arabidopsis-Fusarium graminearum 96-well plate pathogenicity assay

Arabidopsis thaliana (ecotype Columbia) was used for liquid assays, which also included coi1 and jar1 mutants, obtained from Dr. Jeff Dangl, University of North

Carolina. A homozygous T-DNA insertion line (SALK_026801C) affecting the

FLAGELLIN-SENSITIVE 2 (FLS2) gene (At5g46330) was obtained from the

Arabidopsis Biological Resource Center. Assays in liquid media were conducted essentially as outlined in Chapter 2. Briefly, five to ten Arabidopsis seeds were distributed into each well of 96-well plates, with the exception of the 36 most peripheral wells. Plates with seeds were sterilized by exposure to chlorine gas, and 200 μL of liquid media (0.5X Murashige and Skoog (MS) basal media (SigmaAldrich, Oakville,

ON, Canada), 2.5 mM 2-(N-Morpholino)ethanesulfonic acid (MES), pH 5.8

(SigmaAldrich)) was added to each well. After four days of stratification at 4°C, covered plates were placed under continuous light at 22°C. Five-day-old seedlings were inoculated with F. graminearum conidiospore suspensions at a final concentration of

50-500 spores/mL. Covered plates were gently agitated on a Heidolph Titramax 1000 vibrating shaker (VWR, Mississauga, ON, Canada) at 600 rpm under continuous light at 22°C in a controlled environment chamber. Seedling phenotypes were assessed at four days post-inoculation. Images of macroscropic disease symptoms were collected by brightfield microscopy of whole seedlings mounted on 1.5% agar plates. Plant cell 108 death and fungal growth within seedlings were both visualized by lactophenol-trypan blue staining (Koch and Slusarenko 1990). Samples were viewed with a Leica MZFLIII stereomicroscope (Leica Microsystems, Wetzlar, Germany) and all photographs taken with either a Canon EOSD60 digital camera (Canon Inc., Tokyo, Japan) or a

MicroPublisher 3.3 RTV camera (QImaging, Surrey, BC, Canada). For confocal imaging, seedlings were mounted on slides and viewed with a Zeiss LSM 510 META confocal microscope (Carl Zeiss Canada Ltd., Toronto, ON, Canada). GFP-labeled mycelia were visualized using an excitation wavelength of 488 nm and a 500 to 530 nm emission filter. All confocal images were processed with the Zeiss LSM image browser. Images were assembled in Adobe Photoshop CS2 (Adobe Systems,

Mountain View, CA, USA).

Chemical screening

The TimTec NP280 natural product collection (TimTec LLC, Newark, DE, USA) was provided as 2.5 mM stock solutions dissolved in dimethyl sulfoxide (DMSO). One plate of these chemicals (80 compounds) was screened using five-day-old seedlings grown in liquid media as described above. Compounds were added to each well at a final concentration of 25 μM. Each plate included a well containing 25 μM hygromycin as a positive control, along with several negative control wells containing 1% DMSO.

Plates were stored in the dark at room temperature for twelve hours, then inoculated with F. graminearum and incubated as described above. Seedling phenotypes were assessed at three to four days post-inoculation. All compounds were screened in triplicate. Experiments using flg22 peptide (Sheldon Biotechnology Centre, Montreal,

109 QC, Canada) as well as retests of individual compounds (obtained from SigmaAldrich) were conducted in the same manner.

Wheat cultivation and pathogenicity assays

All wheat pathogenicity assays were performed on Triticum aestivum L. cultivar

Roblin, which is susceptible to F. graminearum. Seeds were provided by André

Kalikilio, Agriculture and Agri-Food Canada, Ottawa. Seeds were surface sterilized with 50% sodium hypochlorite and washed three times with sterile distilled water.

Seeds were then transferred to 1% water agar plates supplemented with 50 μg/mL streptomycin. After 48 hrs, germlings were planted out (two per pot) in four-inch fiber pots. Planting medium consisted of three parts topsoil, two parts peatmoss, one part sand, plus dolomitic lime for pH adjustment. Potted seedlings were cultivated in a growth chamber under both fluorescent and incandescent lighting to provide a 16 hr photoperiod and a 22°C/15°C day/night temperature cycle. Soil was amended with 20-

20-20 fertilizer twice weekly for the first four weeks of growth, then once weekly until mid-anthesis (approximately six to seven weeks), at which point pathogenicity assays were performed.

Two different methods were used to evaluate the activity of chemicals in wheat pathogenicity assays. Inocula for “antagonism” experiments contained 50 μM of the chemical compound and 1,000 F. graminearum conidiospores in a 10 μL volume. This solution was applied interior to the lemma of one spikelet midway down the head, using

5 to 10 heads per treatment. A spore suspension containing 1% DMSO was used as a control. For “priming” experiments, chemicals (50 μM) in a 10 μL volume were applied to one spikelet per head, followed by inoculation of an adjacent spikelet 24 hours later 110 with a 10 μL droplet containing 1,000 spores. In a variation of the priming experiment, wheat heads were sprayed with a solution of 250 μM chemical plus 0.01% Silwet L-77 surfactant (GE Silicones, South Charleston, WV, USA), then sprayed 24 hours later with a suspension of 5 x 104 spores/mL plus 0.01% Silwet. For all evaluation methods, inoculated plants were transferred to a spray facility under greenhouse conditions.

Plants were monitored for the development of disease symptoms such as spikelet discolouration and analyzed when heads in the control treatment group exhibited approximately 100% spikelet infection. The concentration of DON in inoculated tissues was measured by ELISA as previously described (Sinha et al., 1995).

Acknowledgements

We are grateful to Dr. Jeff Dangl for Arabidopsis mutant lines, and to Dr. Robert

Proctor for the F. graminearum-GFP strain. We thank Denise Chabot for technical assistance with confocal microscopy. We are grateful to the handling editor and anonymous reviewers for their insightful comments. K.S. was supported by the Natural

Science and Engineering Research Council (NSERC) of Canada. D.D. is a Canada

Research Chair in Plant-Microbe Systems Biology. This work was supported by an

NSERC Discovery Grant and awards from the Canadian Foundation for Innovation and the Ontario Ministry of Research and Innovation to D.D.

111

Chapter 4

Characterization of the Activity of Sulfamethoxazole in

Arabidopsis

(Unpublished data from experiments performed by Karl Schreiber, with the following exceptions: Arabidopsis microarrays were prepared and scanned by Thanh Nguyen at the Centre for the Analysis of Genome Evolution and Function (CAGEF, University of

Toronto). For genetic mapping, whole-genome sequencing was performed by Pauline

Fung and Jianfeng Zhang, with downstream data analysis by Yunchen Gong and Dr.

Ryan Austin, all also associated with CAGEF.)

112 Abstract

Sulfamethoxazole (Smex) protects Arabidopsis seedlings from infection by either

Pseudomonas syringae or Fusarium graminearum, although the exact mechanism by which this occurs is presently unknown. In order to further characterize the activity of this compound in Arabidopsis, we adopted a number of investigative strategies.

Analysis of candidate Smex targets revealed that this compound may affect dihydropteroate synthase, an enzyme involved in folate biosynthesis, although the induction of resistance is folate-independent. Additional candidate gene analysis indicated that the eventual manifestation of disease resistance was not mediated by signalling pathways normally associated with plant defence. Consequently, we initiated two forward genetic screens to identify mutants that exhibit altered sensitivity to Smex in a seedling growth assay. Subsequent mapping of a mutant with reduced sensitivity to Smex (RSS) indicated that a gene encoding 5-oxoprolinase was responsible for this phenotype. A mutation causing enhanced sensitivity to Smex (ESS) was mapped to a gene lacking any functional annotation. Transcriptomic analysis of Smex-treated plants inoculated with P. syringae suggested that this compound may influence lipid metabolism at some level. While jasmonic acid (JA) is one of the products of lipid biosynthesis, preliminary data indicate that Smex does not affect JA signalling.

113 Introduction

Many small molecules can protect plants from pathogen infection (Chapter 1), yet the precise mechanisms underlying this protection are generally not well characterized. We previously identified sulfamethoxazole (Smex) in a screen for small molecules capable of protecting Arabidopsis seedlings from infection by Pseudomonas syringae (Chapter 2) and Fusarium graminearum (Chapter 3). There is considerable evidence that sulfanilamide compounds like Smex inhibit the bifunctional enzyme hydroxymethyldiopterin pyrophosphokinase/dihydropteroate synthase (HPPK/DHPS), which catalyzes one of the early steps in the folate biosynthetic pathway in plants

(Figure 4-1) (Neuburger et al., 1996; Prabhu et al., 1997; Prabhu et al., 1998; Loizeau et al., 2007; Storozhenko et al., 2007). This pathway forms the foundation of one- carbon metabolism, whose products include a variety of key metabolic components such as purines, amino acids, and enzyme cofactors (Jabrin et al., 2003). The mechanism by which inhibition of this pathway would stimulate plant defence responses is currently unknown.

Historically, forward genetic screens have yielded important insights into the signalling pathways that mediate defence induction by small molecules. Some of these screens were based on the expression of reporter genes driven by chemically-inducible promoters. For salicylic acid (SA), pathogenesis-related protein (PR) gene reporters were employed in screens that identified mutants in NPR1 (nonexpressor of PR genes1), which encodes a key SA signalling component (Cao et al., 1994; Shah et al.,

1997). Subsequent suppressor screens using the same reporter shed additional light on the regulation of SA-dependent responses (Li et al., 1999; Shah et al., 1999; Li et al., 2001). In other cases, secondary phenotypes like plant growth or fertility were used

114

115 Figure 4-1: Overview of tetrahydrofolate (THF) biosynthesis in Arabidopsis.

(A) Biochemical inputs to and outputs from the THF biosynthetic pathway.

Polyglutamated THF (THF-Glun) is a key substrate for one-carbon metabolic pathways, which produce a range of biologically important molecules. Abbreviations: PABA = p- aminobenzoic acid, fMet-tRNA = formylmethionyl-tRNA, AdoMet = S-adenosyl-Met.

Adapted from Jabrin et al. (2003) and Loizeau et al. (2007).

(B) Detailed view of the THF biosynthetic pathway. The first two reactions are catalyzed by a bifunctional hydroxymethyldihydropterin pyrophosphokinase

(HPPK)/dihydropteroate synthase (DHPS) enzyme, for which both mitochondrial and cytosolic isoforms are known. The final two steps occur exclusively in mitochondria and are facilitated by dihydrofolate synthase (DHFS) and dihydrofolate reductase

(DHFR). Sulfanilamides inhibit DHPS by competing with PABA for enzyme binding sites, while methotrexate competes with dihydrofolate for binding to DHFR. Adapted from Storozhenko et al. (2007).

(C) Chemical structures of PABA and the sulfanilamide core, where R represents a variable side group.

116 to identify mutants with altered responses to jasmonic acid (JA), β-aminobutyric acid

(BABA), ethylene, or the bacterial flagellin peptide flg22 (Guzmán and Ecker, 1990;

Staswick et al., 1992; Feys et al., 1994; Gómez-Gómez et al., 1999; Ton et al., 2005).

It is possible to conduct a screen based on direct evaluations of chemically-induced disease resistance (Delaney et al., 1995), but a screen of reasonable throughput demands that visual assessments of pathogen infection phenotypes can be conducted easily and reliably. The difficulty of satisfying these criteria in many pathosystems illustrates the appeal of using surrogate screening phenotypes for studying the activity of small molecules in plants.

In this chapter, we describe our efforts to characterize the activity of Smex in

Arabidopsis. Initially, this included evaluations of mutants representing various defence-related signalling components and potential Smex targets, all of which suggested that Smex induces plant defence responses through a novel mechanism that may be initiated by the inhibition of HPPK/DHPS, but does not involve altered folate biosynthesis. To further interrogate this mechanism, seedling growth phenotypes on media containing Smex were used as the basis for forward genetic screens aimed at identifying mutants with altered responses to the compound. Transcriptional profiles of Smex-treated plants in the presence or absence of pathogen infection were also analyzed. Cumulatively, these experiments did provide some insight into the responses of Arabidopsis to Smex, although the connection between these responses and disease resistance remains to be fully discerned.

117 Results

Impact of Smex on bacterial growth and virulence

A number of different approaches were taken to investigate the manner in which

Smex reduces the susceptibility of Arabidopsis to infection by P. syringae. We decided to focus on P. syringae because its interaction with Arabidopsis is more well-studied and amenable to quantitative analysis than the F. graminearum-Arabidopsis pathosystem. For sulfanilamide compounds such as Smex, protective activity may derive from an inhibition of pathogen growth or of some aspect of pathogen virulence, based on the original medical applications of sulfanilamides as antimicrobials (Mueller,

1945). We previously established that, although Smex did slow bacterial growth at high concentrations (250 μM), the growth of P. syringae pv. tomato strain DC3000 (Pto

DC3000) was affected only minimally at the concentrations used for chemical screening (Chapter 2). One important caveat is that these data were obtained by recording the optical density of cultures with a relatively high initial cell concentration

(~5 x 107 cfu/mL). To more accurately reflect the conditions of the liquid assay, media was collected from plates in which seedlings had been grown for five days. This media

(minus the seedlings) was inoculated with Pto DC3000 to 1 x 105 cfu/mL and bacterial growth over time was quantified by serial dilution plating. Under these conditions, Pto

DC3000 growth was not significantly affected by 25 or even 100 μM Smex (Figure 4-2), thus providing additional evidence to exclude bacteriocidal or bacteriostatic mechanisms of protection from infection. We also ruled out inhibition of type III secretion by Smex (Chapter 2), which suggests that that Pto DC3000 should be fully

118

Figure 4-2: Growth of Pseudomonas syringae pv. tomato DC3000 (Pto DC3000) in media containing sulfamethoxazole (Smex). Media from 96-well plates containing five- day-old Arabidopsis seedlings was separated from the seedlings, filter-sterilized, and distributed to a sterile 96-well plate. Media was supplemented with Smex (or 1%

DMSO as a control) and inoculated with Pto DC3000 at a concentration of approximately 1 x 105 cfu/mL. Plates were incubated at room temperature on a vibrating shaker and bacterial populations quantified at 24-hour intervals by dilution plating. Similar results were obtained in two independent experiments.

119 capable of infecting Arabidopsis in the presence of the compound.

Analysis of candidate Smex targets

In the apparent absence of activity on the pathogen side of the interaction, we concluded that Smex likely affects some component of plant metabolism and/or signalling that is associated with disease resistance. High-performance liquid chromatography analyses of seedlings and liquid media collected after five days of incubation with Smex indicated that the compound does not undergo any obvious structural changes over this time period, suggesting that the activity of Smex does not depend on its modification or metabolism in planta (Zhao et al., 2007; S.R. Cutler, personal communication). In terms of predicted in planta targets, the primary candidate was the folate biosynthetic enzyme HPPK/DHPS, whose inhibition by sulfanilamides has been documented in both plants and bacteria (Merali et al., 1990; Prabhu et al.,

1997; Prabhu et al., 1998; Loizeau et al., 2007). Homozygous T-DNA knockout lines of the two HPPK/DHPS genes in Arabidopsis were tested in the liquid assay, revealing that Smex still provided protection from bleaching (Figure 4-3A). In addition, these mutants did not phenocopy Smex activity, remaining susceptible to pathogen infection both in the liquid assay and in soil-grown plants (Figure 4-3). Attempts to generate

HPPK/DHPS double knockout lines were unsuccessful, although further genotypic screening may have been fruitful (see Discussion). In yeast, inhibition of folate biosynthesis by sulfanilamides can be rescued by supplementation with precursor compounds such as p-aminobenzoic acid (PABA) (Kornfeld and Nichols, 2005).

Replacement of immediate downstream intermediates like dihydrofolate (DHF) would presumably also restore folate biosynthesis. When seedlings were co-treated with 120

121 Figure 4-3: Relationship between the enzyme hydroxymethyldiopterin pyrophosphokinase/dihydropteroate synthase (HPPK/DHPS) and sulfamethoxazole

(Smex)-induced disease resistance in Arabidopsis.

(A) Infection phenotypes of T-DNA insertion lines in which the gene encoding either a cytosolic (cyt) or mitochondrial (mit) isoform of HPPK/DHPS is disrupted. Seedlings were treated with 25 μM Smex 12 hours prior to inoculation with P. syringae pv. tomato

DC3000 (Pto DC3000) at a final concentration of 1 x 105 cfu/mL. Images were captured at five days post-inoculation.

(B) In planta growth of Pto DC3000 in HPPK/DHPS knockout lines. Six-week-old soil- grown plants were inoculated by pressure infiltration with a bacterial suspension at 1 x

105 cfu/mL and bacterial populations quantified at three days post-inoculation. Error bars represent standard deviation.

Similar results were obtained in at least two independent experiments.

122

(continued on next page) 123

124 Figure 4-4: Relationship between folate biosynthesis and sulfamethoxazole (Smex)- induced disease resistance in Arabidopsis.

(A,B) Determination of the influence of exogenous dihydrofolate (DHF) and p- aminobenzoic acid (PABA) on Smex-induced disease resistance. Seedlings were co- treated with 25 μM Smex and a range of DHF/PABA concentrations, then inoculated 12 hours later with P. syringae pv. tomato DC3000 (Pto DC3000) to a final concentration of 1 x 105 cfu/mL. Images were captured at five days post-inoculation.

(C) In planta bacterial growth in seedlings co-treated with 25 μM Smex and 3 μM

PABA 12 hours prior to inoculation with 1 x 105 cfu/mL Pto DC3000. Data represent bacterial populations at three days post-inoculation and error bars reflect standard deviation. Asterisks indicate a statistically significant difference relative to the untreated control, within either seedlings or wells, as determined by pairwise Student’s t-tests (α=0.05)

(D) Determination of the activity of the antifolate compound methotrexate in the liquid assay. Seedlings were treated with a range of methotrexate concentrations 12 hours prior to inoculation with Pto DC3000 at a final concentration of 1 x 105 cfu/mL. Images were captured at five days post-inoculation.

Similar results were obtained in at least two independent experiments.

125 Smex and DHF, Smex activity in the liquid assay was unaffected (Figure 4-4A). Co- treatment with PABA, however, did abrogate the protection conferred by Smex (Figure

4-4B,C). Folate biosynthesis can also be blocked downstream of HPPK/DHPS by methotrexate, which inhibits the enzyme dihydrofolate reductase (Prabhu et al., 1998).

Notably, seedlings treated with methotrexate did not exhibit increased resistance to bacterial infection (Figure 4-4D), suggesting that folate biosynthesis in general does not significantly impact disease resistance.

Forward genetic screens for altered responses to Smex

Although Smex may directly impact HPPK/DHPS activity, the downstream components that manifest plant disease resistance are still unknown. Plant defence responses are mediated largely by signalling pathways downstream of a few key molecules (Bari and Jones, 2009). We evaluated several mutants with impaired perception or transmission of signals associated with SA (npr1, nahG, eds16), JA (coi1, jar1), ethylene (ein1, ein2-5), ABA (abi3-9, abi3-10), and reactive oxygen species

(rbohD, rbohF, rbohDrbohF). Regardless of whether Smex was applied at 10 or 25 μM, the ability of this compound to prevent macroscopic infection symptoms was retained in the liquid assay in all mutant genotypes (Figure 4-5, data not shown). Altogether, it appears that Smex induces plant defence responses independently of the common signalling pathways.

As a result, we decided to utilize forward genetic screens to identify the apparently novel mediator(s) of Smex activity. We established a phenotype amenable to high-throughput surveys based on the observation that Arabidopsis (Col-0) seeds germinated on solid media (0.5X MS, 2.5 mM MES; pH 5.8, 0.8% agar) containing 3 126

127 Figure 4-5: Activity of sulfamethoxazole (Smex) in Arabidopsis mutants that affect defence-related signalling pathways.

(A) Infection phenotypes of salicylic acid (SA) signalling mutants in the liquid assay.

Seedlings were treated with 25 μM Smex 12 hours prior to inoculation with P. syringae pv. tomato DC3000 (Pto DC3000) at a final concentration of 1 x 105 cfu/mL. Images were captured at five days post-inoculation.

(B) In planta growth of Pto DC3000 in SA signalling mutants. Seedlings were treated as in (A) and bacterial populations were quantified at three days post-inoculation. Error bars represent standard deviation. While the differences in bacterial counts between

DMSO and Smex treatments are statistically significant for all genotypes, there are no significant differences between genotypes within each group of treatments. Similar results were obtained with 10 μM Smex.

Similar results were obtained in at least two independent experiments.

128 μM Smex yield severely stunted seedlings that are almost completely bleached (Figure

4-6). Neither sulfapyridine nor the sulfanilamide core group itself causes this growth inhibition (Figure 4-6B), which is important given that these two compounds also do not protect seedlings from infection in the liquid assay. We also evaluated a number of additional sulfanilamide compounds (Figure 4-7) and noted no clear association between specific structural features and chemical activity, although the activity of Smex was among the highest of all of the compounds tested.

Mutants with reduced sensitivity to Smex

Based on the activity of Smex in the seedling growth assay, we initiated two forward chemical genetic screens, one of which involved germinating EMS- mutagenized Arabidopsis seeds on media containing 3 μM Smex in order to identify mutants with reduced sensitivity to Smex (RSS). From approximately 16,000 M2 seeds screened, 197 putative RSS mutants were identified, and reduced sensitivity to Smex was confirmed in either the M3 or M4 generation for 37 of these lines. When these mutants were tested in the liquid assay, sixteen exhibited significant reductions in

Smex-mediated protection from infection. Importantly, this seemed to validate the use of a seedling growth assay as a means of addressing Smex activity in the liquid assay.

On the other hand, any attempts to map these mutants would be most easily performed using the seedling growth phenotype, and the most insensitive mutants would provide the clearest phenotype for mapping. In order to quantify the insensitivity of the mutants, each line was sown on media containing a range of Smex concentrations, revealing that nine of the sixteen were significantly less sensitive to Smex than

129

Figure 4-6: Growth phenotypes of Arabidopsis seedlings germinated on media containing sulfamethoxazole (Smex).

(A) Seeds were germinated on Smex, sulfanilamide (Snil), or DMSO as a control.

Images were captured after 16 days of growth.

(B) Fresh weight measurements from seedlings grown in the presence of 3 μM Smex,

Snil, or sulfapyridine (Spyr). For each treatment, three plates were prepared with approximately 40 seeds each. Measurements were taken after 12 days of growth and represent the mean value from three plates ± standard deviation. The asterisk indicates a statistically significant difference between the Smex samples and the

DMSO control as determined by a Student’s t-test (α=0.05).

Similar results were obtained in at least two independent experiments.

130

131 Figure 4-7: Structure-activity relationships for various sulfanilamide compounds. The sulfanilamide core is shown in the bottom left corner, and specific R-groups for each compound indicated above. Activity assays were performed using Arabidopsis (Col-0) seed plated on 0.5X MS agar media containing a range of chemical concentrations.

Seedling phenotypes were assessed after 10-14 days of growth. “EC50” indicates the effective concentration of chemical at which 50% of the seedlings were bleached, and

“LD50” denotes the concentration that was lethal to 50% of the seedlings. Data represent the mean of two independent experiments. The dendrogram on the left was generated using the ChemMine online structural analysis workbench

(http://chemmine.ucr.edu; Girke et al., 2005).

132 wildtype. The open reading frames of both HPPK/DHPS genes were sequenced in all nine mutants, and none were found to contain mutations. Remarkably, eight of the nine selected RSS lines were also insensitive to the antifolate compound methotrexate.

The lone exception, designated RSS 26-1, exhibited the greatest reduction in Smex sensitivity while remaining as sensitive as wildtype to methotrexate. This mutant also resembled wildtype plants in terms of its sensitivity to other phytotoxins such as SA and the herbicide Bialaphos (data not shown).

The apparent specificity of chemical insensitivity in RSS 26-1 suggested that the mutation underlying this phenotype should provide some insight into Smex-induced pathways in Arabidopsis. In preparation for mapping this mutation, RSS 26-1 (M4) was crossed to ecotype Landsberg erecta. Smex-insensitive individuals from the F2 of this cross were recovered on media containing 5 μM Smex, and genomic DNA was extracted from the tissues of 80 individuals. The DNA sample was sequenced using an

Illumina Genome Analyzer in order to identify a genomic region in which putative mutations of interest reside. This analysis generated a short list of candidate genes whose relevance to the RSS phenotype was evaluated using T-DNA insertion lines.

These efforts confirmed that RSS 26-1 was derived from a mutation (S282L at the amino acid level) in a gene encoding an oxoprolinase enzyme (OXP1; At5g37830). A homozygous oxp1 knockout line (oxp1-1) exhibited further reduced sensitivity to Smex relative to RSS 26-1 in seedling germination assays (data not shown). While oxp1-1 mutant plants grown in soil did not differ from wildtype in terms of susceptibility to bacterial infection, oxp1-1 seedlings in liquid media did support slightly higher levels

(~0.5 logs) of bacterial growth (Figure 4-8). Interestingly, the cotyledons of oxp1-1 seedlings became bleached even in the absence of pathogen infection (Figure 4-8), yet

133

134 Figure 4-8: Activity of sulfamethoxazole (Smex) in Arabidopsis oxp1-1 T-DNA disruptants.

(A) Infection phenotypes of oxp1-1 in the liquid assay. Seedlings were treated with 25

μM Smex 12 hours prior to inoculation with P. syringae pv. tomato DC3000 (Pto

DC3000) at a final concentration of 1 x 105 cfu/mL. Images were captured at five days post-inoculation.

(B) In planta growth of Pto DC3000 in oxp1-1 T-DNA disruptants. Seedlings were treated as in (A) and bacterial populations were quantified at three days post- inoculation. Error bars represent standard deviation. An asterisk indicates a statistically significant difference between the two genotypes within a given treatment, as determined by a Student’s t-test (α=0.05). Similar results were obtained with 10 μM

Smex.

Similar results were obtained in at least two independent experiments.

135 pathogen growth was still significantly reduced in the presence of Smex. As such,

OXP1 likely does not contribute to Smex-induced defence responses.

Mutants with enhanced sensitivity to Smex

In addition to screening for insensitivity to Smex, a second forward genetic screen focused on identifying mutants with enhanced sensitivity to this compound. In this screen, seeds were germinated on media containing 0.5 μM Smex, which does not affect the growth or appearance of wildtype seedlings. Approximately 12,000 M2 seeds were screened, and 538 individuals exhibited bleaching and/or stunted growth. A secondary screen conducted on media containing either 0.5 μM Smex or 0.4% DMSO indicated that three mutants displayed Smex-specific phenotypes. The first “enhanced sensitivity to Smex” (ESS) mutant to be confirmed was ESS 3-10, which showed nearly

700-fold greater sensitivity to Smex than did wildtype Arabidopsis (Col-0) (Figure 4-9A).

This phenotype could be partially rescued by the addition of PABA or DHF (Figure 4-

9B, data not shown), indicating that HPPK/DHPS inhibition contributes to Smex hypersensitivity in this mutant. Notably, the chemical hypersensitivity of ESS 3-10 was not a general phenomenon, because it did not differ from wildtype when germinated in the presence of SA, Bialaphos, or methotrexate (Table 4-1). In terms of disease resistance phenotypes, we noted that the susceptibility of ESS 3-10 to bacterial infection was not altered relative to wildtype and that the efficacy of Smex-induced resistance was not enhanced in this mutant (data not shown). Nonetheless, the dramatic hypersensitivity of ESS3-10 provided an opportunity to further dissect plant responses to Smex.

136

Figure 4-9: Phenotypes associated with an “enhanced sensitivity to sulfamethoxazole

(Smex)” mutant (ESS 3-10).

(A) Seedling growth phenotype of ESS 3-10 on media containing 0.5 μM Smex. Scale bar represents 0.5 cm.

(B) Seedling growth phenotypes of ESS 3-10 on media containing both p- aminobenzoic acid (PABA) and 0.5 μM Smex. Similar results were obtained with dihydrofolate (DHF) supplementation, although 10 μM DHF most effectively mitigated the Smex-induced inhibition of seedling growth.

Both images were captured after 14 days of growth.

137 Table 4-1: Phytotoxin sensitivity of wildtype Arabidopsis and a mutant that exhibits enhanced sensitivity to sulfamethoxazole (ESS 3-10)

a b Genotype Compound EC50 (μM) LD50 (μM)

Wildtype Sulfamethoxazole 2 5 ESS 3-10 Sulfamethoxazole 0.003 0.03

Wildtype Sulfanilamide 150 >250 ESS 3-10 Sulfanilamide 5 30

Wildtype Salicylic acid 75 150 ESS 3-10 Salicylic acid 75 150

Wildtype Bialaphos 0.1 0.75 ESS 3-10 Bialaphos 0.1 0.75

Wildtype Methotrexate 0.03 0.1 ESS 3-10 Methotrexate 0.03 0.1

a EC50 indicates the concentration at which 50% of seedlings are bleached. b LD50 indicates the concentration that is lethal to 50% of seedlings.

138 As with RSS 26-1, a mapping population was generated for ESS 3-10 and sequenced en masse. Analyses of data from two sequencing runs produced a list of eight candidate genes for which T-DNA knockout lines were obtained. Subsequent germination assays revealed Smex hypersensitivity in a line bearing a T-DNA insertion within At2g23470. (The original EMS line contained a mutation that caused a Gly-to-

Glu amino acid change at position 219.) Subsequent experiments with this insertion line appeared to confirm the lack of association between At2g23470 and any defence- related phenotypes (data not shown).

Transcriptional profiling of Smex activity in Arabidopsis

In parallel to the genetic screens, we sought to obtain a more detailed picture of

Smex-induced responses in Arabidopsis by conducting transcriptional profiling of

Smex-treated plants. Initially, gene expression analyses were performed on RNA extracted from seedlings grown in liquid media following 12 hours of exposure to either

1% DMSO or 100 μM Smex. The transcriptional changes induced by this treatment were relatively minor, with the expression of 335 genes altered by more than two-fold, only 67 of which changed more than three-fold (Appendix 4). This subtle transcriptional modulation suggested that Smex does not directly stimulate plant defence responses but may instead “prime” for faster and/or more intense responses upon pathogen infection. With this in mind, a priming experiment was performed in which soil-grown plants were sprayed with either 1% DMSO or 500 μM Smex, inoculated with 2 x 108 cfu/mL Pto DC3000 24 hours later, and tissues harvested at 4 hours post-inoculation.

Similar to the seedling experiment, the expression of 333 genes changed by more than

139 two-fold in the priming experiment (188 up- and 145 downregulated genes) (Appendix

5). Some of the transcriptional changes were more dramatic, however, with 35 genes up- or downregulated more than five-fold by pre-treatment with Smex (Tables 4-2 and

4-3). Notably, there was very little overlap between the seedling and priming experiments, with only six significantly upregulated and six significantly downregulated genes shared between the two datasets (Appendix 5). In order to draw general conclusions about the metabolic processes affected by Smex, data from the seedling and priming experiments were analyzed with AtCAST (Arabidopsis thaliana: DNA

Microarray Correlation Analysis Tool), which compares a query transcriptional profile with a database of publicly available microarray data (Sasaki et al., 2011). This analysis indicated that neither dataset shared any significant correlation with the reference data, suggesting a novel mode of defence activation. Indeed, manual analyses of other microarray data indicated little correspondence between our data and the expression profiles associated with pathogen infection or treatment with defence- related small molecules (Table 4-4). Finally, genes in the priming dataset were categorized by predicted function using the program “ChipEnrich” (Orlando et al.,

2009), which revealed that this dataset was enriched for genes with Gene Ontology

(GO) annotations associated with some aspect of lipid metabolism (Table 4-5).

The apparent effect on lipid metabolism was intriguing given the connection between lipids and JA biosynthesis (Gfeller et al., 2010). Importantly, JA-insensitive mutants such as coi1 exhibit enhanced resistance to Pto DC3000 infection when assessed using soil-grown plants (Figure 4-10A, also Kloek et al., 2001; Zhao et al., 2003). This suggested that targeting the JA pathway would be an effective mechanism of chemically-induced disease resistance, as recently demonstrated for BABA (Tsai et al.,

2011). In the liquid assay, however, coi1 and wildtype seedlings were equally 140 Table 4-2: Arabidopsis genes upregulated by at least five-fold in plants treated with sulfamethoxazole versus DMSO prior to bacterial infectiona Arithmetic Locus Description Fold Change

At3g43740 Putative leucine-rich repeat family protein 61.54 At2g01090 Putative mitochondrial ubiquinol-cytochrome C reductase complex 7.8 kDa protein 40.89 At5g58860 Cytochrome P450 CYP86A subfamily member 30.17 At3g44430 Unknown protein 17.91 At5g37690 GDSL-motif lipase/hydrolase family protein 15.40 At3g30720 Unknown protein 12.26 At4g17470 Palmitoyl protein thioesterase family protein 10.99 At4g29770 Unknown protein 10.93 At3g43960 Putative cysteine proteinase 10.53 At2g47200 Unknown protein 10.11 141 At3g29035 Putative transcription factor 8.03 At2g43670 Glycosyl hydrolase family protein 7.83 At5g44550 Integral membrane family protein 7.46 At4g34510 Very-long-chain fatty acid elongase involved in wax biosynthesis 6.89 At3g46660 Potential natural antisense gene 6.76 At3g46980 Transporter-related protein 6.45 At3g46530 NBS-LRR type R protein (RPP13) 6.27 At3g18400 Putative transcription factor 6.10 At1g15010 Unknown protein 5.66 At5g48350 Ribonuclease H-like superfamily protein 5.64 At5g48090 ELP1 (EDM2-LIKE PROTEIN1), putative transcription factor 5.44 At5g47635 Pollen Ole el allergen and extension family protein 5.02

aSix-week-old plants were sprayed with 1% DMSO or 500 μM Smex, then inoculated with Pto DC3000 24 hours later. Tissues were harvested for RNA extraction at four hours post-inoculation. Fold change values are based on data from two biological replicates.

Table 4-3: Arabidopsis genes downregulated by at least five-fold in plants treated with sulfamethoxazole versus DMSO prior to bacterial infectiona Arithmetic Locus Description Fold Change

At3g45070/ Sulfotransferase family protein 63.79 At3g45080 AtCg00430 NADH dehydrogenase subunit K 9.87 At4g05050 Polyubiquitin gene, belongs to a subtype group with UBQ10 and UBQ14 8.93 At2g01520 Major latex protein-related protein 7.60 At3g28960 Amino acid transporter family protein 6.85 At4g25830 Integral membrane family protein 6.27 At1g28170 Sulfotransferase family protein 6.14 At3g44990 Xyloglucan endo-transglycosylase 6.12 At5g26120 Glycosyl hydrolase family protein 5.72 142 At4g37320 Cytochrome P450 CYP81D subfamily member 5.55 At3g50990 Peroxidase 5.51 At3g30290 Cytochrome P450 gene family member 5.45 At1g72260 Thionin (Thi2.1) 5.02

aSix-week-old plants were sprayed with 1% DMSO or 500 μM Smex, then inoculated with Pto DC3000 24 hours later. Tissues were harvested for RNA extraction at four hours post-inoculation. Fold change values are based on data from two biological replicates.

Table 4-4: Comparison of gene expression data from a sulfamethoxazole priming experiment with transcriptional profiles from Arabidopsis tissues exposed to defence- associated molecules or pathogen infection Number of Co-responsive Time Point Genes Treatment Concentration (h)a Up Down Total %b

Salicylic acid 10 μM 3 26 11 37 11.1 Methyl jasmonate 10 μM 3 21 15 36 10.8 ACC 10 μM 3 9 4 13 3.9 flg22 1 μM 4 35 19 54 16.3 HrpZ 10 μM 4 28 36 64 19.3 Bacterial LPS 100 μg/mL 4 17 6 23 6.9 BABAc 200 μM 70 0 0 0 0.0 c 200 μM/ d BABA + Pto DC3000 22 0 0 0 0.0 5 x 107 cfu/mL

Pto DC3000 108 cfu/mL 6 11 6 17 5.1 Pto DC3000 ΔhrcC 108 cfu/mL 6 9 10 19 5.7 Pto DC3000 avrRpm1 108 cfu/mL 6 23 16 39 11.7 Pto DC3000e 2 x 108cfu/mL 4 7 1 8 2.4 Pto DC3000 ΔhrpAe 2 x 108cfu/mL 4 7 0 7 2.1 Pto DC3000 avrRpm1e 2 x 108cfu/mL 4 14 11 25 7.5 Phytophthora infestans 106 spores/mL 6 45 21 66 19.9 Botrytis cinerea 5 x 105 spores/mL 18 30 6 36 10.8 Erysiphe orontii n/a 6 5 8 13 3.9 aTime of tissue collection, in hours post-treatment or post-inoculation, as appropriate. bThe percent of co-responsive genes is calculated from a total list of 332 genes. cData obtained from Tsai et al. (2011). dBABA was applied as a soil-soak 48 hrs prior to inoculation with Pto DC3000. Tissues were collected 22 hrs post-inoculation. The BABA alone treatment reflects the 70 hours of total exposure to the compound. eData obtained from Truman et al. (2006). Unless otherwise indicated, expression data were obtained from the AtGenExpress Pathogen or Hormone Series, accessed through the Bio-Array Resource Expression Browser (Toufighi et al., 2005). Abbreviations: ACC = 1-aminocyclopropane-1- carboxylic-acid (ethylene precursor), flg22 = flagellin peptide, LPS = lipopolysaccharide, BABA = β-aminobutyric acid, Pto DC3000 = Pseudomonas syringae pv. tomato DC3000 (virulent on Arabidopsis), Pto DC3000 ΔhrcC/ΔhrpA = type III secretion-deficient mutants (nonvirulent), Pto DC3000 avrRpm1 = avirulent bacteria, n/a = not available.

143 Table 4-5: Enrichment of Gene Ontology (GO) annotations in Arabidopsis microarray data from a sulfamethoxazole priming experiment # Total # Total Ontology GO Accession Description Query Query Reference Reference p-valuea Genes Genes Genes Genes GO:0006869 lipid transport 7 319 86 23150 0.000 GO:0000038 very-long-chain fatty acid metabolism 3 319 15 23150 0.001 GO:0009556 microsporogenesis 3 319 16 23150 0.001 GO:0006857 oligopeptide transport 4 319 63 23150 0.009 GO:0007568 aging 3 319 43 23150 0.018 GO:0006810 transport 9 319 321 23150 0.021 Biological GO:0009651 response to salt stress 5 319 143 23150 0.034 Process GO:0006633 fatty acid biosynthesis 3 319 57 23150 0.036 GO:0006118 electron transport 11 319 484 23150 0.036 GO:0006464 protein modification 3 319 58 23150 0.038 GO:0051707 response to other organism 3 319 60 23150 0.040 144 GO:0009737 response to abscisic acid stimulus 5 319 152 23150 0.041 GO:0006952 defence response 8 319 324 23150 0.044 GO:0006629 lipid metabolism 5 319 158 23150 0.046

GO:0012505 endomembrane system 88 319 3348 23150 0.000 Cellular GO:0031225 anchored to membrane 10 319 211 23150 0.001 Component GO:0048046 apoplast 4 319 57 23150 0.007 GO:0016020 membrane 22 319 1105 23150 0.021

GO:0016627 oxidoreductase activity 3 319 7 23150 0.000 GO:0008289 lipid binding 7 319 91 23150 0.000 GO:0008415 acyltransferase activity 6 319 66 23150 0.000 GO:0019825 oxygen binding 9 319 219 23150 0.003 Molecular GO:0030145 manganese ion binding 3 319 31 23150 0.008 Function GO:0042626 ATPase activity, coupled to transmembrane transport 5 319 98 23150 0.009 GO:0004601 peroxidase activity 4 319 78 23150 0.018 GO:0005554 molecular function unknown 104 319 7289 23150 0.044 GO:0045735 nutrient reservoir activity 3 319 65 23150 0.048 (continued on next page)

aThe p-value represents a hypergeometric probability calculation which evaluates, based on the frequency of a given GO term in the reference Arabidopsis database, the probability that the observed frequency of these GO terms in a sample of query genes would be obtained by chance. Both up- and downregulated genes were included in the query list. GO categories containing two or fewer query genes are not shown. Note that the program used for this analysis (ChipEnrich) automatically excludes chloroplast and mitochondrial genes so the query gene list is smaller than the number of differentially expressed genes described in Results.

145

Figure 4-10: Influence of jasmonate (JA) signalling on disease resistance in

Arabidopsis.

(A,B) In planta growth of P. syringae pv. tomato DC3000 (Pto DC3000) in soil-grown plants (A) or seedlings grown in liquid media (B). Wildtype plants were compared to coronatine insensitive1 (coi1) mutants, which are incapable of JA perception. In both experiments, an inoculum concentration of 1 x 105 cfu/mL was used. Error bars represent standard deviation. An asterisk indicates a statistically significant difference between wildtype and coi1 as determined by a Student’s t-test (α=0.05).

Similar results were obtained in two independent experiments.

146 susceptible to Pto DC3000 (Figure 4-10B), and BABA did not confer protection from bacterial infection at any concentration (data not shown). Consequently, the effects of

Smex on lipid metabolism do not appear to be associated with JA signalling.

Discussion

One of the major challenges of chemical genomics is the elucidation of the mechanism(s) by which small molecules affect a phenotype of interest. Sulfanilamides such as Smex are known to be active in both bacteria and plants by inhibiting the enzyme DHPS, which catalyzes one of the early steps in folate biosynthesis (Merali et al., 1990; Prabhu et al., 1997; Prabhu et al., 1998; Loizeau et al., 2007). If this inhibition leads to enhanced disease resistance, it should be possible to replicate this effect genetically using loss-of-function mutants. Arabidopsis contains two isoforms of a bifunctional HPPK/DHPS enzyme, which is unusual given that the sequenced genomes of pea, rice, and poplar appear to encode a single mitochondrial isoform

(Rébeillé et al, 1997; Storozhenko et al., 2007). Nonetheless, using Arabidopsis T-

DNA insertion lines that disrupted either the cytosolic or mitochondrial HPPK/DHPS isoforms, we were unable to phenocopy Smex activity. This may be a consequence of examining single knockouts because, despite largely exclusive spatial and temporal patterns of gene expression (Storozhenko et al., 2007), one isoform may be able to compensate for the absence of the second. Indeed, the critical requirement for folate biosynthesis in plants is illustrated by the single gene encoding dihydrofolate synthase

(Ravanel et al., 2001), in which loss-of-function mutations are embryo-lethal (Ishikawa et al., 2003). This may explain the difficulty in obtaining true double HPPK/DHPS knockouts that would completely eliminate folate production. In order to validate this 147 hypothesis, however, additional genotypic screening of progeny from HPPK/DHPS knockout crosses should be performed. Currently we have identified F2 lines that are homozygous for the cytosolic HPPK/DHPS gene insertions but hemizygous at the mitochondrial HPPK/DHPS locus. Twenty F3 lines were screened without identifying any double homozygotes (one out of every four individuals should have been homozygous), although the desired genotype may be found following more exhaustive screening. We are also generating dexamethasone-inducible HPPK/DHPS RNAi lines to bypass the potential lethality of a double HPPK/DHPS knockout.

On the other hand, there are a number of observations that exclude effects on folate levels as the basis for Smex-induced defence responses. Firstly, methotrexate potently blocks folate production at the enzyme dihydrofolate reductase, yet this compound was unable to protect seedlings from P. syringae infection. Moreover, supplementation of Smex-treated seedlings with downstream folate pathway intermediates such as dihydrofolate did not affect the efficacy of Smex in the liquid assay. Finally, Prabhu et al. (1998) suggested that cellular folate pools in Arabidopsis tissues have a relatively long half-life, since treatment with high concentrations of methotrexate (100 μM) did not halt fluxes through key folate-dependent pathways until

96 hours after treatment.

It was surprising, therefore, to observe that co-treatment of seedlings with PABA and Smex virtually eliminated the protective activity of Smex in the liquid assay. As

PABA and Smex compete for binding to the HPPK/DHPS active site, this result implies that inhibition of HPPK/DHPS actually is important for Smex-induced resistance.

Alternatively, Smex and PABA may competitively bind an enzyme other than

HPPK/DHPS, although there is no evidence in the literature to support this idea. While these observations for HPPK/DHPS are unusual, they do have some precedence. 148 Storozhenko et al. (2007) noted that cytosolic HPPK/DHPS (cytHPPK/DHPS) is produced primarily in the early stages of embryo development, but is strongly induced in the vegetative tissues of seedlings exposed to 150 mM NaCl. No other folate biosynthetic genes were induced by this treatment and folate levels did not change following exposure to NaCl. Furthermore, a cytHPPK/DHPS knockout was significantly more sensitive to oxidative, osmotic, and salt stress relative to wildtype in seed germination assays, despite only slight (11%) reductions in total folate content. All of these data point to a potential role for HPPK/DHPS in contributing to folate- independent responses to stress.

If HPPK/DHPS also influences biotic stress responses, the next area of inquiry relates to the specific biochemical stimulus for these responses. In theory, inhibition of

HPPK/DHPS could result in a depletion of cellular dihydropteroate levels and/or accumulation of dihydropterin pyrophosphate (see Figure 4-1). In reality, cellular dihydropterin pyrophosphate concentrations are normally very low because the HPPK portion of HPPK/DHPS is rapidly inhibited by excess levels of this metabolite (Mouillon et al., 2002). Reduced HPPK activity could cause an accumulation of dihydropterin, although this compound is sufficiently unstable that it cannot be purchased commercially. There is no data on the in vivo stability of dihydropterin, which makes it difficult to predict which molecules, if any, would accumulate in tissues treated with

Smex. Nevertheless, supplementation of liquid assay experiments with folate pathway intermediates both up- and downstream of HPPK/DHPS will clarify their contribution to the induced resistance phenotype.

At the same time, additional experiments could be performed to evaluate the potential activity of Smex in Pto DC3000, whose genome also contains a DHPS gene.

We previously demonstrated that Smex does not affect the growth of this pathogen in 149 liquid media or its capacity for type III secretion (Chapter 2). Despite these observations, the failure to identify a host genotype that completely eliminates Smex- induced resistance suggests that there may be some effect on the pathogen side of the interaction. It is worth noting again that methotrexate did not protect Arabidopsis seedlings from infection which, assuming that this compound also inhibits bacterial dihydrofolate reductase, implies that bacterial folate biosynthesis does not directly influence virulence. As for Arabidopsis, then, it is possible that a DHPS- dependent/folate-independent virulence mechanism is affected by Smex. This could be addressed by testing whether overexpression of DHPS in Pto DC3000 alters the ability of this bacteria to bleach seedlings in the presence of Smex. A second experiment could examine whether the virulence of a DHPS knockout would be reduced in a manner that phenocopies Smex treatment, without affecting bacterial growth in liquid media alone. If virulence is reduced, the activity of the type III secretion system in this knockout could be evaluated as described in Chapter 2.

Although DHPS is a well-established target of sulfanilamide compounds in plants and bacteria, additional proteins are known to interact with these chemicals. In humans, it has long been recognized that sulfanilamides can bind to and inhibit carbonic anhydrases (CAs), which catalyze the interconversion of CO2 and bicarbonate

- ions (HCO3 ) (Locke et al., 1941). Plants possess a multitude of CAs (Fabre et al.,

2007), but these enzymes are three to four orders of magnitude less sensitive to inhibition by sulfanilamides or sulfonamides than are other eukaryotic CAs (Maren and

Sanyal, 1983; Hoang and Chapman, 2002; Supuran, 2008). Furthermore, CAs appear to play a positive role in plant disease resistance (Restrepo et al., 2005; Subramanian et al., 2005; Wang et al., 2009), so it seems unlikely that the activity of Smex is mediated by plant CA inhibition. In contrast, relatively low concentrations of 150 sulfonamides are required to inhibit many bacterial CAs, whose contribution to virulence has been demonstrated in both bacterial and fungal pathogens (Maren and

Sanyal, 1983; Smith and Ferry, 2000; Supuran, 2008). Indeed, we screened a collection of P. syrinage pv. maculicola ES4326 (Pma ES4326) transposon disruptants in the 96-well liquid assay and identified three independent CA gene disruptants that failed to elicit infection symptoms in Arabidopsis seedlings (Appendix 6). In soil-grown plants, however, these disruptants did not exhibit any reductions in virulence relative to wildtype Pma ES4326 (data not shown). At a more mechanistic level, the abrogation of

Smex activity by PABA is difficult to reconcile with regards to CAs, as there is no evidence to suggest that PABA could interact with CAs in order to displace Smex from the enzyme’s active site. Aside from CAs, sulfanilamides also interact with serum albumin in mammalian plasma (Davis, 1943; Meyer and Guttman, 1968), although albumin orthologues are not evident in the genomes of either plants or bacteria.

Overall, therefore, DHPS remains the primary candidate for the direct target of Smex, although the relative contributions of DHPS activity in the host and pathogen remain to be fully characterized.

In addition to the direct targets and immediate biochemical consequences of

Smex treatment, we were also interested in determining the mechanism by which this perturbation ultimately reduces the susceptibility of seedlings to infection. Although we originally identified Smex in a liquid media-based pathology assay, this system is not currently amenable to forward genetic screens due to the difficulty of recovering seedlings from the liquid environment, especially if the seedlings are heavily infected.

As such, we sought a surrogate phenotype with which to assess the sensitivity of

Arabidopsis seedlings to Smex. We found that agar media supplemented with 3 μM

Smex caused significant stunting and bleaching of wildtype (Col-0) seedlings, and 151 noted that the activity of sulfanilamide compounds in the liquid assay generally correlated with their activity on solid media. We subsequently used the seedling growth phenotype to determine the structure-activity relationships amongst a larger set of sulfanilamides (Figure 4-7). Although sulfanilamide itself exhibited exceptionally low activity in this assay, it is clear that there is considerable flexibility in the composition of the major R-group with regards to effects on seedling growth. Both five- and six- member ring structures confer similar activity, and this activity is generally retained despite a variety of substitutions within the ring and/or the presence of additional methyl groups at different positions around the ring. One major exception, however, is sulfapyridine which, despite differing from sulfadiazine by only one atom, exhibits drastically reduced activity. The chemical properties of these two ring structures are likely different, but their relation to activity remains unclear. We also noted a wide variation in the magnitude of differences observed between EC50 and LD50 values. In particular, four compounds had an EC50 of around 10 μM, yet the LD50 ranged from 15 to 95 μM. These observations may reflect different processes underlying the bleaching and lethality phenotypes used to determine EC50 and LD50 values, respectively.

Ultimately, docking models of each sulfanilamide with its target could assist in explaining this behaviour.

At any rate, the salient seedling growth phenotype was conducive to forward genetic screens focused on identifying Arabidopsis mutants with altered responses to

Smex. A screen for mutants with reduced sensitivity to Smex yielded a number of hits that were subsequently confirmed as less responsive to Smex in the liquid assay as well. Notably, while it is possible to confer insensitivity to sulfanilamides by a single base pair change in the HPPK/DHPS gene (Guerineau and Mullineaux, 1989;

152 Guerineau et al., 1990), no mutations within the HPPK/DHPS sequences were observed with the mutants of interest. Also notable was the observation that most of these mutants were less sensitive to both Smex and methotrexate, another inhibitor of folate biosynthesis. Such a broad effect on plant responses to two different antifolate compounds may represent a compensatory mutation that increases overall flux through the folate biosynthetic pathway or one that alters the activity of vacuolar ATP-binding cassette proteins, some of which are known to transport folates and methotrexate

(Raichaudhuri et al., 2009). Only one mutant exhibited reduced sensitivity exclusively to Smex, and the relevant mutation was mapped to a gene encoding an oxoprolinase gene (OXP1).

In plants, oxoprolinase catalyzes the conversion of 5-oxoproline (pyroglutamic acid) into glutamate as part of a glutathione recycling pathway. Theoretically, the loss of OXP1 function could lead to an accumulation of glutathione consequent with an enhanced capacity for elimination of xenobiotics by conjugation to this molecule

(Rouhier et al., 2008). In reality, however, the overall composition and concentrations of thiols appear to be unaffected in oxp1-1 mutants (Ohkama-Ohtsu et al., 2008), so the RSS phenotype is likely not the result of increased Smex detoxification. This conclusion also agrees with our previous observations that Smex does not appear to be degraded or otherwise structurally modified in planta. The loss of OXP1 is associated with other metabolic changes, including the accumulation of significant amounts of 5-oxoproline and reduced concentrations of glutamate in leaves (14-30% lower). There is some evidence that 5-oxoproline causes lipid and protein oxidation in animal neural tissues (Pederzolli et al., 2010), but the extent to which this occurs in plants is unknown. The paucity of information on the physiological roles of 5-oxoproline in plants makes it difficult to hypothesize about the connection between OXP1 and 153 Smex activity in Arabidopsis. Placement of OXP1 in the general context of plant defence is also challenging, because the expression of this gene is not dramatically altered (>2-fold) following either pathogen infection or treatment with known defence- related signalling molecules (data not shown; based on AtGenExpress Pathogen and

Hormone Series datasets, accessed through the Bio-Array Resource Expression

Browser; Toufighi et al., 2005). While some plant defence responses are also strongly influenced by cellular redox status and/or glutathione levels (Senda and Ogawa, 2004;

Parisy et al., 2006; Tada et al., 2008), the apparent lack of effects on these characteristics in an oxp1-1 mutant suggests an alternative, perhaps indirect, role for

OXP1 in mediating Smex activity.

A second screen focused on the identification of mutants with enhanced sensitivity to Smex. A highly hypersensitive mutant was recovered from this screen and mapped to a heretofore uncharacterized locus (At2g23470). This locus encodes a protein of unknown function whose only annotation relates to a sequence motif shared with RUS (root UV-B sensitive) proteins that control growth responses to UV light

(Leasure et al., 2009). As with OXP1, surveys of publicly available gene expression data revealed that At2g23470 is not transcriptionally responsive to either pathogen or defence-related chemical stimuli (data not shown). It should be noted that, despite its significant hypersensitivity to Smex, ESS 3-10 does not exhibit altered resistance to pathogen infection, and Smex-mediated protection is not enhanced in the liquid assay.

In addition, while this hypersensitivity could be rescued by co-treatment with the folate precursor PABA, the sensitivity of ESS 3-10 to methotrexate was not altered relative to wildtype. These observations were later confirmed using a homozygous T-DNA insertion line. Overall, the results from the forward genetic screens indicate that Smex can mediate multiple non-overlapping phenotypes in Arabidopsis. 154 While genetic screens can identify specific genes that are required for a given chemically-induced phenotype, transcriptomic analyses can also be useful for revealing the broad metabolic changes underlying these phenotypes. The transcriptional profile of Smex-treated plants inoculated with Pto DC3000 hinted that some aspect of lipid metabolism was important for the induction of disease resistance by this compound.

We determined that JA was not an important factor in this response, implying that some other lipid-based molecule(s) is/are involved in Smex-induced defence priming. A wide range of such lipid molecules are associated with plant defence (Shah, 2005;

Grienenberger et al., 2010; Pinot and Beisson, 2011), and based on the transcriptional data from the Smex priming experiment, it is tempting to speculate about how Smex treatment might facililate the biosynthesis and/or modification of these lipids. It is important to note that the list of genes exhibiting significant differential expression in the

Smex priming dataset does not resemble transcriptional profiles from tissues treated with known defence-inducing small molecules or from those inoculated with bacterial or fungal pathogens (Table 4-4). This corroborates our observations that Smex activity was retained in several different Arabidopsis defence signalling mutants and suggests that such observations do not derive from functional redundancy amongst these signalling pathways. Overall, our transcriptional data may highlight the novelty of the mechanism by which Smex induces disease resistance, but may also indicate the collection of spurious data. Validation of the microarray data is currently underway, and until this task is complete, any predictions based on these data should be made cautiously.

155 Conclusions

In this chapter, we have described three main strategies for characterizing the biological activity of Smex in Arabidopsis. One approach involved probing candidate

Smex targets both genetically and with additional small molecules, which provided some intriguing observations regarding the potential folate-independent functions of

HPPK/DHPS. This investigation was complemented by forward genetic screens based on seedling growth phenotypes, and while mutants with striking Smex response phenotypes were recovered in these screens, we were unable to genetically disrupt the induction of disease resistance by Smex. Surrogate phenotypes such as plant growth have been successfully employed in the past to interrogate defence-related signalling pathways (Guzmán and Ecker, 1990; Staswick et al., 1992; Feys et al., 1994; Gómez-

Gómez et al., 1999; Ton et al., 2005), but for Smex this phenotype appears to be functionally separate from pathways leading to disease resistance. This in itself is a worthwhile discovery for any small molecule, not only for understanding the full range of downstream responses induced by that molecule, but also for revealing additional biological processes for which the molecule could be used as an investigative tool. For the two Smex response mutants described here, there is now an opportunity to interrogate folate-independent Smex activities as well as ascribe novel phenotypes to genes with little or no previous characterization.

The final approach to Smex characterization was based on transcriptional analyses of plants treated with the compound in the presence or absence of pathogen infection. These efforts highlighted an apparently novel mechanism of defence activation which, although based on relatively preliminary data, at least provides a

156 starting point for future investigations of the influence of Smex on lipid signalling in

Arabidopsis.

Experimental Procedures

Plant materials and bacterial strains

Arabidopsis thaliana (ecotype Columbia) was used for both pathogen infection and seedling growth assays. These assays also included SA-signalling mutants such as nahG, npr1-1, eds16, as well as NADPH oxidase-deficient rbohD, rbohF, and rbohDrbohF mutants, all of which were obtained from Dr. Keiko Yoshioka and Dr.

Wolfgang Moeder, University of Toronto. Mutants with impaired ABA perception (abi3-

9, abi3-10) were obtained from Dr. Peter McCourt, University of Toronto. The JA signalling mutants coi1 and jar1 were obtained from Dr. Jeff Dangl, University of North

Carolina. Forward genetic screens were conducted with ethylmethanesulfonate- mutagenized Arabidopsis (Col-0) seeds (Lehle Seeds, Round Rock, TX, USA). The T-

DNA insertion lines SALK_078745C (At5g37830, OXOPROLINASE1) and CS26759

(At2g23470, gene of unknown function) were obtained from the Arabidopsis Biological

Resource Center (ABRC). Additional lines were obtained from the ABRC for

HPPK/DHPS genetic analyses, including SALK_026328 and SALK_026791, which both contain a T-DNA insertion in the first exon of the mitochondrial HPPK/DHPS gene

(At4g30000). A homozygous line bearing a T-DNA insertion in the 5’ end of the second exon of the cytosolic HPPK/DHPS gene (At1g69190, SALK_093782) was provided by

Dr. Dominique Van Der Straeten, Ghent University.

157 Seeds for soil-grown plants were placed on moist soil (ProMix BX, Premier

Horticulture Ltd., Dorval, PQ, Canada) amended with 20-20-20 fertilizer, stratified for four days at 4ºC, then placed in a growth room with a nine-hour photoperiod and a day/night temperature regime of 22ºC/18ºC. For seedling growth assays, surface- sterilized seeds were plated on media composed of 0.5X Murashige and Skoog (MS) basal salts (SigmaAldrich, Oakville, ON, Canada), 2.5 mM 2-(N-

Morpholino)ethanesulfonic acid (MES), pH 5.8 (SigmaAldrich), and 0.8 % agar.

Following four days of stratification at 4ºC, plates were incubated at 22ºC under continuous light.

All P. syringae strains were grown at 28ºC on King’s B media (KB, King et al.,

1954) supplemented with 50 μg/mL rifampicin. Pto DC3000 was obtained from Dr. Jeff

Dangl.

Genotypic screening of Arabidopsis T-DNA insertion lines

Arabidopsis lines bearing homozygous T-DNA insertions in HPPK/DHPS sequences were identified using the primers listed in Table 4-6. For the generation of

HPPK/DHPS double T-DNA insertion lines, homozygous cytosolic and mitochondrial single gene knockouts were crossed and genotyped in the F2 generation. Two putative double homozygotes were identified and allowed to self-fertilize. Genotyping in the subsequent generation revealed that, while the cytosolic HPPK/DHPS T-DNA insertion was homozygous in both lines, there was still segregation at the mitochondrial locus.

As such, plants from the F3 generation were also genotyped using the same sets of primers.

158 Table 4-6: Primers used in this study

Primer Name Sequence F-cytDHPS 5’- AAGGTCAGATCGAAGCAGAC-3’ R-cytDHPS 5’- TAGCCTTGCCGCGTCTACATTATC-3’ F-mitDHPS 5’- TCACCAGCATCGTCTTCCTCAG-3’ R-mitDHPS 5’- TACTTTTGCTGCGTCGGCGTTATG-3’

Arabidopsis-Pseudomonas syringae 96-well plate pathogenicity assay

For liquid assays, approximately 5-10 Arabidopsis thaliana (ecotype Columbia) seeds were distributed into the 60 innermost wells of 96-well plates and sterilized by exposure to chlorine gas for 3.5 hrs. Two hundred microlitres of liquid media (0.5X MS,

2.5 mM MES; pH 5.8) was subsequently added to each well and a lid secured with

Micropore tape. Seeds were stratified for four days at 4ºC, followed by incubation under continuous light at 22ºC in a controlled environment room. After five days of growth, chemicals were added to the appropriate wells and plates stored in the dark at room temperature for 12 hours. Plates were subsequently inoculated with Pto DC3000 at a

5 final concentration of 1 x 10 cfu/mL (OD600=0.0002). Covered plates were gently agitated on a Heidolph Titramax 1000 vibrating shaker (VWR, Mississauga, ON,

Canada) at 600 rpm under continuous light at 22ºC in a controlled environment room.

Seedling phenotypes were generally assessed at five days post-inoculation.

To enumerate bacterial populations in inoculated seedlings in the liquid assay, the media was removed and replaced with 70% ethanol to surface-sterilize the seedlings. After 20 sec. the ethanol was removed and the seedlings rinsed with four washes of sterile distilled water. Six to ten seedlings were homogenized in 200 μl of 10

159 mM MgCl2 and bacteria were quantified by serial dilution plating. The numbers of bacteria in the liquid media of the assay plates were also determined by serial dilution plating.

Genetic mapping by whole-genome sequencing

To map the mutations responsible for altered sensitivity to Smex, mutants of interest were crossed to ecotype Landsberg. For each mutant, at least 100 F2 plants were selected on the basis of Smex sensitivity in seedling germination assays and transferred to soil. For ESS 3-10, stunted and bleached seedlings were rescued on

0.5X MS media containing 1.5% glucose prior to transplanting on soil. After three weeks of growth, tissues from 80 plants were pooled and genomic DNA was extracted using a Gentra Puregene Genomic DNA Extraction Kit (QIAGEN Inc., Mississauga,

ON, Canada). Samples were sequenced on an Illumina Genome Analyzer IIx (Illumina,

Inc., San Diego, CA, USA) according to the manufacturer’s protocol (Pauline Fung and

Jianfeng Zhang, Centre for the Analysis of Genome Evolution and Function (CAGEF),

University of Toronto, ON, Canada). Sequence assembly and analysis were also performed at CAGEF (Yunchen Gong and Dr. Ryan Austin). A list of candidate loci potentially associated with the Smex sensitivity phenotype was subsequently generated using the web-based application, Next-Gen Mapping (http://bar.utoronto.ca/NGM;

Austin et al., 2011). Candidates were confirmed using homozygous T-DNA insertion lines germinated on 0.5X MS agar media containing the appropriate concentration of

Smex.

160 Transcriptional analyses

Two different experiments were performed to evaluate the effects of Smex on gene expression in Arabidopsis. In one experiment, seedlings grown in liquid media were treated with either 1% DMSO or 100 μM Smex for 12 hours. A second analysis involved soil-grown plants sprayed with either 1% DMSO or 500 μM Smex 24 hours prior to inoculation with 2 x 108 cfu/mL Pto DC3000; tissues were harvested at 4 hours post-inoculation. In both cases, RNA was extracted using TriPure reagent (BioShop

Canada Inc., Burlington, ON, Canada). Gene expression profiles for two biological replicates per sample were generated using Affymetrix instruments and Ath1 whole genome arrays (Thanh Nguyen, CAGEF Affymetrix Facility).

Microarray data analysis was performed using the AFFY package (Gautier et al.,

2004) from the Bioconductor software suite (Gentleman et al., 2004), run in an R programming environment (http://www.R-project.org). Data pre-processing involved

GC-robust multiarray analysis (GCRMA, Wu et al., 2004) followed by data filtering to remove probe sets with low variance (genefilter, Gentleman et al., 2009; minimum interquartile range of 0.5 on a log2 scale). Fold change values were calculated and used to compile lists of significantly differentially expressed genes, based on a fold change cutoff of ± 2.0. Gene lists were compared to other publicly available microarray data using the Arabidopsis thaliana: DNA Microarray Correlation Analysis Tool

(AtCAST, Sasaki et al., 2011). Genes in these lists were also categorized by Gene

Ontology and analyzed statistically using the ChipEnrich program (Orlando et al.,

2009).

161

Chapter 5

General Discussion

162 Discussion

One of the major challenges of high-throughput analyses is the development of assays that economize time, space, and resources while also preserving biological relevance. In this project, I sought to develop an assay for studying plant-pathogen interactions in a high-throughput manner. Using Arabidopsis seedlings grown in liquid media in 96-well plates, I established conditions under which robust macroscopic infection phenotypes could be observed following inoculation with either the bacterial pathogen Pseudomonas syringae or the fungal pathogen Fusarium graminearum. In these assays, I observed that P. syringae eventually bleached the cotyledons of infected seedlings, while F. graminearum infection was associated with the appearance of dark, lesion-like spots on cotyledons. These phenotypes were somewhat different from the symptoms of infection observed in adult soil-grown plants, but significant effort was directed towards determining their validity as indicators of the outcome of these plant-pathogen interactions. For P. syringae, I noted that strains with reduced virulence on soil-grown plants caused markedly less bleaching on liquid-grown seedlings, paralleled by lower in planta growth. Furthermore, salicylic acid (SA) retained its ability to induce disease resistance in the liquid assay, as did the pathogen-associated molecular pattern peptide flg22. With regards to F. graminearum, Arabidopsis genotypes previously shown to be resistant to this pathogen in soil-grown plants remained nearly symptom-free in the liquid assay. Overall, the liquid assay appeared to provide a reasonably valid surrogate for more traditional pathosystem assays.

At the same time, however, it is important to acknowledge that there are some differences in the pathogen responses of liquid-grown seedlings and soil-grown plants.

I noted that the hypersensitive response is suppressed in liquid media, as is the 163 normally elevated disease resistance of cpr mutants, although this suppression can be recapitulated in soil-grown plants grown under high humidity (Yoshioka et al., 2001;

Zhou et al., 2004). In addition, jasmonate-insensitive mutants exhibit enhanced resistance to infection by either P. syringae or F. graminearum when assessed using soil-grown plants, but the resistance to P. syringae is lost in a liquid environment. This is a potentially interesting inconsistency, as the retention of resistance to F. graminearum suggests that jasmonate insensitivity influences plant responses to different pathogens through different mechanisms. Altered jasmonate signalling may also underlie the lack of protection from infection in liquid media observed for β- aminobutyric acid (BABA). Finally, one of the key features of the liquid assay is the continuous and complete contact between seedlings, chemicals, and pathogens for the duration of the experiment. This may explain the higher efficacy of sulfamethoxazole

(Smex) in the liquid assay compared to soil-grown plants. On the other hand, these conditions can also reveal host susceptibilities not evident in soil-grown plants, as observed with the oxoprolinase T-DNA disruptant oxp1-1. Similar observations were made by Gopalan and Ausubel (2008), who noted that spray inoculation of soil-grown

Arabidopsis with either Escherichia coli or Bacillus subtilis did not result in significant infection, while seedlings in liquid media were highly susceptible to these bacteria.

Ultimately, by reducing the threshold for successful pathogen infection in the liquid assay, any screen focused on identifying perturbations capable of enhancing host resistance should yield strong hits.

Indeed, the primary impetus for developing the liquid assay was to enable high- throughput chemical genomic screens intended to identify small molecules that protect

Arabidopsis seedlings from pathogen infection. Screens were initially conducted against P. syringae, and the first hits to be confirmed were members of the 164 sulfanilamide family of compounds. Of these, Smex provided the strongest protection against bacterial infection, and was later shown to confer resistance to F. graminearum in both Arabidopsis and wheat. In all cases, this activity did not appear to be antimicrobial in nature, suggesting that Smex may be a general inducer of plant defence. As such, I endeavoured to determine the mechanism by which this induction occurs in Arabidopsis. Based on candidate gene evaluations and transcriptomic analyses, I found that Smex induces disease resistance through an apparently novel mode of action that may originate with the inhibition of dihydropteroate synthase activity. In retrospect, this could affect both the plant and pathogen, and a non-growth- inhibitory impediment of pathogen virulence by Smex remains to be conclusively excluded as an explanation of Smex-mediated protection from infection. Focusing on the plant side of the interaction, further functional interrogation by forward genetic screening yielded mutants with altered growth phenotypes in the presence of Smex, but these mutations did not affect Smex-induced resistance. Cumulatively, it is evident that Smex elicits a complex set of responses in Arabidopsis that result in multiple independent phenotypes.

This conclusion highlights the significant challenges associated with characterizing the function of small molecules in biological systems. In particular, compounds may not specifically interact with a single protein target, especially if those compounds have simple structures with no stereocentres (Stockwell, 2000). This lack of exclusivity may result in the induction of several downstream responses that may or may not functionally overlap. One example of such a multifaceted response is provided by BABA, which affects signalling pathways controlled by abscisic acid, salicylic acid

(SA), and jasmonates in order to enhance drought and salt stress tolerance as well as prime for defence gene expression and callose deposition (Ton and Mauch-Mani, 2004; 165 Jakab et al., 2005; Tsai et al., 2011). Proteins interacting with BABA have yet to be identified, so the exact number of BABA targets is unknown. Similar complexity exists for endogenous signalling molecules such as SA, for which a small number of interacting proteins have been identified (Du and Klessig, 1997; Slaymaker et al., 2002;

Kumar and Klessig, 2003). Many of these proteins are thought to regulate levels of reactive oxygen species in plants, which would influence a subset of SA-mediated defence responses, in addition to the effects of SA on plant growth and development

(Rivas-San Vicente and Plasencia, 2011). Clearly, the induction of plant defences by more well-studied signalling molecules does not follow a simple linear pathway, so the apparent complexity of Smex-induced responses is not unprecedented.

Future Directions

One of the important accomplishments of this project was the development of high-throughput pathosystem assays conducive to chemical genomic screens. Given the robust infection phenotypes obtained with P. syringae and F. graminearum, the liquid assay could be useful for studying other pathogens such as the necrotrophic fungus Botrytis cinerea or the biotrophic oomycete Hyaloperonospora arabidopsidis.

These pathogens have previously been studied on Arabidopsis as models of different pathogen lifestyles (Govrin and Levine, 2002; Slusarenko and Schlaich, 2003), and this work would benefit from an extended capability to manipulate host-pathogen interactions using small molecules. Another potentially interesting aspect of the liquid assay is the containment of both host and pathogen in a small volume of liquid. We have noted that media in which seedlings have been grown support more bacterial growth than the basal nutrient media originally added to the 96-well plates (K. 166 Schreiber, unpublished results). This increased growth likely reflects the presence of some carbon source derived from apoplastic fluid, root excretions, and/or other surface-diffusible metabolites. There is currently considerable interest in determining the nutrient utilization profiles of pathogens such as P. syringae (Rico and Preston,

2008), although sampling apoplastic fluid in Arabidopsis is challenging. As such, analyses of the liquid media by high-performance liquid chromatography could provide a snapshot of the nutrients that are freely available to the pathogen at a given time point, along with nutrients and defence-related small molecules released as a consequence of pathogen infection. This defined liquid environment could also be employed to characterize the relationship between nutritional auxotrophy and pathogen virulence (a possible extension of the transposon mutagenesis outlined in Appendix 6).

With regards to the chemical screening described in this thesis, the issue of screen saturation should be considered. In classical forward genetic screens, saturation can be easily determined based on the number of alleles recovered for each mutated gene of interest (Jürgens et al., 1991). This analysis is less straightforward for chemically-induced perturbations, which are dictated by specific interactions between small molecules and proteins and therefore are not random like mutations (Stockwell,

2004). Furthermore, only a subset of proteins contain structural pockets into which small molecules could potentially fit (Hopkins and Groom, 2002; An et al., 2004). This subset predominantly contains proteins that bind endogenous chemical ligands, such as enzymes and receptors. On the other hand, such analyses of “druggable” proteins generally involve functional extrapolations based on commercially viable pharmaceuticals intended for human use, and are thus limited in scope. Notably, the large and diverse plant metabolome should theoretically be paralleled by a more extensive array of druggable targets (McCourt and Desveaux, 2010). In addition, there 167 is some evidence that small molecules can disrupt protein-protein interactions to modulate enzyme activity (Arkin and Wells, 2004) as well as the function of structural proteins such as tubulin (Gigant et al., 2005). Transcription factors can also be inhibited by small molecules through interference with either protein-DNA or protein- protein interactions (Berg, 2008). Given that these proteins are largely unexplored targets, however, the extent to which they can be chemically perturbed is unknown.

Ultimately, biases in target interrogation will be minimized by screening as many compounds as possible from collections with maximum structural diversity. Despite the commercial availability of at least 5.2 million unique compounds (Chuprina et al., 2010), a number of basic chemical scaffolds are not represented in these collections (Hert et al., 2009), so there is still room for improvement. At any rate, our screen of over 6,000 compounds in the Arabidopsis-P. syringae pathosystem did not achieve even theoretical saturation, so continued screening of additional compounds should be fruitful. The relatively high hit rate obtained in a small-scale screen against F. graminearum (Chapter 3, Appendix 3) indicates that more extensive screening with this pathogen would also be worthwhile.

Of the confirmed hits from the chemical screen, I focused almost exclusively on further characterizing the activity of Smex in Arabidopsis, although much work remains for this endeavour. The surrogate phenotype used to identify mutants with altered sensitivities to Smex did not translate to disease resistance phenotypes, but insights into Smex activity may still be gleaned from the pursuit of alternative phenotypes.

Given that loss of the putative Smex target dihydropteroate synthase compromises salt stress tolerance in Arabidopsis (Storozhenko et al., 2007), abiotic stress responses may be similarly altered in the Smex response mutants. Nevertheless, forward genetic screens will remain important approaches to Smex characterization, although future 168 screens should involve a phenotype more closely related to the liquid assay. Reporter genes have formed the basis for other pathology-related genetic screens (Cao et al.,

1994; Shah et al., 1997), and the microarray data obtained from the Smex priming experiment (Chapter 4) provides a list of candidate genes that could potentially be used as reporters of Smex-induced defence responses. Ideally, the promoter of this reporter construct would confer low basal levels of expression, minimal induction by Smex or P. syringae alone, and significantly increased expression in the presence of both Smex and P. syringae. Transgenic Arabidopsis lines carrying this reporter could then be mutagenized and screened for individuals incapable of reporter gene induction. A major challenge with this screen will be the recovery of screening hits from the liquid assay.

This assay utilizes seedlings, so a non-destructive assay of reporter gene expression, such as for luciferase (Xiong et al., 1999), would be required to accommodate the small amounts of tissue available for analysis. In addition, the loss of reporter gene induction in the liquid assay may correspond to a loss of Smex-induced protection from infection.

In order to avoid losing seedlings to severe infection, the reporter assay would need to occur over a relatively short timecourse for minimal exposure to bacteria. Alternatively, a reporter gene may be identified that exhibits the desired expression patterns in older plants. This would be amenable to high-throughput screens using excised leaf tissues, which was successfully utilized in screens based on PR-1::reporter gene expression

(Cao et al., 1994). In addition to candidate reporter gene selection, the microarray data could also be used for functional analyses in which T-DNA knockouts of differentially- expressed genes are tested in the liquid assay to identify genes that are required for the protective activity of Smex.

Although these experiments would be centered on P. syringae, the activity of

Smex against other pathogens is also of tremendous interest. We demonstrated that 169 this compound reduces the susceptibility of both Arabidopsis and wheat to F. graminearum infection (Chapter 3). The activity of Smex in a priming assay on wheat suggested that a defence-related response was being induced, especially since the concentration of Smex applied was not high enough to inhibit fungal growth.

Nonetheless, it will be important to clarify whether or not this compound impacts some aspect of fungal virulence or development. It would also be interesting to determine if

Smex protects Arabidopsis from pathogens such as B. cinerea or H. arabidopsidis, which would place Smex in the realm of other known broad-spectrum inducers of disease resistance like BTH and BABA (Lawton et al., 1996; Zimmerli et al., 2000;

Cohen, 2002). The enhancement of resistance to oomycete pathogens would be significant, especially if it could be translated to commercially relevant crops. In particular, the efficacy of Smex in liquid media suggests potential applications in hydroponically-grown greenhouse crops, where oomycetes such as Pythium spp. and

Phytophthora spp. are frequently problematic (Vallance et al., 2011). In light of the retention of Smex activity between Arabidopsis and wheat, this type of translation is theoretically possible.

Conclusions

This project has generated a new set of tools for high-throughput analyses of plant-pathogen interactions. These tools were employed for forward chemical genomic screens, yielding a compound (Smex) capable of enhancing disease resistance in various pathosystems. While the mechanism of Smex activity was not fully elucidated, the foundation has been laid for a considerable amount of future work to address this issue. 170 References

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208 Appendix 1

Evaluations of Pathogen Resistance Phenotypes in Arabidopsis Seedlings

Grown in Liquid Media

209

Figure A1-1: Evaluations of pathogen resistance phenotypes in Arabidopsis seedlings grown in liquid media.

(A) Assessment of gene-for-gene resistance. Five-day-old Arabidopsis (Col-0) seedlings in liquid media were inoculated with 1 x 105 cfu/mL Pseudomonas syringae pv. tomato DC3000 (Pto DC3000) containing an empty expression vector (EV) or constructs for the expression of the avirulence proteins AvrRpt2, AvrRpm1, or AvrB.

Bacterial populations were quantified at three days post-inoculation. No statistically significant differences were observed between any of the inocula.

(B) Analyses of Arabidopsis mutants with constitutively active defence phenotypes.

Ecotype Col-0 was used as the wildtype control for cpr1 (constitutive expressor of PR-

1), cpr5, and dnd1 (defence, no death1), while ecotype WS served as the wildtype control for cpr22. Five-day-old seedlings were inoculated with 1 x 105 cfu/mL Pto

DC3000 and bacterial populations quantified at three days post-inoculation. Letters above data points indicate statistical significance groups as determined by pairwise

Student’s t-tests (α=0.05).

210 Appendix 2

Identification of Small Molecules that Modulate the Interaction Between

Arabidopsis and Pseudomonas syringae

Abstract

The field of chemical biology provides a novel approach for investigating the function of biological systems. Here, we describe the application of this approach to the study of plant-pathogen interactions. Using high-throughput assays conducted in

96-well plates, we screened 6,470 compounds from five different chemical libraries against the Arabidopsis-Pseudomonas syringae pathosystem. A number of hits were identified based on their ability to prevent the development of bacterial infection symptoms on Arabidopsis seedlings in liquid media. This chapter details the preliminary characterization of compounds confirmed as true positives as well as experimental refinements intended to increase the true positive identification rate in the screen.

Introduction

Efforts to functionally characterize biological systems often involve perturbing these systems in some manner. In plant biology, these perturbations have traditionally been genetic in nature, arising from techniques such as chemical mutagenesis, fast- neutron bombardment, or T-DNA insertion mutagenesis. Indeed, forward genetic screens have been used with great success in the model plant Arabidopsis thaliana to identify key components of signalling pathways required for defence against pathogens

211 (Bowling et al., 1994; Cao et al., 1994; Century et al., 1995; Glazebrook et al., 1996).

There are, however, some serious limitations to genetic approaches, chiefly the potential masking of phenotypes by functionally redundant gene families and the inability to recover mutants in essential genes. Genetic analyses may also be difficult in non-model systems and in organisms with slow rates of reproduction.

An alternative approach is provided by the recently emerged field of chemical biology (or chemical genetics/genomics), in which small molecules rather than genetic lesions are used to perturb a system (Stockwell, 2000). One major advantage is that chemicals can be applied reversibly for conditional effects, with the intensity of phenotypic modification defined by the concentration of chemical applied (Stockwell,

2004; Kawasumi and Nghiem, 2007). Furthermore, perturbations will generally occur at the proteomic level as chemicals interact with specific three-dimensional pockets on protein surfaces. As such, a single compound can affect the activity of multiple members of a structurally similar and functionally redundant protein family (Smolinska et al., 2008). Different levels of selectivity can also be identified to modulate the activity of more than one type of protein (Cao et al., 2008) or only one specific activity of a multifunctional protein (Haggarty et al., 2003). Small molecules may also disrupt protein-protein interactions (He et al., 2005). Finally, these activities will likely be retained across different cell types and species for structurally similar protein targets

(Kawasumi and Nghiem, 2007).

Despite the relative infancy of modern chemical biology, large collections of small molecules are now widely available to facilitate large-scale forward chemical genetic screens. Different objectives have informed the assembly of these collections, some of which include significantly diverse chemical structures while others are focused on one particular chemical family. Likewise, chemical libraries may be 212 assembled from randomly synthesized compounds and/or small molecules with some type of demonstrated bioactivity. Regardless of the objectives underlying library assembly, virtually all compounds are filtered for properties conducive to predicted biological activity. Generally, this activity relies on the ability of a compound to diffuse through biological membranes. This behaviour is favoured by small molecule size

(<500 Da), the avoidance of extreme hydrophobicity/hydrophilicity, and solubility in common solvents such as water or dimethyl sulfoxide (DMSO) (Lipinski et al., 1997).

Such evaluations may also consider chemical stability and the likelihood that the compound will be a substrate for cellular efflux pumps (Stockwell, 2004). An exception to these rules is noted for many natural products, which exhibit significant activity despite exceeding the 500 Da cutoff or exhibiting low aqueous solubility. The retention of this activity is likely due to the presence of naturally occurring transporters for active uptake of these chemicals. At any rate, the size and variety of chemical libraries is continually increasing, and as of 2009, nearly 8 million compounds representing 5.2 million unique structures were available in commercial collections (Chuprina et al.,

2010).

The exploration of this vast chemical space requires the ability to screen a phenotype of interest in a high-throughput manner. We previously developed an assay to study the Arabidopsis-Pseudomonas syringae pathosystem in liquid media in 96-well plates (Chapter 2). In particular, the assay was used to identify small molecules that reduce the susceptibility of Arabidopsis seedlings to infection by P. syringae. This chapter describes the refinement of the screening protocol over the course of the project, provides a summary of hits from the primary chemical screen, and discusses the preliminary characterization of some of the confirmed hits from the screen.

213 Results

Prior to screening any chemical libraries, assay conditions were first optimized using small molecules known to modulate plant defence responses (Chapter 2).

Specifically, incubation of seedlings with 25 μM salicylic acid (SA) prior to inoculation with 1 x 107 cfu/mL P. syringae pv. tomato DC3000 (Pto DC3000) prevented the bleaching of seedling cotyledons caused by this virulent bacteria. This protection was considerably reduced at lower concentrations of SA (data not shown), so 25 μM was selected as an appropriate concentration for subsequent screening.

The first chemical libraries screened included the TimTec Natural Product

Collection (280 compounds) as well as a collection of 2,030 compounds shown to affect the germination and/or growth of Arabidopsis (LATCA, Library of Active

Compounds in Arabidopsis). Initially, screens were performed in duplicate and yielded a number of putative hits. For each well designated as a hit, bacterial populations in the liquid media were quantified and those hits with strong antibacterial activity were excluded from further analyses. After screening the TimTec and LATCA collections, 21 candidate hit compounds were retested, of which five (sulfathiazole, sulfadiazine, sulfamethoxazole, sulfamonomethoxine, and cobalt (II) chloride) were shown to be true positives (Table A2-1). In an effort to reduce the rate of false positives, subsequent screening was performed in triplicate. In addition, the inoculum concentration was reduced to 1 x 105 cfu/mL to provide greater sensitivity, given that the bleaching phenotype developed over a longer timeframe in seedlings inoculated with this amount of bacteria. These conditions were used for screening TATCA (Tyers Lab Actives), a collection of 1,280 compounds with known bioactivity or cytotoxicity in yeast. Although

214 Table A2-1: Confirmed hits from a screen intended to identify compounds that protect Arabidopsis seedlings from infection by Pseudomonas syringae in liquid media

Compound Library Structure

O H N S S Sulfathiazole LATCA O N

H2N O H N N S Sulfadiazine LATCA O N

H2N O H N N S O Sulfamethoxzaole LATCA O

H2N

O H N O S Sulfamonomethoxine LATCA O NN

H2N

a Cobalt (II) Chloride LATCA CoCl2 • 6 H2O

O Na+ O-

O H Carbenoxolone Spectrum H O -O O H O Na+

O O O O O

Novobiocin Spectrum N HO O H - O Na+ O O HO

NH2 a Although CoCl2 was confirmed as a true positive, its effects in the liquid assay appear to be largely antimicrobial.

215 six candidate hits were identified from this library, none were true positives.

Despite a high false positive rate, we were also concerned about the potential false negative rate of the screen. In particular, some compounds may show activity at lower concentrations which may be obscured by phytotoxicity at 25 μM. As such, we began screening chemicals at 0.25 and 25 μM, starting with the Tripos collection of novel chemical structures. Interestingly, three compounds were identified that protected seedlings from bacterial infection at 0.25 μM, and only one exhibited this activity at 25

μM (Table A2-2). Unfortunately, corporate restructuring of Tripos Inc. rendered these exclusively stocked chemicals unavailable for reordering, so screening with this collection was abandoned after working through 880 compounds.

The final chemical library to be screened was the Spectrum collection of 2,000 known bioactive compounds. This screen was conducted with P. syringae pv. maculicola ES4326 (Pma ES4326) instead of Pto DC3000 for greater alignment with other projects associated with this thesis. The bleaching phenotype induced by Pma

ES4326 occurs over a slightly longer timeframe than that observed for Pto DC3000

(data not shown), so the sensitivity of the screen may be further enhanced by using

Pma ES4326. This screen yielded a relatively high hit rate with 66 putative hits, although 31 of these compounds exhibited strong antibacterial activity. Interestingly, most of the remaining hits were also annotated as antibiotics, yet had little or no effect on the growth of Pma ES4326 in the liquid assay (Table A2-3). It is also notable that

14 sulfanilamide compounds were identified as hits, which provides increased confidence in both the validity of this family of compounds as protective agents and the reproducibility of the screen itself, despite modifications to the screening protocol. Two compounds, carbenoxolone and novobiocin, were selected for retesting and verified as

216 Table A2-2: Novel compounds from the Tripos collection identified as hits in the liquid assay

Compound Concentration (Library Code) (μM)a Structure F O F F

NH RA000013MBC8 0.25 & 25 HN O

O O

N S N S RA000013MBF8 0.25 HN O

O NH

O

N N N

N O

RA000013MBH9 0.25 N S

N

O

aChemicals were screened at 0.25 and 25 mM; the concentration(s) at which protective activity was observed are indicated.

217 Table A2-3: Primary screen hits from the Spectrum chemical library that are annotated as antimicrobial compounds yet do not significantly inhibit the growth of Pseudomonas syringae in the liquid assay

Concentration Antimicrobial Mechanism of Compound (μM)a Action

Cefotaxime sodium 25 Inhibits bacterial cell wall synthesis Azlocillin sodium 25 by interacting with penicillin-binding Piperacillin sodium 25 proteins Penicillin V potassium 25

Piromidic acid 25 Inhibits DNA replication by targeting Nalidixic acid 25 DNA gyrase Novobiocin sodium 25

Lomefloxacin 25 Inhibits DNA replication by targeting hydrochloride DNA gyrase and topoisomerase IV

Inhibits bacterial protein synthesis Meclocycline 0.25 by binding the 30S ribosomal sulfosalicylate subunit Inhibits bacterial protein synthesis Chloramphenicol 25 by binding the 50S ribosomal subunit

Sulfadimethoxine 25 Sulfameter 25 Sulfaquinoxaline sodium 25 Sulfamethoxypyridazine 25 Phthalylsulfathiazole 25 Sulfisoxazole 25 Inhibits folate biosynthesis by Sulfapyridine 25 binding dihydropteroate synthase Sulfamethoxazole 25 Sulfacetamide 25 Sulfadiazine 25 Sulfamethizole 25 Sulfamerazine 25

aChemicals were screened at 0.25 and 25 mM; the concentration at which protective activity was observed is indicated.

218 true positives (Table A2-1). Preliminary characterization of carbenoxolone indicated that the ability of this compound to protect seedlings from infection is dependent on the defence regulator NPR1, but this protection does not require salicylic acid (Figure A2-

1). An overall summary of screening results is provided in Table A2-4.

Discussion

The success of any screen relies not only on the use of a robust screening phenotype amenable to high-throughput analyses, but also on the application of appropriate criteria for evaluating the phenotypic output of the screen. In the 96-well liquid assay, macroscopic symptom development on the cotyledons of inoculated

Arabidopsis seedlings was used to indicate infection by a virulent bacterial or fungal pathogen (Chapters 2 and 3). We conducted a forward chemical genomic screen to identify small molecules that prevent these symptoms. This protection was assessed visually, implying some amount of subjectivity in the identification of screening hits. As such, many of the initial false positives in the P. syringae screen may have resulted from screening criteria that were too lenient, especially when based on only two technical replicates. Screening in triplicate generally did reduce hit rates in the primary screen, but these hits were not rescreened extensively enough to draw conclusions about false positive rates. One obvious solution for reducing false positives is to increase the stringency of the screen, although we are already using highly virulent P. syringae strains and a relatively high inoculum concentration. In fact, we actually lowered the inoculum concentration later in the screen for increased sensitivity. False positives are therefore inevitable in a screen that is biased towards minimizing false negative results. This perspective is corroborated by Stockwell (2004), who assures 219

Figure A2-1: Preliminary characterization of the activity of carbenoxolone (Cbox) in

Arabidopsis. Wildtype (WT) seedlings, as well as mutants compromised in either salicylic acid signalling (npr1) or biosynthesis (nahG and eds16), were treated with 25

μM Cbox and inoculated 12 hours later with 1 x 105 cfu/mL Pma ES4326. Images were taken at 7 days post-inoculation.

220 Table A2-4: Summary of results from a screen intended to identify small molecules that reduce the susceptibility of Arabidopsis seedlings to infection by Pseudomonas syringae

Number of Primary Antimicrobial Library Compounds Screen Retested Confirmed Hits Screened Hits

TimTec 280 5 2 1 0

LATCA 2,030 41 4 20 5

TATCA 1,280 6 0 5 0

Tripos 880 3 0 0 0

Spectrum 2,000 66 31a 2b 2

Total 6,470 121 37 28 7

Overall Hit Rate (Confirmed Hits): 0.11%

aTwo compounds were active at both 0.25 and 25 μM yet exhibited antimicrobial activity only at 25 μM. bFourteen sulfanilamide-family compounds were identified as positives, but retesting was deemed unnecessary based on previous validation from screening the LATCA library.

221 that “a high rate of false negatives and false positives can be tolerated in a screen because as long as a few true positives can ultimately be confirmed, the screen is successful”.

Indeed, a small number of compounds were confirmed as being capable of protecting Arabidopsis seedlings from P. syringae infection in the absence of significant antibacterial activity. In addition to the sulfanilamide family of compounds discussed elsewhere in this thesis, we also identified carbenoxolone as a true positive. This compound is a synthetic analogue of glycyrrhizic acid, which is found in the roots of licorice (Glycyrrhiza glabra) plants. In mammals, carbenoxolone induces heat shock proteins (Kawashima et al., 2009) and inhibits neuronal gap junction ion channels

(Davidson and Baumgarten, 1988; Benfenati et al., 2009). This chemical also possesses anti-inflammatory activity deriving from inhibition of the enzyme 11β- hydroxysteroid dehydrogenase, thus preventing the conversion of glucocorticoids such as cortisol to their inactive metabolites (Stewart et al., 1990). A loose parallel to this activity was observed in plants, where carbenoxolone blocks the conversion of linoleic acid (C18:2ω6) to α-linolenic acid (C18:3ω3) in soybean leaf chloroplasts (Norman et al., 1995). In Arabidopsis, this conversion is catalyzed by three fatty acid desaturases

(FADs) located in chloroplasts (FAD7, FAD8) or microsomes (FAD3) (Arondel et al.,

1992; Iba et al., 1993; Gibson et al., 1994). In the context of plant-pathogen interactions, Yaeno et al. (2004) observed that resistance to virulent Pto DC3000 was not altered in either fad3 or fad7fad8 mutants. It is important to note, however, that linolenic acid biosynthesis is not significantly different from wildtype in fad3 mutants and only reduced by approximately 70% in the fad7fad8 background (Maeda et al.,

2008). A fad3fad7fad8 triple mutant contains negligible amounts of linolenic acid as well as extremely low levels of jasmonic acid (JA), for which linolenic acid is an 222 important precursor (Farmer and Ryan; McConn and Browse, 1996; Vijayan et al.,

1998). Given that Arabidopsis mutants with impaired JA perception or signalling exhibit enhanced resistance to P. syringae (Kloek et al., 2001), the inhibition of FADs by carbenoxolone may provide protection from infection by affecting JA biosynthesis. In rice, RNAi-mediated suppression of FAD3/7/8 orthologues significantly enhanced non- race-specific resistance to the rice blast fungus Magnaporthe grisea (Yara et al., 2007).

Notably, however, the induction of JA-responsive pathogenesis-related protein genes was unaffected by the FAD3/7/8 gene knock-down and the resulting increase in resistance was not altered by exogenous application of JA, suggesting that polyunsaturated fatty acids other than JA are important for disease resistance. Such a result may derive from the study of a fungal pathogen on a monocot host, so it would be useful to examine the Arabidopsis fad3fad7fad8 triple mutant for disease resistance phenotypes.

Alternatively, this data suggests that non-JA mechanisms of fatty acid- modulated resistance may exist as well. Specifically, the relative proportions of fatty acids present may influence defence responses as illustrated by the Arabidopsis ssi2

(suppressor of SA insensitivity2) mutant, whose capacity to desaturate stearic acid

(C18:0) to oleic acid (C18:1) is significantly impaired (Kachroo et al., 2001). Low oleic acid levels were associated with increased SA accumulation and expression of multiple resistance (R) genes, as well as enhanced resistance to P. syringae, turnip crinkle virus, and the oomycete pathogen Hyaloperonospora arabidopsidis (Shah et al., 2001;

Chandra-Shekara et al., 2007). The fatty acid profile of fad3fad7fad8 triple mutants is dramatically different from wildtype Arabidopsis, with negligible levels of trienoic acids

(16:3 and 18:3) countered by large accumulations of dienoic acids (16:2 and 18:2).

223 The cumulative impact of these changes may positively influence disease resistance through a mechanism yet to be elucidated.

One unusual feature of carbenoxolone in the liquid assay is that it confers protection from P. syringae infection via an apparently SA-independent, NPR1- dependent mechanism. The NPR1 (nonexpressor of PR genes1) gene was originally identified in a screen for Arabidopsis mutants incapable of SA-induced expression of pathogenesis-related (PR) protein genes (Cao et al., 1994). Given this association, many defence-related phenotypes that are SA-dependent also require NPR1, although

NPR1-independent pathways downstream of SA are also widely documented (Jirage et al., 1999; Yoshioka et al., 2001; Aviv et al., 2002; Nandi et al., 2003; Durrant and Dong,

2004; Uquillas et al., 2004). On the other hand, there are very few examples of responses that act through NPR1 but do not require SA, likely due to the complex genetic analyses required. Such an analysis was recently applied to a syntaxin gene double mutant (syp121syp122), which exhibits spontaneous cell death, constitutive SA signalling, and enhanced resistance to fungal penetration (Zhang et al., 2008). A suppressor screen identified FMO1 (flavin-dependent mono-oxygenase1) and ALD1

(AGD2-like defence response protein1) as genes important for the cell death phenotype. Quadruple mutants (e.g. syp121syp122fmo1npr1) were required to demonstrate that, while the suppression was largely independent of SA signalling, it did require NPR1. This example is complicated by the incorporation of multiple loss-of- function mutations, but at the very least suggests that this type of regulation can occur.

As such, carbenoxolone could provide an important tool for further dissection of this novel regulatory mechanism.

In addition to carbenoxolone, a large number of compounds annotated as antimicrobials were identified as hits in the primary screen, especially from the 224 Spectrum chemical collection. It is interesting to note that of the 52 allegedly antimicrobial hits, 24 did not significantly inhibit bacterial growth in liquid media.

Granted, some of these compounds are specifically active against Gram-positive bacteria, and we did not thoroughly characterize all primary hits for potential bacteriostatic activity. Beyond these factors, though, P. syringae has acquired/evolved mechanisms of resistance to a variety of antimicrobial compounds (Sundin and Bender,

1993; Stoitsova et al., 2008), and this may explain some of the results. In the absence of any effects on bacterial growth or virulence machinery, the protective activity of these chemicals likely derives from the induction of plant defences. We confirmed that the aminocoumarin antibiotic novobiocin reduces the susceptibility of Arabidopsis seedlings to infection by Pma ES4326 without affecting bacterial growth. Indeed,

Stoitsova et al. (2008) determined that the mean inhibitory concentration of novobiocin against Pto DC3000 is in excess of 1.5 mM, far beyond the 25 μM used in our screening assay. In novobiocin-sensitive bacteria, the compound potently inhibits DNA gyrase by targeting the GyrB subunit of this enzyme (Sugino et al., 1978). The absence of a GyrB orthologue in humans is a key factor enabling the use of this antibiotic in medical practice. In Arabidopsis, however, functional DNA gyrase proteins are localized to chloroplasts and mitochondria (Wall et al., 2004). Arabidopsis cells treated with gyrase-inhibitory compounds exhibit significant depletion of these organelles, and the loss of genes encoding either the GyrA or GyrB enzyme subunits is deleterious to plant growth. At this point, the mechanism through which novobiocin protects Arabidopsis seedlings from infection can only be speculated. Given the important contribution of chloroplasts to the activation of plant defence responses

(Belhaj et al., 2009; Schaller and Stinzi, 2009; Zurbriggen et al., 2009; Schmitz et al.,

2010), it is possible that low concentrations of novobiocin inhibit DNA gyrase in these 225 organelles to the extent that some type of stress response is initiated, such as reactive oxygen species production and/or transcriptional reprogramming, yet chloroplast viability is not compromised. Overall, the antimicrobial compounds that do not affect P. syringae growth are of significant interest for future investigations, both as probes of defence-related activities for proteins of prokaryotic origin and potentially as indicators of novel eukaryotic targets in non-mammalian systems.

Conclusions

The foundation of this thesis project was built on high-throughput chemical screens intended to identify small molecules that protect Arabidopsis seedlings from pathogen infection. Against a seemingly inevitable background of false positives, a small number of compounds were confirmed as true hits. Importantly, there is significant potential novelty in the mechanisms by which these true positives activate plant defences. As such, these chemicals will not only provide new insights into basic questions in plant pathology, but also potentially yield additional resources for crop protection in an applied setting.

226 Experimental Procedures

For the Arabidopsis-P. syringae pathosystem, chemical libraries were screened in a liquid media-based assay as described in Chapter 2, although screening parameters were refined over the course of the project (Table A2-6).

Table A2-6: Summary of conditions used for screening five different collections of small molecules on the Arabidopsis-Pseudomonas syringae pathosystem

Chemical Inoculum P. syringae Library Supplier Concentration Concentration Strain (μM) (cfu/mL)

TimTec LLC TimTec 25 Pto DC3000 1 x 107 (Newark, DE, USA)

S. Cutler (UC LATCA 25 Pto DC3000 1 x 107 Riverside, CA, USA)

TATCA 25 Pto DC3000 1 x 105

Tripos (defunct) 0.25 and 25 Pto DC3000 1 x 105

MicroSource Discovery Systems, Spectrum 0.25 and 25 Pma ES4326 1 x 105 Inc., (Gaylordsville, CT, USA)

227 References

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232 Appendix 3

Identification of Small Molecules that Modulate the Interaction Between

Arabidopsis and Fusarium graminearum

Summary

Previously, conditions were optimized for evaluating the interaction between

Arabidopsis seedlings and F. graminearum in the liquid assay (Chapter 3).

Compounds from the TimTec Natural Product Collection (280 chemicals) were screened in this assay and seven chemicals were found to protect Arabidopsis from infection by F. graminearum (Table A3-1). Quantification of fungal survival/growth in liquid media was less straightforward than with P. syringae, but visual inspection of wells containing screening hits revealed little or no fungal mycelia, contrasting with extensive mycelial growth in control wells. This hit rate (2.5%) may seem surprisingly high, but the dramatic contrast between seedlings in hit and non-hit wells suggested that a relatively high level of confidence could be held with regards to the validity of these hits. In practice, salsoline was the weakest hit from the list and failed to replicate in later retesting. The protective activity of gramine, however, was confirmed in the retest and subsequently demonstrated on wheat as well (Chapter 3). Of the compounds yet to be retested, the known antifungal activity of cycloheximide and antimycin A likely explains their identification in the screen. Although little is known about 7,8,3’-trihydroxyflavone specifically, similar compounds such as apigenin (4’,5,7- trihydroxyflavone) have been characterized as antimicrobial phytoalexins that are produced in response to pathogen infection (Du et al., 2010). Psoralens may also

233 Table A3-1: Primary hits from a small-scale screen intended to identify small molecules that reduce the susceptibility of Arabidopsis seedlings to infection by Fusarium graminearum Compound Structure

N Gramine

N H

HO

Salsoline NH O

O

7,8,3’-Trihydroxyflavone HO O OH OH

O

O O O O Antimycin A NH OH H HN

O O O

Psoralen O O O

O

5-Methoxypsoralen

O O O

O H Cycloheximide HN

O HO O

234 inhibit fungal growth, but their ability to intercalate into DNA and induce DNA damage responses can also activate plant defences (Parsons and Hadwiger, 1998). An implicit long-term objective of this particular screen is the identification of chemicals that could control infections by Fusarium spp. in a field setting, so we would consider both antimicrobial and defence-inducing mechanisms of action as promising approaches to crop protection. Natural product collections are especially attractive for this screen because they represent an extensive evolutionary process of selection for compounds that confer an advantage to the host plant in a natural (“field”) setting where pathogen challenge is a regular occurence. With gramine, we demonstrated that the protective activity of a compound in Arabidopsis can be translated to wheat (Chapter 3), suggesting that this and future screens have tremendous potential to combat agricultural pathogens on their native hosts.

References

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235 Appendix 4

Transcriptional Response of Liquid-Grown Arabidopsis Seedlings

to Sulfamethoxazole

Table A4-1: Arabidopsis genes upregulated by at least two-fold in liquid-grown seedlings treated with 100 μM sulfamethoxazolea

Arithmetic Locus Description Fold Change

At1g52190 Major facilitator superfamily protein 8.34 At5g46890/ Bifunctional inhibitor/lipid-transfer protein/seed storage 2S albumin 6.32 At5g46900 superfamily protein At5g02760 Protein phosphatase 2C family protein 4.65 At5g66985 Unknown protein 4.54 At4g19030 NLM1: NOD26-like major intrinsic protein 1 4.54 At5g39890 Protein of unknown function (DUF1637) 4.38 At5g60020 LAC17: Laccase 17 4.18 COBL9: COBRA-like extracellular glycosyl-phosphatidyl inositol- At5g49270 3.87 anchored family protein At1g43160 RAP2.6: Related to AP2 6 3.79 At5g15280 Pentatricopeptide repeat (PPR) superfamily protein 3.77 At3g25190 Vacuolar iron transporter (VIT) family protein 3.38 At2g41230 Unknown protein 3.33 At3g23840 HXXXD-type acyl-transferase family protein 3.30 At5g15290 Uncharacterised protein family (UPF0497) 3.28 At5g06570 alpha/beta-Hydrolases superfamily protein 3.21 At3g53250 SAUR-like auxin-responsive family protein 3.16 At3g59900 ARGOS: Auxin-regulated gene involved in organ size 3.15 At4g00950 MEE47: Protein of unknown function (DUF688) 3.12 At1g09380 Nodulin MtN21 /EamA-like transporter family protein 3.11 At1g17170 GSTU24: Glutathione S-transferase TAU 24 3.10 At4g13420 HAK5: High affinity K+ transporter 5 3.05 At1g74460 GDSL-like Lipase/Acylhydrolase superfamily protein 3.03 At5g67060 HEC1: Basic helix-loop-helix (bHLH) DNA-binding superfamily protein 3.00 At1g73830 BEE3: BR enhanced expression 3 2.97 At1g30700 FAD-binding Berberine family protein 2.94 At5g53250 AGP22: Arabinogalactan protein 22 2.90 At5g46330 FLS2: Leucine-rich receptor-like protein kinase family protein 2.86 Thiamine pyrophosphate dependent pyruvate decarboxylase family At4g33070 2.83 protein At5g25350 EBF2: EIN3-binding F box protein 2 2.83 At1g18680 HNH endonuclease domain-containing protein 2.82 At1g71440 PFI_TFC E: Tubulin folding cofactor E / Pfifferling (PFI) 2.79

236 Octicosapeptide/Phox/Bem1p (PB1) domain-containing protein / At5g20360 2.78 tetratricopeptide repeat (TPR)-containing protein At5g62620 Galactosyltransferase family protein 2.77 At4g15260 UDP-Glycosyltransferase superfamily protein 2.70 At5g10550 GTE2: Global transcription factor group E2 2.66 At5g15120 Protein of unknown function (DUF1637) 2.61 At4g10270 Wound-responsive family protein 2.59 At1g77420 alpha/beta-Hydrolases superfamily protein 2.58 At2g44080 ARL: ARGOS-like protein 2.58 At3g42950 Pectin lyase-like superfamily protein 2.57 At3g11550 Uncharacterised protein family (UPF0497) 2.57 At1g48610 AT hook motif-containing protein 2.57 At5g62520 SRO5: Similar to RCD one 5 2.52 At1g63220 Calcium-dependent lipid-binding (CaLB domain) family protein 2.50 At3g59670 Unknown protein 2.50 At4g30840 Transducin/WD40 repeat-like superfamily protein 2.48 At3g07190 B-cell receptor-associated protein 31-like 2.47 At1g51420 SPP1: Sucrose-phosphatase 1 2.46 At4g15550 IAGLU: Indole-3-acetate beta-D-glucosyltransferase 2.46 At5g56540 AGP14: Arabinogalactan protein 14 2.45 At4g10955/ alpha/beta-Hydrolases superfamily protein 2.45 At4g10960 At1g12740 Cytochrome P450 CYP87A2 2.45 At1g29330 ERD2: ER lumen protein retaining receptor family protein 2.42 At2g15680 Calcium-binding EF-hand family protein 2.42 At5g60660 PIP2;4 : Plasma membrane intrinsic protein 2;4 2.41 At1g68850 Peroxidase superfamily protein 2.38 At1g28760 Uncharacterized conserved protein (DUF2215) 2.38 2-oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily At3g46490 2.37 protein At1g05680 UGT74E2: Uridine diphosphate glycosyltransferase 74E2 2.35 At1g79710 Major facilitator superfamily protein 2.33 At4g21680 NRT1.8: NITRATE TRANSPORTER 1.8 2.32 At1g75450 CKX5: Cytokinin oxidase 5 2.32 At4g13630 Protein of unknown function, DUF593 2.30 At5g19830 Peptidyl-tRNA hydrolase family protein 2.30 At3g28430 Unknown protein 2.29 At2g39180 CCR2: CRINKLY4 related 2 2.29 At4g32620 Enhancer of polycomb-like transcription factor protein 2.28 At4g33560 Wound-responsive family protein 2.28 At3g02550 LBD41: LOB domain-containing protein 41 2.27 At2g37400 Tetratricopeptide repeat (TPR)-like superfamily protein 2.25 At2g42870 PAR1: Phy rapidly regulated 1 2.25 GATA8: Plant-specific GATA-type zinc finger transcription factor family At3g54810 2.23 protein At4g36980 Unknown protein 2.23 At2g45280 RAD51C: RAS associated with diabetes protein 51C 2.23 At1g18600 RBL12: RHOMBOID-like protein 12 2.22 At1g17860 Kunitz family trypsin and protease inhibitor protein 2.22 At1g02430/ ARFD1B: ADP-ribosylation factor D1B 2.21 At1g02440 At5g17210 Protein of unknown function (DUF1218) 2.21 At3g19680 Protein of unknown function (DUF1005) 2.20

237 At5g04820 OFP13: Ovate family protein 13 2.20 At4g17615 CBL1: calcineurin B-like protein 1 2.18 At5g22310 Unknown protein 2.18 At4g08770 Peroxidase superfamily protein 2.17 At3g05510 Phospholipid/glycerol acyltransferase family protein 2.17 At1g71140 MATE efflux family protein 2.16 At1g04020 BARD1: Breast cancer associated RING 1 2.16 At4g16146 cAMP-regulated phosphoprotein 19-related protein 2.16 At1g17745 PGDH: D-3-phosphoglycerate dehydrogenase 2.15 At5g24090 CHIA: Chitinase A 2.15 At4g13840 HXXXD-type acyl-transferase family protein 2.14 At1g31820 Amino acid permease family protein 2.14 At3g13175 Unknown protein 2.13 At5g65610 Unknown protein 2.12 At4g11660 HSFB2B: Winged-helix DNA-binding transcription factor family protein 2.12 At1g80245 Spc97 / Spc98 family of spindle pole body (SBP) component 2.12 At5g01550 LECRKA4.2: Lectin receptor kinase a4.1 2.11 At1g62150 Mitochondrial transcription termination factor family protein 2.11 S-adenosyl-L-methionine-dependent methyltransferases superfamily At5g10830 2.10 protein At5g64950 Mitochondrial transcription termination factor family protein 2.10 At3g43790 ZIFL2: Zinc-induced facilitator-like 2 2.10 At2g42480 TRAF-like family protein 2.09 At3g59140 MRP14: Multidrug resistance-associated protein 14 2.09 At3g24500 MBF1C: Multiprotein bridging factor 1C 2.07 At1g74310 HSP101: Heat shock protein 101 2.06 At2g10020 Unknown protein 2.06 At1g74670 Gibberellin-regulated family protein 2.04 At1g32450 NRT1.5: Nitrate transporter 1.5 2.03 At2g32400 GLR5: Glutamate receptor 5 2.03 At1g02270 Calcium-binding endonuclease/exonuclease/phosphatase family protein 2.03 At2g43980 ITPK4: Inositol 1,3,4-trisphosphate 5/6-kinase 4 2.02 At3g55920 Cyclophilin-like peptidyl-prolyl cis-trans isomerase family protein 2.02 At3g23150 ETR2: Signal transduction histidine kinase, hybrid-type, ethylene sensor 2.02 At1g14200 RING/U-box superfamily protein 2.00 aFive-day-old seedlings in liquid media were incubated with either 100 μM sulfamethoxazole or 1% DMSO for 12 hours. Fold change calculations represent a comparison of data from sulfamethoxazole- versus DMSO-treated seedlings.

238 Table A4-2: Arabidopsis genes downregulated by at least two-fold in liquid-grown seedlings treated with 100 μM sulfamethoxazolea

Arithmetic Locus Description Fold Change

At5g37260 CIR1_RVE2: Homeodomain-like superfamily protein 15.31 At3g02380 COL2: CONSTANS-like 2 14.96 At5g42760 Leucine carboxyl methyltransferase 8.12 At2g36590 PROT3: proline transporter 3 7.79 At1g66100 Putative thionin 7.33 At2g42360 RING/U-box superfamily protein 6.17 At2g39200 MLO12: Seven-transmembrane MLO family protein 5.21 At3g56400 WRKY70: WRKY DNA-binding protein 70 4.96 At3g62260 Protein phosphatase 2C family protein 4.73 At1g24280 G6PD3: glucose-6-phosphate dehydrogenase 3 4.58 At2g19650 Cysteine/Histidine-rich C1 domain family protein 4.56 At5g17300 RVE1: Homeodomain-like superfamily protein 4.45 At5g52750 Heavy metal transport/detoxification superfamily protein 4.34 At5g26920 CBP60G: Cam-binding protein 60-like G 4.30 At4g10470 Unknown protein 4.29 At3g44450 Unknown protein 4.10 At1g01930 zinc finger protein-related 4.03 At1g27730 ZAT10: Salt tolerance zinc finger 3.97 At2g44370 Cysteine/Histidine-rich C1 domain family protein 3.97 At1g31920 Tetratricopeptide repeat (TPR)-like superfamily protein 3.95 At1g08810 MYB60: MYB domain protein 60 3.83 At4g26150 CGA1_GATA22: cytokinin-responsive gata factor 1 3.83 At2g24980 Proline-rich xtension-like family protein 3.82 At3g52740 Unknown protein 3.82 At1g56510 WRR4: Disease resistance protein (TIR-NBS-LRR class) 3.80 At3g21080 ABC transporter-related 3.71 S-adenosyl-L-methionine-dependent methyltransferases superfamily At2g14060 3.70 protein HMG (high mobility group) box protein with ARID/BRIGHT DNA- At3g13350 3.64 binding domain At1g25390 Protein kinase superfamily protein 3.61 At1g29500 SAUR-like auxin-responsive protein family 3.61 At2g29090 Cytochrome P450 CYP707A2 3.57 At5g24140 SQP2: Squalene monooxygenase 2 3.50 At4g39940 APK2: APS-kinase 2 3.37 At2g28510 Dof-type zinc finger DNA-binding family protein 3.33 S-adenosyl-L-methionine-dependent methyltransferases superfamily At2g41380 3.31 protein At1g23710 Protein of unknown function (DUF1645) 3.28 At4g19960 KUP9: K+ uptake permease 9 3.26 At1g51700 DOF1: DOF zinc finger protein 1 3.24 At1g29430/ SAUR-like auxin-responsive protein family 3.20 At5g27780 At2g23110 Late embryogenesis abundant protein, group 6 3.20 At1g63670 Protein of unknown function (DUF3741) 3.18

239 At5g63920 TOP3A: Topoisomerase 3alpha 3.18 At4g12300 Cytochrome P450 CYP706A4 3.16 At1g23205 Plant invertase/pectin methylesterase inhibitor superfamily protein 3.13 N/A predicted pseudogene 3.02 At3g08720 S6K2: serine/threonine protein kinase 2 2.99 At2g27420 Cysteine proteinases superfamily protein 2.95 At1g21110/ O-methyltransferase family protein 2.93 At1g21120 At4g19170 NCED4: Nine-cis-epoxycarotenoid dioxygenase 4 2.91 At5g67400 RHS19: Root hair specific 19 2.91 At5g65870 PSK5: Phytosulfokine 5 precursor 2.90 At3g62950 Thioredoxin superfamily protein 2.86 At5g01540 LECRKA4.1: Lectin receptor kinase a4.1 2.83 At5g57630 SnRK3.4: CBL-interacting protein kinase 21 2.83 At1g76020 Thioredoxin superfamily protein 2.83 At5g11020 Protein kinase superfamily protein 2.81 At1g10340 Ankyrin repeat family protein 2.81 At2g30540 Thioredoxin superfamily protein 2.79 At1g54110 Membrane fusion protein Use1 2.77 At3g30460 RING/U-box superfamily protein 2.77 At1g18180 Protein of unknown function (DUF1295) 2.73 At3g62620 Sucrose-phosphatase-related 2.70 At2g16630 Pollen Ole e1 allergen and xtension family protein 2.70 At5g02490 Heat shock protein 70 (Hsp 70) family protein 2.70 At1g20670 DNA-binding bromodomain-containing protein 2.70 At3g54420 EP3: Homolog of carrot EP3-3 chitinase 2.70 At4g23210 CRK13: Cysteine-rich RLK (RECEPTOR-like protein kinase) 13 2.70 At3g22640 PAP85: Cupin family protein 2.69 At5g39790 5’-AMP-activated protein kinase-related 2.69 At5g25610 RD22: BURP domain-containing protein 2.68 At5g09520 hydroxyproline-rich glycoprotein family protein 2.68 At2g39700 EXPA4: Expansin A4 2.67 At4g08410 Proline-rich xtension-like family protein 2.67 At5g57180 CIA2: Chloroplast import apparatus 2 2.64 At5g36220 Cytochrome P450 CYP81D1 2.64 At1g44970 Peroxidase superfamily protein 2.64 At4g23300 CRK22: cysteine-rich RLK (Receptor-like protein kinase) 22 2.62 At5g54370 Late embryogenesis abundant (LEA) protein-related 2.61 At3g10930 Unknown protein 2.61 At5g01790 Unknown protein 2.60 At3g09560 PAH1: Lipin family protein 2.60 At2g33700 Protein phosphatase 2C family protein 2.59 At1g70810 Calcium-dependent lipid-binding (CaLB domain) family protein 2.58 At3g50750 BEH1: BES1/BZR1 homolog 1 2.57 At4g17540 Unknown protein 2.57 At1g51800 Leucine-rich repeat protein kinase family protein 2.56 At1g80840 WRKY40: WRKY DNA-binding protein 40 2.55 At3g22520 Unknown protein 2.55 At3g48460 GDSL-like Lipase/Acylhydrolase superfamily protein 2.53 At1g02820 Late embryogenesis abundant 3 (LEA3) family protein 2.51 At4g26200 ACS7 : 1-amino-cyclopropane-1-carboxylate synthase 7 2.51 At2g43620 Chitinase family protein 2.50 At5g66650 Protein of unknown function (DUF607) 2.50

240 At4g07990 Chaperone DnaJ-domain superfamily protein 2.49 At5g24470 PRR5: Pseudo-response regulator 5 2.49 At5g45340 Cytochrome P450 CYP707A3 2.49 LTI78_RD29A: Low-temperature-responsive protein 78 (LTI78) / At5g52310 2.49 desiccation-responsive protein 29A (RD29A) At4g02270 RHS13: Root hair specific 13 2.48 At5g14760 AO: L-aspartate oxidase 2.47 At2g21320 B-box zinc finger family protein 2.46 At5g15960/ KIN1: stress-responsive protein 2.46 At5g15970 At5g56860 GATA21: GATA type zinc finger transcription factor family protein 2.46 At1g19700 BLH10: BEL1-like homeodomain 10 2.43 At1g66540 Cytochrome P450 superfamily protein 2.43 At3g10525 LGO: LOSS OF GIANT CELLS FROM ORGANS 2.42 At1g21060 Protein of unknown function, DUF547 2.42 At1g29440 SAUR-like auxin-responsive protein family 2.42 At2g38470 WRKY33: WRKY DNA-binding protein 33 2.41 At4g36988/ CPuORF49: conserved peptide upstream open reading frame 49 2.41 At4g36990 At3g22840 ELIP1: Chlorophyll A-B binding family protein 2.41 At2g31980 CYS2: PHYTOCYSTATIN 2 2.40 At3g19270 Cytochrome P450 CYP707A4 2.39 At3g03770 Leucine-rich repeat protein kinase family protein 2.39 At1g68585 Unknown protein 2.39 At1g80020 hAT-like transposase family protein 2.38 ATPMEPCRB: Plant invertase/pectin methylesterase inhibitor At4g02330 2.38 superfamily At2g25920 3’-5’ exonuclease domain-containing protein 2.38 At2g22510 hydroxyproline-rich glycoprotein family protein 2.38 At1g27900 RNA helicase family protein 2.38 At1g69310 WRKY57: WRKY DNA-binding protein 57 2.38 At2g46650 CB5-C: cytochrome B5 isoform C 2.37 At5g26610 D111/G-patch domain-containing protein 2.37 At4g28290 Unknown protein 2.36 At4g01250 WRKY22: WRKY family transcription factor 2.36 At2g29460 GSTU4: glutathione S-transferase tau 4 2.36 At4g23660 PPT1: polyprenyltransferase 1 2.36 At4g29520 Unknown protein 2.36 At1g30530 UGT78D1: UDP-glucosyl transferase 78D1 2.35 At2g41250 Haloacid dehalogenase-like hydrolase (HAD) superfamily protein 2.35 At4g31360 Selenium binding protein 2.34 At5g53740 Unknown protein 2.33 At1g29450 SAUR-like auxin-responsive family protein 2.32 At1g29510 SAUR68: SAUR-like auxin-responsive family protein 2.32 At2g02410 Unknown protein 2.31 At1g04550 IAA12: AUX/IAA transcriptional regulator family protein 2.31 At3g19030 Unknown protein 2.30 At5g24150 SQP1: FAD/NAD(P)-binding oxidoreductase family protein 2.29 At3g11580 AP2/B3-like transcriptional factor family protein 2.29 At2g25200 Plant protein of unknown function (DUF868) 2.28 At5g44180 Homeodomain-like transcriptional regulator 2.28 At3g51330 Eukaryotic aspartyl protease family protein 2.27 At1g04190 Tetratricopeptide repeat (TPR)-like superfamily protein 2.26

241 At5g05500 Pollen Ole e1 allergen and xtension family protein 2.26 At1g08570 ACHT4: Atypical CYS HIS rich thioredoxin 4 2.25 At3g17609 HYH: HY5-homolog 2.25 At5g62130 Per1-like family protein 2.24 At1g05160 Cytochrome P450 CYP88A3 (KAO1) 2.24 At3g55080 SET domain-containing protein 2.24 At1g30960 GTP-binding family protein 2.24 At1g05200 GLUR3: Glutamate receptor 3.4 2.24 At1g48960 Adenine nucleotide alpha hydrolases-like superfamily protein 2.23 At1g70700 TIFY7: TIFY domain/Divergent CCT motif family protein 2.23 At1g25400 Unknown protein 2.23 At1g51820 Leucine-rich repeat protein kinase family protein 2.23 At1g06180 MYB13: MYB domain protein 13 2.23 At5g06640 Proline-rich xtension-like family protein 2.23 At3g49210 O-acyltransferase (WSD1-like) family protein 2.23 At1g66880 Protein kinase superfamily protein 2.22 At5g59820 ZAT12: C2H2-type zinc finger family protein 2.22 At5g51190 Integrase-type DNA-binding superfamily protein 2.21 At1g62300 WRKY6: WRKY family transcription factor 2.21 At3g18500 DNAse I-like superfamily protein 2.21 At5g59730 EXO70H7: Exocyst subunit exo70 family protein H7 2.20 At2g17640 SERAT3;1: Trimeric LpxA-like enzymes superfamily protein 2.20 At3g02140 AFP4: AFP2 (ABI five-binding protein 2) family protein 2.19 At5g67280 RLK: Receptor-like kinase 2.18 At5g15310 MYB16: MYB domain protein 16 2.18 At5g43710 Glycosyl hydrolase family 47 protein 2.17 At4g32190 Myosin heavy chain-related protein 2.17 At3g55130 WBC19: White-brown complex homolog 19 2.17 CAP (Cysteine-rich secretory proteins, Antigen 5, and Pathogenesis- At4g25780 2.17 related 1 protein) superfamily protein At3g16350 Homeodomain-like superfamily protein 2.16 At1g09300 Metallopeptidase M24 family protein 2.16 P-loop containing nucleoside triphosphate hydrolases superfamily At2g03750 2.16 protein At2g23000/ SCPL10: Serine carboxypeptidase-like 10 2.16 At2g23010 At1g69370 CM3: Chorismate mutase 3 2.16 At1g49010 Duplicated homeodomain-like superfamily protein 2.16 At1g27370 SPL10: Squamosa promoter binding protein-like 10 2.15 At5g64340/ At5g64341/ SAC51: Sequence-specific DNA binding transcription factor 2.14 At5g64342/ At5g64343 At3g06070 Unknown protein 2.13 At1g69530 EXPA1: Expansin A1 2.13 At5g39660 CDF2: Cycling DOF factor 2 2.13 At1g03530 NAF1: Nuclear assembly factor 1 2.13 At1g78720 SecY protein transport family protein 2.13 At3g17740 Unknown protein 2.13 At3g44735 PSK3: Phytosulfokine 3 precursor 2.13 At5g03860 MLS: Malate synthase 2.13 At4g33980 Unknown protein 2.12 At5g10390 Histone superfamily protein 2.11

242 At5g23010 MAM1: Methylthioalkylmalate synthase 1 2.11 At5g42800 TT3: Dihydroflavonol 4-reductase 2.10 At5g45428/ CPuORF24: Conserved peptide upstream open reading frame 24 2.10 At5g45430 AtMg00070 NAD9: NADH dehydrogenase subunit 9 2.10 At4g08320 Tetratricopeptide repeat (TPR)-like superfamily protein 2.10 At2g15020 Unknown protein 2.10 At1g53260 Unknown protein 2.10 At3g53720 CHX20: Cation/H+ exchanger 20 2.10 At1g01750 ADF11: Actin depolymerizing factor 11 2.09 At4g37610 BT5: BTB and TAZ domain protein 5 2.09 At3g54230 SUA: Suppressor of abi3-5 2.08 At5g47610 RING/U-box superfamily protein 2.07 At1g06670 NIH: Nuclear DEIH-boxhelicase 2.07 At4g15430 ERD (early-responsive to dehydration stress) family protein 2.07 At3g27540 beta-1,4-N-acetylglucosaminyltransferase family protein 2.07 At2g14160 RNA-binding (RRM/RBD/RNP motifs) family protein 2.06 At5g62360 Plant invertase/pectin methylesterase inhibitor superfamily protein 2.06 At2g46070 MPK12: Mitogen-activated protein kinase 12 2.06 At1g48840 Plant protein of unknown function (DUF639) 2.05 At5g52760 Copper transport protein family 2.04 At5g61600 ERF104: Ethylene response factor 104 2.04 At2g38820 Protein of unknown function (DUF506) 2.02 At1g07450 NAD(P)-binding Rossmann-fold superfamily protein 2.02 At2g20570 GLK1: GBF’s pro-rich region-interacting factor 1 2.01 AtMg00660 Hypothetical protein 2.01 At5g41740/ Disease resistance protein (TIR-NBS-LRR class) family 2.01 At5g41750 At1g15840 Unknown protein 2.01 At1g47680 Unknown protein 2.01 At1g64500 Glutaredoxin family protein 2.01 At4g18880 HSF A4A: Heat shock transcription factor A4A 2.00 At5g58760 DDB2: Damaged DNA binding 2 2.00 AtMg00080/ RPL16: Ribosomal protein L16 2.00 AtMg00090 At4g22870/ 2-oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily 2.00 At4g22880 protein aFive-day-old seedlings in liquid media were incubated with either 100 μM sulfamethoxazole or 1% DMSO for 12 hours. Fold change calculations represent a comparison of data from sulfamethoxazole- versus DMSO-treated seedlings.

243 Appendix 5

Transcriptional Response of Plants Treated with

Sulfamethoxazole Prior to Bacterial Infection

Table A5-1: Arabidopsis genes upregulated by at least two-fold in plants treated with sulfamethoxazole versus DMSO prior to bacterial infectiona

Arithmetic Locus Description Fold Change

At3g43740 Putative leucine-rich repeat family protein 61.54 Putative mitochondrial ubiquinol-cytochrome C reductase complex 7.8 At2g01090 40.89 kDa protein At5g58860 Cytochrome P450 CYP86A subfamily member 30.17 At3g44430 Unknown protein 17.91 At5g37690 GDSL-motif lipase/hydrolase family protein 15.40 At3g30720 Unknown protein 12.26 At4g17470 Palmitoyl protein thioesterase family protein 10.99 At4g29770 Unknown protein 10.93 At3g43960 Putative cysteine proteinase 10.53 At2g47200 Unknown protein 10.11 At3g29035 Putative transcription factor 8.03 At2g43670 Glycosyl hydrolase family protein 7.83 At5g44550 Integral membrane family protein 7.46 At4g34510 Very-long-chain fatty acid elongase involved in wax biosynthesis 6.89 At3g46660 Potential natural antisense gene 6.76 At3g46980 Transporter-related protein 6.45 At3g46530 NBS-LRR type R protein (RPP13) 6.27 At3g18400 Putative transcription factor 6.10 At1g15010 Unknown protein 5.66 At5g48350 Ribonuclease H-like superfamily protein 5.64 At5g48090 ELP1 (EDM2-LIKE PROTEIN1), putative transcription factor 5.44 At5g47635 Pollen Ole e1 allergen and xtension family protein 5.02 At3g11430 GPAT5: Glycerol-3-phosphate acyltransferase 5 4.98 At3g04370 PDLP4: Plasmodesmata-located protein 4 4.95 At2g03980 GDSL-like Lipase/Acylhydrolase superfamily protein 4.87 At2g46130 WRKY transcription factor; Group II-c 4.82 At3g19515 Unknown protein 4.78 At3g25855 Copper transport protein family 4.68 Late embryogenesis abundant (LEA) hydroxyproline-rich glycoprotein At1g54540 4.67 family At2g43880 Pectin lyase-like superfamily protein 4.66 At2g22510 Hydroxyproline-rich glycoprotein family protein 4.65 At3g43190 SUS4: Sucrose synthase 4 4.60 At5g15960 KIN1: Cold and ABA inducible protein 4.49 At5g55790 Unknown protein 4.37 At4g31570 Myosin-related protein 4.34

244 At3g45590 SEN1: Splicing endonuclease 1 4.32 At3g18270 Cytochrome P450 pseudogene 4.22 At3g06390 Integral membrane family protein 4.19 At3g44550 FAR5: Fatty acid reductase 5 4.17 At1g30700 FAD-binding Berberine family protein 4.13* At1g68850 Peroxidase superfamily protein 4.09* At2g23540 GDSL-like Lipase/Acylhydrolase superfamily protein 4.04 At5g39100 GLP6: Germin-like protein 6 4.01 At1g04360 RING/U-box superfamily protein 4.01 At4g17215 Pollen Ole e1 allergen and extensin family protein 4.01 At4g20390 Integral membrane family protein 3.93 EDA4: Bifunctional inhibitor/lipid-transfer protein/seed storage At2g48140 3.90 superfamily protein At1g60970 SNARE-like superfamily protein 3.87 At2g02360 PP2-B10: phloem protein 2-B10 3.86 At1g24430 HXXXD-type acyl-transferase family protein 3.82 At3g61880 Cytochrome P450 CYP78A9 3.78 At2g41390 Unknown protein 3.74 At3g04180/ Germin-like protein 3.61 At3g04190 At3g44740 Class II aaRS and biotin synthetases superfamily protein 3.58 At1g55940 Cytochrome P450 CYP708A 3.55 At5g23190 Cytochrome P450 CYP86B1 3.54 At1g56650 Putative MYB domain-containing transcription factor 3.54 At5g42500 Disease resistance-responsive family protein 3.54 At3g04150 RmlC-like cupins superfamily protein 3.31 At4g27050 F-box/RNI-like superfamily protein 3.26 At2g02990 RNS1: Ribonuclease 1 3.26 At2g44260 Potential natural antisense gene 3.24 At2g44460 BGLU28: beta glucosidase 28 3.23 At4g09600 GASA3: GAST1 protein homolog 3 3.20 At1g79330 MC5: Metacaspase 5 3.16 At2g43390 Unknown protein 3.15 At3g28940 AIG2-like (avirulence induced gene) family protein 3.14 At4g23600 CORI3_JR2: Tyrosine transaminase family protein 3.14 At3g44450 Unknown protein 3.10 At3g54420 EP3 chitinase protein 3.08 At1g53885 senescence-associated protein 3.06 At3g29630 UDP-Glycosyltransferase superfamily protein 3.05 Bifunctional inhibitor/lipid-transfer protein/seed storage 2S albumin At2g48130 3.04 superfamily protein At1g17170 Encodes glutathione transferase belonging to the tau class of GSTs. 2.98* At4g29800 PLA IVD_PLP8: PATATIN-like protein 8 2.98 At2g18480 Putative mannitol transporter 2.95 At3g46580 Methyl-CpG-binding domain-containing protein 2.93 At1g73000 PYL3_RCAR13: PYR1-like 3 2.93 At5g63590 FLS3: Flavonol synthase 3 2.91 At1g53270 ABC-2 type transporter family protein 2.88 At5g09530 Hydroxyproline-rich glycoprotein family protein 2.82 At4g38300 Glycosyl hydrolase family 10 protein 2.81 At2g21100 Disease resistance-responsive family protein 2.79 At4g27350 Unknown protein 2.79 At3g28950 AIG2-like (avirulence induced gene) family protein 2.79

245 At4g16640 Matrixin family protein 2.77 At5g22500 FAR1: Fatty acid reductase 1 2.76 At3g20810 Transcription factor 2.75 At1g56320 Unknown protein 2.74 At2g29940 PDR3: Pleiotropic drug resistance 3 2.73 At3g23340 CKL10: Casein kinase I-like 10 2.72 At3g47750/ ATH subfamily member 2.72 At3g47760 At5g27160 Unknown protein 2.71 At2g01660 33 kDa secretory protein-related 2.70 At2g03200 Eukaryotic aspartyl protease family protein 2.69 At5g47240 NUDT8: Nudix hydrolase homolog 8 2.68 At1g76230 Unknown protein 2.66 At4g38080 Hydroxyproline-rich glycoprotein family protein 2.65 S-adenosyl-L-methionine-dependent methyltransferases superfamily At5g38780 2.62 protein At2g39110 Protein kinase superfamily protein 2.62 At3g62660 GATL7: Galacturonosyltransferase-like 7 2.62 At3g21520 Unknown protein 2.61 At4g37360 Cytochrome P450 CYP81D 2.61 At2g02960 RING/FYVE/PHD zinc finger superfamily protein 2.60 At5g37130 Protein prenylyltransferase superfamily protein 2.58 At3g43210 NACK2_TES: ATP binding microtubule motor family protein 2.55 At1g61240 Unknown protein 2.51 At1g02900 RALFL1: Rapid alkalinization factor 1 2.50 At4g33985 Unknown protein 2.49 AtCg00070 PSII K protein 2.49 At3g03540 NPC4: Phosphoesterase family protein 2.48 At2g04025 RGF3: Root meristem growth factor 2.48 At4g35420 DRL1: Dihydroflavonol 4-reductase-like1 2.48 At5g07390 RBOHA: Respiratory burst oxidase homolog A 2.47 At4g13790 SAUR-like auxin-responsive protein family 2.47 At3g26290 Putative cytochrome P450 2.44 At4g38480 Transducin/WD40 repeat-like superfamily protein 2.44 At1g19900 Glyoxal oxidase-related protein 2.42 At5g12420 O-acyltransferase (WSD1-like) family protein 2.41 At3g44720 ADT4: Arogenate dehydratase 4 2.41 At2g40570 Initiator tRNA phosphoribosyl transferase family protein 2.40 At2g44010 Unknown protein 2.40 At3g27200 Cupredoxin superfamily protein 2.40 At4g24140 alpha/beta-Hydrolases superfamily protein 2.40 At2g02800 APK2B: Protein kinase 2B 2.39 At5g09520 Hydroxyproline-rich glycoprotein family protein 2.39 At1g79470 Aldolase-type TIM barrel family protein 2.39 At5g20940 Glycosyl hydrolase family protein 2.38 At3g07650 COL9: CONSTANS-like 9 2.37 At2g23910 NAD(P)-binding Rossmann-fold superfamily protein 2.36 At1g30110 NUDX25: Nudix hydrolase homolog 25 2.34 At3g45730 Unknown protein 2.34 At3g53510 ABC-2 type transporter family protein 2.33 At5g39520 Unknown protein 2.32 At2g37360 ABC-2 type transporter family protein 2.30 At3g47070 Thylakoid soluble phosphoprotein 2.28

246 At2g05910 Unknown protein 2.27 At3g27220 Galactose oxidase/kelch repeat superfamily protein 2.26 At1g17710 Phosphoric monoester hydrolase 2.25 At3g16280 DREB subfamily transcription factor family 2.25 At4g28085 Unknown protein 2.24 At5g09480 Hydroxyproline-rich glycoprotein family protein 2.24 At1g19230 Riboflavin synthase-like superfamily protein 2.22 At5g56540 AGP14: Arabinogalactan protein 14 2.21* At4g15680 Thioredoxin superfamily protein 2.21 At5g56300 GAMT2: Gibberellic acid methyltransferase 2 2.21 At1g61580 RPL3B: R-protein L3 B 2.20 At2g03210 Member of glycosyltransferase family 37 2.20 At4g33560 Wound-responsive family protein 2.19* At5g66380 FOLT1: Folate transporter 1 2.18 At2g14260 Proline iminopeptidase 2.18 At1g62200 Major facilitator superfamily protein 2.17 At1g17650 GR2: Glyoxylate reductase 2 2.16 At5g57240 Oxysterol-binding family protein 2.16 At2g41690 Heat stress transcription factor (HSF) family member 2.16 At4g24110 Unknown protein 2.16 At3g29575 AFP3: ABI five binding protein 3 2.15 At5g42900 COR27: cold regulated gene 27 2.15 At1g22110 structural constituent of ribosome 2.14 At1g72070 Chaperone DnaJ-domain superfamily protein 2.13 At3g46970 PHS2: alpha-glucan phosphorylase 2 2.13 At1g76560 CP12-3: CP12 domain-containing protein 3 2.13 At5g27200 ACP5: Acyl carrier protein 5 2.12 At4g34320 Unknown protein 2.11 At4g15120 VQ motif-containing protein 2.11 At3g57770 Protein kinase superfamily protein 2.11 At3g60410 Unknown protein 2.10 At4g18920 Unknown protein 2.10 At3g22240 Unknown protein 2.09 AtMg01330 Hypothetical mitochondrial protein 2.08 At4g01180 XH/XS domain-containing protein 2.07 At1g68500 Unknown protein 2.07 At1g79900 BAC2: Mitochondrial substrate carrier family protein 2.07 At1g73410 R2R3-MYB transcription factor family member 2.06 At1g64000 WRKY Transcription Factor; Group II-c 2.06 At3g01970 WRKY Transcription Factor; Group I 2.06 At5g16230 Putative acyl-(acyl-carrier-protein) desaturase 2.05 At5g46050 PTR3: Peptide transporter protein 3 2.03 At1g49430 LRD2: Long-chain acyl-CoA synthetase 2 2.02 At5g45140 RNA polymerase III subunit 2.02 At5g04000 Unknown protein 2.01 At2g36590 ProT3: Proline transporter 3 2.01 At4g23990 Cellulose synthase-like protein 2.01 At5g35940 Mannose-binding lectin superfamily protein 2.01 At1g10750 Unknown protein 2.01 At4g10270 Wound-responsive family protein 2.00* At2g02220 PSKR1: Phytosulfokine receptor 1 2.00 At3g29375 XH domain-containing protein 2.00

247 aSix-week-old soil-grown plants were sprayed with 1% DMSO or 500 μM sulfamethoxazole, then inoculated with Pto DC3000 24 hours later. Tissues were harvested for RNA extraction at four hours post-inoculation. *Also upregulated in seedlings by treatment with sulfamethoxazole alone (Appendix 4).

248 Table A5-2: Arabidopsis genes downregulated by at least two-fold in plants treated with sulfamethoxazole versus DMSO prior to bacterial infectiona

Arithmetic Locus Description Fold Change

At3g45070/ Sulfotransferase family protein 63.79 At3g45080 AtCg00430 NADH dehydrogenase subunit K 9.87 Polyubiquitin gene, belongs to a subtype group with UBQ10 and At4g05050 8.93 UBQ14 At2g01520 Major latex protein-related protein 7.60 At3g28960 Amino acid transporter family protein 6.85 At4g25830 Integral membrane family protein 6.27 At1g28170 Sulfotransferase family protein 6.14 At3g44990 Xyloglucan endo-transglycosylase 6.12 At5g26120 Glycosyl hydrolase family protein 5.72 At4g37320 Cytochrome P450 CYP81D subfamily member 5.55 At3g50990 Peroxidase 5.51 At3g30290 Cytochrome P450 gene family member 5.45 At1g72260 Thionin (Thi2.1) 5.02 At1g59500/ IAA-amido synthase 4.87 At4g37390 At5g03200 Zinc finger (C3HC4-type RING finger) family protein 4.73 Protease inhibitor/seed storage/lipid transfer protein (LTP) family At4g33550 4.41 protein At4g03060 2-oxoglutarate-dependent dioxygenase 4.39 At3g44070 Unknown protein 4.13 At4g15750 Invertase/pectin methylesterase inhibitor family protein 4.07 At2g39510 Nodulin MtN21 family protein 4.04 At2g14560 Unknown protein 3.93 At5g26980 SYP4 syntaxin family member 3.70 At4g24510 HXXXD-type acyl-transferase family protein 3.69 At2g39210 Nodulin family protein 3.66 AtCg00270 PSII D2 protein 3.63 AtCg00810 Chloroplast ribosomal protein L22 3.53 At5g24150 Squalene monooxygenase gene homolog 3.42# At5g36910 THI2.2: Thionin 2.2 3.39 At5g45820 Serine/threonine protein kinase 3.35 At3g29190 Terpene synthase/cyclase family protein 3.25 At2g44500 Unknown protein 3.20 AtCg01060 Photosystem I PsaC subunit 3.16 At2g41100 Calmodulin-like protein 3.09 AtCg01070 NADH dehydrogenase ND4L 3.03 At1g29500 SAUR-like auxin-responsive protein family 3.02# At5g64120 Peroxidase superfamily protein 3.01 At5g57810 TET15: Tetraspanin15 2.99 At5g64070 Putative phosphatidylinositol 4-kinase 2.92 At2g35860 beta-Ig-H3 domain-containing protein 2.89 At5g27270 Pentatricopeptide (PPR) repeat-containing protein 2.87 AtCg00800 Chloroplast ribosomal protein S3 2.87

249 At1g24540 Cytochrome P450 CYP86C family member 2.82 At5g39990 Glycosyltransferase family 14 protein 2.81 At5g42720 Glycosyl hydrolase family 17 protein 2.78 At5g25390 ERF/AP2 transcription factor, subfamily B-6 2.74 At1g25450 KCS5: 3-ketoacyl-CoA synthase 5 2.73 At5g16250 Unknown protein 2.71 At4g24780 Pectate lyase family protein 2.69 AtCg00530 CemA: Chloroplast envelope membrane protein 2.68 At5g07580 ERF/AP2 transcription factor, subfamily B-3 2.68 At4g17340 TIP2;2: Tonoplast intrinsic protein 2;2 2.68 At5g22460 alpha/beta-Hydrolases superfamily protein 2.67 At4g12910 SCPL20: serine carboxypeptidase-like 20 2.67 Bifunctional inhibitor/lipid-transfer protein/seed storage 2S At5g55450 2.66 albumin superfamily protein At1g52190 Major facilitator superfamily protein 2.65 At2g47670 Invertase/pectin methylesterase inhibitor superfamily protein 2.64 At4g08850 Leucine-rich repeat family protein 2.60 At5g60220 TET4: Tetraspanin4 2.57 At2g44740 CYCP4;1: Cyclin p4;1 2.56 AtMg00660 Hypothetical mitochondrial protein 2.56# At3g46900 Copper transporter family member 2.55 At4g25710 Kelch repeat-containing F-box family protein 2.54 At5g51950 Glucose-methanol-choline (GMC) oxidoreductase family protein 2.53 At5g10140 MADS-box protein 2.53 At2g43620 Chitinase family protein 2.48# Encodes a protein required for photosystem I assembly and AtCg00520 2.44 stability At2g39280 Ypt/Rab-GAP domain of gyp1p superfamily protein 2.41 Chloroplast gene encoding a CP43 subunit of the photosystem AtCg00280 2.39 II reaction center At1g56100 Pectinesterase inhibitor domain-containing protein 2.39 At4g21080 Dof-type zinc finger domain-containing protein 2.38 At3g46110 Unknown protein 2.37 At3g16370 GDSL-motif lipase/hydrolase family protein 2.36 At2g37130 PER21: Peroxidase 21 2.36 At5g02410 DIE2/ALG10 family 2.35 At2g41090 Calcium-binding EF-hand family protein 2.33 At5g04530 KCS19: 3-ketoacyl-CoA synthase 19 2.33 v-SNARE (vesicle soluble NSF attachment protein receptor) At3g29100 2.32 family member At4g22400 Unknown protein 2.32 At3g26520 TIP2: Tonoplast intrinsic protein 2 2.32 At1g12350/ Phosphopantothenoylcysteine synthetase 2.31 At5g02080 (phosphopantothenoylcysteine ligase) At2g34190 Xanthine/uracil permease family protein 2.31 At1g61090 Unknown protein 2.31 At1g36340 UBC31: Ubiquitin-conjugating enzyme 31 2.30 At1g01060 LHY1: Homeodomain-like superfamily protein 2.30 At1g75880 SGNH hydrolase-type esterase superfamily protein 2.29 Bifunctional inhibitor/lipid-transfer protein/seed storage 2S At5g38180 2.28 albumin superfamily protein At2g04032 ZIP7: Zinc transporter 7 precursor 2.28

250 DIR1: Bifunctional inhibitor/lipid-transfer protein/seed storage 2S At5g48485 2.27 albumin superfamily protein At5g47500 Pectin lyase-like superfamily protein 2.27 At1g14870 Unknown protein 2.26 At5g44930 ARAD2: Exostosin family protein 2.26 At3g04210 Disease resistance protein (TIR-NBS class) 2.25 At3g10890 Glycosyl hydrolase superfamily protein 2.25 At4g01140 Unknown protein 2.25 At1g04645 Plant self-incompatibility protein S1 family 2.25 At1g75040 PR5: Pathogenesis-related gene 5 2.25 At3g21220 MKK5: MAP kinase kinase 5 2.24 At4g18260 Cytochrome b561/ferric reductase transmembrane family protein 2.24 At2g21130 Cyclophilin-like peptidyl-prolyl cis-trans isomerase family protein 2.24 Gamma interferon responsive lysosomal thiol (GILT) reductase At4g12960 2.23 family protein At5g51190 ERF/AP2 transcription factor, subfamily B-3 2.22# At2g18550 HB21: homeobox protein 21 2.21 At5g27990 Unknown protein 2.20 At3g06070 Unknown protein 2.20# At3g23970 F-box family protein 2.20 At1g16190 DNA repair protein RAD23 2.19 At1g52140 Unknown protein 2.18 At4g32490 Plastocyanin-like domain-containing protein 2.17 At2g31270 CDT1A: Homolog of yeast CDT1 A 2.15 EIN4: Signal transduction histidine kinase, hybrid-type, ethylene At3g04580 2.15 sensor At3g53960 Major facilitator superfamily protein 2.15 At5g26220 ChaC-like family protein 2.13 At4g38110 ARM repeat superfamily protein 2.13 At1g73620 Pathogenesis-related thaumatin superfamily protein 2.13 RAT4: Nucleotide-diphospho-sugar transferases superfamily At5g03760 2.12 protein At4g15830 ARM repeat superfamily protein 2.11 At3g61520/ At5g28370/ Pentatricopeptide (PPR) repeat-containing protein 2.11 At5g28460 At4g33790 Jojoba acyl CoA reductase-related male sterility protein 2.11 At2g40960 Single-stranded nucleic acid binding R3H protein 2.11 At3g08770 Lipid transfer protein 6 2.10 At2g27700 Eukaryotic translation initiation factor 2 family protein 2.10 AtCg00350 Photosystem I reaction center protein psaA 2.10 At5g40830 Unknown protein 2.09 At3g16980 NRPE9A: RNA polymerases M/15 kDa subunit 2.09 At1g76800 Vacuolar iron transporter (VIT) family protein 2.08 AtCg01050 NAD(P)H dehydrogenase complex subunit 2.08 At5g43270 SPL2: Squamosa promoter binding protein-like 2 2.07 At5g45020 Glutathione S-transferase family protein 2.07 At5g26720 Unknown protein 2.07 At2g46720/ 3-Keto acyl coenzyme A synthase 2.07 At3g10280 At5g42370 Calcineurin-like metallo-phosphoesterase superfamily protein 2.05 At2g17440 PIRL5: Plant intracellular ras group-related LRR 5 2.05 At1g19960 Unknown protein 2.05

251 At4g35090 CAT2: Catalase 2 2.03 At3g62610 MYB11: MYB domain protein 11 2.03 At1g02300 Putative cathepsin B-like cysteine protease 2.03 At2g40270 Protein kinase family protein 2.03 At2g35960 Non-race specific disease resistance (NDR1)-like protein 2.02 At5g04220 C2 domain-containing protein 2.01 At4g36910 CDCP2: Cystathionine beta-synthase (CBS) family protein 2.01 At5g66330 Leucine-rich repeat (LRR) family protein 2.01 At2g01570 RGA1: GRAS family transcription factor family protein 2.00 At3g56900 Transducin/WD40 repeat-like superfamily protein 2.00 At4g22870 Putative leucoanthocyanidin dioxygenase 2.00 At5g52580 RabGAP/TBC domain-containing protein 2.00 aSix-week-old soil-grown plants were sprayed with 1% DMSO or 500 μM sulfamethoxazole, then inoculated with Pto DC3000 24 hours later. Tissues were harvested for RNA extraction at four hours post-inoculation. #Also downregulated in seedlings by treatment with sulfamethoxazole alone (Appendix 4).

252 Appendix 6

Summary of Results from a Forward Genetic Screen Intended to

Identify Novel Virulence Determinants in Pseudomonas syringae

pv. maculicola ES4326

Summary

Based on the bacterial infection phenotype of Arabidopsis seedlings in liquid media (Chapter 2), a forward genetic screen was initiated to identify novel virulence determinants in Pseudomonas syringae pv. maculicola ES4326 (Pma ES4326). A mini-Tn5 transposon bearing a kanamycin resistance gene (Alexeyev et al., 1995) was introduced into Pma ES4326 by triparental mating and disruptants recovered on selective media (King’s B plus 300 μg/mL streptomycin and 50 μg/mL kanamycin).

Arabidopsis seedlings in liquid media were inoculated with these disruptants at 1 x 105 cfu/mL (one disruptant per well) and seedling phenotypes assessed after seven days of incubation on a vibrating shaker under continuous light. Experiments were conducted in triplicate, and those disruptants that failed to cause the bleaching of seedling cotyledons in all three replicates were considered hits. Bacterial populations in hit wells were quantified by dilution plating as a preliminary assessment of potential auxotrophy.

For disruptants presumed to be non-auxotrophs, the genomic location of each transposon was determined by vectorette PCR (Arnold and Hodgson, 1991).

Approximately 12,600 disruptants were screened in the liquid assay, yielding 38 non-auxotrophic hits (Table A6-1). Half of the disruptants involved genes associated with either the structure or function of the type III secretion system (TTSS), including five independent disruptions of the TTSS ATPase hrcN. Six flagellar gene disruptants

253 Table A6-1: Genes identified in Pseudomonas syringae pv. maculicola ES4326 (Pma ES4326) that contribute to pathogen virulence on Arabidopsis seedlings grown in liquid media Gene Disruptant (Putative) Protein Function Location Within Operon Affected Type III Secretion 3G3 42F5 48C10 hrcN ATPase hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU 74D9 175B4 5F8 hrcQb type III secretion-associated protein hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU 100F9 10B7 hrpS TTSS transcriptional regulator hrpR-hrpS

31F4 hrpG TTSS regulatory protein hrpF-hrpG-hrcC-hrpT-hrpV

254 inner membrane structural TTSS 43F3 hrpQ hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU component 62F2 hrpB ATP-dependent helicase hrpZ1-hrpB-hrcJ-hrpD

77C3 hrcJ lipoprotein; inter-membrane bridge hrpZ1-hrpB-hrcJ-hrpD 116G4 133F11 hrcU TTSS inner membrane component hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU

146F7 hrpO regulator of TTSS protein export hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU

149B7 hrcS TTSS structural component hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU

150D10 hrcV TTSS structural component hrpJ-hrcV-hrpQ-hrcN-hrpO-hrpP-hrcQa-hrcQb-hrcR-hrcS-hrcT-hrcU

161E11 hrpR TTSS transcriptional regulator hrpR-hrpS

197G3 hrcC outer membrane TTSS protein hrpF-hrpG-hrcC-hrpT-hrpV

Gene Disruptant Affected (Putative) Protein Function Location Within Operon

Flagellar Motility . 20G3 fleN negative regulator of flagellar number flhF-fleN

74C8 fliH putative flagellar assembly protein fliE-fliF-fliG-fliH-fliI-fliJ 144C2 76E4 flgF flagellar basal-body rod protein flgF-flgG-flgH-flgI-flgJ-flgK-flgL

82D2 fliG flagellar motor switch protein fliE-fliF-fliG-fliH-fliI-fliJ

86E11 flgH flagellar L-ring protein (FlgH) flgF-flgG-flgH-flgI-flgJ-flgK-flgL

General Metabolism 46C6 gltB glutamate synthase (large subunit) single gene 182F11

255 49E4 carbonic anhydrase - nitrogen “cynT-like” single gene (closely related to Pto DC3000 locus PSPTO_0994) 196G2 metabolism/cyanate hydrolysis 203C3 71E5 cbrB sensory box histidine kinase cbrA-cbrB

D-erythrose 4-phosphate 73B10 gapB/epd epd-pgk dehydrogenase

78F7 kinB sensory box histidine kinase algB-kinB

UTP-glucose-1-phosphate 135F10 galU single gene uridylyltransferase

141C5 mdoG periplasmic glucan biosynthesis mdoG-mdoH

155B4 mdoH periplasmic glucan biosynthesis mdoG-mdoH

histidinol dehydrogenase - histidine 204G6 hisD hisD-hisC biosynthesis Phosphoserine phosphatase - Gly 209G11 serB single gene and Ser utilization, Ser biosynthesis

were confirmed as hits, although this was based on a more subtle reduction in seedling bleaching than was observed for TTSS disruptants. Additional flagellar gene disruptants were likely present in the collection, but hits shown to be nonmotile in a parallel motility screen (Appendix 7) were not actively characterized in the later part of the virulence screen. The final class of disruptants included an assortment of genes loosely categorized as having some metabolic function in P. syringae. It is interesting to note that, despite the wide variety of biological functions represented in this group, multiple independent disruptions were recovered for two genes, gltB and a cynT-like gene.

Many of the disruptants were further characterized with regards to in planta growth in soil-grown plants following inoculation by pressure infiltration. On average,

TTSS disruptants grew 1.2-1.5 logs less than wildtype, while the flagellar gene disruptants did not exhibit any significant growth reductions. Some of the metabolic disruptants were also evaluated in these assays, revealing that the disruption of gltB, kinB, cbrB, or the cynT-like gene did not negatively affect in planta growth, but the loss of gapB/epd function lowered bacterial growth by approximately 1.3 logs. While these results are intriguing, these experiments should be replicated in the future using spray inoculations, which presumably would more closely mimic the mode of bacterial entry in the liquid assay.

Overall, this screen yielded a number of positive results. Although most of the disruptants identified through the screen were hardly novel virulence components, they were not previously available in Pma ES4326. Importantly, some disruptants have already been utilized as controls for type III secretion and motility in various experiments (Appendix 8). In addition, some novelty may be derived from the class of non-auxotrophic metabolic disruptants, especially for genes that are important for the 256 bleaching of seedling cotyledons in liquid media, yet apparently dispensable for virulence in soil-grown plants. Finally, the collection of transposon disruptants assembled for this screen provides a valuable resource for future genetic screens in

Pma ES4326.

References

Alexeyev, M.F., Shokolenko, I.N., and Croughan, T.P. (1995). New mini-Tn5 derivatives for insertion mutagenesis and genetic engineering in Gram-negative bacteria. Can. J. Microbiol. 41, 1053-1055. Arnold, C., and Hodgson, I.J. (1991). Vectorette PCR: A novel approach to genomic walking. PCR Methods Appl. 1, 39-42.

257 Appendix 7

Summary of Results from a Forward Genetic Screen Intended to

Identify Negative Regulators of Flagellar Motility in Pseudomonas syringae pv. maculicola ES4326 Grown Under Type III Secretion

System-Inducing Conditions

Summary

When Pseudomonas syringae pv. maculicola ES4326 (Pma ES4326) is grown on media that induces the type III secretion system (TTSS), flagellin protein production is reduced and swimming motility is significantly restricted (Appendix 8). In order to identify the gene(s) responsible for this negative regulation, high-throughput motility assays were conducted with a collection of 6,587 Pma ES4326 transposon disruptants as described in Appendix 8. We identified fifteen disruptants whose motility was no longer restricted under TTSS-inducing conditions (Table A7-1) and determined the genomic location of transposons by vectorette PCR (Arnold and Hodgson, 1991).

Several unusual features were apparent in this list of disruptants. Interestingly, the majority of hits from the screen contained transposons in genes with little or no previous characterization aside from homology-based predictions of protein function.

For two disruptants, the transposons were actually localized to intergenic regions. On the other hand, the screen did identify the TTSS regulator hrpR as a hit, which corroborated previous observations from Erwinia amylovora in which the loss of the downstream TTSS regulator hrpL results in relative hypermotility under TTSS-inducing conditions (Cesbron et al., 2006). Strangely, however, flagellin immunoblots of cell

258 Table A7-1: Genes identified in Pseudomonas syringae pv. maculicola ES4326 (Pma ES4326) that contribute to the downregulation of motility under type III secretion system (TTSS)-inducing conditions

Disruptant Gene Affecteda (Putative) Protein Function Location Within Operonb

osmotically inducible, transport-associated periplasmic 112E6 ~PSYR_0262 single gene protein

131F2 ~PSPTO_2711 response regulator single gene

136D7 ~PSPTO_2717 sensory box histidine kinase/response regulator 2718-2717

165E5 181G7 ~PSPTO_2718 conserved hypothetical protein 2718-2717 193G7 155B2 n/a intergenic region between two hypothetical proteins n/a - at 5' end of both genes

259 156D7 ~PSPTO_0413 unknown 0413-mutM

161E11 hrpR TTSS transcriptional regulator hrpR-hrpS

161G10 DegQ-like protease and positive regulator of alginate algW algW 181D8 biosynthesis intergenic region between TetR (~PSPTO_1758) and ComEA 167B3 n/a n/a - at 3' end of both genes (~PSPTO_1759)

187E9 csdA cysteine sulfinate desulfinase 1529-1528-csdA-sufA

197B5 ~PSPTO_1734 rhodanese-like domain protein 1734-1735-1736

140E5 glnE glutamate-ammonia-ligase adenylyltransferase glnE aWhere loci correspond to unknown or uncharacterized genes, locus identifiers of the nearest orthologue in P. syringae pv. syringae B728a (PSYR) or P. syringae pv. tomato DC3000 (PSPTO) are indicated. n/a = not applicable. bUnknown/uncharacterized genes are represented by the digits from loci identifiers of the nearest P. syringae orthologue.

lysates revealed that most of the disruptants downregulated flagellin production on

TTSS-inducing media in a manner similar to wildtype Pma ES4326 (Figure A7-1). For hrpR, this contradicts the results obtained with E. amylovora ΔhrpL mutants (Cesbron et al., 2006). At this time, it is unclear how bacteria that restrict flagellin production can remain motile in swimming assays.

There were exceptions to these obervations, however, including disruptants in a gene encoding the protease AlgW as well as in a two-gene operon composed of a conserved hypothetical protein gene and a sensory box histidine kinase/response regulator gene. Of these genes, only algW appeared to influence pathogen virulence.

The contribution of algW to motility regulation and virulence in Pma ES4326 is described in Appendix 8.

References

Arnold, C., and Hodgson, I.J. (1991). Vectorette PCR: A novel approach to genomic walking. PCR Methods Appl. 1, 39-42. Cesbron, S., Paulin, J.P., Tharaud, M., Barny, M.A., and Brisset, M.N. (2006). The alternative sigma factor HrpL negatively modulates the flagellar system in the phytopathogenic bacterium Erwinia amylovora under hrp-inducing conditions. FEMS Microbiol. Lett. 257, 221-227.

260

Figure A7-1: Preliminary evaluation of flagellin production by Pma ES4326 transposon disruptants that fail to downregulate motility under TTSS-inducing conditions. Bacteria were grown for 24 hours on plates comprised of minimal media containing either 10 mM citrate (C) or 10 mM fructose (F). Total bacterial proteins were then separated by

SDS-PAGE, transferred to a nitrocellulose membrane, and incubated with an anti- flagellin antibody. The molecular weight of Pma ES4326 flagellin is 29.4 kDa. The band corresponding to flagellin is indicated by an arrow. Ponceau staining of the membrane was used as a loading control.

261

Appendix 8

AlgW Regulates Multiple Pseudomonas syringae Virulence

Strategies

Previously published as:

AlgW regulates multiple Pseudomonas syringae virulence strategies

Karl J. Schreiber and Darrell Desveaux (2011)

Molecular Microbiology 80, 364-377

Author contributions: K.J.S. performed all experiments and wrote the manuscript, with input and direction from D.D.

262 Abstract

Gram-negative bacterial pathogens have evolved a number of virulence- promoting strategies including the production of extracellular polysaccharides such as alginate and the injection of effector proteins into host cells. The induction of these virulence mechanisms can be associated with concomitant downregulation of the abundance of proteins that trigger the host immune system, such as bacterial flagellin.

In Pseudomonas syringae, we observed that bacterial motility and the abundance of flagellin were significantly reduced under conditions that induce the type III secretion system. To identify genes involved in this negative regulation, we conducted a forward genetic screen with P. syringae pv. maculicola ES4326 using motility as a screening phenotype. We identified the periplasmic protease AlgW as a key negative regulator of flagellin abundance that also positively regulates alginate biosynthesis and the type III secretion system. We also demonstrate that AlgW constitutes a major virulence determinant of P. syringae required to dampen plant immune responses. Our findings support the conclusion that P. syringae coordinately regulates virulence strategies through AlgW in order to effectively suppress host immunity.

263 Introduction

Faced with formidable opposition from host immune systems, pathogenic organisms have evolved numerous strategies to promote the infection of potential hosts. The initial invasion of host tissues is facilitated by flagella-mediated swimming motility in many bacterial pathogens (Naito et al., 2008; Ormonde et al., 2000; Tans-

Kersten et al., 2001; Zhang et al., 1993). These pathogens also produce various complex extracellular polysaccharides (EPSs) such as lipopolysaccharides and peptidoglycan, which provide physical reinforcement as well as protection from antimicrobial molecules (Guenin-Macé et al., 2009; Silipo et al., 2010). At the same time, however, the detection of microbe- or pathogen-associated molecular patterns

(MAMPs or PAMPs) such as the flagellar protein flagellin or certain EPSs can elicit an array of defence responses (Gómez-Gómez et al., 1999; Jones and Dangl, 2006; Pier,

2007; Pitzschke et al., 2009; Schwessinger and Zipfel, 2008; Wang and Ligoxygakis,

2006). This can be mitigated by additional EPSs such as alginate in Pseudomonas spp. or xanthan in Xanthomonas spp., which actively suppress host defence mechanisms and/or their underlying signalling pathways (Aslam et al., 2008; Cobb et al., 2004). Another key component of virulence for many Gram-negative bacterial pathogens is the needle-like structure known as the type III secretion system (TTSS), through which type III-secreted effector (TTSE) proteins are delivered directly into host cells (Galan and Collmer, 1999; Marlovits and Stebbins, 2010). Many TTSE proteins act to suppress defence responses by blocking host immune signalling (Boller and He,

2009; Hauser, 2009; Lewis et al., 2009). Despite the efficacy of TTSEs as offensive countermeasures to host defences, an important strategy for minimizing PAMP-related liabilities could also involve tightly regulating PAMP production. 264 Flagellar biosynthesis is conditionally downregulated in a variety of bacterial pathogens. Expression of the flagellin gene fliC is significantly reduced in

Pseudomonas aeruginosa within two hours of exposure to muco-pulmonary fluid from chronically infected cystic fibrosis patients, suggesting that the absence of flagellin is important for such infections (Wolfgang et al., 2004). In Salmonella enterica, Ellermeier and Slauch (2003) identified the rtsAB operon as a key mediator of the inverse relationship between virulence gene activation and flagellar biosynthesis. In Bordetella bronchiseptica and the plant pathogen Erwinia amylovora, media that activate pathogen virulence systems concomitantly repress production of flagellin protein

(Akerley et al., 1995; Cesbron et al., 2006). As the flagellum represents a major PAMP of Pseudomonas syringae (Guo et al., 2009; Kvitko et al., 2009; Li et al., 2005; Shimizu et al., 2003), we hypothesized that flagellar biosynthesis is coordinately regulated with expression of the P. syringae type III secretion system.

In this study, we characterize the regulation of flagellin abundance in the bacterial phytopathogen P. syringae pv. maculicola ES4326 (Pma ES4326). We demonstrate that flagellin production is downregulated under TTSS-inducing conditions, and that flagellar motility is dispensable for virulence within plant tissues.

Through a forward genetic screen, we identify algW as a gene that not only controls the abundance of flagellin, but also expression of the TTSS and alginate production. We also demonstrate that AlgW is an important virulence factor required for optimal growth in Arabidopsis thaliana (hereafter Arabidopsis) as well as suppression of host defence responses. Overall, we show that AlgW is a critical component of P. syringae virulence required for effective suppression of host defences.

265 Results

Flagellin abundance is conditionally regulated and dispensable for apoplastic growth

The inverse relationship between virulence gene expression and flagellin production observed in several bacterial pathogens led us to investigate the possibility of similar regulation in the plant pathogen Pma ES4326. Apoplastic fluid is known to induce the P. syringae TTSS (Rico and Preston, 2008; Xiao et al., 1992), and this induction can be recapitulated using a defined minimal media supplemented with various carbon sources (Huynh et al., 1989). When cultures of Pma ES4326 were transferred from a rich media (King’s B) known to suppress the TTSS to a TTSS- inducing minimal media containing fructose (MMF), we noted that expression of the flagellin gene fliC was significantly reduced (five to seven-fold) within six hours post- transfer (Figure A8-1A). We also observed a striking downregulation of flagellin protein in MMF (Figure A8-1B). Flagellin levels gradually diminished upon exposure to MMF and were barely detectable by four hours post-transfer (Figure A8-2). This behavior was not simply due to comparing rich and minimal media because Pma ES4326 maintained flagellin levels in minimal media containing citrate (MMC) (Figure A8-1B).

While MMC does still induce TTSS gene expression, this induction is at least one order of magnitude lower than that provided by MMF (data not shown). These observations suggest that a specific threshold of TTSS induction must be exceeded before flagellin abundance is affected. Finally, transmission electron microscopy revealed the morphological consequences of flagellin downregulation, in that Pma ES4326 grown in

MMF were typically aflagellate (96%) relative to King’s B (33%; Figure A8-1C,D).

266

267 Figure A8-1: Influence of media conditions on flagellin abundance in Pma ES4326.

(A) Transcription of the flagellin gene fliC in TTSS-suppressing King’s B media (KB) and TTSS-inducing minimal media (minimal media containing 10 mM fructose, MMF).

Expression values were normalized with the housekeeping gene gyrB as described in

Experimental Procedures and reflect three technical replicates. Error bars represent standard deviation.

(B) Production of flagellin protein by Pma ES4326 in different types of media. Bacteria were grown for 24 hours on plates comprised of KB, minimal media containing 10 mM citrate (MMC), or MMF. Total bacterial proteins were then separated by SDS-PAGE, transferred to a nitrocellulose membrane, and incubated with an anti-flagellin antibody

(see Experimental Procedures). The molecular weight of Pma ES4326 flagellin is 29.4 kDa. The band corresponding to FliC is indicated by an arrow. Ponceau staining of the membrane was used as a loading control.

(C) Visualization of flagellar abundance in Pma ES4326 cultured in different types of media. Bacteria were grown for 24 hours on plates comprised of KB or MMF and prepared for transmission electron microscopy as described in Experimental

Procedures. Arrow in the left panel indicates the flagellum. Scale bars represent 1 μm.

(D) Quantification of flagellar abundance from transmission electron microscopy images of Pma ES4326 cultured in different types of media as in (C). Values represent the percentage of bacteria in each category of flagellar abundance from samples of approximately 100 bacteria.

All experiments were performed at least three times with similar results.

268

Figure A8-2: Timecourse of flagellin protein abundance in Pma ES4326 upon exposure to TTSS-inducing media.

Cultures grown in TTSS-suppressing King’s B media were collected by centrifugation, washed twice with minimal media, then resuspended in liquid minimal media containing either 10 mM citrate (MMC) or 10 mM fructose (MMF). Sampling times are indicated as hours post-transfer (hpt) to minimal media. The band corresponding to FliC is indicated by an arrow. Ponceau staining of the membrane was used as a loading control.

269 We next considered the potential virulence cost of downregulating flagellar expression during infection. Two disruptants with impaired flagellar assembly were examined in both in vitro and in planta assays. One disruptant contained a transposon in the fliH gene, which encodes a regulator of an ATPase important for flagellar assembly, and the other affected flgF, a component of the flagellar basal body. In a swimming motility assay, both disruptants were nonmotile (Figure A8-3A). This impairment significantly reduced the ability of these bacteria to infect plant tissues when sprayed on the leaves of Arabidopsis plants, resulting in approximately one log lower in planta growth versus wildtype Pma ES4326 (Figure A8-4A). In contrast, when leaves were inoculated by pressure infiltration, no such growth reductions were observed (Figures A8-3C and A8-4). To investigate a potential role for flagella in bacterial spread within leaf tissues, we inoculated portions of Arabidopsis leaves with

Pma ES4326 and quantified bacterial growth in both inoculated and uninoculated parts of the leaves. Over time, chlorotic symptoms developed in the inoculated region, but spread minimally into uninoculated portions (Figure A8-3B). In addition, bacteria were infrequently detected outside of the original area of inoculation (Figure A8-3D). Overall, this suggested that flagella are dispensable for full virulence in the apoplast, and that active deflagellation could occur in this environment as a virulence strategy.

Screening for negative regulators of flagellin abundance

In order to identify genes required for the negative regulation of flagellin abundance under TTSS-inducing conditions, we performed a forward genetic screen with Pma ES4326. We selected swimming motility as a salient screening phenotype that is directly related to flagellar assembly and function. Furthermore, we noted that 270

271 Figure A8-3: Motility of Pma ES4326 within Arabidopsis leaves following localized inoculations. In addition to wildtype Pma ES4326, two transposon disruptants were examined, one affecting the regulation of flagellar assembly (fliH) and the other disrupting a structural component of flagella (flgF). Bacteria (1 x 105 cfu mL-1 ) were infiltrated into the distal end of leaves using a needleless syringe. The border of the inoculated area was traced with a marker.

(A) Effect of flagellar gene disruption on swimming motility in Pma ES4326. To assess motility, equal quantities of bacteria were spotted onto King’s B media containing 0.3% agar and images captured after 48 hours of growth at 28ºC.

(B) Chlorosis of tissues inoculated with either wildtype Pma ES4326 or the nonmotile disruptant fliH::mTn5. Images were captured at five days post-inoculation and are representative of phenotypes observed from a sample size of 60 leaves. Scale bar represents 1 cm. Black and white circles represent typical locations for sampling bacterial populations in inoculated and uninoculated regions, respectively.

(C) Bacterial growth in inoculated leaf areas, quantified at zero and five days post- inoculation (dpi). Error bars reflect standard deviation.

(D) Distribution of bacterial population measurements in uninoculated regions at five days post-inoculation. One sample represents a measurement taken from four leaves of one plant. Three independent experiments were performed with similar results.

272

Figure A8-4: Virulence of nonmotile transposon disruptants of Pma ES4326 on

Arabidopsis (Col-0). Two disruptants were examined, one with effects on the regulation of flagellar assembly (fliH) and the other disrupting a structural component of flagella (flgF).

(A) Bacterial growth following spray inoculation. Adaxial leaf surfaces were sprayed with 4 x 108 cfu mL-1 bacteria, and in planta bacterial growth was quantified at three days post-inoculation.

(B) Bacterial growth following inoculation by pressure infiltration. A needleless syringe was used to infiltrate 1 x 105 cfu mL-1 bacteria into the abaxial side of Arabidopsis leaves. Bacterial populations were quantified at zero and three days post-inoculation

(dpi).

For both (A) and (B), error bars represent standard deviation. Letters above data points indicate statistical significance groups as determined by pairwise Student’s t- tests (α=0.05). Three independent experiments were performed with similar results.

273 the motility of wildtype Pma ES4326 was substantially reduced on MMF compared to

King’s B media or MMC (Figure A8-5A). Based on these observations, we conducted high-throughput motility assays with a collection of 6,587 Pma ES4326 transposon disruptants, focusing on the identification of those individuals exhibiting relative hypermotility on MMF.

AlgW regulates multiple virulence mechanisms in Pma ES4326

Through this screen, we identified two independent disruptants in which a putative orthologue of the P. aeruginosa gene algW is interrupted. This gene encodes a periplasmic DegS-like protease that was first identified as a key regulator in the production of the cell wall polysaccharide alginate (Qiu et al., 2007; Wood et al., 2006).

Although indistinguishable on King’s B media, the algW disruptant (Pma ES4326 algW::mTn5) was significantly more motile than wildtype Pma ES4326 on MMF (Figure

A8-5A). Importantly, the abundance of flagellin protein and fliC transcript in Pma

ES4326 algW::mTn5 was largely unaffected by exposure to MMF (Figures A8-5 and

A8-6A). However, a slight reduction in flagellin protein abundance was observed in

MMF relative to MMC, suggesting that additional proteins may contribute to the regulation of flagellin production. Both motility and flagellin production were complemented to near-wildtype levels on MMF by heterologous expression of algW from its native promoter, indicating that AlgW negatively regulates flagellin expression and motility in TTSS-inducing MMF media (Figures A8-5A,B).

In P. aeruginosa, AlgW positively regulates the activity of the alternative sigma factor AlgU, also known as AlgT or σ22 (Boucher et al., 1996). Downstream effects of

P. aeruginosa AlgU activation include induction of alginate biosynthesis (Qiu et al., 274

Figure A8-5: Motility-related phenotypes of transposon disruptants in the Pma

ES4326 gene algW.

(A) Swimming motility of wildtype bacteria and two independent algW transposon disruptants on low-agar King’s B (KB), minimal media plus citrate (MMC), and minimal media plus fructose (MMF). The bacteria contain either an empty pUCP20Tet vector (+

EV) or a version of this vector in which algW is expressed from its native promoter (+ algW). A nonmotile disruptant (flgF::mTn5) is included for comparison. Images were recorded after 48 hours of growth at 28ºC.

(B) Production of flagellin (FliC) protein in the algW disruptant. Bacteria were grown for 24 hours on plates comprised of minimal media (MM) containing either 10 mM citrate (C) or 10 mM fructose (F). Total bacterial proteins were then separated by SDS-

PAGE, transferred to a nitrocellulose membrane, and incubated with an anti-flagellin antibody (see Experimental Procedures). The band corresponding to FliC is indicated by an arrow. Ponceau staining of the membrane was used as a loading control.

275

Figure A8-6: Flagellin gene transcription in Pma ES4326 algW::mTn5 cultured in

TTSS-suppressing King’s B liquid media (KB) and TTSS-inducing minimal media containing 10 mM fructose (MMF).

Expression values were normalized with the housekeeping gene gyrB as described in

Experimental Procedures and reflect three technical replicates. Error bars represent standard deviation. Three independent experiments were performed with similar results.

276 2007) and repression of type III secretion (Wu et al., 2004). As such, we used qRT-

PCR to compare the expression of TTSS- and alginate-associated genes in wildtype

Pma ES4326 and the algW disruptant under TTSS-inducing conditions. Relative to wildtype bacteria, expression of the TTSS regulatory gene hrpL was 15-fold lower in

Pma ES4326 algW::mTn5, while the TTSS structural gene hrcU exhibited nearly six- fold lower expression (Figure A8-7A). Genes associated with alginate biosynthesis, algC and algD, were also transcribed at lower levels in Pma ES4326 algW::mTn5 than in wildtype bacteria (2.5- and 50-fold, respectively). Alginate gene expression in TTSS- suppressing rich media followed a similar pattern, albeit with less dramatic differences between the two Pma ES4326 genotypes (Figure A8-8). These observations were not the result of a general transcriptional repression because fliC was expressed more highly in Pma ES4326 algW::mTn5 than in wildtype (Figure A8-6) and expression of the housekeeping gene gyrB was not significantly altered by the disruption of algW (data not shown). We also extended these transcriptional observations to their phenotypic outputs of alginate production and TTSS activity. Alginate production was slightly reduced (nearly two-fold) in the algW disruptant relative to wildtype Pma ES4326 when grown on either MMF or rich media (Figures A8-7B and A8-8B). To evaluate TTSS activity, we inoculated an Arabidopsis ecotype (Eilenburg-0) in which Pma ES4326 induces a rapid programmed cell death response termed the hypersensitive response

(HR; Figures A8-7C,D). This HR is TTSS-dependent (Figures A8-7C,D) and thus provides a proxy readout of TTSS activity. In this ecotype, the HR induced by Pma

ES4326 algW::mTn5 was somewhat delayed relative to that induced by wildtype Pma

ES4326 (Figure A8-7C). We also measured ion leakage from tissues inoculated with these bacteria as an indicator of plant cell death (and in turn TTSS activity), and found that the algW disruptant stimulated less ion leakage than wildtype Pma ES4326 (Figure 277

278 Figure A8-7: Effects of algW disruption on alginate production and type III secretion in

Pma ES4326.

(A) Comparative transcriptional profiles for genes associated with alginate biosynthesis

(algC, algD) and type III secretion (hrpL, hrcU) in wildtype Pma ES4326 and algW::mTn5. Bacteria were cultured in minimal media containing fructose (MMF) for six hours prior to RNA extraction. Expression values were normalized with the housekeeping gene gyrB as described in Experimental Procedures and reflect three technical replicates. Error bars represent standard deviation. Three independent experiments were performed with similar results.

(B) Alginate production by wildtype Pma ES4326, algW::mTn5, and kinB::mTn5 on

MMF plates. Bacteria were collected from plates and alginate quantified as described in Experimental Procedures. Error bars represent standard deviation. Letters above data points indicate statistical significance groups as determined by pairwise Student’s t-tests (α=0.05). Three independent experiments were performed with similar results.

(C) Macroscopic symptoms following high-dose inoculation of Arabidopsis ecotype

Eilenburg-0 with Pma ES4326. Half of each leaf was inoculated with 5 x 107 cfu mL-1 wildtype Pma ES4326, hrcN::mTn5 (type III secretion-deficient), algW::mTn5, or 10 mM

MgCl2. Images were captured at 20 hours post-inoculation. Asterisks denote leaves exhibiting a hypersensitive response in the inoculated (left) side of the leaf.

(D) Ion leakage induced by Pma ES4326 in Arabidopsis ecotype Eilenburg-0. Leaves were inoculated with 2 x 106 cfu mL-1 wildtype Pma ES4326, hrcN::mTn5, algW::mTn5, or 10 mM MgCl2 and ion leakage measured as an increase in solution conductivity over time. Error bars represent standard deviation.

279

Figure A8-8: Pma ES4326 alginate-associated phenotypes in King’s B media.

(A) Expression of alginate biosynthetic genes in Pma ES4326 algW::mTn5 cultured in liquid media. Expression values were normalized with the housekeeping gene gyrB as described in Experimental Procedures and reflect three technical replicates. Error bars represent standard deviation. Three independent experiments were performed with similar results.

(B) Alginate production by wildtype Pma ES4326, algW::mTn5, and kinB::mTn5 on

King’s B plates. Bacteria were collected from plates and alginate quantified as described in Experimental Procedures. Error bars represent standard deviation.

Letters above data points indicate statistical significance groups as determined by pairwise Student’s t-tests (α=0.05). The two wildtype data points represent the same data displayed on different scales due to the dramatic differences in alginate production for the algW and kinB disruptants.

280 A7-7D). Pma ES4326 algW therefore positively regulates alginate production and

TTSS activity.

Further support for this regulation comes from the sensor kinase KinB, whose disruption results in elevated AlgW activity (Damron et al., 2009). In TTSS-suppressing media, Pma ES4326 kinB::mTn5 exhibited increased expression of alginate- and

TTSS-associated genes, as well as both transcriptional- and proteomic-level reductions in flagellin production (Figure A8-9). Massive increases in alginate production were also observed (Figures A8-7B and A8-8B).

AlgW is required for full virulence of Pma ES4326 on Arabidopsis

Given the positive role of algW in at least two virulence mechanisms, type III secretion and alginate biosynthesis, we hypothesized that the capability of Pma

ES4326 algW::mTn5 to suppress host defences would be compromised. We therefore examined the expression of two early defence signalling genes, NHL10 (NDR1/HIN1-

LIKE 10, also known as YLS9; At2g35980) and FRK1 (FLG22-INDUCED RECEPTOR

KINASE1; At2g19190), as well as the pathogenesis-related protein gene PR-1

(At2g14610), as reporters of Arabidopsis defence activation. In tissues inoculated with

Pma ES4326 algW::mTn5, all three defence genes were more strongly induced than in tissues inoculated with wildtype Pma ES4326 (Figure A8-10A). This increase was 9-,

19- and 3.6-fold for NHL10, FRK1 and PR-1, respectively. The enhanced defence gene expression was dramatically diminished by heterologous expression of algW in Pma

ES4326 algW::mTn5 (Figure A8-10A). Finally, we investigated the requirement of algW for in planta growth. The growth of the algW disruptant was significantly lower

(~1 log) in Arabidopsis compared to wildtype Pma ES4326 when assayed by either 281

282 Figure A8-9: Phenotypes associated with loss of the sensor kinase KinB, a negative regulator of AlgW.

(A) Transcriptional profile of Pma ES4326 kinB::mTn5 compared to wildtype. Bacteria were cultured in TTSS-suppressing liquid media (King’s B) for six hours prior to RNA extraction. Expression values were normalized with the housekeeping gene gyrB as described in Experimental Procedures and reflect three technical replicates. Error bars represent standard deviation.

(B) Flagellin protein production in Pma ES4326 kinB::mTn5. Total bacterial proteins from overnight plate cultures (King’s B media) were separated by SDS-PAGE, transferred to a nitrocellulose membrane, and incubated with an anti-flagellin antibody

(see Experimental Procedures). Ponceau staining of the membrane was used as a loading control.

(C) Mucoid growth exhibited by a kinB transposon disruptant (kinB::mTn5) relative to wildtype Pma ES4326, likely reflective of excessive alginate production. Bacteria were grown for 24 hours at 28oC on King’s B media.

All experiments were performed three times with similar results.

283

284 Figure A8-10: In planta phenotypes associated with the disruption of algW in Pma

ES4326.

(A) Defence gene induction in Arabidopsis. Leaves were inoculated by pressure infiltration with 1 x 108 cfu mL-1 suspensions of wildtype Pma ES4326, algW::mTn5, or algW::mTn5 containing a heterologous algW expression construct. Tissue samples were collected at zero and six hours post-inoculation (hpi) for RNA extraction. Data are depicted as ratios of gene expression relative to values from tissues inoculated with wildtype Pma ES4326 and reflect three technical replicates. Error bars represent standard deviation. Three independent experiments were performed with similar results.

(B-C) In planta growth of Pma ES4326. Plants were inoculated by pressure infiltration

(B) or spray inoculation (C) with bacteria at 1 x 105 cfu mL-1 or 4 x 108 cfu mL-1, respectively. Bacterial populations were quantified at zero (for pressure infiltration) and three days post-inoculation (dpi). Error bars represent standard deviation. Letters above data points indicate statistical significance groups as determined by pairwise

Student’s t-tests (α=0.05). Three independent experiments were performed with similar results.

285 pressure infiltration or spray inoculation (Figures A8-10B,C). This reduction in growth did not derive from general differences in bacterial growth rates because wildtype Pma

ES4326 and the algW disruptant grew similarly in MMF (Figure A8-11). In planta growth of the algW disruptant was restored to nearly wildtype levels by the introduction of an algW expression construct (Figures A8-10B,C). The development of chlorotic infection symptoms was also markedly reduced in plants inoculated with Pma ES4326 algW::mTn5, while the wildtype and algW complementation strains exhibited similar symptoms (Figure A8-12).

In Arabidopsis, flagellin proteins are detected by the FLS2 receptor, which subsequently activates basal immune responses (Felix et al., 1999; Gómez-Gómez et al., 1999). However, the in planta growth of Pma ES4326 algW::mTn5 was not altered in FLS2 knockout plants suggesting that deregulated flagellin production in the algW disruptant is not the primary cause of impaired Pma ES4326 virulence (Figures A8-

13A,B). Nevertheless, the growth reduction of Pma ES4326 algW::mTn5 was similar to that of the TTSS-deficient disruptant Pma ES4326 hrcN::mTn5 (Figure A8-13C) emphasizing the importance of AlgW for P. syringae virulence.

Discussion

A key element of successful pathogenesis is the capability to suppress or avoid host immune responses. Bacterial flagellin is a strong inducer of PAMP-triggered immunity and is a significant liability to P. syringae virulence in the apoplast, given that some flagellar mutants can grow better than their wildtype counterparts (Guo et al.,

2009; Kvitko et al., 2009; Li et al., 2005; Shimizu et al., 2003). We therefore hypothesized that flagella are dispensable for apoplastic growth of P. syringae. We 286

287 Figure A8-11: Growth of wildtype Pma ES4326 and an algW transposon disruptant

(algW::mTn5) in minimal media containing 10 mM fructose (MMF) (A) or King’s B media (B). Bacteria from King’s B media plates were resuspended in the appropriate

6 -1 media, adjusted to approximately 5 x 10 cfu mL (OD600 ≈ 0.01), and incubated with shaking at 28ºC. Aliquots were removed at regular intervals for quantification of viable cells by dilution plating. Error bars represent standard deviation. Three independent experiments were performed with similar results.

288

Figure A8-12: Pma ES4326 infection symptoms on Arabidopsis. The adaxial surface of Arabidopsis leaves was sprayed with 4 x 108 cfu mL-1 suspensions of wildtype Pma

ES4326, algW::mTn5, or algW::mTn5 containing a heterologous algW expression construct (+ algW). “+ EV” indicates the presence of an empty pUCP20Tet vector.

Images were recorded at three days post-inoculation and are representative of observations from at least three independent experiments.

289

290 Figure A8-13: Comparisons of in planta growth by Pma ES4326 algW::mTn5 and a

TTSS-deficient transposon disruptant (Pma ES4326 hrcN::mTn5). Plants were inoculated by pressure infiltration (A, C) or spray inoculation (B) with bacteria at 1 x 105 cfu mL-1 or 4 x 108 cfu mL-1, respectively. Bacterial populations were quantified at zero

(for pressure infiltration) and three days post-inoculation (dpi). Bacterial growth in plants lacking the flagellin receptor (“fls2”) was also examined (A, B). Error bars represent standard deviation. Letters above data points indicate statistical significance groups as determined by pairwise Student’s t-tests (α=0.05). Three independent experiments were performed with similar results.

291 used two nonmotile flagellar gene disruptants of Pma ES4326 to demonstrate that, although motility was important for complete virulence on spray-inoculated Arabidopsis leaves, this characteristic was dispensable for growth when bacteria were introduced directly into the apoplast of leaf tissue. This supports previous observations with the tobacco pathogen P. syringae pv. tabaci, where mutations that affect flagellin glycosylation or assembly, as well as deletions of flagellar structural genes, yield nonmotile bacteria whose in planta growth is significantly reduced when applied to the surface of tobacco leaves (Ichinose et al., 2003; Naito et al., 2008; Nguyen et al., 2009;

Taguchi et al., 2006). However, such impairments are much less evident when leaves are inoculated by pressure infiltration (Naito et al., 2008; Taguchi et al., 2006).

Admittedly, the spread of disease symptoms is reduced in nonmotile P. syringae pv. tabaci mutants when assayed by point inoculation of tobacco leaves (Ichinose et al.,

2003; Naito et al., 2008; Nguyen et al., 2009). When we inoculated portions of

Arabidopsis leaves with Pma ES4326, the spread of chlorosis from the inoculated area was minimal and very few bacteria were detected outside of this area. This discrepancy is likely due to differences between various host-pathogen combinations, as Godfrey et al. (2010) also noted minimal dispersal of P. syringae pv. phaseolicola in bean leaves. Overall, our observations reinforced the conclusion that flagella are not required for growth of Pma ES4326 in the Arabidopsis apoplast.

Given the apparent dispensability of flagella for apoplastic growth, we hypothesized the presence of a negative regulatory pathway in P. syringae to downregulate flagellar expression during the infection process. There is precedent for this type of regulation in other bacterial pathogens (Akerley et al., 1995; Cesbron et al.,

2006; Ellermeier and Slauch, 2003; Wolfgang et al., 2004) and transcriptomic analyses of P. syringae pv. tomato DC3000 demonstrated a slight downregulation of flagellar 292 genes in TTSS-inducing media (Lan et al., 2006). Similarly, upon exposure to MMF,

Pma ES4326 exhibited significant reductions in flagellin production at the transcriptional- and most remarkably at the proteomic-level. Through a forward genetic screen, we identified one of the components responsible for negative regulation of flagellar biosynthesis as an orthologue of the P. aeruginosa gene algW.

In P. aeruginosa, algW encodes a periplasmic DegS-like protease that controls the activity of the transcriptional regulator AlgU (Qiu et al., 2007; Wood et al., 2006).

When not required by the cell, AlgU remains sequestered at the plasma membrane by the transmembrane protein MucA, which in turn associates with AlgW in the periplasm.

Perturbations of the bacterial cell wall cause the unfolding of outer membrane proteins such as MucE, exposing specific peptide sequences that bind to and activate AlgW

(Cezairliyan and Sauer, 2009). Importantly, the components of the P. aeruginosa AlgW signalling pathway all have orthologues in Pma ES4326, indicative of similar mechanisms of AlgW activation (Qiu et al., 2007; D.S. Guttman, personal communication). Once activated, AlgW then cleaves MucA, liberating AlgU to activate gene expression. Consequently, AlgW functions as a sensor of extracellular stresses and coordinates downstream responses such as the production of alginate.

Alginate biosynthesis in P. aeruginosa is activated by heat shock, high osmolarity, ethanol-induced membrane perturbation, as well as antibiotics and detergents that compromise cell wall integrity (DeVault et al., 1990; Schurr et al., 1995;

Wood and Ohman, 2009; Zielinski et al., 1992). P. aeruginosa mutants that lack alginate are more sensitive to oxidative stress and exhibit reduced survival in macrophages and neutrophils (Martin et al., 1994; Yu et al., 1996). Alginate can facilitate infections by inhibiting phagocytosis, attenuating host defence responses and apoptotic activities, and enhancing resistance to antibiotics and reactive oxygen 293 species (Cobb et al., 2004; Pier et al., 2001; Simpson et al., 1988; Simpson et al.,

1989). In plants, alginate chelates calcium ions in order to suppress Ca2+-dependent plant defence responses (Aslam et al., 2008). Boch et al. (2002) noted that the alginate biosynthetic gene algA was induced in P. syringae when inoculated into

Arabidopsis leaves. Like P. aeruginosa, P. syringae alginate biosynthesis is stimulated by reactive oxygen species both in vitro and in planta (Keith and Bender,

1999; Keith et al., 2003). In addition, the epiphytic fitness of alginate-nonproducing strains is severely compromised, due in part to increased susceptibility to oxidative stress (Schenk et al., 2006; Yu et al., 1999). Alginate is therefore an important aspect of pseudomonad virulence that is regulated by AlgW.

We demonstrated that AlgW also positively regulates the TTSS in Pma ES4326.

In the current paradigm of TTSS activation, the two-component regulatory system

GacA/GacS responds to specific environmental cues by stimulating a series of transcription factors to induce TTSS genes (Tang et al., 2006). AlgW thus provides another input for this regulatory mechanism, likely integrating signals of extracellular stress. Such stresses may derive from host defence responses, which include the production of reactive oxygen species as well as antimicrobial compounds. AlgW may play an opposite role in P. aeruginosa TTSS regulation, since mutations that confer constitutive AlgU activity are associated with the suppression of TTSS genes (Wu et al., 2004). Although this difference may be due to gain-of-function phenotypes versus the loss-of-function phenotypes in this study, it may also reflect a difference in virulence strategies. The effector proteins of P. aeruginosa are generally cytotoxic, and some suppress host immune responses by killing phagocytic macrophages (Coburn and

Frank, 1999; Hauser and Engel, 1999). Constitutive AlgU activity leads to excessive alginate production, which provides enhanced protection from phagocytosis (Leid et al., 294 2005) and may negate the requirement for further effector secretion. Despite this difference both P. syringae and P. aeruginosa exhibit crosstalk between alginate biosynthesis and type III secretion that is regulated by AlgW. The exact mechanism through which this crosstalk occurs remains to be elucidated. In P. fluorescens, gacA disruptants are nonmucoid, mucA mutants are highly mucoid, and mucA gacA double mutants are also nonmucoid, suggesting that GacA acts downstream of the primary alginate regulatory proteins including AlgW (Schnider-Keel et al., 2001). It is interesting to speculate that GacA may also be downstream of AlgW in the regulation of the TTSS.

However, the loss of gacA does not affect algU gene expression in either P. fluorescens or Azotobacter vinelandii but does impair algD expression, albeit in a growth phase-dependent manner, highlighting the apparent complexity of the alginate regulatory system (Castañeda et al., 2001; Schnider-Keel et al., 2001).

In contrast to its positive regulatory role in expression of the TTSS and in alginate biosynthesis, AlgW mediates the downregulation of flagellin (FliC) expression in Pma ES4326 exposed to MMF. In P. aeruginosa, fliC transcription is also reduced by 80% after two hours of exposure to respiratory fluids from cystic fibrosis patients

(Wolfgang et al., 2004) and this repression was shown to be AlgU-dependent (Garrett et al., 1999). Furthermore, mucoid P. aeruginosa obtained from cystic fibrosis patients are typically aflagellate and nonmotile (Tart et al., 2006). This flagellar downregulation involves repression of the major flagellar regulatory gene fleQ by AlgU (Tart et al.,

2005). We were unable to detect a significant difference in fleQ gene expression between wildtype Pma ES4326 and the algW disruptant in MMF (data not shown).

This difference, however, would likely be very subtle, since the loss of AlgU in P. aeruginosa only results in a three-fold increase in fleQ gene expression (Tart et al.,

2005). We presume that loss of AlgW does not completely eliminate AlgU function 295 since there is still some expression of the AlgU-dependent gene algD (Figure A8-7).

This, in combination with potential post-transcriptional regulation of fleQ (Hickman and

Harwood, 2008), may render undetectable any AlgW-dependent effects on fleQ gene expression in Pma ES4326.

Interestingly, the TTSS regulators HrpL and HrpR/S have been demonstrated to negatively regulate flagellar expression in Erwinia amylovora and P. syringae pv. tomato DC3000, respectively (Cesbron et al., 2006; Lan et al., 2006). More recently,

HrpL and the TTSS structural subunit HrcC were shown to negatively regulate the motility of P. syringae pv. phaseolicola 1448A, suggestive of a negative regulatory role in flagellar function (Ortiz-Martín et al., 2010). If the TTSS also negatively regulates flagellar function in Pma ES4326, then upregulation of the TTSS by AlgW could provide a mechanism for the downregulation of flagellar abundance.

Conclusions

Overall, it is clear that AlgW regulates multiple virulence mechanisms in P. syringae (Figure A8-14). This type of control allows a pathogen to coordinate complex responses to various stimuli through the induction of virulence-promoting activities and the suppression of virulence liabilities. The mutation or loss of key regulators such as

AlgW in turn causes manifold virulence deficiencies. Consequently, the virulence of

Pma ES4326 algW::mTn5 is severely attenuated and host defence mechanisms can more effectively limit its in planta growth. This suggests that regulatory proteins such as AlgW could be effective targets for novel “anti-virulence” compounds. Inhibition of these proteins would affect numerous downstream processes associated with virulence and provide an advantage to the host immune system in dealing with an infection. The identification of additional regulatory proteins influenced by AlgW will provide greater insight into the coordinated events that underlie bacterial pathogenesis. 296

Figure A8-14: Model of AlgW activity in Pma ES4326. AlgW is activated by conditions that induce the type III secretion system (TTSS). Once activated, AlgW positively regulates alginate- and TTSS-associated gene expression, and negatively regulates flagellin abundance. Relevant genes whose expression was analyzed in this study are indicated in green. Genes shown in blue represent key mediators of specific bacterial virulence mechanisms: amrZ (Tart et al., 2006), hrpR/S (Hutcheson et al., 2001), and algU (Boucher et al., 1996; Schenk et al., 2006). The dashed line indicates that regulators of the TTSS that are upregulated by AlgW may negatively regulate flagellin abundance (see Discussion). The sensor kinase KinB negatively regulates AlgW activity.

297 Experimental Procedures

Bacterial strains and media

All bacterial strains used in this study are described in Table A8-1. Transposon disruptants were prepared by introducing a mini-Tn5 transposon (Alexeyev et al., 1995) into Pma ES4326 by triparental mating (Rainey et al., 1997) using pRK600 as a helper plasmid. All other plasmids were introduced by electroporation. P. syringae strains were grown at 28ºC on King’s B media (King et al., 1954) supplemented with the following antibiotics, where appropriate: 300 μg mL-1 streptomycin, 50 μg mL-1 kanamycin, and 10 μg mL-1 tetracycline. Pseudomonas minimal media (Huynh et al.,

1989) was supplemented with either 10 mM fructose (MMF) or 10 mM citrate (MMC).

The fliH and flgF transposon disruptants were identified by their nonmotile phenotypes in the motility screen (Figure A8-3A) and the kinB disruptant was identified by its mucoidy phenotype (Figure A8-9).

Cloning

All expression constructs were based on the broad host-range vector pUCP20

(West et al., 1994), which was modified to confer tetracycline resistance (pUCP20Tet;

P. Wang and D.S. Guttman, unpublished data). The open reading frame of Pma

ES4326 algW and 400 nt of upstream sequence were amplified from wildtype Pma

ES4326 genomic DNA by PCR using a 10:1 mixture of Taq:Pfu polymerase

(Fermentas Canada Inc., Burlington, ON, Canada) and the primers described in Table

298 Table A8-1: Bacterial strains used in this study

Strain Descriptiona Reference or Source

Pma ES4326 Wildtype Pseudomonas syringae pv. maculicola ES4326, StR D.S. Guttman

algW::mTn5 algW transposon disruptant, KnR, StR This study

algW transposon disruptant containing an expression construct algW::mTn5 +algW This study comprised of algW behind its native promoter, TeR KnR, StR

K.J. Schreiber and D. fliH::mTn5 fliH transposon disruptant, KnR, StR Desveaux, unpublished data

K.J. Schreiber and D. flgF::mTn5 flgF transposon disruptant, KnR, StR 299 Desveaux, unpublished data

K.J. Schreiber and D. kinB::mTn5 kinB transposon disruptant, KnR, StR Desveaux, unpublished data

K.J. Schreiber and D. hrcN::mTn5 hrcN transposon disruptant, KnR, StR Desveaux, unpublished data

Wildtype containing an expression construct comprised of fleQ +fleQ OE This study behind the lac promoter, TeR, StR

Wildtype containing an expression construct comprised of fleN +fleN OE This study behind the lac promoter, TeR, StR

F- φ80lacZΔM15 Δ(lacZYA-argF)U169 recA1 endA1 hsdR17(rk-, E. coli DH5α + - Invitrogen mk ) phoA supE44 thi-1 gyrA96 relA1 λ aSt = streptomycin, Kn = kanamycin, Te = tetracycline

A7-2. The amplicon was purified using a gel extraction kit (Bio Basic Inc., Markham,

ON, Canada) and used as the template in a second PCR to incorporate a hemagglutinin tag at the 3’ end of the gene. The amplicon was restriction-digested and ligated into the XbaI and EcoRI sites of pUCP20Tet, then verified by sequencing. The same procedure was used to prepare fleQ and fleN overexpression constructs except that the open reading frames of these genes were ligated into the EcoRI and XbaI sites of pUCP20Tet such that expression was driven by the lac promoter. Expression constructs were propagated in E. coli DH5α on Luria-Bertani media at 37ºC.

Bacterial motility assays

For high-throughput motility assays, sixty transposon disruptants were grown overnight at 28ºC on King’s B media. Bacteria were resuspended in minimal media lacking a carbon source in 96-well plates and diluted to OD600 ≈ 0.1. Two microlitres of this suspension were pipetted onto MMF containing 0.3% agar and motility was assessed after two days of growth at 28ºC. Sixty disruptants were evaluated on each motility plate and hypermotility was determined visually based on the average motility exhibited by bacteria on that plate. The phenotype of putative hypermotile disruptants was retested in additional assays using the same procedure, except that the bacteria were plated onto both MMF and King’s B. The genomic location of transposons in disruptants of interest was determined by vectorette PCR (Arnold and Hodgson, 1991).

Primers used in this study are described in Table A8-2.

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Table A8-2: Primers used in this study

Primer name Sequence • Cloning F(XbaI)-algW-prom GCTCTAGACCAGCAGGCTGATGTCGTGCTTG R-HA-algW-ORF GAACATCGTAAGGGTAGGCCTGCTCCGGCGCAGCAACCGGTGTC F(EcoRI)-FleQ GGAATTCATGTGGCGTGAAATCAAGATTCTG R-HA-fleQ-ORF GAACATCGTAAGGGTAGGCCTGATCCTCCGCCTGTTCGTCACCCTC F-(EcoRI)-FleN GGAATTCATGCATCCCGTACAGGTGATC R-HA-FleN-ORF GAACATCGTAAGGGTAGGCCTGTTGCACAGGCCCCGCACTGGTC R(XbaI)-HA GCTCTAGATCATGCGTAATCAGGAACATCGTAAGGGTA R(EcoRI)-HA GGAATTCTCATGCGTAATCAGGAACATCGTAAGGGTA • RT-qPCRa P. syringae gyrB_F(894) GACGCGTAACCTGAACAACTAC gyrB_R(1022) TTGTCCTTGGTCTGCGAACTGAA fliC_F(146) TAACGCAAACCAAGATCACTTC fliC_R(325) GACCTTCCGAGCTGTTACTGTC algC_F(1516) AGCCACAACCCGAAAGACTAC algC_R(1631) TGCGAAGTCAGGTTATTGGTC algD_F(945) AGTTGCACTGTTGGGTCTGAG algD_R(1077) TGCATATTCAACGTTGCTGTC hrpL_F(53) GTCCACTGGCATTCGGCAGTTGAC hrpL_R(219) GGTTTGCGGTTTACTGGCATGCTG hrcU_F(237) CTCGGTGTTGCTGAGCTTTAC hrcU_R(371) AACGGGTTGATCTTGTTGATG algW_F(346) GCTACATCCTGACCAATAACCAC algW_R(489) GTTTTTCAGGTCGATCTTCAACAC fleQ_F(752) GTTGCCGATGCAGGTCAAACTGTTG fleQ_R(899) CGAAAGCTGCCGATCTCGATCATG Arabidopsis Atef-1a_F(401) TGAGCACGCTCTTCTTGCTTTCA Atef-1a_R(477) GGTGGTGGCATCCATCTTGTTACA PR1_F(170) CTATGCTCGGAGCTACGCAGAAC PR1_R(279) GACGCCAGACAAGTCACCGCTAC AtNHL10_F(278) AGCCCTCACTGTTCCTGTCCGTAAC AtNHL10_R(402) TTGATAGAAAGGAGTTAACGTGATG AtFRK1_F(552) ACTACTTATGAGACTCCTTACGATG AtFRK1_R(741) GTAGCCATTGTTAAGAAATTGATC

aNumbers in parentheses indicate the nucleotide positions at which primers anneal within the open reading frame of a given gene.

301

Immunodetection of flagellin

Overnight plate cultures of P. syringae on King’s B media were suspended in minimal media lacking a carbon source and washed twice in this media by brief centrifugation and gentle resuspension. The final suspension was adjusted to OD600 =

15 (quantified using 1:10 dilutions) and 250 μL was plated onto MMF or MMC. After 24 hours of incubation at 28ºC, bacteria were resuspended in minimal media (no carbon source), and equivalent amounts of bacteria were recovered by centrifugation.

Seventy-five microlitres of SDS-PAGE loading buffer was added to each pellet and after boiling for five minutes, 15 μL was separated on 12% SDS-PAGE gels and blotted onto a nitrocellulose membrane (Bio-Rad Laboratories Ltd, Mississauga, ON, Canada).

Flagellin protein was detected with a polyclonal anti-FliC antibody (generously provided by Dr. Reuben Ramphal, University of Florida) used at a 1:50,000 dilution. Antibody binding was visualized with horseradish peroxidase-conjugated goat anti-rabbit IgG secondary antibody in combination with the ECL Western Blotting Detection System

(GE Healthcare, Baie d’Urfé, QC, Canada) and Kodak BIOMAX (Kodak, Rochester,

New York) X-ray films. While the anti-FliC antibody was raised against P. aeruginosa flagellin, we confirmed that P. syringae flagellin could also be detected with minimal background hybridization (Figure A8-15).

Transcriptional analyses

For analyses of gene expression in P. syringae, overnight cultures were subcultured in King’s B media and grown to OD600 = 0.8. Bacteria were recovered by

302

303

Figure A8-15: Specificity of an anti-flagellin antibody for flagellin from Pseudomonas syringae.

(A) Total protein from plate cultures of Pma ES4326 was separated by SDS-PAGE, transferred to a nitrocellulose membrane, and incubated with a polyclonal antibody raised against Pseudomonas aeruginosa flagellin (1:50,000 dilution) (see Experimental

Procedures). Antibody specificity was evaluated with Pma ES4326 containing an empty pUCP20Tet vector (EV) or pUCP20Tet-derived constructs for overexpression of

FleQ (FleQ OE) or FleN (FleN OE). FleQ and FleN are master regulators of flagellar biosynthesis with positive and negative regulatory functions, respectively (Dasgupta and Ramphal, 2001; Dasgupta et al., 2003). The molecular weight of Pma ES4326 flagellin is 29.4 kDa. Ponceau staining of the membrane was used as a loading control.

(B) Heterologous production of FleQ and FleN. Samples were prepared as in (A) except that the nitrocellulose membrane was incubated with an anti- hemagglutinin

(HA) tag antibody (1:30,000 dilution) to detect heterologous protein production. The molecular weights of FleQ and FleN, including the HA tag, are 56.7 and 30.7 kDa, respectively.

304 low-speed centrifugation (2,500 x g, 8 min) and resuspended in an equal volume of minimal media with no additional carbon source. Low-speed centrifugation and resuspension were repeated for a total of two washes with minimal media. The washed cells were then added to either King’s B or MMF at OD600 = 0.025 or 0.8, respectively, and incubated with shaking for six hours at 28ºC. After this incubation, both cultures were at OD600 ≈ 0.8, and RNA extractions were performed immediately using RiboPure-Bacteria reagents (Applied Biosystems, Streetsville, ON, Canada). All samples were DNaseI-treated prior to gene expression analysis. For analyses of defence gene expression in Arabidopsis, plants were inoculated by pressure infiltration

8 -1 with bacterial suspensions at 1 x 10 cfu mL (OD600 = 0.2) to ensure a synchronous host response (Truman et al., 2006). Tissues were collected immediately after inoculation and at six hours post-inoculation for extraction of RNA using TriPure reagent (BioShop Canada Inc., Burlington, ON, Canada). For both bacterial and plant samples, cDNA was generated from 1.5 μg of total RNA using Superscript II reverse transcriptase (Invitrogen Canada Inc., Burlington, ON, Canada) and the primers described in Table S2. Subsequent real-time quantitative PCR was performed with iQ

SYBR Green Supermix (Bio-Rad Laboratories Ltd) in conjunction with the iCycler iQ real-time PCR detection system (Bio-Rad Laboratories Ltd). Following PCR, melt- curve analysis was performed to confirm the specificity of the amplification reaction.

Relative transcript abundance was calculated using the ΔΔCt method (Livak and

Schmittgen, 2001), having verified similar amplification efficiencies for all primer sets.

P. syringae transcriptional data were normalized to the housekeeping gene gyrB, which exhibited no consistent deviations in expression between rich and minimal media, as also noted by Ortiz-Martín et al. (2010). The expression of a given gene relative to gyrB

305

is calculated as the difference in qPCR threshold cycles (ΔCt = Ctgene of interest - CtgyrB).

Comparisons between genotypes are calculated as the difference between ΔCt values

(ΔΔCt). Since one PCR cycle represents a two-fold difference in template abundance, fold change values are calculated as: 2-ΔΔCt.

Transmission electron microscopy

Plate cultures of wildtype Pma ES4326 were prepared as described in

Immunodetection of flagellin. After 24 hours of growth at 28ºC, approximately 100 μL of water was placed on the plate, and a formvar-coated 200-mesh copper grid (Electron

Microscopy Sciences, Hatfield, PA, USA) held on the surface of the drop for 10 sec.

The grid was then held upright for 1 min of settling, followed by 30 sec of drying, and 1 min of staining with 1% uranyl acetate. Specimens were observed with a Hitachi

H7000 TEM at 75 kV.

Bacterial TTSS activity assays and alginate quantification

We previously observed that Pma ES4326 elicits a hypersensitive response

(HR) in the Arabidopsis ecotype Eilenburg-0 (K.J. Schreiber and D. Desveaux, unpublished data). Macroscopic HR development was examined by infiltrating half of a leaf with a 5 x 107 cfu mL-1 bacterial suspension using a needleless syringe. Plants were kept under continuous light and HR symptoms recorded at 16-20 hours post- inoculation. To quantify HR-associated cell ion leakage, leaves were inoculated with bacterial suspensions at 2 x 106 cfu mL-1. For each replicate, four leaf discs (1.5 cm2)

306 were collected, incubated in distilled water for 45 min, then transferred to 6 mL of distilled water. Ion leakage was measured at regular intervals using an Orion 3 Star conductivity meter (Thermo Electron Corporation, Beverly, MA).

For quantification of bacterial alginate production, overnight plate cultures of P. syringae on King’s B media were suspended in minimal media lacking a carbon source and pelleted by brief centrifugation (30 sec at 12,000 rpm). Pellets were resuspended in minimal media and centrifuged again. This was repeated for a total of four washes, after which 250 μL of bacterial suspension (OD600 ≈ 35) was spread onto either MMF or

King’s B media. After six hours of incubation at 28ºC on MMF (or overnight on King’s

B), cells were scraped off the media and resuspended in 0.9% NaCl for alginate extraction and quantification as per May and Chakrabarty (1994).

Plant growth and inoculation procedures

The Columbia (Col-0) ecotype of Arabidopsis was used for all plant experiments.

A homozygous T-DNA insertion line (SALK_026801C) affecting the FLAGELLIN-

SENSITIVE 2 (FLS2) gene (At5g46330) was obtained from the Arabidopsis Biological

Resource Center. Seeds for soil-grown plants were placed on moist soil (ProMix BX,

Premier Horticulture Ltd., Dorval, PQ, Canada) amended with 20-20-20 fertilizer, stratified for four days at 4ºC, then placed in a growth room with a nine-hour photoperiod at 22ºC. Bacterial growth assays were performed on five- to six-week-old plants. For inoculation by pressure infiltration, bacterial suspensions were adjusted to

5 -1 1 x 10 cfu mL (OD600 = 0.0002) in 10 mM MgCl2 and introduced into the abaxial side of leaves using a needleless syringe. Spray inoculations were performed with a

8 -1 solution of 4 x 10 cfu mL bacteria (OD600 = 0.8) in 10 mM MgCl2 containing 0.02% 307

Silwet L-77 surfactant (GE Silicones, South Charleston, WV, USA). Inocula were sprayed on adaxial leaf surfaces to the point of runoff using a Preval aerosol sprayer

(Babco Sales Ltd, Surrey, BC, Canada). Plants were covered with a clear plastic dome for 24 hours after spraying in order to maintain conditions of high humidity. Bacterial growth within inoculated tissues was quantified as described previously (Katagiri et al.,

2002), although tissue samples from spray inoculations were surface-sterilized with

70% ethanol for 30 sec, then washed with sterile distilled water for 30 sec prior to this analysis.

Quantification of in planta bacterial growth following point inoculation

5 -1 Bacterial suspensions were adjusted to 1 x 10 cfu mL (OD600 = 0.0002) in 10 mM MgCl2 and infiltrated into the abaxial side of Arabidopsis leaves using a needleless syringe. Importantly, only the distal end of the leaf was inoculated so that approximately one-third of the leaf contained inoculum. The border of the inoculated area in each leaf was then denoted with a fine-tip marker. At five days post-inoculation, bacterial growth was quantified both within the inoculated area and in the uninoculated region, two millimetres away from the border drawn at the time of inoculation. Tissue samples were surface-sterilized with 70% ethanol for 30 sec, then washed with sterile distilled water for 30 sec prior to analysis. Bacterial populations were quantified as described previously (Katagiri et al., 2002).

308

Acknowledgements

We are grateful to Dr. Reuben Ramphal for his generous gift of anti-FliC antibody. We thank Dr. David Guttman for providing Pma ES4326 and plasmids for transposon mutagenesis and gene expression. We also thank Henry Hong and

Audrey Darabie for technical assistance with TEM and Dr. Jennifer Lewis and Brenden

Hurley for critical reading of the manuscript. We are grateful to anonymous reviewers for their insightful comments. K.S. was supported by the Natural Science and

Engineering Research Council (NSERC) of Canada. D.D. is a Canada Research Chair in Plant-Microbe Systems Biology. This work was supported by an NSERC Discovery

Grant and awards from the Canadian Foundation for Innovation and the Ontario

Ministry of Research and Innovation to D.D.

309

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Copyright Acknowledgements

Chapter 1 - Reprinted from: Schreiber, K. and Desveaux, D., 2008, Message in a bottle: Chemical biology of induced disease resistance in plants, Plant Pathology Journal 24:245-268.

Chapter 2 - Reprinted from: Schreiber, K., Ckurshumova, W., Peek, J., and Desveaux, D., 2008, A high-throughput chemical screen for resistance to Pseudomonas syringae in Arabidopsis, Plant Journal 54:522-531.

Chapter 3 - Reprinted from: Schreiber, K.J., Nasmith, C.G., Allard, G., Singh, J., Subramaniam, R., and Desveaux, D., 2011, Found in translation: High- throughput chemical screening in Arabidopsis thaliana identifies small molecules that reduce Fusarium head blight disease in wheat, Molecular Plant-Microbe Interactions 24:640-648.

Appendix 8 - Reprinted from: Schreiber, K.J. and Desveaux, D., 2011, AlgW regulates multiple Pseudomonas syringae virulence strategies, Molecular Microbiology 80:364-377.

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