Fungi and Cytokinins: Investigating the Impact Of

FUNGI AND CYTOKININS: INVESTIGATING THE IMPACT OF

CYTOKININS ON FUNGAL DEVELOPMENT AND DISEASE PROGRESSION

IN THE Ustilago maydis- Zea mays PATHOSYSTEM

A dissertation submitted to the Committee of Graduate Studies

in partial fulfillment of the requirements

for the degree of

Doctor of Philosophy

in the faculty of Arts and Science

Trent University

Peterborough, Ontario, Canada

Environmental & Life Sciences Ph. D. Graduate Program

May 2016

ABSTRACT

Fungi and Cytokinins:

Investigating the impact of cytokinins on fungal development and disease

progression in the Ustilago maydis- Zea mays pathosystem

Erin Nicole Morrison

Cytokinin biosynthesis in organisms aside from plant species has often been viewed as a byproduct of tRNA degradation. Recent evidence suggests that these tRNA degradation products may actually have a role in the development of these organisms, particularly fungi. This thesis examines the importance of cytokinins, a group of phytohormones involved in plant cell division and differentiation as well as the phytohormone abscisic acid, involved in plant response to environmental factors, and their presence and role in fungi.

An initial survey was conducted on 20 temperate forest fungi of differing nutritional modes. Using HPLC-ESI MS/MS, cytokinin and abscisic acid were detected in all fungi regardless of their mode of nutrition or phylogeny. The detection of the same seven CKs across all fungi suggested the existence of a common CK biosynthetic pathway and dominance of the tRNA pathway in fungi. Further, the corn smut fungus

Ustilago maydis is capable of producing CKs separate from its host and different U. maydis strains induce disease symptoms of differing severity. To determine if CK production during infection alters disease development a disease time course was conducted on cob tissue infected with U. maydis dikaryotic and solopathogenic strains.

Dramatic changes in phytohormones including an increase in ABA followed by increases in cisZCKs were detected in tumour tissue particularity in the more virulent dikaryon infection, suggesting a role for CKs in strain virulence. Mining of the U. maydis genome identified a sole tRNA-isopentenyltransferase, a key enzyme in CK biosynthesis.

Targeted gene deletion mutants were created in U. maydis which halted U. maydis CK production and decreased pathogenesis and virulence in seedling and cob infections. CK and ABA profiling carried out during disease development found that key changes in these hormones were not found in deletion mutant infections and cob tumour development was severely impaired. These findings suggested that U. maydis CK production is necessary for tumour development in this pathosystem. The research presented in this thesis highlights the importance of fungal CKs, outlines the dominant

CK pathway in fungi, identifies a key enzyme in U. maydis CK biosynthesis and reveals the necessity of CK production by U. maydis in the development of cob tumours.

KEYWORDS: Ustilago maydis, Zea mays, abscisic acid, cytokinins, fungi, high performance liquid chromatography-electrospray ionization tandem mass spectrometry, tRNA degradation pathway.

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PREFACE

This thesis is presented in manuscript format. Each chapter is either published or has been submitted for publishing. Co-authors and their contributions are listed in the preface of each chapter. Permission from copyright holders for each chapter is presented in Appendix I.

Additional publication not included in thesis

Morrison EN, Donaldson ME, Saville BJ. 2012. Identification and analysis of genes expressed in the Ustilago maydis dikaryon: uncovering a novel class of pathogenesis genes. Canadian Journal of Plant Pathology 34:417-435.

ACKNOWLEDGEMENTS

As all great stories go, a seemingly inconsequential switch to a plant biology course during my undergraduate studies put me on the path that has led me here today. There have been many people who have helped me along that path and I thank you all for your encouragement and support.

I would first like to thank my co-supervisors Dr. Neil Emery and Dr. Barry

Saville for giving me the opportunity to pursue combined research in their labs. You have both helped to shape me into the researcher I am today, and it has been an honour and a privilege to learn from and work with you both. I would also like to thank my committee member Dr. Jim Sutcliffe for his valued advice. Thank you to Linda

Cardwell, Mary-Lynn Scriver, Jane Rennie and Erin Davidson, for their much appreciated administrative direction over the years.

Thank you to the Emery and Saville labs and their members, both past and present. You are a ‘wonderfully-kooky’ bunch that have made my academic journey all the better. I would particularly like to thank Dr. Mike Donaldson. Your guidance, instruction, friendship and encouragement helped me grow as a researcher. Special thanks to my office mates Colleen Doyle and Kitty Cheung for your support and help over the years.

Thank you to my family and friends for your continued presence, encouragement, and prayers. Specifically, thank you to my parents Grant and Debra Morrison, who have inspired, directed, supported, and prayed me through this chapter of my life, as well as the ones that came before. Without your love and support, this road would have looked

v very different. To my sister Lizzy I thank you for being such an amazing sister and best friend. Thank you for always being there for me. Thank you to Dustin Bowers, your love and support has helped me through. Also, I think people would be disappointed if I did not mention the cups that fill my recycling bin and the fuel that started my days: Tim

Horton's tea (I will be buying shares in the company soon).

Importantly, I thank my Lord and Saviour Jesus Christ who has seen me through this and taught me many things along the way. When I am weak, He is strong.

Finally, thank you to Trent University as a whole. It is here where I was given the space to grow and learn not only as a scientist but also as a person. I have been truly blessed.

TABLE OF CONTENTS

PAGE

TITLE PAGE i

ABSTRACT ii

KEYWORDS iii

PREFACE iv

ACKNOWLEDGEMENTS v

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xiii

CHAPTER 1 General Introduction. ABSCISIC ACID 1 CYTOKININS 3 tRNA MODIFICATION 5 FUNGAL PLANT-PATHOGENS AND PHYTOHORMONES 6 USTILAGO MAYDIS 8 RESEARCH OBJECTIVES 10 FIGURES 13 REFERENCES 15

CHAPTER 2 Detection of phytohormones in temperate forest fungi predicts consistent abscisic acid production and a common pathway for cytokinin biosynthesis.

PREFACE 20 ABSTRACT 21 INTRODUCTION 22 MATERIALS AND METHODS 25 RESULTS 29 DISCUSSION 32 TABLES AND FIGURES 42 SUPPLEMENTARY MATERIAL 47 ACKNOWLEDGEMENTS 48

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REFERENCES 49

CHAPTER 3 Phytohormone involvement in the Ustilago maydis– Zea mays pathosystem: relationships between abscisic acid and cytokinin levels and strain virulence in infected cob tissue.

PREFACE 55 ABSTRACT 56 INTRODUCTION 58 MATERIALS AND METHODS 60 RESULTS 67 DISCUSSION 72 CONCLUSIONS 82 TABLES AND FIGURES 84 SUPPLEMENTARY MATERIAL 95 ACKNOWLEDGEMENTS 96 REFERENCES 97

CHAPTER 4 Interplay between fungal and plant derived cytokinins is necessary for normal Ustilago maydis infection of corn.

PREFACE 103 ABSTRACT 104 INTRODUCTION 106 MATERIALS AND METHODS 110 RESULTS 122 DISCUSSION 131 CONCLUSIONS 139 TABLES AND FIGURES 141 SUPPLEMENTARY MATERIAL 154 ACKNOWLEDGEMENTS 180 REFERENCES 181

CHAPTER 5 General discussion.

INTRODUCTION 188 PHYTOHORMONE DETECTION IN FOREST FUNGI 189 PHYTOHORMONES AND DISEASE DEVELOPMENT 190 CONTROL OF CK BIOSYNTHESIS IN U. MAYDIS 192 FURTHER CHARACTERIZATION OF tRNA-IPT 194 THE ROLE OF CKS AT DIFFERENT FUNGAL LIFESTAGES 195 PLANT AND PATHOGEN GENE EXPRESSION 196 ABA AND CK INTERACTION 198 CONCLUSIONS 200 FIGURES 201 REFERENCES 203

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APPENDIX I Permission from copyright holders.

CHAPTER 2 206 CHAPTER 3 208

LIST OF TABLES

PAGE

Table 2.1. Fungi used in this study. 42

Table 3.1. Tissue sampling for phytohormone analysis. 84

Table 3.2. Cytokinin concentrations (pmol g -1 FW) in mock-infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 85

Table 3.3. Cytokinin concentrations (pmol g -1 FW) in U. maydis dikaryon infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 86

Table 3.4. Cytokinin concentrations (pmol g -1 FW) in U. maydis solopathogen infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 87

Table 4.1. Cytokinin concentrations (pmol g -1 FW) for SG200 filamentous tissue grown on minimal medium (CK negative) and double complete medium (CK positive). 141

Table 4.2. Cytokinin concentrations (pmol g -1 FW) in mock-infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 142

Table 4.3. Cytokinin concentrations (pmol g -1 FW) in SG200∆ipt1 infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 143

Table 4.4. Cytokinin concentrations (pmol g -1 FW) in SG200 infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. 144

Table 4.5. Putative candidate CK signaling and biosynthesis orthologs identified in U. maydis through blastp analysis and reciprocal best blast hits. 145

LIST OF FIGURES

PAGE

Fig. 1.1. CK biosynthesis pathway. 13

Fig. 1.2. Ustilago maydis life cycle. 14

Fig. 2.1. Abscisic acid concentration (pmol g-1 FW) in ectomycorrhizal, wood-rot and saprotrophic fungi. 43

Fig. 2.2. Total cytokinin concentration (pmol g-1 FW) in ectomycorrhizal, wood-rot and saprotrophic fungi. 44

Fig. 2.3. Cytokinin types (A) isopentenyl CKs (iPRP, iPR and iP), (B) cis-zeatin CKs (cisZRP and cisZR) and (C) methylthiol CKs (2MeSZR and 2MeSZ) reported as percentage of total cytokinin in ectomycorrhizal, wood-rot and saprotrophic fungi. 45

Fig. 2.4. Proposed tRNA degradation pathway. 46

Fig. 3.1. Representative time course of disease progression for Zea mays- U. maydis cob assay. 88

Fig. 3.2. Abscisic acid concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). 89

Fig. 3.3. Representative CK structures for analytes detected/scanned for, in the Zea mays- U. maydis cob assay time course. 90

Fig. 3.4. Total CK glucoside concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). 92

Fig. 3.5. Total methylthiol CK concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). 93

Fig. 3.6. Total FBRNT CK concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). 94

Fig. 4.1. Radial unrooted phylogenetic tree of IPT proteins. 146

Fig. 4.2. Disease symptoms for U. maydis infected corn seedlings at 7, 14 and 21 days post infection (dpi). 147

Fig. 4.3. Representative time course of disease progression for Z. mays- U. maydis cob infection assay. 148

Fig. 4.4. Abscisic acid concentration (pmol g-1 FW) for mock-infected control, SG200∆ipt1 and SG200 injected cob tissue at specific days post infection (dpi). 149

Fig. 4.5. CK groups: CK glucosides (DHZOG, DHZROG, DHZ9G, transZOG, transZROG, trans/cisZ9G, cisZOG, and cisZROG), methylthiol CKs (2MeZR, 2MeSZ, 2MeSiPR, and 2MeSiP) and FBRNTs (iP, iPR, iPRP, DHZ, DHZR, DHZRP, transZ, transZR, transZRP, cisZ, cisZR, and cisZRP), reported as a percentage of the total cytokinins detected in each treatment type at specific days post infection (dpi). 150

Fig. 4.6. cisZCK FBRNT concentration (pmol g-1 FW) for mock-infected control, SG200∆ipt1 and SG200 injected cob tissue at specific days post infection (dpi). 151

Fig. 4.7. Proposed U. maydis CK biosynthetic pathway. 152

Fig. 4.8. Model of cytokinin involvement in tumour development in the Ustilago maydis – Zea mays pathosystem. 153

Fig. 5.1. Proposed U. maydis MVA pathway leading to CK and ABA biosynthesis. 201

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LIST OF ABBREVIATIONS

∆ gene deletion µg microgram µL microliter µm micrometer ß beta 2MeS methylthiol 2MeSCKs 2MeSZ+2MeSZR 2MeSiP N6- (∆2-isopentenyl) adenine-2-methylthio 2MeSiPR N6- (∆2-isopentenyl) adenine-2-methylthio, 9-riboside 2MeSZ zeatin-2-methylthio 2MeSZR zeatin-2-methylthio, 9-riboside aa amino acid ABA abscisic acid AM/D/TP adenine- mono, di-, tri- phosphate ANOVA analysis of variance BA N6-benzyladenine BAR N6-benzyladenine-9-riboside BLAST basic local alignment search tool blastp search protein database using a protein query C celcius CD conserved domain CHASE cyclases/histidine kinases associated sensor extracellular cisZ cis-zeatin cisZCKs cisZRP+ cisZR+ cisZ cisZR cis-zeatin-9-riboside cisZRP cis-zeatin-9-riboside-5’-mono, di-, tri- phosphate CK cytokinin CK forms free base, riboside, nucleotide CK types transCKs, cisCKs, iPCKs, 2MeSCKs, CK glucosides, DHZCKs CKX cytokinin oxidase cm centimeter CM complete medium DCM double complete medium dH2O deionized water DHRMP dihydrozeatin-9-riboside-5’-monophosphate DHZ dihydrozeatin DHZR dihydrozeatin-9-riboside DHZRP dihydrozeatin-9-riboside-5’-mono, di-, tri- phosphate D.I. disease index DIG digoxigenin DMAPP dimethylallyl-pyrophosphate DOXP deoxy-xylulose phosphate dpi days post infection

xiii

DW dry weight E expect threshold EC enzyme commission number ESI electrospray ionization ex. for example F forward FB free base FBRNT free base, riboside, nucleotide FW fresh weight g units of gravity g gram GC-MS gas chromatography- mass spectrometry h hour HK histidine kinase HMBDP hydroxymethylbutenyl diphosphate HPLC high performance liquid chromatography HPLC-ELISA high performance liquid chromatography- enzyme linked immunoassay HPLC-ESI MS/MS high performance liquid chromatography- electrospray ionization tandem mass spectrometry i.e. in other words iP N6- (∆2-isopentenyl) adenine/isopentenyladenine iPCKs iPRP+ iPR+ iP iPP isopentenyl-pyrophosphate iPR N6- (∆2-isopentenyl) adenine-9-riboside iPRP N6- (∆2-isopentenyl) adenine-9-riboside-5’-mono, di-, tri- phosphate IPT isopentenyltransferase kb kilobase Kin N6 –furfuryladenine (kinetin) LB Luria-Bertani LC-MS liquid chromatography- mass spectrometry LOG lonely guy M molar MCX mixed mode, reverse-phase, cation-exchange MEP methylerythritol phosphate MIPS Munich Information Center for Protein Sequences mL milliliter mm micrometer mM millimolar MM minimal medium MRM multiple reaction monitoring MS mass spectrometer MUMDB MIPS Ustilago maydis database MVA mevalonate mZ mega hertz

xiv n/N sample number N nitrogen N/A not applicable/not available NCBI National Center for Biotechnology Information ng nanogram NT nucleotide OD optical density PCR polymerase chain reaction pmol picomole R reverse R riboside RH relative humidity RIA radioimmuoassay rpm revolutions per minute RT room temperature RT-PCR reverse transcriptase- PCR SA salicylic acid sdH2O sterile deionized water SE standard error sp. species SPE solid phase extraction TCS two component system transZ trans-zeatin transZR trans-zeatin-9-riboside transZRP trans-zeatin-9-riboside-5’-mono, di-, tri- phosphate transZRMP trans-zeatin-9-riboside-5’-monophosphate tRNA transfer RNA U Uracil v volume vs. versus v/v volume per volume w weight w/v weight per volume YEPS yeast extract, peptone, sucrose Z zeatin Z9G zeatin-N(9)-glucoside ZOG zeatin-O-glucoside ZR zeatin-9-riboside

CHAPTER 1

GENERAL INTRODUCTION

Phytohormones are traditionally viewed as plant produced compounds that occur at minute levels (<10-8M; Hoyerová et al., 2006) and function in complex networks of signaling interactions that impact the growth and development of plants (El-Showk et al.,

2013). While the vast majority of phytohormone studies have investigated production by, and action in plants, current research is highlighting the importance of these compounds in other systems including fungi, and their role in plant-microbe interactions (Nambara and Marion-Poll 2005, reviewed in Tsavkelova et al., 2006, Walters and McRoberts

2006, Hartung 2010, reviewed in Stirk and van Staden 2010, Frébort et al., 2011, Spichal

2012). While some phytohormones, such as jasmonic acid and salicylic acid, are often associated with plant response to pathogen attack, increasing attention has been placed on abscisic acid (ABA) and cytokinins (CK) and their role in plant-pathogen interactions.

Notable in these studies has been the discovery that these phytohormones are produced by the pathogens themselves. The connection between pathogen-produced phytohormones and phytohormone changes during plant-pathogen interactions is the focus of this thesis.

ABSCISIC ACID

The phytohormone ABA aids in the initiation of plant responses to environmental change and plays a role in seed maturation and dormancy (Mauch-Mani and Mauch 2005,

Nambara and Marion-Poll 2005).

Isoprenoid biosynthesis, which provides precursor compounds for ABA biosynthesis, can be separated into two pathways the deoxy-xylulose phosphate (DOXP) or methylerythritolphosphate (MEP) pathway and the mevalonate (MVA) pathway

(Oritani and Kiyota 2003, Nambara and Marion-Poll 2005, Finkelstein 2013). The compound farnesyl pyrophosphate acts as a multiple branch point in isoprenoid biosynthesis for several terpenoids including carotenoids (Wang et al., 2014). Plants and fungi have distinct routes for ABA biosynthesis. Plant ABA biosynthesis follows an indirect route through the enzymatic cleavage of carotenoids from the DOXP pathway

(Oritani and Kiyota 2003, Finkelstein 2013) whereas fungal ABA biosynthesis is synthesized directly from farnesyl pyrophosphate from the MVA pathway (Oritani and

Kiyota 2003, Finkelstein 2013). The convergent molecules for plant and fungal ABA biosynthesis are found early in biosynthesis however the pathways generating the precursors and steps following farnesyl pyrophosphate synthesis diverge into the direct and carotenoid pathway, both eventually resulting in ABA synthesis (Oritani and Kiyota

2003). While there has been suggestion of a carotenoid pathway in fungi most consider the MVA pathway the most common for fungal ABA production (Nambara and Marion-

Poll 2005).

ABA has been detected in many organisms including moss, algae and fungi, and while ABA has been detected in the saprotrophic fungi Agrocybe praecox and Coprinus domesticus (Crocoll et al., 1991), as well as phytopathogenic fungi including Cercospora rosicola, Cercospora cruenta, Cercospora pini-densiflorae, Botrytis cinerea,

Ceratocystis coerulescens, and Ustilago maydis (Kettner and Dörffling 1987, Crocoll et al., 1991, Nambara and Marion-Poll 2005, Bruce et al., 2011), no clear role for ABA has

3 been determined in fungi. The study of ABA in plant-pathogen interactions has often produced contrasting results (Ton et al., 2009). In some cases increases in ABA can stimulate callose deposition providing a degree of resistance for the plant to pathogen attack as in some viral-plant interactions (reviewed in Mauch-Mani and Mauch 2005); however, in other cases, ABA acts to stimulate host susceptibility to pathogen attack as in the infection of tomato plants by Botrytis cinerea (Audenaert et al., 2002), or infection of rice by Magnaporthe grisea (Jiang et al., 2010). ABA stimulates different responses depending on the pathosystem and therefore must be examined within the context of each system.

CYTOKININS

Another phytohormone group often associated with plant-pathogen interactions is cytokinins. Cytokinins are known to play a pivotal role in plant cell division (Sakakibara

2006), and are often found in actively dividing plant tissues. Changes to CK levels have been associated with pathogen infection of plants and increased accumulation of this phytohormone is thought to promote pathogen establishment and development (Walters and McRoberts 2006, reviewed in Stirk and van Staden 2010). Although typically classified as a plant hormone, free and tRNA-bound cytokinins have been detected in: humans, nematodes, insects, bacteria and symbiotic and pathogenic fungi (Walters and

McRoberts 2006, reviewed in Stirk and van Staden 2010).

Cytokinin levels are controlled through the balance of: biosynthesis, interconversion (between different CK forms), transport /diffusion and degradation

(Miyawaki et al., 2004). Changes to any of these processes can result in abnormal phenotypic responses by the plant.

Cytokinins are adenine derivatives which carry an isoprene-derived or aromatic side chain. The isoprenoid CKs are more frequently found in plants (Sakakibara 2006).

CK biosynthesis is often divided into two main pathways: the methylerythritol phosphate

(MEP) or de novo pathway from which isopentenyladenine (iP) and trans-zeatin (transZ) type CKs predominantly originate, and the mevalonate (MVA) or tRNA degradation pathway, which is the widely accepted source of cis-zeatin (cisZ) CKs (Hwang and

Sakakibara 2006, Sakakibara 2006). Cytokinins can be divided into various forms based on their chemical structure (Sakakibara 2006). The precursor forms are referred to as nucleotides followed by the intermediate and biologically active riboside, as well as the most active free base form (Sakakibara 2006). Based on the side chain modification these forms can be further separated into CK types which include iP, trans or cis-zeatin and dihydrozeatin (DHZ; Fig. 1.1). The ability to detect and distinguish between these different types and forms provides information about the dominance of either the de novo or tRNA degradation pathway (Sakakibara 2006).

The first step in isoprenoid CK biosynthesis is catalyzed by isopentenyltransferase

(IPT). The de novo pathway involves the transfer of an isopentenyl sidechain derived from either dimethyallyl pyrophosphate (DMAPP) or hydroxymethylbutenyl diphosphate

(HMBDP) to an adenosine from ATP, ADP or AMP, this reaction is catalyzed by adenosine phosphate-isopentenyltransferase (Hwang and Sakakibara 2006; Fig. 1.1). In the tRNA degradation pathway the transfer of an isopentenyl sidechain is catalyzed by tRNA-isopentenyltransferase (tRNA-IPT) and is transferred to a tRNA molecule. tRNA

5 degradation has often been overlooked as a major contributor to the overall CK pool but with evidence suggesting cisZ CK dominance in certain plant species and its detection in other organisms including fungi, this pathway is becoming an area of interest for phytohormone research (Emery et al., 1998, Golovko et al., 2002, Sakakibara 2006,

Frébort et al., 2011, Gajdosova et al., 2011).

tRNA MODIFICATION

Degradation of specifically modified tRNA molecules is the accepted source for cisZCKs. These tRNA modifications can enhance and optimize the role of tRNA in translation by increasing the efficiency and fidelity of the anticodon-codon interaction

(Persson et al., 1994, Yarian et al., 2002). Most organisms contain a modified adenine, referred to as a cytokinin, situated next to the anticodon at position 37 on certain tRNAs that bind to most codons starting with U (Durand et al., 1997, Golovko et al., 2000,

Golovko et al., 2002). A large diversity of modified nucleosides have been noted at this position in the tRNA of many organisms including eukaryotes, and bacteria but not

Archaea (Persson et al., 1994, Yarian et al., 2002). Further modifications can include methylthiolation or hydroxylation, of the adenine, which further influences translational efficiency and fidelity (Golovko et al., 2000). In bacterial analysis it has been noted that cis-zeatin riboside and methylthiolzeatin are released during tRNA degradation (Koenig et al., 2002). While tRNA modification has mostly been studied for its influence on translation, the abundant presence of cisZ CKs detected in plant-pathogen interactions including maize leaf infection by Colletotrichum graminicola, corn seedling infection by

Ustilago maydis, and Arabidopsis thaliana infection by the bacterium Rhodococcus

6 fascians (Pertry et al., 2009, Bruce et al., 2011, Behr et al., 2012) makes this pathway a key area of study for understanding the importance of CKs in host manipulation by pathogens.

FUNGAL PLANT-PATHOGENS AND PHYTOHORMONES

Plant-pathogens have developed various strategies to invade, feed on, and reproduce within their host (Berger et al., 2007). For the purposes of this thesis, focus will be placed on fungal plant-pathogens. Fungal plant-pathogens can be subdivided based on their mode of nutrient acquisition into necrotrophs, biotrophs and hemibiotrophs.

Necrotrophic fungi like Botrytis cinerea (which causes grey mould attacking more than

200 different plant species) obtains nutrients by destroying host tissue (Govrin and

Levine 2000). By contrast, biotrophic fungi require living tissue for growth and reproduction (Berger et al., 2007). This can be seen in the rust fungi such as Puccinia triticina, the cause of wheat leaf rust, and the smut fungus Ustilago maydis, the causal agent of corn smut, which are both dependent on a living host for completion of their lifecycle (Hu et al., 2007). Hemibiotrophs, like Venturia inaequalis (the causative agent of apple scab) and Pyrenopeziza brassicae (the cause of light leaf spot disease of

Brassica sp.); exhibit both biotrophic and necrotrophic modes of nutrition during their lifecycle (Majer et al., 1998, Ashby 2000). The ability of biotrophic and hemibiotrophic fungi to maintain a close physiological relationship with their host plant without causing devastating tissue damage is critical for the maintained growth and development of the fungus (Ashby 2000). The reallocation of nutrients towards sites of infection and creation of nutrient sinks as well as phenotypic changes to host morphology, specifically

7 at sites of pathogen infection, are often influenced by alterations in phytohormone levels

(Ashby 2000). For example, a well-studied model for plant-pathogen interactions is the relationship between the crown gall forming bacterium Agrobacterium tumefaciens and one of its hosts, Arabidopsis thaliana (Jameson 2000). Upon infection, bacterial biosynthetic genes for cytokinin and auxin are integrated into the plant nuclear genome; this modifies the synthesis of auxin and CK and, this elevated synthesis is essential for tumourgenesis (Sakakibara et al., 2005).

The role of CKs in biotrophic fungal infection is poorly defined, although recent analysis by Hinsch et al. (2015) shed light on the role of fungal derived CKs in the

Claviceps purpurea: rye interaction. Clearly more information on different systems is necessary as each pathogen-host interaction is affected by the ability of the plant to respond to signals produced or triggered by the pathogen. Symptoms of pathogen infection such as tumours, green island formation, galls and growth malformations are unique to each plant-pathogen interaction however they often reflect alterations in the plant hormones auxin and CK (Jameson 2000).

Elevated levels of CKs have been observed in galls formed during infection of

Zizania latifolia by the smut fungus Ustilago esculenta (Lin and Lin 1990). Furthermore, the smut fungus Ustilago maydis produces CKs separate from its host plant and elevated levels of CKs have been detected in the tumour tissue of U. maydis infected maize seedlings (Mills and Van Staden 1978, Bruce et al., 2011). Another growth promoting phytohormone, auxin, has been thoroughly examined in U. maydis and deletion mutants created (Basse et al., 1996, Doehlemann et al., 2008a, Reineke et al., 2008, Zuther et al.,

2008). Tumour formation in infected corn plants was not affected when mutant strains

8 impaired in auxin production were used (Basse et al., 1996, Reineke et al., 2008), suggesting that auxin production by U. maydis is not necessary for triggering tumour formation (Bölker et al., 2008). While auxin has been examined in U. maydis, the production of CKs by U. maydis and its impact on pathogenic development has not been thoroughly studied, even though current evidence suggests that CKs influence tumour development during infection. Commonly, infection by biotrophic fungi causes reduced plant photosynthetic rates and nutrient mobilization toward the site of infection resulting in the formation of a nutrient sink; all of which can be mimicked through exogenous CK application (Walters and McRoberts 2006). Reduced photosynthetic rates, the inability to switch from sink to source leaves resulting in the maintenance of sinks (Horst et al.,

2008), elevated levels of total soluble sugars, and increased nitrogen accumulation in infected tumours (Horst et al., 2010) have all been associated with the interaction between U. maydis and Zea mays; however, to date, no link between CKs and these symptoms has been drawn. Investigating CKs’ role in the U. maydis- Zea mays pathosystem is a main focus of the research presented in this thesis.

USTILAGO MAYDIS

Ustilago maydis is the causative agent of common smut of corn. Tumour formation on aerial portions of the plant is a hallmark of this disease (Kämper et al., 2006). It is thought that the release of fungal effectors by U. maydis initiates host cell differentiation and that tumour expansion is likely dependant on plant hormones (Walbot and Skibbe

2010). Accumulation of CKs in this pathosystem has been detected in both seedling and cob infected tissues (Bruce et al., 2011, Morrison et al., 2015). The nonpathogenic yeast

9 like haploid cells of U. maydis divide by budding and are easily grown on artificial medium in the lab. This cell type can be altered by gene replacement to generate mutants

(Bölker et al., 1995). On the plant surface, fusion of compatible haploid cells (mating) results in the formation of a pathogenic dikaryon (Kahmann and Kämper 2004). This cell fusion and filamentous dikaryon formation can be forced in the laboratory through growth on solid medium containing charcoal (Day and Anagnostakis 1971, Bölker et al.,

1995). The pathogenic dikaryon invades the plant through natural openings such as stomata, silks of the corn ear or direct penetration (Banuett and Herskowitz 1996,

Martínez-Espinoza et al., 2002, Kämper et al., 2006; Fig. 1.2). During penetration

(facilitated by the formation of a special cell type termed an appressorium) the plasma membrane of the infected plant cell surrounds the penetrating hyphae (Doehlemann et al.,

2008b), forming a biotrophic interface. This close interaction between the plant and pathogen allows for the transfer of nutrients and various assimilates (Horst et al., 2010).

Rapid unbranched growth of the hyphae occurs, followed by profuse branching within and between plant cells which corresponds to the beginning of tumour development

(Kahmann and Kämper 2004, Perez-Martin et al., 2006). Tumour formation is accompanied by massive fungal proliferation, followed by nuclear fusion and fragmentation of hyphae, leading to the formation of diploid teliospores which act as the dispersal agent for the fungus (Banuett and Herskowitz 1989, Basse and Steinberg 2004,

Kämper et al., 2006). The pathogenic lifecycle of U. maydis can be completed within 21 days, following its injection into corn, allowing the impact of genetic manipulation on fungal pathogenesis and development to be rapidly assessed.

Cytokinin and ABA accumulation in the U. maydis- Zea mays pathosystem has been associated with tumour formation (Bruce et al., 2011). U. maydis is capable of producing CKs and ABA separate from the plant (Mills and Van Staden 1978, Bruce et al., 2011) making the contribution of phytohormones from the plant and fungus hard to decipher. U. maydis can be readily manipulated in the lab and has well established protocols for genetic analysis and molecular manipulation including homologous gene replacement (Basse and Steinberg 2004), and is amenable to phytohormone extraction

(Bruce et al., 2011) making it an ideal system for examining how fungal infection alters the CK balance in a plant-pathogen interaction and how fungal CK production is controlled.

RESEARCH OBJECTIVES

At the onset of research presented in this thesis very little was known about cytokinin production among fungi. While some fungi were capable of producing plant hormones separate from their host plant, key questions remained: How widespread was this production? And was it restricted to pathogens and/or symbionts? The overall objective of this thesis was to examine the importance of CKs and ABA in the development of fungi, with specific focus on Ustilago maydis. This thesis is presented as a compilation of three manuscripts, each representing a single chapter; followed by a general discussion in which the overall findings and future directions are discussed.

The research objectives of this thesis were to: 1. Assess the prevalence of cytokinins among a variety of fungi independent of host interaction and 2. Determine how fungal infection impacts phytohormone balance within a host plant. To achieve

11 these goals, phytohormone profiles were generated from 20 temperate forest fungi

(Chapter 2) as well as the solopathogenic strain of U. maydis (Chapter 4). These profiles were used to generate a proposed active CK pathway in fungi (Chapters 2 and 4). U. maydis strains of differing virulence were used in cob infection time course analysis to evaluate the connection between the severity of infection symptoms and CK levels

(Chapter 3). A challenge to working with plant-pathogen systems is separating the phytohormone contribution of the pathogen and the plant from each other. The dominance of CK products from the tRNA degradation pathway lead to targeted U. maydis gene deletion of the rate limiting enzyme in this pathway (Chapter 4). In doing so this eliminated CK production by U. maydis and permitted the balance of CKs by the pathogen and plant to be compared.

Chapter 2 presents an environmental screen of 20 basidiomycete forest fungi with differing modes of nutrient acquisition. The screen was conducted to determine whether

CKs and ABA were present in field-collected fruiting bodies of 20 temperate forest fungi and whether CK and ABA profiles vary among these fungi with differing modes of nutrient acquisition. Screening of these fungi revealed the widespread presence of ABA and CKs in the fungi sampled independent of their mode of nutrient acquisition or phylogenetic relation. CK profiles revealed the dominance of CK products from the tRNA degradation pathway which led to the development of a fungal specific CK pathway which was the first to be published in this area of research.

Chapter 3 focuses specifically on the U. maydis- Zea mays pathosystem and the differing disease symptoms that develop based on the U. maydis strain used for infection.

We sought to examine differences in ABA and CK profiles between mock-infected and

U. maydis infected cob tissue at specific time points post infection, and if U. maydis strains (dikaryon vs. solopathogen) with contrasting virulence would result in different

ABA and CK profiles during infection. CK and ABA profiling of tissue collected during tumour development revealed a dominance of certain CKs, specifically cisZCKs, in infected tissue. The level of cisZCKs was elevated in tissue where more dramatic, larger, tumours developed.

Chapter 4 builds on the data from Chapters 2 and 3, and examines U. maydis and its ability to synthesize CKs separate from the plant. With the knowledge of the dominant pathway in fungi and the predominance of tRNA degradation CK products present during infection (Chapters 2 and 3) the U. maydis CK biosynthetic and putative signaling pathways were outlined based on similarity searches to known CK proteins in organisms. This chapter sought to determine if deletion of an U. maydis tRNA- isopentenyltransferase gene would impact CK production by U. maydis. A targeted deletion strain was created which blocked the first and rate limiting step in CK biosynthesis halting any CK production in the fungus and hampering its pathogenicity and virulence in planta. Chapter 4 culminates with a model that outlines the importance of CK production by U. maydis in order for successful development of the fungus in its plant host. It also describes how key changes in other phytohormone systems (ABA) are dependent on fungal CKs.

This Ph.D. research revealed novel insights into the widespread presence of the phytohormones CK and ABA in fungi and the impact of these phytohormones on pathogenic development in the U. maydis- Zea mays pathosystem.

Fig. 1.1. CK biosynthesis pathway. Adapted from Persson et al. (1994); Sakakibara (2006); Frébort et al. (2011); Spichal (2012); Morrison et al. (2015). Numbers represent inferred enzymes as follows: 1. adenylate isopentenyltransferase (EC 2.5.1.27); 2. tRNA- isopentenyltransferase (EC 2.5.1.8); 3.cytochrome P450 mono-oxygenase; 4. phosphatase (EC 3.1.3.1); 5. 5’ ribonucleotide phosphohydrolase (EC 3.1.3.5); 6. adenosine nucleosidase (EC 3.2.2.7); 7. CK phosphoribohydrolase ‘Lonely guy: LOG’; 8. purine nucleoside phosphorylase (EC 2.4.2.1); 9. adenosine kinase (EC 2.7.1.20); 10. adenine phosphoribosyltransferase (EC 2.4.2.7); 11.cytokinin dehydrogenase (CKX) (EC. 1.5.99.12); 12. N-glucosyl transferase (EC 2.4.1.118); 13. O-glucosyl transferase; 14. ß- glucosidase (EC 3.2.1.21); 15. zeatin reductase (EC 1.3.1.69); 16. zeatin isomerase; 19. cis-hydroxylase.

Fig. 1.2. Ustilago maydis life cycle. Used with permission from Saville et al. (2012).

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CHAPTER 2

PREFACE

Title: Detection of phytohormones in temperate forest fungi predicts

consistent abscisic acid production and a common pathway for

cytokinin biosynthesis.

Authors: Erin N. Morrison, Sarah Knowles, Allison Hayward, R. Greg Thorn,

Barry J. Saville, R.J.N. Emery

Reference: Published in Mycologia (2015), 107(2): 245-257

doi: 10.3852/14-157

2014/2015 Impact Factor: 2.471

Contributions: ENM assembled hormone data, created figures and wrote the manuscript.

SK harvested, extracted and conducted initial analysis on hormone data. AH analyzed raw data and conducted preliminary data analysis. BJS and RGT aided in fungal identification. RJNE conceived, directed and obtained funding for research present in the study. ENM, BJS, RGT and RJNE edited the manuscript prior to submission.

CHAPTER 2

Detection of phytohormones in temperate forest fungi predicts consistent abscisic

acid production and a common pathway for cytokinin biosynthesis.

Published in: Mycologia (2015), 107(2): 245-257

doi: 10.3852/14-157

ABSTRACT

The phytohormones, abscisic acid and cytokinin, once were thought to be present uniquely in plants, but increasing evidence suggests that these hormones are present in a wide variety of organisms. Few studies have examined fungi for the presence of these

“plant” hormones or addressed whether their levels differ based on the nutrition mode of the fungus. This study examined 20 temperate forest fungi of differing nutritional modes

(ectomycorrhizal, wood-rotting and saprotrophic). Abscisic acid and cytokinin were present in all fungi sampled; this indicated that the sampled fungi have the capacity to synthesize these two classes of phytohormones. Of the 27 cytokinins analyzed by HPLC-

ESI MS/MS, seven were present in all fungi sampled. This suggested the existence of a common cytokinin metabolic pathway in fungi that does not vary among different nutritional modes. Predictions regarding the source of isopentenyl, cis-zeatin and methylthiol CK production stemming from the tRNA degradation pathway among fungi are discussed.

INTRODUCTION

Phytohormones, including cytokinins (CKs) and abscisic acid (ABA), are naturally occurring organic molecules that, at low concentrations (<10-8 M), influence the growth and development of plants (Costacurta and Vanderleyden 1995, Hoyerová et al., 2006,

Berger et al., 2007). These phytohormones function in complex signaling networks and, in the case of CK and ABA, an antagonistic interplay appears to modulate their metabolic regulation (Cowan et al., 1999, Schmelz et al., 2003, Nishiyama et al., 2011). Although these phytohormones are commonly associated with plants, they are also present in a wide variety of organisms including fungi (Nambara and Marion-Poll 2005, reviewed in

Tsavkelova et al., 2006, Hartung 2010, reviewed in Stirk and van Staden 2010, Frébort et al., 2011, Spichal 2012); however, little is known about their role and importance beyond plant systems.

Cytokinins are a complex group of N6 substituted adenine derivatives that are important in a number of plant growth processes including cell division, seed germination, promotion of apical dominance, nutrient mobility, and senescence (Roitsch and Ehneß 2000, Mok and Mok 2001, Ferreira and Kieber 2005). CKs are characterized by the structure of the CK side chain, which can be aromatic or isoprenoid. Most studies have focused on the biosynthesis of isoprenoid CKs, which appear to be more abundant in natural systems (Kakimoto 2003, Hwang and Sakakibara 2006). Isoprenoid CKs can be conceptually grouped based on their stereoisomer conformation and structure as: N6-

(∆2-isopentenyl) adenine (iP) type or zeatin (Z)-type, dihydrozeatin (DHZ), trans-zeatin

(transZ) or cis-zeatin (cisZ), depending on the orientation of the hydroxylated side chain, and methylthio derivatives (Persson and Bjork 1993, Pertry et al., 2010). CK metabolites

23 include free bases with their corresponding nucleotide and riboside forms; the ability to detect these different CKs provides useful information about the CK biosynthetic pathway (Sakakibara 2006). Isoprenoid CK biosynthesis is often divided into two main pathways: the methylerythritol phosphate (MEP) or de novo pathway from which iP and transZ type CKs predominantly originate, and the mevalonate (MVA) or tRNA degradation pathway, which is thought to be the main source of cisZ CKs (Hwang and

Sakakibara 2006, Sakakibara 2006). While tRNA degradation has been considered a minor contributor to overall CK levels, it is the only widely accepted pathway producing cisZ, which is a major CK in certain plant species (Emery et al., 1998, Frébort et al.,

2011, Gajdosova et al., 2011). Furthermore these isoprenoid CKs and their methylthiol- modified derivatives have been identified as specific components of tRNA in all living organisms except for Archaea (Persson et al., 1994, Yarian et al., 2002, Spichal 2012).

ABA plays an important role in seed dormancy and plant development including regulation of stomatal aperture and adaptation of the plant to various environmental conditions including biotic and abiotic stressors (Audenaert et al., 2002, Mauch-Mani and

Mauch 2005, Schmidt et al., 2008). It has been noted that increased ABA results in increased susceptibility of a plant to pathogen attack (Audenaert et al., 2002). On the other hand, the presence of ABA provides a degree of resistance to pathogen attack by stimulating callose deposition (Mauch-Mani and Mauch 2005). To our knowledge, while

ABA production by fungi has been considered a component of the interaction with host plants, no role has been determined for ABA in fungi. The main pathways for ABA biosynthesis are the deoxy-xylulose phosphate (DOXP) or MEP pathway and the MVA pathway (Oritani and Kiyota 2003, Nambara and Marion-Poll 2005). Plant ABA is

24 synthesized through the MEP pathway, whereas fungal ABA commonly is thought to originate from the MVA pathway (Oritani and Kiyota 2003, Nambara and Marion-Poll

2005). Fungal ABA production can be divided into two parts based on the precursors used to synthesize ABA. These precursors differ among fungi (Oritani and Kiyota 2003).

The capacity to produce CKs and ABA is present in at least some fungi; however, the function of these compounds during fungal growth or development in association with other organisms is largely unknown (Mauch-Mani and Mauch 2005, Tsavkelova et al., 2006). It has been suggested that plant-interacting fungi are more likely to produce phytohormones or to alter the flux of phytohormones in host plants (Ashby 2000), and there is a prevailing view that among these fungi production may be restricted based on the mode of nutrient acquisition (Walters et al., 2008). In support of this, studies examining plant pathogenic fungi with different modes of nutrition indicated that biotrophic fungi are more likely to produce CKs than necrotrophic fungi (Murphy et al.,

1997, Cooper and Ashby 1998), and that ABA is detectable in cultures of phytopathogenic fungi (Dörffling et al., 1984, Kettner and Dörffling 1987). This may suggest that there is specificity in phytohormone production based on the mode of nutrition of the fungus; however, CKs also have been detected in the saprotrophic yeasts

Saccharomyces cerevisiae and Schizosaccharomyces pombe (Laten and Zahareas-Doktor

1985), and Crocoll et al. (1991) found that parasitic and saprotrophic fungi were capable of producing ABA in culture.

Analyses of phytohormone production by fungi have detected CKs and ABA using callus bioassays (Rypacek and Sladky 1972, Ng et al., 1982), gas and liquid chromatography combined with mass spectrometry (GC/LC-MS: Crocoll et al., 1991,

Kraigher et al., 1991), enzyme linked immunoassay (HPLC-ELISA: Jameson and Morris

1989, Murphy et al., 1997, Cooper and Ashby 1998) or radioimmunoassay (RIA: Laten and Zahareas-Doktor 1985, HPLC-RIA: Jameson and Morris 1989, Novák et al., 2003).

These methods lack sufficient selectivity and sensitivity for identifying specific CK forms. The current study employs the use of high performance liquid chromatography- electrospray ionization tandem mass spectrometry (HPLC-ESI MS/MS), which provides more sensitive analyte detection and separation of stereoisomers as well as simultaneous quantification of a wide spectrum of CKs in one run. This level of detection is not possible with other technologies (Hoyerová et al., 2006). Furthermore the analysis employed in this study allows for detection and identification of CK metabolites and

ABA from the same tissue sample. The current study sought to determine whether CKs and ABA were present in the field-collected fruiting bodies of 20 temperate forest

Agaricomycete fungal species and whether CK and ABA profiles vary among these fungi with differing modes of nutrient acquisition. In this analysis wood-rotting fungi were considered to be a specialized group of the saprotrophs. To our knowledge, this is the first comparison of phytohormone production among forest fungi with different nutritional modes.

MATERIALS AND METHODS

Tissue collection and identification

Samples were collected from a forested area in Hastings Highlands, Ontario, Canada, located between Dickey and Freen Lake [+44° 47’ 50.31”, -77° 45’ 28.40”44.769527, -

77.749944] (collection dates: 30 August 30 2010, 18 September 2010). The fruiting

26 bodies of fungal samples were removed from the ground or associated plant host and temporarily stored at -18 C before moving to -80 C for storage before phytohormone isolation. Fungal identification was carried out to the genus or species level based on photographs of fruiting bodies in field and lab, and information on substrate or association. Identified fungi were grouped, through literature searches, into ectomycorrhizal, wood-rotting or saprotrophic categories for analysis (Table 2.1).

Hormone (CK and ABA) extraction and purification

Hormone extraction and purification were carried out as described in Ross et al. (2004) for ABA and Dobrev and Kaminek (2002), as modified in Hayward et al. (2013) for CKs.

Effort was made to sample from a similar area for each fruiting body. Approximately 0.1 g frozen tissue was homogenized in cold (-20 C) modified Bieleski #2 extraction buffer

(Methanol: Water: Formic Acid; CH3OH:H2O:HCO2H [15:4:1, v/v/v]) using a ball mill grinder and stainless steel cylinders (25 mZ, 2 minutes, 4 C, Retsch MM300). Internal standards were added to enable endogenous hormone quantification through isotope dilution (Jacobsen et al., 2002). These standards were added: 150 ng labeled internal

2 ABA standard ( H4ABA) (PBI, Saskatoon) and 10 ng labeled internal CK standard mix

2 2 2 2 2 2 2 2 ( H7BA, H7BAR, H5ZOG, H7DHZOG, H5ZROG, H7DHZROG, H6iP7G, H5Z9G,

2 2 2 2 2 2 2 2 H5MeSZ, H6MeSiP, H5MeZR, H6MeSiPR, H6iPR, H5ZR, H3DHZR, H6iP,

2 2 2 2 2 H3DHZ, H5Z, H6iPRMP, H6ZRMP and H3DHZRMP) (OlchemIm Ltd., Olomouc,

Czeckoslovakia). Due to the fact that labeled cisZ CKs were not commercially available at the time of extraction, quantification and identification of these compounds was based off of the recovery of labeled trans-isomers and relative retention times of unlabeled cisZ

CKs in standard runs. After tissue homogenization, samples were sonicated, vortexed and allowed to extract passively overnight at -20 C. Following overnight extraction, samples were centrifuged at 8400 x g for 10 minutes and the supernatant collected.

Solids were re-extracted and allowed to extract passively in modified Bieleski #2 extraction buffer for 30 minutes at -20 C. Pooled supernatants were dried in a speed vacuum concentrator at ambient temperature (UVS400, Thermo Fisher Scientific,

Waltham, Massachusetts). Dried supernatant residues were reconstituted in 1 mL 1M

HCO2H and subjected to solid phase extraction (SPE) on a mixed mode, reverse-phase, cation-exchange cartridge (Oasis MCX 6 cc; Waters, Mississauga, Ontario). Cartridges were activated with 5 mL CH3OH and equilibrated with 5 mL 1M HCO2H. Samples were loaded onto the cartridge and washed with 5 mL 1M HCO2H. ABA was eluted first with 5 mL CH3OH. CKs were eluted based on their chemical properties, nucleotide CK forms were eluted second with 5 mL 0.35 M ammonium hydroxide (NH4OH) followed by free base and riboside CK forms eluted with 5 mL 0.35 M NH4OH in 60% CH3OH.

Samples were evaporated and stored at -20 C.

CK nucleotides were reconstituted in 1 mL 0.1 M ethanolamine-HCl (pH 10.4) and dephosphorylated to form ribosides using 3.4 units bacterial alkaline phosphatase

(Sigma, Oakville, Ontario) for 12 h at 37 C. Resulting CK ribosides were evaporated in a speed vacuum concentrator at ambient temperature. Due to the conversion of nucleotides to ribosides, detection of nucleotides potentially reflects pooled contribution of mono, di- or tri- phosphates in that the isopentenyl or hydroxylated moiety can be transferred to

AMP, ADP or ATP (Quesnelle and Emery 2007). The dephosphorylated nucleotides were reconstituted in 1.5 mL Milli-Q H2O for further purification on a reverse-phase C18

column (Oasis C18 3 cc; Waters, Mississauga, Ontario). Cartridges were activated using

3 mL CH3OH and equilibrated with 6 mL Milli-Q H2O. Samples were loaded onto the

C18 cartridge and eluted by gravity. The sorbent was washed with 3 mL Milli-Q H2O and analytes were eluted using 1.5 mL CH3OH:H2O (80:20 v/v). All samples were evaporated and stored at -20 C until analysis.

Purified ABA, CK nucleotides, CK riboside and free base fractions were reconstituted in 1 mL initial mobile phase conditions (95:5 H2O:CH3OH with 0.08% acetic acid (CH3CO2H)). Samples were transferred to glass auto-sampler vials and stored at 4 C until analysis.

HPLC-ESI MS/MS methods and multiple reaction monitoring (MRM) channels, specific for each analyte, were carried out as described in Ross et al. (2004) and Farrow and Emery (2012). Detection limits were as listed in Farrow and Emery (2012). Samples were analyzed and quantified by HPLC-ESI MS/MS (Dionex HPLC machine connected to a Sciex Applied Biosystem 5500 API mass spectrometer) with a turbo V-spray ionization source. A 20 L sample was injected onto a Kinetex C18 column (2.1 x 100 mm, 1.9 m solid core, 0.35 m porous shell; Phenomenex, Torrance, California); all

ABA samples were analyzed in negative-ion mode and all CK samples were analyzed in positive-ion mode. All hormone fractions were eluted with component A: H2O with

0.08% CH3CO2H and component B: CH3OH with 0.08% CH3CO2H, at a flow rate of 0.2 mL minute-1. Initial conditions for the ABA fraction were 50% B changing on a linear gradient to 80% B over 8 minutes. This ratio was held constant for 2 minutes before returning to starting conditions and equilibrating for 8 minutes. The CK nucleotide fraction was eluted with a multistep gradient. Starting conditions were 10% B increasing

29 linearly to 50% B over 2 minutes followed by a linear increase to 95% B over 6 minutes;

95% B was held constant for 3 minutes before returning to starting conditions for 6 minutes. The CK free base and riboside fraction was run with a multistep gradient, which started at 10% B and increased linearly to 70% B over 12 minutes. The gradient then increased 70% B- 95% B over 3 minutes and was held constant for 3 minutes before returning to starting conditions for 9 minutes.

Data analysis

All data was analyzed with Analyst (v. 1.5) software (AB SCIEX, Concord, Canada).

ABA and CKs were identified based on their MRM channels and retention times.

Concentrations were determined according to isotope dilution analysis based on direct comparison of the endogenous analyte peak area to that of the recovered internal standard

(Jacobsen et al., 2002). Fungal hormone profiles were grouped based on mode of nutrition as well as by phylogeny. From 2 to 3 replicates were used for each fungus.

Statistical analysis was carried out using an ANOVA with the Tukey-Kramer post-hoc test. Significant differences refer to a p-value of <0.05.

RESULTS

Fungal samples

Multiple samples of 20 fungal species were collected and used for hormone analysis.

Each sample was identified to genus and/or species, and the mode of nutrient acquisition was determined for each identified fungus based on literature searches. In cases where more than one mode of nutrition was noted, the more dominant nutrition mode (the one

30 that occurs for the majority of the lifecycle) was listed (Table 2.1). All 20 fungal species belonged to the phylum Basidiomycota (Table 2.1) and 13 of these were identified as having a saprotrophic mode of nutrition. Among the fungi sampled, those in the

Agaricales were ectomycorrhizal or saprotrophic, while those in the orders Polyporales,

Hymenochaetales and Auriculariales were wood-rotting or saprotrophic (Table 2.1).

Abscisic acid

Fungal samples were extracted and analyzed for the presence of ABA by HPLC-ESI

MS/MS. ABA was present in all fungal species with concentrations ranging from 1.8

-1 (Mycena leaiana) to 24.4 pmol g FW (Amanita bisporigera) (Fig. 2.1). There were no significant differences in ABA levels within nutritional groupings or between nutritional groups (p < 0.05). Fungal species were also grouped and analyzed based on phylogeny and no significant difference was found (p < 0.05) (data not shown).

Cytokinin

Total fungal CK, composed of the individual CK types, ranged from 24 (Piptoporus betulinus) to 210.4 pmol g-1 FW (Mycena leaiana) (Fig. 2.2). Of the 27 endogenous CKs monitored, only 7 CKs were detected: N6- (∆2-isopentenyl) adenine-9-riboside-5’- mono, di-, tri- phosphate (iPRP), N6- (∆2-isopentenyl) adenine-9-riboside (iPR), iP, cis-zeatin-9- riboside-5’-mono, di-, tri- phosphate (cisZRP), cis-zeatin-9-riboside (cisZR), zeatin-2- methylthio, 9-riboside (2MeSZR), and zeatin-2-methylthio (2MeSZ). No significant difference was found within nutritional groupings or between nutritional groups when

31 using the average total CKs for each fungus (p < 0.05). Grouping the fungi based on phylogeny did not reveal any clear trend in CK profiles (data not shown).

Individual cytokinin types were compared within and between all fungal samples

(Fig. 2.2). iP, cisZ and methylthiol (2MeS) CK types were detected in all samples at varying levels. In order to assess the contribution of each CK type to the relative profile of CKs, each CK form was represented as a percentage of the total concentration of CKs

(Fig. 2.3). Comparisons were divided into iP, cisZ and 2MeS CK types, followed by their forms: nucleotide, riboside and free base (Fig. 2.3). The nucleotide, riboside and free base iPCK forms (iP+iPR+iPRP) were present in all fungi sampled with the nucleotide and riboside forms representing the majority of the iPCKs (Fig. 2.3A). In most cases cisZ and 2MeS CK types comprised the majority of the cytokinin pool among the fungi sampled (Fig. 2.3B, C). cisZR was the dominant cisZCK form representing greater than 50% of the total cisZCK type across 7 of 20 fungal species (Fig. 2.3B).

2MeSZ was the dominant 2MeSCK form across all fungal species with the exception of

Phellinus igniarius (Fig. 2.3C). To determine if there was a higher contribution of a particular CK type to the total CK pool, fungi were highlighted when the dominant CK type represented a value of two times the value of the less abundant CK type, i.e. in the case of cisZCK dominance: of the fungi sampled, cisZCKs equaled 60% or higher of the total CK pool and 2MeSCKs represented 30% or lower of the total CK pool, in cases of

2MeSCK dominance: 2MeSCKs equaled 50% or higher of the total CK pool and cisZCKs represented less than 30% of the total CK pool. In cases where the majority of the CK pool was composed of cisZCK types, as in Hygrocybe sp., Phellinus igniarius,

Hypsizygus ulmarius, Exidia glandulosa, and Trichaptum biforme there was a marked

32 reduction in the total percentage of iP and 2MeS CK types. In cases where there was a high representation of the 2MeSCK types, as in Pleurotus ostreatus, Mycena leaiana,

Clitocybula abundans, and Trametes pubescens, there was a reduction in the total level of iP and cisZ CK types (Fig. 2.3). In most fungal samples the percentage of total CKs is strongly composed of one CK type (iP, cisZ or 2MeS) and with high representation of a specific CK form (nucleotide, riboside or free base).

Total percentage of cytokinin types was further separated based on fungal order as well as mode of nutrition (Fig. S2.1). No clear trend was noted. Those fungi that were classified as more dominant in a particular CK type, cisZ or 2MeS, were found within all groupings of fungi.

DISCUSSION

The importance of CKs and ABA in growth and development has been well researched in plants. However, increasing evidence suggests that these phytohormones play an important role in other organisms including fungi. Few studies have involved environmental surveys of fungi to examine phytohormone levels.

In this study 20 fungal species were examined for the presence of CKs and ABA.

All 20 fungi sampled had notable levels of ABA and the same seven CK forms. No relationship was detected between the mode of fungal nutrient acquisition and hormone presence or level, suggesting that these hormones play an important role in the development of the fungus rather than being produced only for the purpose of interacting with plants.

Fungal production of ABA

ABA is a plant hormone that plays a role in the initiation of stress response and may act antagonistically with CKs, resulting in their metabolic regulation (Cowan et al., 1999,

Schmelz et al., 2003, Nishiyama et al., 2011). Mycena leaiana (this study) had the lowest level of ABA and the highest level of total CK compared to all other fungi sampled, suggesting a regulating interplay between these two hormones. ABA is produced by some plant pathogenic fungi via a biosynthetic route different from that of

ABA biosynthesis in plants (Mauch-Mani and Mauch 2005). The phytopathogens

Cercospora rosicola, Cercospora cruenta, Cercospora pini-densiflorae, and Botrytis cinerea are known to produce ABA (Nambara and Marion-Poll 2005). Ceratocystis coerulescens produces detectable ABA in mycelium and exudes considerable amounts into culture medium during growth (Kettner and Dörffling 1987). Axenic culturing of the biotrophic pathogen Ustilago maydis showed ABA synthesis that averaged 313.61 pmol g-1 FW (Bruce et al., 2011). The 20 fungi examined here show ABA ranging from 1.8 pmol g-1 FW to 24.4 pmol g-1 FW. Lower concentrations in field-sampled fungi relative to axenic cultures may be correlated to the growth stage of the fungus when sampled (ex. fruiting body vs. mycelia) or may be a result of differential loss of phytohormones in fruiting body isolation versus culture isolation. Examination of 10 fungi of differing nutritional characteristics showed that both saprotrophic and parasitic fungi produce ABA in culture media ranging from 11 ng g-1 DW to 2074 ng g-1 DW (Crocoll et al., 1991).

Crocoll et al. (1991) detected ABA in the media culture filtrate of Trametes versicolor at a maximum 12 ng g-1 DW, our data from fruiting body isolates revealed 3.4 pmol g-1 FW, further highlighting the fact that hormone levels may be tissue dependent within fungi.

The present research shows that ABA production does not follow any pattern based on the nutrient mode of the fungus and therefore is not limited to parasitic fungi.

Role of CKs in fungal development

Cytokinins play an important role in plant-pathogen interactions (reviewed in Ashby

2000) and may also be important in fungal growth and development separate from the plant (Rypacek and Sladky 1972, Rypacek and Sladky 1973). In the current study CKs were found in all fungi sampled ranging from 24 pmol g-1 FW to 210.4 pmol g-1 FW

(Piptoporus betulinus and Mycena leaiana, respectively), with no direct link to nutrient acquisition. Although the affect of CK production on the development of fungi was not measured, studies have shown that CKs vary during different developmental stages

(Rypacek and Sladky 1972, Rypacek and Sladky 1973). Sampling of Lentinus tigrinus revealed high quantities of CKs in caps when basidiospores were formed and high levels also were associated with intensive growth of young vegetative mycelium in culture

(Rypacek and Sladky 1972, Rypacek and Sladky 1973). Differences in hormone levels among the 20 fungi in the current study may be due to the stage at which the fruiting body was sampled. Attempts were made to harvest fungi at mid-fruiting stage, but the exact age of fruiting bodies was not determined. Furthermore, the comparison of fungal fruiting bodies that exhibited morphological differences may mean that regions sampled are not directly comparable. Sampling at different areas or stages of development may reveal differences in CK profiles within a fungal sample. A role for cytokinins in fungal development also can be seen in experiments that indicate exogenous CK application yields a developmental response in fungi (Braaksma et al., 2001, Nasim and Rahman

2009, Sood 2011). The endogenous presence of CKs (this study) along with the impact of exogenous CK application on several fungal species is consistent with a potential role for CKs in fungal development.

Studies of fungi with differing modes of nutrition (necrotrophic, hemibiotrophic and biotrophic) noted a trend toward CK production by biotrophic fungi (reviewed in

Ashby 2000). In the current study it is suggested that CKs play a role in the development of fungi that do not require a plant host for lifecycle completion. Analysis of the hemibiotroph Pyrenopeziza brassicae showed production of both iPR and ZR in extracts of mycelia and culture filtrates, with the highest amount recovered from mycelium at 125 pmol g-1 FW of ZR (Murphy et al., 1997). Murphy et al. (1997) examined fungi with different nutrition modes and found that the necrotrophic fungi Botrytis cinerea and

Penicillium expansum did not produce CKs in culture whereas Cladosporium fulvum and

Erysiphe graminis (biotrophs) and Pyrenopeziza brassicae and Venturia inaequalis

(hemibiotrophs) did produce CKs. While focus has been placed on plant-interacting fungi, even analyses of yeast extracts using HPLC-ELISA and RIA have detected low transZ and transZR and significant iP and iPR CKs (Jameson and Morris 1989).

Although there is debate about CK production among different fungi, the data presented in this study supports the widespread production of CKs by fungi and that CK production is independent of the mode by which the fungus acquires nutrients.

Cytokinins and other growth hormones are known to play an important role in mycorrhizal associations (Barker and Tagu 2000). Many plants that form mycorrhizae accumulate high concentrations of iP-like compounds in shoots and roots (Vadassery et al., 2008). The endophytic fungus Piriformospora indica produces iP and cisZ CK types

36 with elevated levels accumulating in colonized roots of Arabidopsis (Vadassery et al.,

2008). Extracted and purified CKs from liquid cultures of the mycorrhizal fungi

Rhizopogon luteolus, Boletus elegans and Suillus luteus were thought to be Z and ZR (Ng et al., 1982). Filtrates of two ectomycorrhizal fungi, Laccaria bicolor and Thelephora terrestris, were analyzed for the presence of CKs (Kraigher et al., 1991). Laccaria bicolor produced iPR and Thelephora terrestris produced iPR, iP, ZR and Z, detected with HPLC GC-MS and HPLC-RIA (Kraigher et al., 1991). Ectomycorrhizal fungi in the current study range in CK concentrations from 40.4- 143.5 pmol g-1 FW (Amanita bisporigera and Hygrocybe sp., respectively) with detectable iP and cisZ CK types as found in other mycorrhizal fungi.

Fungi sampled in the current study have detectable levels of the same 7 CK forms

(iPRP, iPR, iP, cisZRP, cisZR, 2MeSZR, and 2MeSZ), suggesting that CK production is not limited to plant-interacting fungi and that these fungi share a common CK biosynthetic pathway. The absence of transZ CKs and detection of cisZ, iP and 2MeS

CK types suggests the activation of the tRNA degradation pathway and not the de novo pathway. In contrast to these findings studies detected the presence of transZ among fungi (Jameson and Morris 1989). This discrepancy may be due to the instrumentation used for hormone detection and analysis. In earlier studies, GC/LC-MS, or HPLC-

ELISA/RIA were used previously to separate and detect CKs. Standard CK bioassays were customized for transZ isomer detection, resulting in the low activity of cisZ isomers in these tests (Schmitz et al., 1972, Mok et al., 1978, Kaminek 1982, Quesnelle and

Emery 2007). Cis and trans isomers have subtly different chromatographic behaviors and cis isomers may go undetected by GC-MS and LC-MS if not adequately resolved

(van Rhijn et al., 2001, Quesnelle and Emery 2007). It is possible that Ng et al. (1982),

Jameson and Morris (1989), Kraigher et al. (1991), and Murphy et al. (1997) may not have had the resolving power to detect cis isomers (van Rhijn et al., 2001). Separation of these isomers is critical for correctly determining the production pathway of the detected

CKs (Novák et al., 2003). The HPLC-ESI MS/MS technique and analyses reported here have the capacity to separate and distinguish cis and trans isomers, thereby allowing the detection of the 7 CK forms.

Due to the widespread occurrence of CKs in all fungi and the similarity in CK types present, we suggest that CKs have a role in influencing the growth and/or development of fungi. Furthermore all CKs present are consistent with origins from within the tRNA degradation pathway. Hence the presence of these compounds can be used to predict a common metabolic pathway for CK production.

tRNA degradation pathway

The absence of any transZ derived CKs in the 20 fungal CK profiles suggests that the tRNA degradation pathway is the predominant pathway in the fungi sampled. Although tRNA degradation has been considered a minor contributor to overall CK levels in plants, it is the only widely accepted pathway for the sources of cisZ, and this CK form is a major component of CK profiles in certain plant species (Emery et al., 1998, Golovko et al., 2002, Frébort et al., 2011, Gajdosova et al., 2011). Modification of the adenine can include addition of an isopentenyl group, hydroxylation and methylthiolation, all of which play an important role in translational efficiency and fidelity (Golovko et al.,

2000). A pathway that links methylthiol derivatives to current schemes of CK biosynthesis has not been proposed.

The basic CK moiety in tRNA is iP (reviewed in Prinsen et al., 1997); data presented in this paper suggests that from this prenyl-tRNA all three CK types, detected in these fungi, can be formed (Fig. 2.4). Hydroxylation of a terminal methyl group of N6-

(∆2-isopentenyl) adenine-2-methylthio, 9-riboside (2MeSiPR) results in 2MeSZR

(Prinsen et al., 1997); the presence of 2MeSZ and 2MeSZR in the fungi suggests that this modification can occur among fungi even though the methylthioriboside derivative is thought to be more predominant in bacterial tRNA and in some plant tRNAs (reviewed in

Prinsen et al., 1997). Degradation of the prenyl-tRNA results in the release and detection of the iPCK types. The cisZ type CK branch results from the hydroxylation of the prenyl-tRNA resulting in cis-prenyl-tRNA. The common substrate (prenyl-tRNA) for these three branches of the pathway suggests that the dominance of some CK forms noted among the fungi may be due to competition for the same substrate (see Fig. 2.3). Based on the CK profiles of these fungi and information known from plant and bacterial systems we have proposed a tRNA degradation pathway which accounts for the presence of the common seven CK metabolites found in the sampled fungi (Fig. 2.4). The metabolic pathway (Fig. 2.4) incorporates data from the current study and information from other studies to suggest that iP CK forms are derived from the tRNA degradation pathway and that these act as a possible source for the production of methylthiol derivatives.

The current study analyzed CK types and amounts at a specific time in fungal development. The types of CKs detected were consistent with those detected in other

39 fungal studies and indicate the presence of a tRNA degradation pathway for CK production among fungi. Although it cannot be excluded that the fungi in this study acquired some level of CKs from living hosts, it is likely that fungi can synthesize these hormones. Axenic haploid and dikaryon Ustilago maydis cultures contain both ABA and

CKs, revealing that production of these hormones can occur separate from the plant

(Bruce et al., 2011). High cisZ and iP CK forms in Ustilago maydis profiles (Bruce et al., 2011) suggests the activation of the tRNA degradation pathway. The first step in CK biosynthesis is catalyzed by isopentenyltransferase (IPT); in the case of the tRNA degradation pathway, synthesis is initiated by a tRNA-IPT (Sakakibara 2006). During infection of maize by the hemibiotroph Colletotrichum graminicola changes to the CK profile were observed, which included substantial increases of cisZR and cisZ-9-riboside-

5’monophosphate relative to the noninfected control (Behr et al., 2012).

Isopentenyltransferase activity was postulated in this fungus in that it was able to synthesize Z isoforms with the addition of dimethylallyl-pyrophosphate (DMAPP) substrate to minimal media (Behr et al., 2012). Frébort et al. (2011) noted that among available fungal genomes nothing similar to the adenylate-isopentenlytransferase was present (responsible for de novo CK synthesis). Consistent with this, Spichal (2012) reported that tRNA-isopentenyltransferases are conserved throughout a broad range of organisms while adenylate IPTs were only found in plants. Identification of the tRNA-

IPT in fungi indicates that at least some have the potential to synthesize CKs (Kakimoto

2003, Bölker et al., 2008, Tsai et al., 2014). A tRNA-IPT gene has been identified in the model fungus U. maydis, which is known to produce CKs, specifically those products of the tRNA degradation pathway (Bölker et al., 2008, Bruce et al., 2011). The biotrophic

40 plant pathogens of the genus Taphrina cause plant deformation and are able to synthesize

CKs (Johnston and Trione 1974). Genetic comparisons of four major genomes of the

Taphrina species identified a putative ortholog for tRNA-IPT (Tsai et al., 2014).

Although genome sequencing has not been done on the fungi sampled in the current study, linking the products found to a potential biosynthetic pathway provides information as to the source of these analytes and leads to the hypothesis that all enzymes suggested by the proposed pathway are present in the sampled forest fungi. The production of iP and cisZ by other fungi (as listed above) also suggests the dominance of the tRNA degradation pathway in fungi. The tRNA degradation pathway for CK production among fungi will need to be confirmed. One way to accomplish this would be to delete genes predicted to be important in CK biosynthesis and determine whether the resulting CK profiles are altered. This would require the use of a model fungal species for which genome annotation information is available and biochemical analysis is relatively straightforward. U. maydis can be used as such a model. Preliminary data indicates that deletion of the tRNA-IPT gene in this fungus blocks production of cisZ and iP CK types (Morrison, Emery and Saville unpublished). These data may further support the importance of the tRNA degradation pathway and its function in CK production among fungi.

All fungi in this study produce CKs and ABA independent of their mode of nutrition. CK profiles were strikingly consistent among all 20 fungal species, producing iP, cisZ and 2MeS CK types, suggesting that the tRNA degradation pathway is responsible for CK biosynthesis among these fungi. Given the information gained from this study a model that explains the source of these CKs from the tRNA degradation

41 pathway is presented. This study further shows that ABA, although present at varied amounts, is not limited to phytopathogenic fungi. The widespread detection of CKs and

ABA in fungi suggests that these phytohormones are not simply used for plant interaction but are likely important in fungal development.

TABLES AND FIGURES

Table 2.1. Fungi used in this study. Taxonomy Common name Order IDa Ectomycorrhizal Amanita bisporigera 87325 Destroying angel Agaricales Hygrophorus sp. 71942 Waxy cap Agaricales Hygrocybe sp.b 51006 Waxy cap Agaricales Wood-rot Phellinus igniarius 40472 White rot fungus Hymenochaetales Oxyporus populinus 139378 Mossy maple/cap polypore Hymenochaetales Ganoderma applanatum 29884 Artist’s fungus Polyporales Piptoporus betulinus 40450 Razor strop fungus Polyporales Saprotrophic Bjerkandera adusta 5331 White rot fungus/ smoky bracket Polyporales Lycoperdon perlatum 90686 Common puffball Agaricales Hypsizygus ulmarius 71891 Elm leech/ oyster Agaricales Pleurotus ostreatus 5322 Oyster mushroom Agaricales Mycena leaiana 182004 Orange mycena Agaricales Exidia glandulosa 5219 Black witches’ butter Auriculariales Trichaptum biforme 50381 Violet-toothed polypore Hymenochaetales Tyromyces chioneus 83250 White rot fungus Polyporales Trametes versicolor 5325 Turkey tail Polyporales Clitocybula abundans N/A Coin cap fungus Agaricales Hymenopellis sp. 937605 Deep root mushroom Agaricales Hygrocybe miniata 182064 Vermilion wax cap Agaricales Trametes pubescens 154538 Turkey tail-like fungus Polyporales aTaxonomic identification (Taxonomy IDs) numbers for each fungal sample were acquired with NCBI Taxonomy Browser (http://www.ncbi.nlm.nih.gov/Taxonomy/Browser). bThe nutritional mode of this fungus is still under debate (Seitzman et al., 2011).

Fig. 2.1. Abscisic acid concentration (pmol g-1 FW) in ectomycorrhizal, wood-rot and saprotrophic fungi. N=2–3, error bars represent standard error (SE).

Fig. 2.2. Total cytokinin concentration (pmol g-1 FW) in ectomycorrhizal, wood-rot and saprotrophic fungi. N=2–3, except in cases where the compound was below detection limits.

Fig. 2.4. Proposed tRNA degradation pathway. Information for this pathway was inferred from the current study and plant and bacterial investigations (Persson and Bjork 1993, Persson et al., 1994, Sakakibara 2006, Frébort et al., 2011, Spichal 2012). Numbers represent inferred enzymes as follows: 1. tRNA-isopentenyltransferase (EC 2.5.1.8); 2. cis-hydroxylase; 3. 5’ribonucleotide phosphohydrolase (EC 3.1.3.5); 4. adenosine nucleosidase (EC 3.2.2.7); 5. CK phosphoribohydrolase ‘Lonely guy’; 6. purine nucleoside phosphorylase (EC 2.4.2.1); 7. adenosine kinase (EC 2.7.1.20); 8. adenine phosphoribosyltransferase (EC 2.4.2.7); 9. miaB,C, Fe and Cys; 10. miaE and O2; 11. cytochrome monooxygenase CYP450.

SUPPLEMENTARY MATERIAL

Fig. S2.1. Percentage of total CKs divided into isopentenyl, cis-zeatin and methythiol CK types based on: (A) Mode of nutrition; ectomycorrhizal, wood-rot and saprotrophic. (B) Phylogeny; grouped based on order. N=2–3, except in cases where the compound was below detection limits.

ACKNOWLEDGEMENTS

We acknowledge the Natural Sciences and Engineering Research Council (NSERC) of

Canada for financial support (BJS, RJNE) and the Ontario Graduate Scholarship program for student support (ENM).

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CHAPTER 3

PREFACE

Title: Phytohormone involvement in the Ustilago maydis– Zea mays

pathosystem: relationships between abscisic acid and cytokinin levels and

strain virulence in infected cob tissue.

Authors: Erin N. Morrison, R.J.N. Emery, Barry J. Saville

Reference: Published in PlosOne (2015), 10(6): e0130945

doi:10.1371/journal.pone.0130945

2014 Impact Factor: 3.234

Copyright: © 2015 Morrison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Contributions: Conceived and designed the experiments: ENM, RJNE, BJS. Performed the experiments: ENM. Analyzed the data: ENM, RJNE, BJS. Contributed reagents/materials/analysis tools: RJNE, BJS. Wrote the paper: ENM, RJNE, BJS.

Amanda Charlesworth contributed data associated with Fig. S3.1.

BJS and RJNE conceived, directed and obtained funding for research present in the study. ENM conceived and conducted all experiments and wrote the initial draft of the manuscript. ENM, BJS, and RJNE edited the manuscript prior to submission.

CHAPTER 3

Phytohormone involvement in the Ustilago maydis– Zea mays pathosystem:

relationships between abscisic acid and cytokinin levels and strain virulence in

infected cob tissue.

Published in: PlosOne (2015), 10(6): e0130945

doi:10.1371/journal.pone.0130945

ABSTRACT

Ustilago maydis is the causative agent of common smut of corn. Early studies noted its ability to synthesize phytohormones and, more recently these growth promoting substances were confirmed as cytokinins (CKs). Cytokinins comprise a group of phytohormones commonly associated with actively dividing tissues. Lab analyses identified variation in virulence between U. maydis dikaryon and solopathogen infections of corn cob tissue. Samples from infected cob tissue were taken at sequential time points post infection and biochemical profiling was performed using high performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI MS/MS).

This hormone profiling revealed that there were altered levels of ABA and major CKs, with a marked reduction in CK glucosides, increases in methylthiol CKs and a particularly dramatic increase in cisZ CK forms, in U. maydis infected tissue. These changes were more pronounced in the more virulent dikaryon relative to the solopathogenic strain suggesting a role for cytokinins in moderating virulence during biotrophic infection. These findings highlight the fact that U. maydis does not simply mimic a fertilized seed but instead reprograms the host tissue. Results underscore the

57 suitability of the Ustilago maydis– Zea mays model as a basis for investigating the control of phytohormone dynamics during biotrophic infection of plants.

INTRODUCTION

A key strategy for successful pathogen establishment often involves hijacking an already existing plant network. Manipulation of host metabolism through the production of phytohormones by plant pathogens, or the activation of host phytohormone biosynthesis, is often used as a component of establishing pathogen growth within the host (Walters and McRoberts 2006, Choi et al., 2011).

Phytohormone manipulation has often been associated with the infection strategy of biotrophic fungi through; nutrient diversion, suppression of plant defense responses, and increased host susceptibility, all of which have been mimicked through the exogenous application of the phytohormones cytokinins (CK) or abscisic acid (ABA)

(Cooper and Ashby 1998, Ashby 2000, Audenaert et al., 2002).

The phytohormone group cytokinins are N6 substituted adenine derivatives which are important in a number of developmental processes within the plant including cell division and differentiation (Mok and Mok 2001); abscisic acid, is often referred to as the plant stress hormone, and is involved in plant development as well as adaptation to various environmental biotic and abiotic stressors (Audenaert et al., 2002, Mauch-Mani and Mauch 2005, Schmidt et al., 2008).

While phytohormone production is often associated with biotrophic fungi, the key questions remain as to why non-plant associated microbes produce phytohormones? And, what is the mechanism by which microbial phytohormone production provides a pathogenic advantage in a host-pathogen interaction? (Ashby 2000, reviewed in

Tsavkelova et al., 2006, Hartung 2010, Stirk and van Staden 2010, Frébort et al., 2011,

Spichal 2012, Morrison et al., 2015). Here we examine the latter of the two questions.

Studies examining the infection process of the basidiomycete corn smut fungus

Ustilago maydis have suggested that phytohormone manipulation, by this fungus, may play a role in host infection (Bölker et al., 2008, Doehlemann et al., 2008a). Infection of corn by the U. maydis pathogenic dikaryon stimulates uncoordinated cellular division, resulting in tumour formation on aerial portions of the plant including the cob (Banuett and Herskowitz 1996, Kämper et al., 2006). Within these tumours black, diploid teliospores are produced which act as the dispersal agent for the fungus (Banuett and

Herskowitz 1989, Kämper et al., 2006). U. maydis infection of Zea mays results in reduced photosynthetic rate, maintenance of nutrient sinks (Horst et al., 2008), elevated levels of total soluble sugars, and increased nitrogen accumulation in infected tumours

(Horst et al., 2010). These features are common among biotrophic fungal infections and have been mimicked through the application of exogenous CKs (Walters and McRoberts

2006). However, the link to CKs during the U. maydis- Zea mays interaction has not been thoroughly examined, although previous studies have shown that cultured U. maydis

(sporidia and dikaryon) were capable of producing CKs and ABA, and that specific CK forms varied during infection of maize seedlings (Mills and Van Staden 1978, Bruce et al., 2011), none have examined the hallmark of this disease, cob tumour formation.

Information for U. maydis phytohormone manipulation and pathogenesis has mostly been done in corn seedlings however, seedling infections elicit symptoms that are distinctly different from those seen in cob tissue and, therefore, likely result in different

CK profiles. U. maydis pathogenesis assays are often carried out using the U. maydis dikaryon, which results from the fusion of two compatible haploid sporidia, or using a genetically engineered haploid solopathogen (Banuett and Herskowtiz 1989, Kämper et

60 al., 2006). In lab observations it was noted that infection of corn seedlings and cob tissue by these two strains resulted in different rates of disease development and severity of disease symptoms, with the dikaryon being more virulent (Fig. S3.1). With this in mind we sought to examine the changes in ABA and CK profiles between mock-infected and

U. maydis infected cob tissue at specific time points post infection, and determine if U. maydis strains (dikaryon vs. solopathogen) with contrasting virulence will result in different ABA and CK profiles during infection. Samples, from infected cob tissue, were taken at various time points post infection and biochemical profiling conducted using high performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI MS/MS). The use of HPLC-ESI MS/MS in this study permits the detection and separation of ABA and CK analytes from the same tissue sample

(Morrison et al., 2015). In this study, it was observed that ABA levels were elevated in infected tissue. CK levels specific to the free base, riboside, nucleotide (FBRNT) group of CKs increased dramatically in U. maydis infected tissue relative to the mock-infected control, and further differences were found when comparing the dikaryon and solopathogen infections. This comparison of ABA and CK profiles between different U. maydis strain infections will provide new insight into virulence factors experienced during infection.

MATERIALS AND METHODS

Ustilago maydis strains and growth conditions

Ustilago maydis strains used in the experiments include: FB1 (a1b1) and FB2 (a2b2), provided by Flora Banuett (Banuett and Herskowitz 1989), and the solopathogenic

61 haploid strain SG200 (a1 mfa2 bE1bW2); a FB1 derived strain engineered to grow filamentously and cause disease without a mating partner, obtained from Jörg Kämper

(Karlsruhe Institute of Technology, Karlsruhe, Germany; Bölker et al., 1995, Kämper et al., 2006). Budding cultures were grown on solid YEPS medium (1% w/v yeast extract,

2% w/v peptone, 2% w/v sucrose) containing agar for 3-4 days at 28 C; for SG200, solid medium was supplemented with 20 µg mL-1 phleomycin (InvivoGen). Single colonies were inoculated into liquid YEPS medium and grown overnight (28 C, 250 rpm). Two hundred µL of overnight culture was inoculated into 200 mL of liquid YEPS medium and grown overnight (28 C, 250 rpm). Cultures were diluted to a final OD600 of 1 using sterile dH2O. For compatible haploids (FB1 x FB2) equal volumes of diluted culture were combined. For solopathogenic (SG200) injections, cultures were diluted to a final

OD600 of 1.

Plant growth conditions, tissue injection and sampling

Zea mays L. ‘Golden Bantam’ (Ontario Seed Company, Canada) seeds were planted (16 per 38 cm pot, reduced to 8 plants per pot) in Sunshine Professional Growing Mix

(Mix#1, Sungro Horticulture Canada). Two pots with a total of 10 cobs were used for the mock-infected treatment, three pots with a total of 14 cobs were used for the dikaryon

(FB1 x FB2) treatment and four pots with a total of 13 cobs were used for the solopathogen (SG200) treatment. Germination and growth occurred under 16 h light, 60-

80% RH, 24-27 C, 8 h dark, 60-80% RH, at 19-22 C (Aurora Greenhouse, Conviron,

Canada). Corn plants were detasseled to prevent pollination of ovules and increase the likelihood of cob infection (Snetselaar et al., 2001, Pataky and Chandler 2003). Cobs

62 were injected, as described in Morrison et al. (2012). Briefly, U. maydis injection of cobs was carried out using 6 mL of culture (FB1 x FB2 or SG200), which was diluted to an

OD600 of 1 and injected down the silk shaft of cobs using a 10 mL syringe and 18 gauge needle. If strong back pressure occurred (suggesting insertion into the cob) the needle was drawn back or reinserted through the husk at a different location. Mock-infections

(controls) were injected in the same manner using diluted YEPS (50% v/v sdH2O).

Time course tissue sampling

Disease progression was monitored and tissue samples were taken at 10, 13, 16, 20, 24 and 28 days post infection (dpi). Fig. 3.1 shows the progression of disease symptoms for the mock-infected control, dikaryon (FB1 x FB2), and solopathogen (SG200). Sample days were based on in-lab observations of disease progression and documented stages in

Pataky and Snetselaar (2006). Sampling of infected cobs was heavily reliant on the presence of infected tissue and absence of secondary infection. Tissue was selected based on disease progression at a given time point, therefore sampling was not limited to a single pot per treatment. Cobs were opened in-line with husk growth and examined for signs of infection. Infected sites were excised using a razor blade, weighed, frozen in liquid nitrogen and stored at -80 C until phytohormone extraction could take place.

Following sampling, cobs were covered again using existing husk material. While infection rates can increase with silk-channel injection, not all cobs will develop disease symptoms (Snetselaar et al., 2001). To gain adequate sample numbers, infected cobs were sampled throughout the progression of the disease even if samples were previously taken from the same cob; however, tissue was not sampled from a previously excised

63 region of the cob even if re-growth was visible. U. maydis infected tissue from early time points required pooling of small tumours to reach the tissue mass required for hormone extraction. Later time points, with larger tumours, allowed single tumours to represent a single sample. Each tumour in later time points was considered an individual sample even if it was taken from the same cob. Table 3.1 presents a summary of the number of cobs sampled and the total number of samples collected at each time point. Unfertilized ovules from mock-infected controls were often pooled to represent one sample. For each time point, an attempt was made to examine a previously unopened cob, when available.

CK and ABA extraction and purification

Hormone extraction and purification were carried out as described in Ross et al. (2004) for ABA and in Dobrev and Kamínek (2002), as modified in Morrison et al. (2015) for

CKs. Briefly, frozen tissue was reweighed and internal standards added during the first extraction step to enable endogenous hormone quantification through the isotope dilution technique (Jacobsen et al., 2002). Internal standards included 146.9 ng of labeled ABA

2 ( H4ABA) (PBI, Saskatoon), and 10 ng of the following CK’s:

2 2 2 2 2 2 2 2 H7BA, H7BAR, H5ZOG, H7DHZOG, H5ZROG, H7DHZROG, H6iP7G, H5Z9G,

2 2 2 2 2 2 2 2 H5MeSZ, H6MeSiP, H5MeZR, H6MeSiPR, H6iPR, H3DHZR, H6iP, H3DHZ,

2 2 H6iPRMP, and H6DHZRMP (OlchemIm Ltd., Olomouc, CZ). Similarity in retention

2 2 2 time allowed the use of labeled H3DHZR, H3DHZ, and H6DHZRMP for the quantification of transZ, transZR, transZRP, and cisZ isomers. Since deuterated standards were not commercially available for cis-CKs, levels of these compounds were quantified using the recovery of the corresponding DHZ-CK deuterated standard. Frozen

64 tissue was homogenized in pre-cooled (-20 C) modified Bieleski #2 extraction buffer

(Methanol: Water: Formic Acid; CH3OH:H2O:HCO2H [15:4:1, v/v/v]) using a ball mill grinder and zirconium oxide grinding beads (Comeau Technique Ltd., Vaudreuil-Dorion,

Canada; 25 mZ, 5 minutes, 4 C) for tissue ~0.25 g or less. Stainless steel grinding cylinders were used for tissue greater than ~0.25 g (25 mZ, 30 seconds, 4 C, Retsch

MM300). Following tissue homogenization samples were sonicated, vortexed and allowed to extract passively overnight at -20 C for approximately 12 h. Following overnight extraction, samples were centrifuged at 8400 x g for 10 minutes (Sorvall ST 16

Centrifuge or Fisher Scientific Centrifuge at maximum speed) and the supernatant collected. Pellets were re-extracted and allowed to extract passively in modified Bieleski

#2 extraction buffer for 30 minutes at -20 C. Samples were centrifuged as above and pooled supernatants were dried in a speed vacuum concentrator at ambient temperature

(Savant SPD111V, UVS400, Thermo Fisher Scientific, Waltham, MA). Dried samples were stored at -20 C until use. Dried supernatant residues were reconstituted in 1 mL of

1M HCO2H, to allow for complete protonation of CKs, and subjected to solid phase extraction (SPE) on a mixed mode, reverse-phase/ cation-exchange cartridge (Oasis

MCX 6 cc; Waters, Mississauga, Canada). Cartridges were activated with 5 mL CH3OH and equilibrated with 5 mL 1M HCO2H. Following equilibration the sample was loaded and washed with 5 mL 1M HCO2H. ABA was eluted first using 5 mL CH3OH. CKs were eluted based on their chemical properties, with CK nucleotide forms eluted second, using 5 mL 0.35 M ammonium hydroxide (NH4OH) followed by riboside, free base, methylthiol, and glucoside CK forms eluted using 5 mL 0.35 M NH4OH in 60% CH3OH.

Collected fractions were evaporated to dryness and stored at -20 C.

CK nucleotides were reconstituted in 1 mL 0.1 M ethanolamine-HCl (pH 10.4) and dephosphorylated to form ribosides using 3.4 units of bacterial alkaline phosphatase

(Sigma, Oakville, Canada) for 12 h at 37 C. Resulting CK ribosides were evaporated to dryness in a speed vacuum concentrator at ambient temperature. Due to the need for nucleotide to riboside conversion for detection purposes, resultant nucleotide data potentially reflects pooled contribution of mono, di- or tri- phosphates as the isopentenyl or hydroxylated moiety can be transferred to an AMP, ADP or ATP (Quesnelle and

Emery 2007) this is represented in the current study by using iPRP, DHZRP, transZRP and cisZRP to represent the respective pooled nucleotide data for that particular analyte.

Dephosphorylated nucleotides were reconstituted in 1.5 mL Milli-Q H2O and further purified using a reversed-phase C18 SPE column (Oasis C18 3 cc; Waters, Mississauga,

Canada). Column activation and equilibration were carried out using 3 mL CH3OH and 6 mL Milli-Q H2O, respectively. Samples were loaded and allowed to pass through the column under gravity. The sorbent bed was washed with 3 mL Milli-Q H2O and samples were eluted using 1.5 mL CH3OH. Samples were dried in a speed vacuum concentrator and stored at -20 C until analysis.

Purified fractions of ABA, CK nucleotides, CK ribosides/ free base/ methylthiol/ glucosides were reconstituted in 1.5 mL of initial HPLC mobile phase conditions (95:5

H2O: CH3OH with 0.08% acetic acid (CH3CO2H)) for ABA and (95:5 H2O: Acetonitrile

(C2H3N) with 0.08% CH3CO2H) for CKs. Samples were transferred to glass auto- sampler vials and stored at 4 C until analysis.

HPLC-ESI MS/MS methods with multiple reaction monitoring (MRM) channels, specific for each analyte, were carried out as described in Ross et al. (2004) and Farrow

66 and Emery (2012). Detection limits were as listed in Farrow and Emery (2012). Samples were analyzed and quantified by HPLC-ESI MS/MS (Agilent 1100 series HPLC connected to a Sciex Applied Biosystem 5500 API mass spectrometer) with a turbo V- spray ionization source. A 20 L sample was injected onto a Luna C18 reverse-phase

HPLC column (3 m, 150 x 2.0 mm; Phenomenex, Torrance, CA, U.S.A.); all ABA samples were analyzed in negative-ion (ESI-) mode and all CK samples were analyzed in positive-ion (ESI+) mode. ABA was eluted using component A: H2O with 0.08%

CH3CO2H and component B: CH3OH with 0.08% CH3CO2H, at a flow rate of 0.2 mL

-1 minute . CKs were eluted using component A: H2O with 0.08% CH3CO2H and

-1 component B: C2H3N with 0.08% CH3CO2H, at a flow rate of 0.2 mL minute . Initial conditions for the ABA fraction were 50% B changing on a linear gradient to 80% B over

8 minutes. This ratio was then held constant for 2 minutes before returning to starting conditions and equilibrating for 8 minutes. The CK fractions were eluted using a multistep gradient. Starting conditions were 5% B increasing linearly to 95% B over 17 minutes. 95% B was held constant for 5 minutes before returning to starting conditions for 18 minutes.

Data analysis

Data sets were analyzed using Analyst (v. 1.5) software (AB SCIEX, Concord, Canada).

ABA and CKs were identified based on their MRM channels and retention times.

Analyte concentrations were determined using isotope dilution analysis based on direct comparison of the endogenous analyte peak area to that of the recovered internal standard

(Jacobsen et al., 2002). Final hormone concentrations were normalized to the initial fresh

67 weight of the sample. Statistical analysis was carried out using an analysis of variance

(ANOVA) with the Tukey-Kramer post-hoc test, which takes unequal sample size into account. Significant differences refer to a p-value of <0.05. Where appropriate Student t-tests were also conducted (two tailed, assuming unequal variance). In the case of ABA analysis, data points were subjected to the Grubb’s test for outlier detection.

RESULTS

Disease progression and tissue sampling

Disease symptoms were monitored and recorded over the course of 28 days. Multiple tissue samples were taken at each time point from the mock-infected (control), the dikaryon and the solopathogen injections. While effort was taken to prevent kernel pollination, in some cases cobs had a mix of fertilized and unfertilized kernels.

Snetselaar et al. (2001) noted that kernel pollination was not necessary for U. maydis infection and may actually interfere with fungal development. An effort was made to collect only unfertilized tissue from control cobs, as this was thought to be more representative of the tissue that would be infected by U. maydis. During the early stages of disease, small, white, disorganized galls were visible (day 10) (Fig. 3.1). Gall enlargement had begun by day 13 and in most cases by day 16 the tumours took on a grey appearance. In some cases, exposed U. maydis tumours also became green or purple in appearance. By day 20, enlarged tumour tissue was darkened by the development/maturation of teliospores within the tissue. By days 24-28 most tumour tissue had begun to dehydrate. All opened or harvestable cobs were tracked to evaluate the progression of disease. Samples selected for hormone analysis were those in which

68 cob tissue developed disease symptoms. Because of the nature of the experiment, which included destructive and repeated sampling, any cob with secondary infection was discarded. Tissue sample numbers ranged from 2-15, and were determined by the day during which samples were taken, the treatment type and the presence of diseased tissue.

During early time points, infection differences were qualitatively observed between the dikaryon and solopathogen strains. Dikaryon infected tissue resulted in tumours that were larger and more bulbous than those from the solopathogen treatment (Fig. 3.1, day

10-16). Infection percentages were determined for the dikaryon and solopathogen treatments, and these were based on whether an individual cob contained tumours that could be harvested for hormone analysis. The dikaryon had 57% harvestable cobs whereas the solopathogen had 38%.

Abscisic acid

Tissue samples were extracted and analyzed for the presence of ABA by HPLC-ESI (-)

MS/MS. ABA was present in all treatments at all time points. The control treatment ranged from 29.84 pmol g-1 FW at day 10 to 794.62 pmol g-1 FW at day 28 (Fig. 3.2).

The dikaryon treatment reached its highest level of ABA content at day 13 (574.23 pmol g-1 FW), which was greatly reduced by day 16 with subsequent days ranging from 70.2 pmol g-1 FW to 231.84 pmol g-1 FW (days 20 and 28 respectively). The solopathogenic treatment showed an increase in ABA levels at day 13 (732.13 pmol g-1 FW), followed by a gradual decrease in total ABA (Fig. 3.2). Significant differences were detected between the solopathogen and other treatments at day 16 (Tukey Kramer p<0.05) and between the control tissue and infected tissue at days 24 and 28 (Tukey Kramer p<0.05).

Cytokinins

Total CKs, comprised of individual CK types and forms, were extracted from collected tissue and quantified. CKs were grouped based on their known function or structure into one of three categories: CK glucosides, methylthiol (2MeS) CKs, or freebase, riboside and nucleotide (FBRNT) CKs. The structures for these grouped CKs are shown in Fig.

3.3. Those CKs shown in Fig. 3.3 represent all compounds scanned for on the HPLC-ESI

MS/MS (excluding aromatic CKs) including those that were undetected. CK glucosides are considered inactive CK forms (Sakakibara 2006), and were grouped to include the following analytes: DHZOG, DHZROG, DHZ9G, transZOG, transZROG, transZ9G, cisZOG, cisZROG, and cisZ9G (iP9G and 7Gs were not detected in this study).

Methylthiol CKs are modified at C2 with the addition of a methylthiol group (Sakakibara

2006) (Fig. 3.3b) and, for this study 2MeSCKs included the following analytes: 2MeZR,

2MeSZ, 2MeSiPR, and 2MeSiP. FBRNT CKs represent the putatively active CK forms and their immediate precursors. In this study, the FBRNT CK grouping included the following analytes: iP, iPR, iPRP, DHZ, DHZR, DHZRP, transZ, transZR, transZRP, cisZ, cisZR, and cisZRP. Analyte concentrations are found in Tables 3.2, 3.3 and 3.4 for the mock-infected control, dikaryon and solopathogen infected tissues. No aromatic CKs were detected in any tissue type and were therefore not listed in Tables 3.2, 3.3 and 3.4.

CK glucosides represented 93% (day 10) to 99% (days 13, 20 and 28) of the total

CKs found in control tissue (Table 3.2). During dikaryon infection, glucosides represented the main CK type during early stages of infection at 81% and 82% at days 10 and 13. The relative amount of glucosides decreased at day 16 (65%) and was lowest at

70 day 28 (47%) (Table 3.3). Methylthiol CKs (2MeSCKs) represented a small percentage of the total CK levels, and were present only in later stages of infected tissue, starting at day 20 (Tables 3.3 and 3.4). FBRNT CKs increased during dikaryon infection, representing over 50% of all CKs during later stages of infection (days 24, 28). During solopathogenic infection glucosides represented 73%-89% of the total CK level, whereas

FBRNT CKs represented less than 17% of the total CKs detected during the time course, differing from the increased representation of FBRNT CKs noted in the dikaryon infection (days 10-24; Table 3.4). The following sections describe the dynamics of each

CK grouping.

CK glucosides. Total glucosides were compared between all treatments at each time point (Fig. 3.4), with the control tissue maintaining the highest level of total glucosides throughout the time course. Total glucoside levels were significantly different between the control tissue and dikaryon tissue on days 16, 20, 24 and 28 (Tukey-Kramer p<0.05), and differences between the control tissue and solopathogen tissue were also noted at days 20 and 28 (Tukey-Kramer p<0.05).

Glucosides were further separated, based on the location of glucosylation, into O- glucosides (DHZOG, DHZROG, transZOG, transZROG, cisZOG, cisZROG) and N- glucosides (DHZ9G, transZ9G, cisZ9G; Fig. 3.3c), which revealed distinct profile changes within the tissues examined. O-glucosides can be readily cleaved by - glucosidase and act as stable storage forms of CKs, whereas N-glucosides are thought to be irreversibly modified or inactive, as they are not cleaved by -glucosidase (Sakakibara

2006, Spichal 2012). Control tissue had higher levels of N-glucosides (>65% of total glucosides), specifically transZ9G and cisZ9G throughout most of the time course (Table

3.2). Whereas infected tissue showed a reduction in N-glucoside forms, particularly transZ9G and cisZ9G, relative to the control tissue, while having a higher representation of O-glucoside forms during days 10-20 (Tables 3.2, 3.3 and 3.4). Within infected tissue cisZ9G and cisZROG represented the majority of detected glucosides (Tables 3.3 and

3.4).

Methylthiol CKs. Methylthiol CKs (2MeSCKs) were analyzed in the control, dikaryon and solopathogenic tissue (Fig. 3.5). 2MeSCKs were not detected in control tissue at any time point; however they were detected in infected dikaryon and solopathogenic tissue beginning at day 20 (Fig. 3.5). Total 2MeSCK levels increased after their initial detection at day 20 in both dikaryon and solopathogenic tissue. Significant differences were detected between the dikaryon tissue, and other tissues at day 20 (Tukey-Kramer p<0.05). Differences between the dikaryon and solopathogen infections were detected at day 24 and 28 (two tailed Student t-test assuming unequal variance p<0.05). Total

2MeSCKs in the dikaryon tissue ranged from 2.84 pmol g-1 FW at day 20 to >16 pmol g-1

FW for days 24 and 28, whereas solopathogenic tissue maintained low levels <4.5 pmol g-1 FW throughout the time course. 2MeSZR was the abundant 2MeSCK present in the infected tissue (Tables 3.3 and 3. 4).

FBRNT CKs. Total free base, riboside and nucleotide (FBRNT) CKs varied among treatments throughout the time course. Specifically, in the control tissue, total FBRNT

CKs maintained a concentration between 8 pmol g-1 FW and 26 pmol g-1 FW (Fig. 3.6).

CK levels were elevated in infected tissue relative to the control as the infection time course progressed. Dikaryon infected tissue had FBRNT levels significantly higher than control tissue at days 13-28 (Tukey-Kramer p<0.05), and significantly higher from

72 solopathogen tissue at days 20-28 (Tukey-Kramer p<0.05) (Fig. 3.6). The major FBRNT

CKs found in the tissue samples were the nucleotide forms, followed by the ribosides, with low representation of the free base form across all treatments and time points (Fig.

3.6). Further dividing FBRNTs into FBR forms, significant differences were detected at day 10 and 16 between the control and infected tissues (Tukey-Kramer p<0.05).

Differences were also detected at day 20 between the dikaryon and other tissues (Tukey-

Kramer p<0.05). While relatively low in total CKs, cisZRP represented the major

FBRNT CK in control tissue (>50%) for all time points with the exception of day 28

(Table 3.2). Infected tissue showed an accumulation of cisZRP and cisZR during the course of infection, with a 27-fold increase in cisZR levels in the dikaryon infection and a

9-fold increase in cisZR levels for the solopathogenic infection between days 10 and 28

(Tables 3.3 and 3.4). cisZ-isomer CK types constituted the majority of the total FBRNT

CK pool in infected tissue as time progressed. iPCKs were found only in infected tissue starting at day 10 (Tables 3.2, 3.3 and 3.4) and increased in the dikaryon infection during the time course (Tables 3.3 and 3.4).

DISCUSSION

During host pathogen interactions CKs aid in the creation of nutrient sinks, as well as the formation of green islands or galls, whereas abscisic acid has been conflictingly implicated in increased host susceptibility as well as host resistance (Ashby 2000,

Jameson 2000, Audenaert et al., 2002, Ton et al., 2009). During U. maydis infection the formation of characteristic tumours is thought to be initiated by the release of fungal effectors whereas tumour expansion is likely dependant on plant hormones (Kämper et

73 al., 2006, Walbot and Skibbe 2010). The knowledge that U. maydis produces phytohormones and that it induces different host responses in different tissues suggested the need to examine CK and ABA levels in infected cobs (Skibbe et al., 2010, Bruce et al., 2011, Gao et al., 2013). Tumour tissue collected at specific time points during dikaryon and solopathogen infection revealed slightly elevated levels of ABA, reduced

CK glucosides, presence of 2MeSCKs, and dramatic increases in specific FBRNT CKs.

These distinct alterations in the phytohormone profile indicated that U. maydis uses phytohormone manipulation as one of its approaches to modulate the plant host’s physiology.

U. maydis cob infection leads to phenotypic differences between two strains and among tissue collections

Dikaryon and solopathogen infections differed in pathogenic development and phytohormone levels. Tumour formation progressed similar to that outlined in Pataky and Snetselaar (2006) with slightly reduced virulence, or less pronounced visual symptoms in the solopathogen infections relative to the dikaryon infection at early time points (days 10-16).

This variability in virulence between the dikaryon and other U. maydis strains is consistent with previous observations by Babu et al. (2005) (dikaryon vs. diploid) and the

Saville Lab (Fig. S3.1, dikaryon vs. solopathogen) in corn seedling infections. The differences in phytohormone levels noted in the current study provide a possible link between strain type and virulence level in the U. maydis- Z.mays interaction.

Virulence differences have been noted between strains, yet the severity of U. maydis cob tumour formation can also be influenced by the time of inoculation and pollination (Pataky and Chandler 2003). In order to control for pollination, corn was detasseled in the current study. Snetselaar et al. (2001) noted that when cobs were shielded from pollen they were more susceptible to U. maydis infection. Pollination may act to protect ovaries from infection due to the formation of an abscission zone at the base of the silk preventing multiple pollen tubes from reaching the ovary and inhibiting U. maydis entrance into the ovary (Snetselaar et al., 2001). Furthermore, fertilized seeds yield a very distinct CK profile from unfertilized ovules (Rijavec et al., 2011). For these reasons careful visual inspection of the cob was done in order to exclude potentially fertilized seeds from the control analysis, as unfertilized tissue more accurately represented the tissue that would be infected by U. maydis. Moreover, consistent sampling times-of-day were used to control for potential fluxes in CK diurnal levels

(Novakova et al., 2005).

Hormone profiling

ABA levels are elevated in infected tissue. ABA plays a key role in plant development including seed dormancy and response to abiotic and biotic stressors (Audenaert et al.,

2002, Mauch-Mani and Mauch 2005, Schmidt et al., 2008, Rodriguez-Gacio et al., 2009).

Increased levels of ABA have been associated with elevated susceptibility of plants to pathogen attack (Audenaert et al., 2002; reviewed in Cao et al., 2011); however callose deposition stimulated by ABA can also provide a degree of resistance (Mauch-Mani and

Mauch 2005). The role of ABA in host-pathogen relations is influenced by the infection

75 strategy of the pathogen and the infection stage at which it is triggered (Ton et al., 2009).

Hence ABA’s role in pathogen infection is finely balanced. In the current study the increase in ABA at earlier time points (day 10, Fig. 3.2) in U. maydis disease development suggests a possible role for ABA in initiating host susceptibility and tumour expansion. Increased ABA levels due to exogenous application or fungal production have resulted in increased susceptibility of the tomato plant to Botrytis cinerea infection

(Audenaert et al., 2002), and rice to Magnaporthe grisea infection (Jiang et al., 2010).

U. maydis is capable of producing ABA, and ABA levels were elevated at 14 dpi during corn seedling infection (Bruce et al., 2011). This increased susceptibility associated with

ABA may also be due to the complex interaction and cross-talk between many phytohormones (Xu et al., 2013). Studies have detected an antagonistic interaction between ABA and salicylic acid (SA) which influences host susceptibility. SA production is an important defense response strategy for plants and is commonly associated with defense against biotrophic pathogens (Xu et al., 2013). Pre-treatment of plants with ABA results in the suppression of the SA pathway. SA suppression has been detected during the interaction between Magnaporthe grisea and rice (Jiang et al., 2010),

Arabidopsis thaliana and Pseudomonas syringae pv.tomato (Mohr and Cahill 2007),

Xanthomonas oryzae pv. Oryzae and rice (Xu et al., 2013) among others resulting in increased host susceptibility. Suppression of plant SA appears to play a minor role in U. maydis virulence (Doehlemann et al., 2008b, Djamei et al., 2011) and deletion of an U. maydis SA-degrading enzyme, salicylate hydroxylase, does not appear to impact virulence during corn seedling infection (Rabe et al., 2013). Many complex interactions occur between phytohormone systems; manipulation of these by the pathogen can greatly

76 influence plant immunity (Xu et al., 2013). The proposed initial suppression of host defenses through elevated ABA levels, as seen in the current study, is consistent with development within the U. maydis– Zea mays pathosystem.

During the dikaryon infection ABA levels were elevated above control levels at day 13 and quickly decreased by day 16. This pattern is modified in the solopathogen infection as ABA levels were >2 fold higher than the dikaryon at day 16 and were higher than the dikaryon infection from days 13-20. The higher level of ABA in the solopathogen infection may play a role in the virulence reduction noted during the time course. Elevated levels of ABA are known to result in decreased cell division in normal maize seed development and can also trigger other plant hormone defense responses when produced later on in the infection process (proliferation stage) (Myers et al., 1990,

Ton et al., 2009). The mock-infected control follows a different pattern for ABA accumulation when compared to the infected tissue. In control tissue, ABA levels gradually increased. During normal seed development, increases in ABA facilitate the maintenance of seed dormancy (Jones and Setter 2000) and two ABA peaks occur during early and late seed maturation stages (Cheng et al., 2014), ABA levels are not typically measured in unfertilized ovules. In this study, the increased ABA level detected in unfertilized ovules was likely due to the natural dessication of the cob.

In the current system ABA may allow for increased susceptibility of the host to U. maydis infection initially, but past a certain point in U. maydis development may actually result in decreased cell division and lower virulence.

CKs in tumour formation. During normal seed development cytokinins act to stimulate cell division and lead to increased organ size and enhanced sink strength (reviewed in

Rijavec et al., 2012). However, during infection, U. maydis does not simply grow within the constraints set for a developing seed, but manipulates and reprograms the already existing sink tissue in order to complete its lifecycle.

In the current study total CKs decreased upon U. maydis infection, due to an overall reduction in CK glucosides (Tables 3.2, 3.3 and 3.4). A similar decrease in total

CKs was also reported by Behr et al. (2012) during Colletotrichum graminicola infection of maize leaves, and was likely due to considerable decreases in O-glucosides. However

U. maydis infection, while resulting in the decrease of CK glucosides, results in the accumulation of more active CK forms and their precursors. By subdividing CKs into groups, as per the current study, changes in the precursor, active, storage and sometimes overlooked CKs (i.e. 2MeSCKs) can more clearly be seen. All of these CKs appear to play an important role in this pathosystem.

CK glucosides. CK glucoside levels decreased considerably during infection, particularly the transZ and DHZ forms, which all but disappeared. cisZ glucoside forms remained relatively high in infected tissue, suggesting that glucosylation was limited to cis-isomers in infected tissue. Notably, the levels of N-glucosides were reduced in infected tissue when compared to the mock-infected control. The reduced glucoside levels in infected tissue may be due to the fungus acting to inhibit the plant’s glucosylation activity by potentially targeting Zea mays N9-glucosyl transferase (ZmCNGT), responsible for N- glucosylation of CKs, or other zeatin-O-glucosyltransferase genes (Martin et al., 2001,

Veach et al., 2003). Changes in CK glucoside balance appear to be highly tissue and pathogen specific. C. graminicola infection of maize leaves results in significant decreases in cisZOG following infection (Behr et al., 2012); whereas in the current study

78 the N-glucosides: transZ9G and cisZ9G were greatly reduced upon cob infection by U. maydis.

Another way in which glucoside balance can be altered is through the activation of -glucosidases (Schafer et al., 2015), which catalyze the deglycosylation of O- glucosides (Sakakibara 2006). -glucosidase activity has been detected in other fungi

(Cooper and Ashby 1998), and -glucosidase genes have been identified in U. maydis with elevated expression levels during corn seedling infection (5 and 13 days post infection; Doehlemann et al., 2008a). One such gene, UMAG_00446, is characterized as a probable -glucosidase, the enzyme commission number (EC) for UMAG_00446 (EC

3.2.1.21) is the same as the identified EC for -glucosidase listed in Spichal (2012). This consistency between UMAG_00446 and listed -glucosidases suggests that this U. maydis enzyme could function to convert the more abundant CK O-glucosides to active

CK free bases or ribosides during the course of infection (Mok and Mok 2001,

Doehlemann et al., 2008a). In the current study transZ derived as well as cisZR CKs increased in dikaryon infected tissue as time progressed (Table 3.3). In this case, the fungus may be hijacking the already existing environs of the plant to increase its sink strength through the release of active CKs.

2MeSCKs. The function of methylthiol CKs (2MeSCKs) is not well understood and very little is known regarding their importance in plant systems. Recent reports have detected

2MeSCKs in various basidiomycete forest fungi (Morrison et al., 2015), and have also highlighted their potential importance in plant-insect-microbe interactions (Giron and

Glevarec 2014). U. maydis is not known to produce 2MeSCKs separate from the plant yet 2MeSCKs have been found as components of the tRNA of all organisms with the

79 exception of Archaea (Persson et al., 1994, Yarian et al., 2002, Spichal 2012). In the current study, 2MeSZR and 2MeSZ accumulated in U. maydis infected tissue during the later stages of infection but were not detected in the control tissue. Little is known about tRNA accumulation/degradation during end stage U. maydis infection. The potential for tRNA accumulation off set by degradation may influence the level of 2MeSCKs detected during the current infection time course. 2MeSZ and 2MeSZR were the more predominant 2MeSCKs detected in the current study, this parallels the findings of

Morrison et al. (2015). Furthermore, pathogenic strains of Rhodococcus fascians contain the same spectrum of CKs as their nonpathogenic counterpart yet with higher levels of

2MeScisZ, iP and cisZ, of which 2MeScisZ and cisZ were found to accumulate in infected Arabidopsis thaliana tissue (Pertry et al., 2009). Little is known about the bioactivity of 2MeSCKs, but the authors suggested that 2MeSZ may be less cytotoxic than other classic cytokinins and therefore this may account for its accumulation during infection (Pertry et al., 2009). The low but consistent presence of 2MeSCKs may be important in eliciting plant responses during disease development (Giron and Glevarec

2014). The similar accumulation of 2MeSCKs in U. maydis infected tissue may be functionally based in the fact that they are less cytotoxic to the plant or they may also evade attempts by the host to balance CKs through the use of cytokinin oxidase.

Cytokinin oxidase acts to permanently degrade CKs; however, 2MeSZ and cisZ, were found to be poor substrates for 3 apoplastic cytokinin oxidases, permitting their accumulation in tissue (Pertry et al., 2009). Although fungi are capable of producing

2MeSCKs (Morrison et al., 2015) it may be that host-stimulated or fungal-supplied

2MeSCKs, during infection, influence the host cells and permits the continued

80 proliferation of tissue around the site of infection. In the current study the presence of

2MeSCKs in infected tissue may indicate a fungal stimulated origin for these CKs and their importance in promoting tissue proliferation.

FBRNTs. FBRNTs include free base, riboside and nucleotides which respectively represent the active, transport and precursor forms, of these CKs (Sakakibara 2006, Kudo et al., 2010, Behr et al., 2012). In this study they have been grouped together to reflect the importance of the NT-R-FB pathway in eliciting classic CK responses in plants.

Fertilized seeds have a peak in CK levels 6 days after pollination, which is earlier than unfertilized ovules. Fertilized seeds also have CK levels 60 fold higher than unfertilized ovules (Jones and Setter 2000, Rijavec et al., 2011). U. maydis tissue does not mirror the early CK peak seen in fertilized seeds, suggesting that it does not simply mimic a fertilized seed, but instead reprograms the host tissue. FBRNTs, notably cisZRP and cisZR, increased dramatically in dikaryon and solopathogen infected cob tissue relative to the control starting at day 16 (Fig. 3.6). This similar cisZCK accumulation has been detected during maize leaf infection by C. graminicola, corn seedling infection by U. maydis, and Arabidopsis thaliana infection by the bacterium Rhodococcus fascians

(Pertry et al., 2009, Bruce et al., 2011, Behr et al., 2012). CK accumulation is likely dependent on host substrate specificities (Pertry et al., 2009). The abundance of cisZ type CKs in maize (Gajdosova et al., 2011), cytokinin receptors that are responsive to cisZ CKs (Yonekura-Sakakibara et al., 2004), and zeatin-O-glucosyltransferase genes specific to cisZCKs (Martin et al., 2001, Veach et al., 2003), suggests that maize has the capacity to respond to the accumulation of cisZCKs during U. maydis infection.

CK levels did not change dramatically in control tissue during the time course; which supports the approach of this study to only use unfertilized ovules. The high levels of glucosides in the unfertilized control tissue in the current study may reflect a counter- balance to the low levels of FBRNT CKs detected. The accumulation of FBRNTs in infected tissue may also be due to the inhibition of CK degradation which is primarily driven by cytokinin oxidase (CKX) in most plant systems (Brugiere et al., 2003). CKX removes the N6-substituted isoprene chain of CKs or their ribonucleosides to produce adenine and the corresponding aldehyde, thus removing any CK activity (reviewed in

Brugiere et al., 2003). Brefort et al. (2014) found that the Zea mays cytokinin oxidase 3 gene is up-regulated following infection by U. maydis strains in which an effector gene cluster has been deleted; suggesting that during normal infection these effectors act to suppress CK oxidase production. Microarray data from U. maydis infected corn seedlings (Doehlemann et al., 2008b) noted a >3 fold increase in the Zea mays CK receptor: AHK4 histidine kinase receptor, starting at 4 dpi as well as a decrease in a Zea mays potential glycosyltransferase at 2 dpi following U. maydis infection of corn seedlings. These changes in host gene expression profiles suggest that U. maydis is capable of manipulating the host’s CK signaling and storage pathways. Furthermore, during normal Z. mays development CKX levels are higher in the embryo, in order to prevent precocious germination (Jones and Setter 2000). U. maydis appears to take over the role of the embryo, resulting in the collapse of the ovule inside the ovary and a hollow appearance of tumours (Snetselaar et al., 2001). This targeted suppression would effectively hamper the plants ability to control CK balance within the seed, and lead to

82 specific (cis-isomer) CK accumulation; this is supported by the current study’s phytohormone infection profiles.

CONCLUSIONS

This study found that U. maydis infection specifically alters the CK balance within Zea mays, with specific reduction of CK glucosides and increases to cisZCKs, iPCKs and

2MeSCKs. CK accumulation is more dramatic in the dikaryon infection and may account for the greater tumour manifestation seen during this infection. The increased

CK levels may be working to promote sink development, distribution of nutrients and increased cell division, which may effectively reprogram the host tissue resulting in larger tumours. The changes in ABA were not as clear as has been seen previously in U. maydis infected corn seedlings (Bruce et al., 2011). However, ABA accumulation and maintenance during early and later cob infection stages likely requires a delicate balance.

Further study must be done in order to determine if the higher maintained levels of ABA starting at day 16 (in solopathogen infections) can result in heightened plant response and reduced virulence.

CK homeostasis requires a direct balance of the rate of import, biosynthesis, inactivation and degradation (Brugiere et al., 2003). Based on the CK profiles in this study it is hypothesized that the accumulation of specific CKs (cytokinin-mix strategy)

(Giron and Glevarec 2014), induction of fungal -glucosidase, as well as the manipulation of cytokinin oxidase and CK-glucosylation activity in the plant, play a role in the resulting CK accumulation and tumour development in infected tissues. U. maydis, through various factors, including the modulation of phytohormones, effectively hijacks

83 and reprograms the host tissue. CK biosynthesis genes have been identified in U. maydis and are currently under investigation (Morrison et al., 2015). Examination of CK biosynthesis genes in other fungi including the ergot fungus Claviceps purpurea, indicated that deletion of an isopentenyltransferase fused ‘lonely guy’ gene (ipt-log) and a p450 monooxygenase gene (involved in the hydroxylation of the isopentenyl side chain) specifically impacts transZ production; however, it has no impact on pathogenesis during infection of rye plants (Hinsch et al., 2015). CKs secreted by fungi also impact other phytohormone pathways; for example, during interactions between Magnaporthe oryzae and rice, CK secretion by the fungus enhances the SA defense response of the rice plant.

This highlights the fact that a fine balance of multiple phytohormone systems is necessary for successful pathogen establishment (Jiang et al., 2013). We postulate that the ability of U. maydis to synthesize CKs (Bruce et al., 2011) and specifically manipulate cisZ CK levels, influences the establishment and pathogenicity of this interaction. Furthermore, fungal CK accumulation likely stimulates CK signaling and metabolism genes within the host plant as seen in other systems (Jiang et al., 2013,

Hinsch et al., 2015, and others). All of these factors play a role in U. maydis pathogenicity, and further identify potential target genes that may be important to examine within the context of U. maydis and Z. mays CK metabolism.

TABLES AND FIGURES

Table 3.1. Tissue sampling for phytohormone analysis. Days Post Injected Number of Cobs Newly opened Total Infection strain sampled Cobs samples (n) 10 Control 2 2 2 FB1xFB2 2 2 2 SG200 2 2 2 13 Control 3 1 3 FB1xFB2 3 1 3 SG200 3 1 3 16 Control 4 2 4 FB1xFB2 4 1 4 SG200 4 2 4 20 Control 6 1 6 FB1xFB2 5 1 5 SG200 4 0 5 24 Control 3 0 3 FB1xFB2 6 1 11 SG200 4 0 5 28 Control 4 1 4 FB1xFB2 8 2 15 SG200 4 0 6

Table 3.2. Cytokinin concentrations (pmol g -1 FW) in mock-infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Mock-infected control dpi 10 13 16 20 24 28 n 2 3 4 6 3 4 Free base iP DHZ transZ cisZ Riboside iPR DHZR 0.894 ± 0.178 1.316 ± 0.473 1.298 ± 0.347 0.232 ± 0.232 transZR 0.766 ± 0.591 cisZR 0.781 ± 0.399 0.901 ± 0.901 0.435 ± 0.435 6.643 ± 1.916 Nucleotide iPRP DHZRP transZRP 11.637 ± 11.637 2.232 ± 1.844 3.360 ± 1.145 2.196 ± 1.693 5.063 ± 2.540 7.323 ± 4.438 cisZRP 13.408 ± 6.592 8.541 ± 3.200 8.408 ± 1.842 5.387 ± 1.561 5.196 ± 1.007 7.287 ± 1.762 Glucoside iP7G iP9G DHZOG 33.433 ± 0.599 49.700 ± 8.251 39.251 ± 6.734 87.827 ± 19.847 56.571 ± 11.410 186.302 ± 58.786 DHZROG 10.181 ± 10.181 130.352 ± 50.510 53.194 ± 25.736 146.892 ± 68.871 10.808 ± 10.808 554.287 ± 354.411 DHZ9G 6.251 ± 4.365 9.333 ± 3.162 8.201 ± 2.958 13.351 ± 3.831 7.499 ± 2.585 23.176 ± 8.332 transZOG 1.289 ± 1.289 3.364 ± 1.115 1.280 ± 0.918 transZROG transZ9G 102.735 ± 35.905 356.656 ± 216.054 242.197 ± 75.138 353.577 ± 71.406 181.965 ± 64.293 407.302 ± 198.627 cisZOG 5.407 ± 5.407 2.617 ± 1.660 cisZROG 15.978 ± 8.585 112.918 ± 47.038 93.553 ± 46.092 108.389 ± 49.763 23.611 ± 10.991 91.305 ± 53.553 cisZ9G 151.646 ± 47.509 330.692 ± 60.193 405.499 ± 123.200 322.048 ± 42.930 352.297 ± 29.230 504.984 ± 65.255 Methylthiol 2MeSZR 2MeSZ 2MeSiPR 2MeSiP Values are means ± standard error (SE) (n=2-15) at specific days post infection (dpi). Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE.

Table 3.3. Cytokinin concentrations (pmol g -1 FW) in U. maydis dikaryon infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Dikaryon (FB1xFB2) dpi 10 13 16 20 24 28 n 2 3 4 5 11 15 Free base iP 0.725 ± 0.725 3.867 ± 1.335 1.410 ± 0.969 DHZ transZ 2.845 ± 1.760 8.447 ± 2.166 12.101 ± 2.955 20.164 ± 5.771 cisZ 1.023 ± 0.608 0.196 ± 0.196 1.663 ± 0.505 Riboside iPR 3.540 ± 1.377 2.260 ± 0.807 4.748 ± 1.557 7.066 ± 1.429 12.092 ± 3.084 20.273 ± 3.914 DHZR 0.993 ± 0.384 0.650 ± 0.259 0.178 ± 0.071 0.359 ± 0.163 0.680 ± 0.366 transZR 2.545 ± 2.545 0.778 ± 0.091 0.750 ± 0.204 0.404 ± 0.118 1.008 ± 0.218 2.007 ± 0.383 cisZR 3.895 ± 2.062 5.090 ± 0.829 13.081 ± 3.806 37.268 ± 5.463 69.589 ± 17.792 108.695 ± 25.004 Nucleotide iPRP 7.131 ± 2.470 2.837 ± 1.439 12.612 ± 3.654 12.297 ± 2.722 13.665 ± 2.258 15.622 ± 4.402 DHZRP transZRP 25.780 ± 22.862 5.323 ± 0.841 4.010 ± 1.155 1.566 ± 0.309 1.533 ± 0.256 2.112 ± 0.444 cisZRP 9.673 ± 1.850 31.596 ± 10.957 91.997 ± 21.851 140.087 ± 24.705 178.246 ± 26.170 203.240 ± 40.095 Glucoside iP7G iP9G DHZOG 0.251 ± 0.251 0.213 ± 0.213 DHZROG 24.643 ± 11.293 32.723 ± 3.358 32.638 ± 2.931 23.804 ± 5.304 19.218 ± 2.806 27.221 ± 4.876 DHZ9G transZOG 0.016 ± 0.016 transZROG 0.150 ± 0.150 transZ9G 3.087 ± 3.087 3.778 ± 0.539 4.651 ± 0.921 5.760 ± 1.338 6.370 ± 1.172 13.909 ± 3.055 cisZOG cisZROG 145.494 ± 81.046 152.440 ± 33.993 171.386 ± 32.640 122.555 ± 20.715 121.681 ± 24.195 167.706 ± 29.310 cisZ9G 59.823 ± 45.756 34.579 ± 4.953 39.088 ± 12.088 57.224 ± 7.402 101.084 ± 27.120 133.917 ± 15.054 Methylthiol 2MeSZR 2.839 ± 1.009 10.657 ± 3.531 11.058 ± 3.425 2MeSZ 7.777 ± 2.779 4.911 ± 1.297 2MeSiPR 0.048 ± 0.048 0.157 ± 0.128 2MeSiP Values are means ± standard error (SE) (n=2-15) at specific days post infection (dpi). Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE.

Table 3.4. Cytokinin concentrations (pmol g -1 FW) in U. maydis solopathogen infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Solopathogen (SG200) dpi 10 13 16 20 24 28 n 2 3 4 5 5 6 Free base iP 0.681 ± 0.681 DHZ transZ 1.618 ± 1.177 1.210 ± 1.210 cisZ 0.675 ± 0.418 0.606 ± 0.606 Riboside iPR 6.639 ± 1.205 5.473 ± 2.527 5.266 ± 2.290 1.125 ± 0.729 2.989 ± 1.867 4.231 ± 2.730 DHZR 1.298 ± 0.001 0.512 ± 0.140 0.402 ± 0.159 transZR 0.456 ± 0.456 2.041 ± 0.780 1.192 ± 0.412 1.239 ± 0.626 0.290 ± 0.165 0.381 ± 0.206 cisZR 4.737 ± 0.818 6.577 ± 1.506 9.766 ± 1.614 6.625 ± 0.589 17.296 ± 7.172 43.776 ± 14.370 Nucleotide iPRP 5.753 ± 1.152 12.449 ± 4.122 2.996 ± 1.284 1.746 ± 1.075 1.555 ± 1.049 DHZRP 1.070 ± 1.070 3.553 ± 2.248 transZRP 2.150 ± 0.960 6.472 ± 2.959 4.638 ± 2.185 6.085 ± 3.121 0.590 ± 0.457 0.977 ± 0.902 cisZRP 9.552 ± 4.151 13.696 ± 5.122 40.350 ± 9.122 40.066 ± 10.466 36.132 ± 10.872 49.930 ± 8.874 Glucoside iP7G iP9G DHZOG DHZROG 4.965 ± 4.965 35.314 ± 4.853 53.615 ± 10.033 51.055 ± 6.515 22.559 ± 3.466 12.849 ± 4.752 DHZ9G transZOG transZROG transZ9G 37.648 ± 34.977 5.543 ± 3.849 6.320 ± 2.562 2.803 ± 0.801 5.597 ± 1.744 7.973 ± 1.497 cisZOG cisZROG 115.323 ± 12.890 240.574 ± 12.735 284.930 ± 41.237 225.570 ± 23.700 179.474 ± 60.483 109.364 ± 18.227 cisZ9G 31.344 ± 7.821 60.714 ± 19.536 58.718 ± 5.551 81.739 ± 21.534 168.372 ± 26.592 172.959 ± 14.869 Methylthiol 2MeSZR 0.397 ± 0.257 2.275 ± 0.987 4.468 ± 1.565 2MeSZ 1.104 ± 0.816 2MeSiPR 2MeSiP Values are means ± standard error (SE) (n=2-15) at specific days post infection (dpi). Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE.

Fig. 3.1. Representative time course of disease progression for Zea mays- U. maydis cob assay. (a) Mock-infected controls (b) Dikaryon (FB1 x FB2) infected (c) Solopathogen (SG200) infected. Days post infection (dpi) appear in the top right-hand corners of individual photographs.

Fig. 3.2. Abscisic acid concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). n=2-15, error bars represent standard error (SE). Letters denote significant differences within time points (ANOVA and Tukey-Kramer post hoc analysis, p<0.05).

Fig. 3.3. Representative CK structures for analytes detected/scanned for, in the Zea mays- U. maydis cob assay time course. (a) Free base, riboside, nucleotide CKs (b) Methylthiol CKs (c) CK glucosides including O-glucosides (left) and N-glucosides (right). Green boxes indicate addition of side chains; large green boxes show the different side chains. Blue boxes indicate the structure of glucose and location of

91 glucosylation for O-glucosides. Red boxes indicate the structure of glucose and location of glucosylation for N-glucosides. Adapted from: Esberg et al. (1999), Sakakibara (2006), Frébort et al. (2011). *The 7G form of these analytes was not scanned for.

Fig. 3.4. Total CK glucoside concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). n=2-15, error bars represent standard error (SE). Letters denote significant differences within time points (ANOVA and Tukey-Kramer post hoc analysis, p<0.05).

Fig. 3.5. Total methylthiol CK concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). n=2-15, error bars represent standard error (SE). Letters denote significant differences within time points (ANOVA and Tukey-Kramer post hoc analysis, p<0.05). Asterisks (*) denote significant differences between the dikaryon and solopathogen infection within time points (two tailed Student t-test assuming unequal variance p<0.05).

Fig. 3.6. Total FBRNT CK concentration (pmol g -1 FW) for control, dikaryon and solopathogen injected cob tissue at specific days post infection (dpi). Total FBRNT is subdivided into the Freebase, Riboside, and Nucleotide forms to show the representation of each form. n=2-15, error bars represent standard error (SE). Letters denote significant differences within time points (ANOVA and Tukey-Kramer post hoc analysis, p<0.05).

SUPPLEMENTARY MATERIAL

Fig. S3.1. Pathogenesis assay for U. maydis infected corn seedlings at 14 days post infection. The dikaryon (FB1x FB2) and solopathogen (SG200) strains of U. maydis were injected into seven day old corn seedlings and pathogenesis scored using the disease symptoms presented in the legend. The percentage of symptom formation is indicated for each treatment. A non-parametric Mann-Whitney U test was conducted to assess statistical significance (p<0.05). Statistical significance is indicated by an asterisk (*). N equals total sample size. Each disease symptom was assigned a numerical value; the average of this is represented by the value associated with the disease index (D.I.).

ACKNOWLEDGEMENTS

The authors declare that they have no conflict of interest. The authors acknowledge

Amanda Charlesworth for data associated with Fig. S3.1.

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CHAPTER 4

PREFACE

Title: Interplay between fungal and plant derived cytokinins is necessary for

normal Ustilago maydis infection of corn.

Authors: Erin N. Morrison, R.J.N. Emery, Barry J. Saville

Reference: Under revision in Plant Pathology: April, 2016

2016 Impact Factor: 2.121

Contributions: ENM, RJN, BJS designed the research; ENM performed the research;

ENM, RJN, BJS wrote the article.

Note: The published version of this manuscript will appear different from the chapter presented here. It is currently under revision to address reviewer comments.

104

CHAPTER 4

Interplay between fungal and plant derived cytokinins is necessary for normal Ustilago

maydis infection of corn.

Under revision in: Plant Pathology (April 2016)

ABSTRACT

Fungal derived phytohormones play a key role in regulating plant-pathogen interactions however deciphering the separate contribution of the pathogen from the plant during infection has been difficult. Here the Ustilago maydis-Zea mays pathosystem was used to investigate this chemical exchange. U. maydis, the causative agent of corn smut, produces cytokinins (CK) which are a group of phytohormones responsible for directing plant development. The characteristic symptom of smut disease is the formation of tumours composed of plant and fungal tissue. Isopentenyltransferase (IPT) catalyzes the rate limiting step in CK biosynthesis and U. maydis strains in which the sole tRNA-IPT gene was deleted no longer produced CKs. These deletion strains elicit fewer, smaller tumours than SG200. High performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI MS/MS) was used to detect and quantify phytohormone levels in infected tissue. This revealed that key hormone changes in

SG200 infections were not present in deletion strains; suggesting that CK production by

U. maydis is required for the altered phytohormone profile in infected tissue relative to uninfected tissue. Separate analyses indicated that U. maydis tRNA-IPT mutants may be altered in their ability to metabolize CKs taken up from the environment. Mining the U. maydis genome identified genes coding putative CK signaling and biosynthesis proteins.

105

A model is presented illustrating how U. maydis CK production may alter Z. mays phytohormone production to facilitate tumour development.

106

INTRODUCTION

Fungal plant-pathogens modify host environments to facilitate their growth and development. In some instances these modifications result in physical manifestations of disease such as green islands, altered reproductive structures or tumour formation

(Walters and McRoberts 2006, Walters et al., 2008). Phytohormones are critical regulators in the normal growth and development of plants. The various classes of plant hormones often interact in a network to bring about developmental change (El Showk et al., 2013). These hormone networks are frequently targeted and manipulated by invading plant-pathogens as a strategy for disease establishment (Nambara and Marion-Poll 2005, reviewed in Tsavkelova et al., 2006, Walters and McRoberts 2006, Hartung 2010 reviewed in Stirk and van Staden 2010, Frébort et al., 2011, Spichal 2012). The hormone target and the mechanism of perturbation varies amongst pathogens (Lopez et al., 2008,

Ton et al., 2009). The presented work focusses on the alteration of cytokinin (CK) and absicic acid (ABA) detected in Zea mays during infection by the corn smut fungus,

Ustilago maydis. The mechanism explored involves U. maydis producing and responding to CKs during disease development, characterized by the production of tumours composed of plant and fungal tissue.

CKs are important modifiers of plant cell division and differentiation (Mok and

Mok 2001). They are adenine derivatives that carry an isoprene-derived or aromatic side chain (Sakakibara 2006). Isoprenoid cytokinins can be grouped based on the nature of their side chain as isopentenyl (iP), dihydrozeatin (DHZ), trans-zeatin (transZ) or cis- zeatin (cisZ) types, and based on their form, as nucleotide, riboside or freebase. The first and rate limiting step in the biosynthesis of isoprenoid cytokinins is catalyzed by

107 isopentenyltransferase (IPT). This is carried out by adenylate-IPT through the methylerythritol phosphate (MEP) pathway or by tRNA-IPT through the mevalonate

(MVA) pathway (Hwang and Sakakibara 2006). These pathways are also referred to as the de novo and tRNA degradation pathways respectively. Investigations into the fungal control of CK production and influence on plant systems have been limited to adenylate-

IPT systems. Hinsch et al. (2015) recently described the deletion of an adenylate-IPT fused lonely guy (LOG) gene in Claviceps purpurea, a biotrophic pathogen of rye; however the deletion of this gene did not abolish CK production by the fungus and had little impact on the overall CK levels within the pathosystem. Since fungal CKs are predominantly produced through the tRNA degradation pathway (Morrison et al., 2015a), focus on a tRNA degradation fungal system as opposed to a de novo derived system would therefore be more representative of most fungi (Morrison et al., 2015a). The tRNA degradation pathway is considered the main source of cisZCKs (Sakakibara 2006).

In contrast to C. purpurea which is transZCK dominated U. maydis synthesizes cisZCKs, separate from its host (Mills and Van Staden 1978, Bruce et al., 2011). Previous research showed that CKs, specifically cisZ isomers accumulate in U. maydis infected corn seedlings and tumour tissue (Bruce et al., 2011, Morrison et al., 2015b). Z. mays itself has CK receptors that respond to cisZCKs and these CKs types accumulate during U. maydis infection (Yonekura-Sakakibara et al., 2004, Bruce et al., 2011, Morrison et al.,

2015b). The presented work uncovers a major role for the tRNA degradation pathway and cisZCKs in the U. maydis-Z. mays pathosystem.

108

U. maydis is a biotrophic fungal plant pathogen which infects its corn host and grows within and between plant cells, eliciting the formation of tumours composed of plant and fungal tissue (Banuett and Herskowitz 1996, Kämper et al., 2006). Although many pathogen induced symptoms can be mimicked through the application of exogenous CKs (Walters and McRoberts 2006) the dramatic tumour development in the

U. maydis- Z. mays pathosystem cannot (Walbot and Skibbe 2010).

During U. maydis infection, a biotrophic interface is formed where the close interaction between the plant and pathogen allows for the transfer of nutrients and assimilates (Horst et al., 2010) including CKs. Another phytohormone, abscisic acid

(ABA) has also been detected as a product from fungi (Crocoll et al., 1991, Nambara and

Marion-Poll 2005, Morrison et al., 2015a). ABA is important in plant stress response as well as maintenance of quiescence in seeds and buds (Tsavkelova et al., 2006) its biosynthesis occurs through the deoxy-xylulose phosphate (DOXP) or MEP pathway and the MVA pathway (Oritani and Kiyota 2003, Nambara and Marion-Poll 2005). Abscisic acid accumulation has been linked to host resistance during infection of Arabidopsis thaliana by Alternaria brassicicola (Flors et al., 2008, reviewed in Lopez et al., 2008), as well as increased susceptibility of the plant to pathogen attack, as in Botrytis cinerea infection of tomato plants and Magnaporthe grisea infection of rice (Audenaert et al.,

2002, Ton et al., 2009, Jiang et al., 2010, Yazawa et al., 2012). In U. maydis infections, the level of CK accumulation is inversely correlated with ABA production at a transition phase in tumour formation (Morrison et al., 2015b), by altering U. maydis CK production this hormone transition may also be affected.

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Investigating the relationship between CK production by U. maydis and the accumulation of other phytohormones requires the ability to produce U. maydis strains that do not synthesize CKs. Genes coding for enzymes predicted to be in the U. maydis

CK biosynthetic pathway were identified and strains were created in which the only candidate isopentenyltransferase gene, tRNA-IPT, was deleted. Phytohormone profiling and pathogenesis assays using a U. maydis solopathogenic strain, SG200, and deletion mutant strains of U. maydis revealed that deletion of tRNA-IPT blocks the fungus’ ability to produce CKs, halts characteristic phytohormone changes (CK and ABA) in U. maydis tumour development, and decreases overall virulence in seedlings and pathogenesis in cobs. This study highlights the importance of fungal derived CKs in the U. maydis- Z. mays pathosystem and begins to tease apart the complex interactions between plant and pathogen hormone systems.

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MATERIALS AND METHODS

Identification of a potential cytokinin biosynthetic gene in Ustilago maydis and its phylogeny

Previously identified isopentenyltransferases (Kakimoto 2003, Frébort et al., 2011; listed in Table S4.1) were used in NCBI non-redundant blastp searches of U. maydis (taxid:

5270) protein sequences (https://blast.ncbi.nlm.nih.gov). Searches were conducted using the BLOSUM62 matrix and default parameters with the exception that max target sequences were limited to 10 and the ‘EXPECT’ was set at E<1e-4.

Phylogenetic analyses were conducted using the IPTs listed in Table S4.1 and the identified tRNA-IPT ortholog in U. maydis. Protein sequences obtained from NCBI were used to identify conserved domains via NCBI Batch-CD

(http://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi). IPT sequences were trimmed to contain just the P-loop_NTPase superfamily domain and these were used in subsequent analyses. Protein sequences were aligned using MAFFT

(http://www.ebi.ac.uk/Tools/msa/mafft) and visualized using Jalview 2.8.2. The MAFFT alignment was entered into ProtTest 3 to identify the best-fit model (Guindon and

Gascuel 2003, Darriba et al., 2011). The best-fit model for phylogenetic analysis was identified as LG+I+G+F. MrBayes 3.2 (Huelsenbeck and Ronquist 2001, Ronquist and

Huelsenbeck 2003) was used to construct a Bayesian consensus tree using an LG+I+G+F model. Default MrBayes parameters were used with the exception ngen=2000000, nchains=4 and samplefreq=200 with a 25% burnin. An unrooted radial tree was visualized using FigTree (http://tree.bio.ed.ac.uk/software/figtree/). Groupings were labeled based on Frébort et al. (2011).

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Strains and culture conditions

The Ustilago maydis solopathogenic haploid strain SG200 (a1 mfa2 bE1bW2); a FB1 derived strain engineered to grow as filaments and cause disease without a mating partner, was obtained from Jörg Kämper (Karlsruhe Institute of Technology, Karlsruhe,

Germany; Bölker et al., 1995, Kämper et al., 2006). SG200 was used as the strain background to create ipt1 deletion mutants. Budding cultures were grown on solid YEPS medium (1% yeast extract, 2% peptone, 2% sucrose) containing agar (2% w/v), supplemented with 20 µg mL-1 phleomycin (InvivoGen) or, for ipt1 deletion strains, 20

µg mL-1 phleomycin and 4 µg mL-1 carboxin (Sigma Aldrich), for 3-4 days at 28-30 C.

Single colonies were inoculated into liquid YEPS medium and grown overnight (28-30

C, 250 rpm), unless otherwise stated.

Creation of an Ustilago maydis ipt1 deletion mutant

Deletion of the ipt1 gene and replacement with a carboxin resistant cassette was carried out following the PCR-based method originally described by Kämper (2004) and further outlined by Morrison et al. (2012). The carboxin cassette was isolated from the pMF1-c plasmid (http://www-public.rz.uni-duesseldorf.de/~mikrobio/plasmids/; Brachmann et al., 2004); obtained from Jörg Kämper (Karlsruhe Institute of Technology, Karlsruhe,

Germany) and used to replace the U. maydis ipt1 gene. Primer sequences for deletion were designed using Primer3 (Rozen and Skaletsky 2000). All procedures were carried out as suggested by the manufacturers unless otherwise stated. Briefly, primers

UM10043LB3FLANK-F and UM10043LB3FLANK-R SfiI, and UM10043

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RB5FLANK-R and UM10043 RB5FLANK-F Sfi1 (Table S4.2) were used to amplify

~1.3 kb regions flanking the ipt1 gene with Phusion High-Fidelity DNA Polymerase

(New England Biolabs). PCR products were purified using the QIAquick PCR

Purification Kit (Qiagen). The carboxin cassette was obtained from plasmid pMF1-c which was purified from Escherichia coli using the GFX Micro Plasmid Prep Kit (GE

Healthcare). E. coli cultures were grown at 37 C on LB plates (1% tryptone, 0.5% yeast extract, 1% NaCl, 2% agar) and in liquid LB shaking at 250 rpm, each containing 100 µg mL-1 ampicillin (Bioshop). pMF1-c and PCR purified flanks were digested with SfiI

(New England Biolabs). Digested products were separated on an agarose gel (1% w/v, 1

X TAE), visualized following ethidium bromide staining, and excised from the gel.

Flanking regions and the ~1.9 kb carboxin resistant cassette were purified using the

QIAquick Gel Purification Kit (Qiagen) and ~0.8 µg of each was ligated overnight at

16°C using T4 DNA ligase (New England Biolabs). The ~4.5 kb fragment containing the flanking sequences and the carboxin resistance cassette was isolated using the QIAquick

Gel Purification Kit (Qiagen) and amplified using nested primers UM10043&FLANK-L and UM10043&FLANK-R (Table S4.2). The resulting ~4.3 kb fragment was used to transform U. maydis; ~1.6 µg of DNA was used per transformation.

Preparation of competent protoplasts

Preparation of competent protoplasts was carried out using a modification of the Wang et al. (1988) and Yee (1998) protocols. Single colonies of SG200 were grown overnight in complete medium (CM; 0.25% casamino acids, 0.15% ammonium acetate, 1% yeast

-1 -1 extract, 1% sucrose, and 62.5 mL L of salt solution composed of: 16 g L K2HPO4, 4 g

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-1 -1 -1 -1 -1 L Na2SO4, 8 g L KCl, 2 g L MgSO4 7dH2O, 1 g L CaCl2 2dH2O, and 8 mL L

-1 -1 -1 trace elements solution [60 ng L H3BO3, 220 ng L MnCl2H2O, 400 ng L ZnCl2, 40

-1 -1 -1 ng L Na2MoO42H2O, 100 ng L FeCl3, 626 ng L CuSO45H2O, pH 7]. 100 µL of culture was inoculated into 100 mL of liquid CM and grown at 30 C, 250 rpm until a minimum OD600 of 1.5 was reached. The 100 mL culture was divided and centrifuged at

2095 x g for 5 minutes (Allegra x 15R Centrifuge, Beckman Coulter). Each pellet was resuspended, by vortexing, in 20 mL of freshly prepared 5 mM EDTA pH 8, 25 mM 2- mercaptoethanol. Cells were then incubated at room temperature (RT) for 20 minutes with gentle shaking (Rocking platform model 100, VWR Scipod). Cells were centrifuged at 2095 x g and resuspended by vortexing in buffer I (1M D-sorbitol, 50 mM sodium citrate, pH 5.8). 5 mL of buffer I with lysing enzyme (1 g lysing enzyme Trichoderma harzianum (Sigma Aldrich)/ 5 mL buffer I) was added and cells were mixed by inversion.

A 5 µL aliquot of the cells was used to monitor spheroplast formation under a light microscope (Zeiss Scope A1, Axio Cam1CM1, Zeiss). During spheroplast monitoring cells were incubated at RT with gentle shaking as above and then centrifuged at 60 x g for 10 minutes. Spheroplast formation continued during centrifugation (Wang et al.,

1988). Spheroplasts were resuspended in 10 mL of buffer I and centrifuged at 60 x g for

10 minutes. Pelleted cells were resuspended in 10 mL of buffer II (1M D-sorbitol, 25 mM Tris-HCl pH 7.5, 50 mM CaCl2) and centrifuged at 60 x g for 10 minutes. Collected protoplasts were resuspended in 2 mL of buffer II and combined. Cell concentration was determined using a 1:10 dilution in buffer II and cells counted using a hemacytometer

(Hausser Scientific). Cells were diluted to ~2 x 108 in buffer II. For each mL of protoplasts 250 µL of 50% polyethylene glycol solution (50% w/v PEG3350 with 25 mM

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Tris-Cl pH 7.5 and 50 mM CaCl2), 60 µL dimethyl sulfoxide, and 10 µL 2- mercaptoethanol was added; protoplasts were stored frozen at -80 C until use.

DNA addition

Ustilago maydis SG200 cells were transformed using the protocol described in Morrison et al. (2012) with the exception that colonies were plated on double complete medium(DCM; 1% casamino acids, 0.3% ammonium acetate, 2% yeast extract, 125 mL

L-1 salt solution pH 7 with 100 mM glucose and 1 M sorbitol, 2% Bacto agar) plates supplemented with 4 µg mL-1 carboxin for ipt1 deletion transformations, and additional transfers to fresh YEPS agar plates containing 4 µg mL-1 carboxin, followed by a final transfer to YEPS agar plates containing 20 µg mL-1 phleomycin and 4 µg mL-1 carboxin.

Screening of ipt1 deletion mutants

Following culturing of ipt1 deletion mutants, genomic isolation was carried out as outlined in Hoffman and Winston (1987). PCR conditions followed the manufacturer’s suggested protocol. Genomic PCR screens were carried out at the ipt1 locus to identify putative transformants. PCR screens used primers located in the ipt1 gene (um10043RT-

ORF-F and um10043RT-ORF-R), in the carboxin resistant cassette and an area outside of the transformed region; pMF1-CARBseqF and um10043LB3FLANK-F, or pMF1-

CARBseqR and um10043RB5FLANK-R (Table S4.2); as well as primers located within and outside the transformed region (Table S4.2). The transformed region was amplified from the ipt1 deletion mutants and sequenced using primers listed in Table S4.2.

Sequencing was carried out as previously described by Ho et al. (2007) using Big Dye

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Terminator chemistry (ABI). Raw sequence data was imported into the SeqManII module of Lasergene v.5.0 (DNASTAR) and trimmed based on sequence quality using default settings. Consensus sequences were created and compared using MEGA M5 and

NCBI blast. RNA was isolated from SG200 and SG200ipt1 putative transformants.

Loss of transcript for ipt1 was confirmed through the absence of RT-PCR amplification using the primer pair (um10043RT-ORF-F and um10043RT-ORF-R) relative to the

SG200 control.

Southern

Total DNA was isolated from SG200 and ipt1 deletion mutant strains. DNA was digested using EcoRI (Invitrogen) and ethanol precipitated as described in Sambrook and

Russell (2001). Digested DNA was electrophoretically separated on a 0.8% w/v agarose gel (1 X TAE) at 50 volts for 21 h. Depurination, DNA transfer and fixation followed procedures as described in Sambrook and Russell (2001) and the supplementary material of the DIG High Prime DNA labeling and Detection Starter Kit 1 (Roche). DNA transfer occurred overnight onto a positively charged nylon membrane (Roche). DNA was bound to the membrane using a UV Cross linker (UVP Laboratory Products, Hybrilinker HL-

2000) and the membrane stored dry at 4 C until use.

The carboxin cassette was amplified from the pMF1-c plasmid using primers pMF1carb(1.8)F and pMF1carb(1.8)R (Table S4.2) and labeled with digoxigenin (DIG) using DIG-High Prime mix as described in DIG High Prime DNA labeling and Detection

Starter Kit 1 (Roche). All procedures for probe labeling, quantification, hybridization and detection were carried out as described by the manufacturer. Membranes were

116 hybridized overnight with the DIG-labeled carboxin probe at 42 C in DIG-Easy Hyb with gentle agitation using Hybridiser HB1D and cylinders (Techne). Two post hybridization washes at RT for 5 minutes in 2 X SSC, 0.1% SDS and two 15 minutes washes at 65 C in

0.5 X SSC, 0.1% SDS were followed by colour development, which was a 2-16 h incubation in NBT/BCIP solution. Colour development was stopped using TE (10 mM

Tris-HCl, 1 mM EDTA, pH 8.0) and membrane stored at 4 C.

Filamentous growth

U. maydis strains (SG200, SG200∆ipt1, SG200∆ipt1 progeny) were streaked from frozen stock onto minimal medium (MM; 0.3% potassium nitrate, 62.5 mL L-1 salt solution, pH

7, 1% glucose) agar plates and DCM agar plates and grown for 2-3 days at 28 C. Single colonies were inoculated into 4 mL liquid MM (for those grown on MM agar plates) or 4 mL liquid DCM (for those grown on DCM agar plates) and grown at 28 C, 250 rpm.

Following overnight growth in DCM or 74 h of growth in MM, cultures were diluted to a final OD600 of 1 and spotted onto DCM agar plates+ charcoal (1%) or MM agar plates+ charcoal (0.1%) respectively to induce filamentous formation as described in Day and

Anagnostakis (1971) and Banuett and Herskowitz (1989). Ten 10 μL aliquots were spotted onto charcoal containing agar plates. All plates were incubated at 28 C and filamentous growth monitored. Fuzz was harvested using a sterile scoopula following 4 days of growth. Fungal tissue was weighed and frozen in liquid nitrogen and stored at

-80 C until phytohormone extraction was carried out. Sterile medium was also collected for phytohormone extraction.

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Plant growth conditions and seedling pathogenesis assays

Growth conditions for corn seedlings were as described in Morrison et al. (2012).

Briefly, Zea mays L. ‘Golden Bantam’ (Ontario Seed Company, Canada) seeds were planted (18 per 20 cm pot) in Sunshine Professional Growing Mix (Mix#1, Sungro

Horticulture Canada). Growth occurred in a Conviron CMP 4030 growth chamber (18 h light, 70% RH, 30 C; 6 h dark, 70% RH, 25 C).

For U. maydis culturing leading to seedling pathogenesis assays, single colonies were grown overnight in liquid YEPS medium. 100 µL of overnight culture was inoculated into 100 mL of YEPS and grown overnight at 28 C, 250rpm. Cultures were diluted to an equivalent final OD600 (1 or 1.5 depending on assay) using sterile dH2O.

~0.5 mL of each U. maydis strain (SG200 and distinct ipt1 deletion mutants) was directly injected into the stem of seven-day-old ‘Golden Bantam’ corn seedlings using a 1 mL syringe and 20 gauge needle. Three pots for each strain were used with approximately 15 plants per pot; a water injected control pot was also included. Progression of disease symptoms was scored at 7, 14 and 21 days post infection (dpi) using a modified 0-6 disease scoring scale based on Gold et al. (1997) and Kämper et al. (2006). Disease ratings included: 0 = no symptoms; 1 = chlorosis and/or anthocyanin; 2 = leaf tumours of any size; 3 = stem tumours <1 mm in diameter; 4 = stem tumours >1 mm not associated with bending of stem; 5 = stem tumours >1 mm associated with bending of infected stem;

6 = plant death. Three independent pathogenesis assays were performed using SG200,

SG200∆ipt1, and SG200∆ipt1 progeny 1 and 2.

Teliospore isolation and germination

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Teliospores were isolated from SG200∆ipt1 infected corn seedlings essentially as described in Zahiri et al. (2005). Isolated teliospores were treated overnight with 1.5%

-1 CuSO4, rinsed and plated onto CM supplemented with 160 µg mL streptomycin

(Bioshop; 2-3 days at 28 C). Single colonies were subsequently patched onto YEPS medium and grown for 2-3 days at 28 C. Colonies were selected and grown on YEPS medium supplemented with 20 µg mL-1 phleomycin and 4 µg mL-1 carboxin.

SG200∆ipt1 progeny (∆ipt1 progeny 1 and 2) were screened using PCR and confirmed using Southern blot analysis to be ipt1 deletion mutants.

Cob infection and tissue sampling

Corn growth, infection and harvesting were done as described in Morrison et al. (2015b).

Briefly, 200 µL of overnight culture was inoculated into 200 mL of YEPS liquid medium and grown overnight (28-30 C, 250 rpm). U. maydis SG200 and SG200∆ipt1 cultures were respectively diluted to an OD600 of 1. 6 mL of diluted U. maydis culture was injected down the silk shaft of detasseled Zea mays L. ‘Golden Bantam’ (Ontario Seed

Company, Canada) cobs using a 10 mL syringe and 18 gauge needle. Mock-infections were injected in the same manner using sterile dH2O.

Tissue samples were taken at 6, 13, 20 and 28 dpi as described in Morrison et al.

(2015b). Sampling of SG200 infected tissue was restricted to tumour tissue whereas

SG200∆ipt1 tissue was collected even if disease symptoms were not present. Tissue was excised from injected cobs using a razor blade, weighed, frozen in liquid nitrogen and stored at -80 C until phytohormone extraction could be carried out. Injected cobs were sampled throughout the time course to provide adequate sample sizes; however sampling

119 did not occur if secondary infection or re-growth from a previously excised region was visible. Samples were separated based on mass required for phytohormone extraction; tissue was pooled within a single cob in order to gain adequate mass for phytohormone extraction. As described in Morrison et al. (2015b) unfertilized ovules from mock- infected controls were used as control tissue. When available, samples were collected from previously unsampled cobs.

Phytohormone extraction and purification

Hormone extraction and purification were carried out as described in Morrison et al.

(2015ab) following modification of Ross et al. (2004) for ABA and Dobrev and Kaminek

(2002) for CKs. Briefly, internal standards were added to enable endogenous hormone quantification through the isotope dilution technique (Jacobsen et al., 2002). Internal

2 standards included 150 ng of labeled ABA ( H4ABA) (PBI, Saskatoon), and 10 ng of the

2 2 2 2 2 2 following CK’s: H7BA, H7BAR, H5ZOG, H7DHZOG, H5ZROG, H7DHZROG,

2 2 2 2 2 2 2 2 H6iP7G, H5Z9G, H5MeSZ, H6MeSiP, H5MeZR, H6MeSiPR, H6iPR, H3DHZR,

2 2 2 2 H6iP, H3DHZ, H6iPRMP, and H6DHZRMP (OlchemIm Ltd., Olomouc, CZ) were added. Due to the fact that labeled cisCKs were not commercially available, quantification of cis-isomers was based off of the corresponding trans-isomers and retention times of unlabeled cisZ in standard runs. Isolated tissue was homogenized in pre-cooled (-20 C) modified Bieleski #2 extraction buffer (CH3OH:H2O:HCO2H [15:4:1, v/v/v]) using a ball mill grinder and zirconium oxide grinding beads (Comeau Technique

Ltd., Vaudreuil-Dorion, Canada; 25 mZ, 5 minutes, 4 C). Extraction, purification and analysis followed methods previously described in Morrison et al. (2015a) for time

120 course analysis and Morrison et al. (2015b) for the remaining tissue extractions. HPLC-

ESI MS/MS methods with multiple reaction monitoring (MRM) channels, specific for each analyte, were carried out as described in Ross et al. (2004) for ABA and Farrow and

Emery (2012) for CKs. Detection limits were as listed in Farrow and Emery (2012).

Data analysis

Statistical analysis was conducted using ‘Real Statistics Using Excel’. A Kruskal-Wallis analysis of variance (ANOVA) coupled with a Dunn multiple-comparison test was conducted for seedling pathogenesis assays. Phytohormone data was analyzed using

Analyst (v1.5) software (AB SCIEX, Concord, Canada). ABA and CK analytes were identified based on their MRM channels and retention times. Direct comparison between endogenous analyte peak area to that of the recovered internal standard was used to determine analyte concentration (Jacobsen et al., 2002). Statistical analysis of phytohormone data was conducted using an ANOVA with a Tukey-Kramer post-hoc test.

For statistical analysis all significant differences refer to a p-value of <0.05.

Identifying putative U. maydis CK signaling and biosynthesis orthologs

Previously identified proteins involved in CK biosynthesis and signaling derived from

Spichal (2012), van der Graaff et al. (2006), Sakakibara (2006), Persson and Bjork

(1993), and Esberg et al. (1999; Table S4.3) were used in blastp searches to identify putative U. maydis orthologs. Many, but not all, of the sequences used as queries were

Arabidopsis thaliana proteins. Query protein descriptions and accession numbers

(according to NCBI) are listed in Table S4.3. These proteins were used in NCBI non-

121 redundant blastp searches against the U. maydis (taxid: 5270) sequence database (July

2015, https://blast.ncbi.nlm.nih.gov). Searches were conducted using the BLOSUM62 matrix and default parameters with the exception that max target sequences were limited to 10 and the ‘EXPECT’ was limited to E<1e-4. For initial searches the Evalue was kept at <1e-4 to permit a larger catchment for putative orthologs across kingdoms. Conserved domains were identified for all query proteins in Table S4.3 using NCBI Batch-CD search (July 2015, http://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi). U. maydis CK biosynthetic enzyme orthologs with similarity to the majority of the conserved domains identified in the query sequence were analyzed using NCBI Batch-

CD searches to identify other domains. In an attempt to ensure reciprocal best blast hits were identified, accession numbers for predicted U. maydis CK biosynthetic enzyme orthologs were used in non-redundant blastp searches against the A. thaliana (taxid:

3702) sequence database. In cases where the original query protein was not of A. thaliana origin a blastp was conducted against the reference organism listed in Table

S4.3. In all cases when the reciprocal best blast hit was confirmed the U. maydis proteins were considered ‘candidate’ CK enzymes. In case where the reciprocal hit was not identified but a related protein was identified these were indicated as ‘possible’ CK enzymes. In cases where similar descriptions to the predicted protein function were not found, those U. maydis proteins were not analyzed further.

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RESULTS

Identifying the tRNA-IPT in U. maydis

Blastp analysis, using bacterial and eukaryotic IPTs (Table S4.1), identified the sole

Ustilago maydis candidate IPT, as UMAG_10043, referred to as “related to a tRNA isopentenylpyrophosphate transferase” by the Munich Information centre for Protein

Sequences (MIPS) Ustilago maydis database (MUMDB; Mewes et al., 2008; http://pedant.helmholtz-muenchen.de). No other IPTs were identified in U. maydis (max target limited to 10 and E<1e-4).

To examine the relatedness of the U. maydis tRNA-IPT to other IPTs from a phylogenetically diverse group of organisms (Table S4.1), trimmed IPT sequences were aligned (Fig. S4.1) and a radial unrooted phylogenetic tree was constructed (Fig. 4.1).

UMAG_10043 (ipt1) grouped with other ‘Eukaryotic tRNA-IPTs’ based on IPT categories previously established by Frébort et al. (2011). Within the same analyses

UMAG_10043 was also grouped with other fungal IPTs that were previously identified as belonging to the dimethylallylpyrophosphate (DMAPP): tRNA-IPT functional group by Kakimoto (2003). Alignment of UMAG_10043 with S. cerevisiae and H. sapiens tRNA-IPTs revealed conservation of tRNA substrate interaction sites as well as a

DMAPP binding site (Fig. S4.2). To functionally characterize U. maydis tRNA-IPT and its putative role in U. maydis CK biosynthesis, UMAG_10043 (ipt1) was deleted from

SG200, thereby creating SG200∆ipt1. SG200∆ipt1 was used to infect corn seedlings and, although virulence was decreased, a limited number of teliospores were isolated and germinated following CuSO4 treatment. SG200∆ipt1progeny strains 1 and 2 were isolated from the germination products. PCR screens and southern analysis of

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SG200∆ipt1 progeny strains 1 and 2 showed that deletion of the ipt1 locus was maintained following passage through the corn host.

Biosynthesis, uptake and processing of phytohormones by U. maydis filamentous tissue

Prior to fungal CK analysis a suitable growth medium, with no contaminating CKs, was identified. Sterile U. maydis growth mediums (liquid MM, YEPS, and solid DCM medium) were analyzed for the presence of cytokinins. Cytokinins were not detected in liquid MM samples; however, CKs were detected in YEPS liquid medium and solid

DCM. iP CK forms made up the majority of CKs, representing 100% of CKs detected in

DCM (iPRP: 75.4 pmol g-1 FW; iPR: 54.0 pmol g-1 FW; iP: 2.9 pmol g-1 FW) and 99.6% of total CKs detected in YEPS (iPRP: 117.6 pmol g-1 FW; iPR: 204.9 pmol g-1 FW; iP:

17.4 pmol g-1 FW). The detection of iPCK forms in this growth medium is consistent with other studies of growth medium containing yeast extract (Jameson and Morris 1989,

Timmusk et al., 1999).

Phytohormone analysis was carried out on SG200 as well as ipt1 deletion strains to determine if CK production by SG200∆ipt1 and SG200∆ipt1 progeny strains was impaired. Strains were cultured on sterile MM (CK negative medium) containing charcoal to induce filamentous growth. Resulting colonies were harvested and used for phytohormone analysis. Phytohormone profiles for SG200 detected cisZCKs representing 77% of total CKs, followed by iPCKs at 20% and transZCKs at 3% (Table

4.1). The dominant CK, cisZRP, represented 72% of the total CKs detected in SG200.

Phytohormone profiles for SG200∆ipt1 and SG200∆ipt1 progeny showed no detectable

124 levels of CKs, indicating that deletion of ipt1 removes the ability of the fungus to synthesize CKs. No ABA was detected in any U. maydis strains grown on MM.

To determine if CK presence in the medium impacts fungal CK profiles, ipt1 deletion strains and SG200 were grown on DCM (which contains iP CK forms). iP CKs typically act as the base CK form from which side chain modifications (i.e. hydroxylation) occur; hence any accumulation of other CK forms detected in fungal profiles is likely due to triggering production or modification of exogenous CKs. When grown solely in and on DCM, ipt1 deletion strains were positive for the presence of iPR

(2.3-2.5 pmol g-1 FW) and did not contain any other CKs. When SG200 was grown in

DCM, iPCKs represented the major CK type at 55%, followed by cisZCKs at 44% and transZCKs at 1% of total CKs. Furthermore cisZR, iPRP, iPR and iP concentrations were significantly higher (p<0.05) in SG200 grown on DCM relative to SG200 grown on

MM (Table 4.1). This alteration in CK profile in SG200 was not seen in the ipt1 deletion strains. When not impaired in CK biosynthesis, U. maydis may take up, process and convert CKs which are available from the medium. ABA was not detected in any U. maydis filamentous growth form.

Pathogenesis: seedling and cob assays

U. maydis disease symptoms present differently depending on the tissue type that is infected. In order to assess pathogenesis in different tissues, U. maydis infection was carried out in corn seedlings and cob tissue. Seven-day-old corn seedlings were injected with SG200, SG200∆ipt1 and SG200∆ipt1 progeny to assess pathogenesis. Scoring of symptom formation is presented in Fig. 4.2a. SG200 injections resulted in 97% seedling

125 infection whereas injection of SG200∆ipt1 and SG200∆ipt1 progeny resulted in 79% and

64 % seedling infection respectively. Of those infected, 84% of SG200 infections showed signs of leaf tumours or more severe symptoms whereas 17% of SG200∆ipt1 and

36% of SG200∆ipt1 progeny infections showed signs of leaf tumours or further symptom progression at 14 dpi. SG200 had significantly more severe disease symptoms than the

SG200∆ipt1 and the SG200∆ipt1 progeny. There was no significant difference between

SG200∆ipt1 and the SG200∆ipt1 progeny (Kruskal-Wallis ANOVA with a Dunn

Multiple Comparisons p<0.001). Fig. 4.2b presents a visual representation of the most frequently observed disease symptom for each treatment at the specified dpi. Together the data indicates that deletion of ipt1 resulted in a decreased ability to infect and reduced virulence during seedling pathogenesis.

Infection of cobs was conducted independently six times for SG200 and

SG200∆ipt1 and three times for the SG200∆ipt1 progeny. A total of 44, 38 and 30 cobs were injected for SG200, SG200∆ipt1 and SG200∆ipt1 progeny, respectively. Cobs, which showed severe infection, were counted as one successful infection, and those cobs with three or fewer tumours were counted as 0.5 of a successful infection. For SG200

19.5 of 44 cobs showed infection symptoms (44%), for SG200∆ipt1 0 of 38 cobs showed signs of infection, and for SG200∆ipt1 progeny 1.5 of 30 cobs showed infection symptoms (5%). The tumours formed in SG200∆ipt1 progeny infections were smaller and less developed than those formed during SG200 infection.

Phytohormone analysis: cob infection time course

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Infected seedling tissue CK profiles have been shown previously (Bruce et al., 2011) with this in mind this study focussed only on CK analysis of cob infected tissue. Cob tissue was injected with water (mock-infection), SG200∆ipt1 and SG200. Disease symptoms were monitored over the course of 28 days. While effort was made to prevent kernel pollination, a mix of fertilized and unfertilized kernels occurred. Unfertilized kernels were sampled from mock-infections as this tissue type more likely represents the tissue stage infected by U. maydis (Snetselaar et al., 2001, Morrison et al., 2015b). Fig.

4.3 presents a visual representation of symptoms on injected cobs at specific time points.

Mock-infected and SG200∆ipt1 infected cobs showed no signs of disease whereas SG200 infections progressed as previously described in Morrison et al. (2015b) with the development of large bulbous tumours. Multiple tissue samples were taken from the three infection types for phytohormone profiling by HPLC-ESI MS/MS.

Abscisic acid

Abscisic acid extracted from cob tissue was analyzed using HPLC-ESI (-) MS/MS. ABA was detected in all treatments at all time points (Fig. 4.4). ABA concentration in the control treatment increased over the time course ranging from 38.29 pmol g-1 FW at day

6 to 253.62 pmol g-1 FW at day 28. In the SG200∆ipt1 infected tissue ABA concentrations were lowest at 173.98 pmol g-1 FW at day 13. ABA levels increased in

SG200 infected tissue at day 13 (555.92 pmol g-1 FW) which was significantly higher than either the control or SG200∆ipt1 infection at this timepoint (Tukey Kramer p<0.05).

Cytokinins

127

Total cytokinins were extracted from the mock-infected control, SG200∆ipt1 and SG200 injected Z. mays cob tissue and quantified at 6, 13, 20 and 28 dpi. CKs were grouped based on their structure into one of the following categories: CK glucosides, methylthiol

(2MeS) CKs or freebase, riboside and nucleotide (FBRNT) CKs (Morrison et al., 2015b).

CK glucosides represent the inactive or storage form of CKs (Sakakibara 2006) and in this study included the following analytes: DHZOG, DHZROG, DHZ9G, transZOG, transZROG, trans/cisZ9G, cisZOG, and cisZROG (iP9G and 7Gs were not detected in this study). Methylthiol CKs are modified through the addition of a methylthiol group at the C2 position and can be further hydroxylated at the isopentenyl side chain (Sakakibara,

2006, Giron et al., 2014) and include the following analytes: 2MeZR, 2MeSZ, 2MeSiPR, and 2MeSiP. FBRNT CKs represent the classic CK metabolite pathway, including active and immediate precursor forms. The following analytes are included in the FBRNT category: iP, iPR, iPRP, DHZ, DHZR, DHZRP, transZ, transZR, transZRP, cisZ, cisZR, and cisZRP. No aromatic CKs were detected in any treatment tissue.

Analyte concentrations can be found in Tables 4.2, 4.3, and 4.4 for the mock- infected control, SG200∆ipt1 and SG200 infected cob tissues, samples were divided based on tissue mass. The following sections describe the dynamics of each CK group.

CK glucosides

CK glucosides comprised the majority of each CK profile (Fig. 4.5), representing >68% of the total CKs in mock-infected tissue; >93% in SG200∆ipt1; and >70% in SG200 infected tissue (Fig. 4.5). Total glucosides represented >93% of the CK profile for

SG200∆ipt1 at all timepoints whereas for the mock-infected tissue and SG200 this level

128 fluctuated. Total glucosides were significantly higher in SG200∆ipt1 at 13 and 20 dpi relative to the other tissue types (p < 0.05).

Methylthiol CKs

Specific methylthiol CKs (2MeSCKs) were detected in the different treatment types at varying levels during the time course (Tables 4.2, 4.3, 4.4). No 2MeSiPCKs were detected in any treatment type whereas 2MeSZR was only detected at day 28 in SG200 infected tissue.

FBRNT CKs

Total FBRNT levels decreased during the time course for the mock-infection treatment from >31% at day 6 to <8% and stayed relatively constant for the ipt1 deletion (<7% throughout). The reduction in total FBRNTs seen in the control was not mirrored in the

SG200 time course where total FBRNTs increased from 5.32% to >27% between days 13 and 28 respectively. The nucleotide form made up the majority of FBRNTs for each treatment and time point with the exception of SG200 at day 28 where total ribosides increased to represent >82% of the total FBRNTs (Table 4.4). This increase in riboside forms, found in SG200 infected tissue at day 28, was due to elevated levels of cisZFBRNTs, specifically cisZR which represented >75% of the total FBRNTs. SG200, cisZR was significantly higher than other treatments at 20 and 28 dpi and total cisZFBRNTs were significantly elevated in SG200 treatments relative to other treatments at day 28 (p < 0.05; Fig. 4.6).

129

CK signaling and biosynthesis

The deletion of the ipt1 gene in U. maydis stops CK production by the fungus and results in an altered disease phenotype in planta. To determine the potential capability of U. maydis to modify and impact other systems and respond to external CK cues the U. maydis genome was mined using known CK signaling and biosynthesis proteins through blastp analysis (Table S4.3). Table 4.5 lists the candidate U. maydis othologs identified, their putative function, the current description for each U. maydis protein and the reciprocal best blast hit and corresponding Evalue for the reference sequence used in similarity searches. Table S4.4 expands on Table 4.5 and lists all putative U. maydis orthologs in the CK signaling and biosynthetic pathway. Reference sequences, which were used to identify the U. maydis proteins and the top similarity reference protein

Evalue are listed. U. maydis orthologs are listed in order of likelihood for their predicted function for each reference protein examined (Table S4.4). This order is based on their similarity to reference sequences, with those listed first being the most likely ortholog. A schematic of each reference protein and putative ortholog in U. maydis with similar conserved domains highlighted are shown in Fig. S4.3. In plants CK signaling occurs in a multistep phosphorelay with a cytokinin binding to the cyclases/histidine kinases associated sensor extracellular (CHASE) domain of a histidine kinase receptor and initiating the cascade (Kieber and Schaller 2014). In U. maydis one candidate and two possible putative histidine kinases, one histidine phosphotransfer protein and three putative response regulators were identified; the presence of these putative orthologs may indicate U. maydis’ ability to respond to external CK signals (Table 4.5; Table S4.4).

130

Putative U. maydis CK biosynthesis enzymes downstream of ipt1 were identified through searches using characterized plant CK biosynthetic enzymes. The resulting list of candidate U. maydis CK enzymes is presented in Table 4.5. Multiple cytochrome p450 monooxygenases were identified with only the top four listed (Table S4.4). Two phosphatase enzymes, classified under enzyme commission number (EC) 3.1.3.1, the same EC associated with the phosphatase in CK biosynthesis, were also identified

(Spichal 2012; Table S4.4). Adenosine kinase: UMAG_00797, adenine phosphoribosyltransferase: UMAG_10904, and ß-glucosidase UMAG_00446 all had EC numbers associated with the CK enzymes listed in Spichal (2012) (EC 2.7.1.20; EC

2.4.2.7; and EC 3.2.1.21 respectively; Table S4.4). Putative CK dehydrogenases (CKX) all lacked the CK binding domain; however contained the FAD domain associated with

CKX (Fig. S4.3n). Together, Table 4.5, Table S4.4 and Fig. S4.3 show the similarity between identified U. maydis proteins and the reference proteins. Those conserved domains that are important to the proposed function of each protein are coloured and conserved domains that are present in the protein but not overlapping specific conserved domains in the reference sequences are represented by broken line boxes (Fig. S4.3).

A putative U. maydis CK biosynthesis pathway is presented in Fig. 4.7 based on: the known analytes produced by U. maydis; the recognized pathway (tRNA degradation) which is likely functioning for CK production; and the identified enzymes listed in Table

4.5 and Table S4.4.

131

DISCUSSION

It is becoming increasingly clear that phytohormone networks are targeted and manipulated by invading pathogens. Key to understanding the complexities of these interactions is to identify the phytohormone contribution by the pathogen. In the current study the sole U. maydis IPT, a tRNA-IPT, was identified and deleted. This deletion blocked CK production by the fungus; this impacted its ability to modify CKs from medium relative to SG200, decreased virulence in corn seedlings, inhibited tumour formation in cob infections and altered phytohormone profiles of infected cob tissue.

Traditionally, the tRNA degradation pathway and thereby tRNA-IPTs by extension, were not viewed as important in CK biosynthesis, however more recently the recognized contribution of tRNA degradation products to CK pools has brought this pathway to the forefront of CK research (Schafer et al., 2015). To examine how U. maydis tRNA-IPT (ipt1), may be related to other IPTs from a phylogenetically diverse group of organisms, trimmed IPT sequences were aligned and phylogenetically analyzed.

U. maydis Ipt1 grouped with other ‘Eukaryotic tRNA-IPTs’ identified in Frébort et al.

(2011), as well as with DMAPP: tRNA-IPTs identified in Kakimoto (2003). Alignments of the entire amino acid sequence of U. maydis Ipt1 with S. cerevisiae and H. sapiens tRNA-IPTs showed similar tRNA interaction sites and also identified DMAPP substrate sites (Fig. S4.2). Since ipt1 is required for U. maydis to produce cytokinins, this suggested that cytokinins produced by U. maydis have side chains derived from DMAPP.

This also suggested that DMAPP in U. maydis links the MVA biosynthetic pathway to

CK production. The MVA pathway enzymes have been identified in U. maydis

(Lombard and Moreira 2011). However, the enzymes involved in the synthesis of cis and

132 trans CKs by U. maydis have not. Candidate enzymes in the CK biosynthetic pathway were identified in the U. maydis genome through similarity searches (Table 4.5; Table

S4.4).

Having a single tRNA–IPT involved in CK production distinguishes U. maydis from other fungi with characterized steps in CK biosynthesis. Hinsch et al. (2015) identified an adenylate-ipt fused log gene in the ergot fungus, Claviceps purpurea.

Deletion of the ipt-log gene did not affect levels of iP or cisZ but resulted in reduced transZ CKs. A tRNA-ipt was also identified in Claviceps purpurea but was not deleted.

The authors suggested that deletion of both IPTs in this fungus may result in further reduction to fungal CK production (Hinsch et al., 2015). In contrast to Hinsch et al.

(2015) deletion of a single tRNA-IPT in U. maydis blocked its ability to synthesize all

CKs and modified processing of CKs from the medium.

The role of ipt1 in U. maydis CK production and disease formation

Growth of U. maydis SG200 on medium containing CKs revealed that it may be capable of taking up and processing CKs. This can be seen in the accumulation of iP forms in the

U. maydis strains. Further to this there were significant differences in the cisZ forms detected in SG200 grown on DCM vs. MM, suggesting that CK conversion may be occurring during fungal growth. CK profiles of U. maydis ∆ipt1 strains did not show this accumulation of cisZ forms even when grown on CK containing medium. This difference between the CK producing (SG200) and the non CK producing strains suggested that a degree of ‘self-priming’ may be necessary for CK processing to occur.

CK biosynthesis is a complex pathway with various checks, interconversion and feedback

133 mechanisms which can occur within the biosynthetic pathway, this feedback of CK production may be necessary for maintained CK biosynthesis within this fungus.

Separate experiments provided preliminary evidence that U. maydis secretes CKs into surrounding medium with cisZR detected in the supernatant (0.3 pmol g-1 FW) as well as in the pellet (8.2 pmol g-1 FW) of U. maydis cells grown in non-CK containing medium.

CK interconversion and processing have been noted in Colletrichum graminicola in in vitro cultures (Behr et al., 2012). This may suggest that since U. maydis and other fungi can take up and metabolize CKs from medium, perhaps they are also capable of reacting to and modifiying CK products from the plant.

Phytohormone analysis: cob infection time course

U. maydis strains in which ipt1 was deleted showed reduced virulence in seedling assays and greatly reduced tumour formation in infected cob tissue. The capacity for U. maydis to synthesize, and potentially process and, respond to CKs is imperative to the progression of disease symptoms during the U. maydis-Z. mays interaction. To examine the role of CKs and ABA during this infection process a disease time course followed by phytohormone extraction and analysis was carried out.

Cytokinins

Accumulation of cisZCKs during U. maydis infection of Z. mays is a distinct feature of this pathosystem and was noted by Bruce et al. (2011), during U. maydis infection of seedlings and by Morrison et al. (2015b) during U. maydis infection of cob tissue.

Morrison et al. (2015b) noted that dikaryotic infection of cob tissue was more virulent and resulted in higher levels of cisZCKs relative to solopathogenic infection. This

134 finding may suggest that the capacity of a fungal strain to produce higher levels of CKs may play a role in its virulence level. This is consistent with the decreased virulence observed for non-CK producing ipt1 strains of U. maydis. Infections with SG200ipt1 strains did not result in increased levels of cisZR, further suggesting that this cisZR increase may be a result of fungal CK production.

The dominance of the cisZCKs in U. maydis has been discussed previously

(Bruce et al., 2011, Morrison et al., 2015b) as a strategy by which the fungus predominantly produces CKs to which its host can respond. cisZCK receptors have been identified in Z. mays and cisZCKs are the more abundant form of CKs isolated from Z. mays tissue (Yonekura-Sakakibara et al., 2004, Gajdosova et al., 2011). CK production by the fungus is important in normal disease development and is needed to stimulate the accumulation of cisZCKs and the production of methylthiol CKs.

A distinct accumulation of 2MeSZR was detected in SG200 infected tissue which was not mirrored in control or SG200∆ipt1 infected tissues. This analyte accumulation was also detected in Morrison et al. (2015b). No methylthiol CKs were detected in U. maydis when grown separate from the plant, and it appears that the accumulation of

2MeSZR occurs specifically in successfully infected tumour tissue. Accumulation of

2MeSCKs has been detected during infection of Arabidopsis thaliana by pathogenic strains of Rhodococcus fascians (Pertry et al., 2009).

Abscisic acid

An increase in ABA prior to cisZCK accumulation was not detected in cobs infected with

SG200∆ipt1. The absence of this characteristic ABA spike (current study and Morrison

135 et al., 2015b) in SG200∆ipt1 may suggest its necessity in triggering CK accumulation and tumour development in this pathosystem. ABA’s role in pathogen-host relations has been implicated in both suppression and stimulation of host defenses, depending on the infection strategy and time at which ABA accumulation occurs (Ton et al., 2009). The mock-infected control and SG200∆ipt1 infections showed gradual increases in ABA levels during the time course, however, SG200 infected tissue displayed a peak in ABA content at day 13 followed by overall decreases in ABA comparable to the other treatments on subsequent days. Removal of fungal derived CKs, as in SG200∆ipt1 infection, resulted in a profile that more closely resembled uninfected tissue, which appears to follow the normal desiccation of the cob (Morrison et al., 2015b). The peak in

ABA during the proliferation and tumour expansion stage has been detected previously

(Morrison et al., 2015b) and may be necessary for initiation of further host susceptibility and tumour expansion in this pathosystem (Morrison et al., 2015b). The absence of the

ABA spike in SG200∆ipt1 infections may contribute to its decreased virulence.

During normal SG200 infection there is a switch to cisZCK dominance at day 20 following the day 13 spike in ABA. However in the SG200ipt1 strain infections there is no ABA spike and the CK production continues in manner similar to the mock-infections.

This suggests that the ABA spike may trigger the switch from combined CK production through the de novo and tRNA degradation pathways to a dominance of production through the tRNA degradation pathway in the U. maydis- Z. mays pathosystem. It is also possible that CK production by the fungus acts to trigger the ABA spike which then stimulates cisZCK type accumulation.

136

Signaling and Biosynthesis

CK production by the fungus is needed for successful tumour development. This pathosystem, as in most plant-pathogen interactions, is quite complex and although CKs may act to stimulate growth, it is the combination of fungal and plant CKs that permits maintenance and development in the U. maydis-Z. mays pathosystem. As noted by

Walbot and Skibbe (2010), application of phytohormones including cytokinins alone does not induce U. maydis disease symptoms. Moreover, in the presented research fungal presence without fungal CK production leads to reduced disease development in seedlings and the inhibition of tumour formation in cobs. Unraveling the interaction between U. maydis and Z. mays during pathogenic development requires understanding the ability of U. maydis to alter host regulatory systems and redirect nutrient accumulation while permitting host viability.

The characterization of SG200ipt1 and its comparison to SG200 revealed that ipt1 is necessary for CK biosynthesis in U. maydis. The deletion of ipt1 also negatively impacted the ability of U. maydis to modify exogenous CKs from medium, decreased virulence in corn seedlings, inhibited tumour formation in cob infections, failed to stimulate the production of an ABA spike and blocked cisZCK accumulation during infection of Z. mays. Together these findings suggest that during disease development both U. maydis and Z. mays contribute to CK biosynthesis and both may respond to the

CKs produced; however the production of CKs by U. maydis is required to bring about full disease development.

CK biosynthesis

137

Candidate signaling proteins and biosynthetic enzymes were identified in U. maydis. The proposed U. maydis CK pathway is presented in Fig. 4.7 and putative orthologs for CK signaling and biosynthesis are listed in Table 4.5 and Table S4.4. Pathways for CK production in fungi have previously been proposed by Behr et al. (2012), Hinsch et al.

(2015) and Morrison et al. (2015a). The presented U. maydis pathway highlights the initiation of CK production via a tRNA-IPT (Ipt1).

Fig. S4.4 outlines a potential pathway for CK production during the U. maydis- Z. mays interaction based on detected CK products found in the current study and Morrison et al. (2015ab) as well as data from Spichal (2012). The enzymes involved in several of the steps in cisZ CK production are unknown (Schafer et al., 2015). For example, the methylthiol pathway has not been readily characterized and 2MeSCKs are not detected in

U. maydis axenic culture. During the fungal plant interaction 2MeSZR accumulates.

Among the 2MeSCK pathway enzymes (Esberg et al., 1999, Mathevon et al., 2007), only the MiaC like enzyme (UMAG_05632) was detected in U. maydis. As outlined in

Persson and Bjork (1993), MiaB and MiaC work together in the methylthiolation of tRNA. There is a potential MiaB ortholog in Z. mays (NCBI accession: XP_008670849; a predicted:CDK5RAP1-like protein) and the observed products of tRNA methylthiolation may represent the combined activity of proteins from pathogen and host.

Signaling

The ability to detect and respond to exogenous CK has only been implicated in other fungi (Braaksma et al., 2001, Nasim and Rahman 2009, Sood 2011). Cabrera-Ponce et al. (2012) were able to stimulate a major morphological transition in U. maydis through

138 indirect contact with maize calli. However it is possible that the phytohormones present in the medium to maintain the calli may have contributed to the U. maydis morphological transition. As such it cannot be ruled out that U. maydis possibly responds to CKs, produced by Z. mays, through a signal transduction pathway.

CK response in plants involves a histidine kinase two component system (TCS).

This signal transduction pathway has been described in many systems including lower eukaryotes, and bacteria (West and Stock 2001, reviewed in Spichal 2012). The plant histidine kinases contain a characteristic CHASE domain that acts to bind CKs (Gruhn et al., 2014). However, traditional CHASE domains are not found in algal histidine kinases

(Pils and Heyl 2009, Spichal 2012) and yet algae respond to CKs (Noble et al., 2014).

Consistent with Lavin et al. (2010) we identified putative histidine kinases, a putative histidine phosphotransfer protein and three putative response regulators in U. maydis by sequence similarity searches. The identified U. maydis histidine kinases lack the CHASE domain (Fig. S4.3a). U. maydis HKs UMAG_02739 and UMAG_11957 are classified as

Type I hybrid HKs which contain a sensory module at the N-terminal; in the case of

UMAG_02739 this sensory module is a repeated HAMP domain and for UMAG_11957 a PAS domain, which are implicated in sensing light among other stimuli (reviewed in

Lavin et al., 2010). UMAG_04773 is classified as a single GAF domain (SGD)-HK,

GAF domains can act as binding sites for small ligands and molecules (reviewed in Lavin et al., 2010). It is possible that UMAG_04773 could bind CKs leading to signal transduction.

Proposed model for the role of cytokinin in the U. maydis - Z. mays pathosystem

139

The U. maydis- Z. mays interaction is a dynamic process to which both organisms contribute. This study shows that without fungal CK production disease symptoms do not manifest normally and there is no cisZCK accumulation in the fungal/plant tissue. A more dynamic model can also be proposed, which examines the influence fungal CKs have on other hormone systems and how this may further influence CK accumulation during tumour development. Fig. 4.8 presents a putative fungal and plant CK pathway interaction. In it U. maydis produced cisZCKs are taken up by Z. mays, or bind to a CK receptor, which alters CK biosynthesis in Z. mays. This leads to increased production and release of CKs by the plant. Some of these CKs are either taken up by U. maydis or stimulate it to respond. Because of the close interaction, CK production by the pathogen and plant likely influence each other. Both sources of CK feed into a pool that brings about the development of tumours composed of plant and fungal tissues. The tumours also produce CKs that feed back to the plant and fungus creating cycles of CK stimulation and production that, in turn, stimulate tumour devlopment. Then at a given point, around 13 days in to tumour development in cobs, a spike in ABA production is stimulated by U. maydis’ CK production. This spike stimulates the increased production of cisZCKs resulting in a shift in tumour development from the initiation phase to a phase of greater expansion. It is at this time that a fungal developmental transition also occurs with mycelia fragmentation and teliospore formation. The dynamic interaction then ends with tumours breaking down and teliospores being released.

CONCLUSIONS

140

The tRNA isopentenyltransferase gene, ipt1, is required by U. maydis for the production of CKs. The production and characterization of SG200ipt1 strains revealed that CK production by U. maydis is necessary for the full expression of pathogenesis and virulence in seedlings and cobs. In seedlings, relative to ipt1 deletion strains, fungal CK production leads to increased numbers of tumours being formed and to larger tumour formation and in cobs CK production appears to be required for tumour production. The interactions in disease development are not however, as simple as the fungus producing

CKs and the plant responding, rather a complex interaction in which both the host and the pathogen contribute to CK production in the tumours and both respond to CK production through developmental change. All of these finely balanced interactions are severely reduced or fail to develop if U. maydis does not produce cisZCKs. This indicates the importance of the often overlooked (Schafer et al., 2015) tRNA degradation pathway and cisZCKs during plant-pathogen interactions.

141

TABLES AND FIGURES

Table 4.1. Cytokinin concentrations (pmol g -1 FW) for SG200 filamentous tissue grown on minimal medium (CK negative) and double complete medium (CK positive). Values are means ± standard error (SE; n=sample number). Medium Treatment

Minimal medium Double complete medium n 2 4 transZRP 0.81 ± 0.15 1.50 ± 0.33 transZR 0.22 ± 0.11 transZ cisZRP 21.06 ± 1.58 60.44 ± 14.47 cisZR 1.58 ± 0.57 23.81 ± 2.96 cisZ iPRP 4.66 ± 0.56 28.34 ± 2.77 iPR 1.17 ± 0.73 63.45 ± 9.58 iP 10.42 ± 2.43

142

Table 4.2. Cytokinin concentrations (pmol g -1 FW) in mock-infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Values are means ± standard error (SE; n=3-5) at specific days post infection (dpi). The number of cobs from which samples were taken is presented. Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE. Mock-infected control dpi 6 13 20 28 Cobs 2 3 3 3 n 3 3 4 5 Free base iP 3.18 ± 0.66 1.34 ± 0.30 1.34 ± 0.09 0.87 ± 0.11 DHZ 30.26 ± 17.75 transZ 972.68 ± 469.07 3.75 ± 2.48 2.18 ± 1.47 3.75 ± 1.16 cisZ 0.18 ± 0.18 0.97 ± 0.30 Riboside iPR 120.38 ± 16.31 0.18 ± 0.18 3.03 ± 0.69 DHZR 34.08 ± 12.24 0.11 ± 0.08 transZR 908.17 ± 36.30 5.39 ± 1.83 2.89 ± 0.93 8.15 ± 3.16 cisZR 19.01 ± 2.77 2.80 ± 0.83 4.17 ± 1.20 0.72 ± 0.13 Nucleotide iPRP 250.45 ± 64.89 27.67 ± 13.44 18.23 ± 10.42 12.00 ± 2.54 DHZRP 12.38 ± 2.65 transZRP 3330.24 ± 683.42 48.33 ± 21.86 29.19 ± 13.79 36.94 ± 14.02 cisZRP 68.41 ± 4.92 25.31 ± 4.39 24.51 ± 7.80 1.98 ± 0.36 Glucoside iP7G iP9G DHZOG 157.83 ± 39.14 16.75 ± 2.07 40.11 ± 16.45 32.83 ± 4.61 DHZROG 10086.20 ± 2923.26 286.54 ± 92.99 170.12 ± 44.18 71.29 ± 21.36 DHZ9G 244.30 ± 65.07 26.05 ± 3.09 64.93 ± 28.21 3.92 ± 1.22 transZOG 23.46 ± 7.85 6.12 ± 1.22 8.29 ± 0.89 7.88 ± 0.75 transZROG 20.25 ± 4.16 6.36 ± 1.38 3.12 ± 1.60 1.31 ± 0.40 trans/cisZ9G 331.33 ± 74.34 401.15 ± 27.65 603.29 ± 83.07 796.40 ± 63.77 cisZOG 761.30 ± 191.32 0.80 ± 0.05 0.72 ± 0.24 0.40 ± 0.19 cisZROG 759.06 ± 239.03 138.65 ± 52.89 74.01 ± 18.44 38.68 ± 7.94 Methylthiol 2MeSZR 2MeSZ 6.73 ± 4.10 6.42 ± 1.71 2MeSiPR 2MeSiP

143

Table 4.3. Cytokinin concentrations (pmol g -1 FW) in SG200∆ipt1 infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Values are means ± standard error (SE; n=3-5) at specific days post infection (dpi). The number of cobs from which samples were taken is presented. Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE. SG200∆tRNA-ipt1 dpi 6 13 20 28 Cobs 2 3 3 5 n 4 3 3 5 Free base iP 1.23 ± 0.21 1.89 ± 0.62 1.47 ± 0.60 0.97 ± 0.25 DHZ 0.36 ± 0.36 1.64 ± 1.64 transZ 7.33 ± 4.88 7.12 ± 2.43 1.02 ± 0.66 0.82 ± 0.82 cisZ 0.13 ± 0.13 1.17 ± 0.72 Riboside iPR 0.16 ± 0.16 33.98 ± 21.84 3.09 ± 2.50 DHZR 2.30 ± 0.52 1.87 ± 0.95 0.13 ± 0.13 0.27 ± 0.27 transZR 7.85 ± 3.23 30.06 ± 3.98 2.84 ± 1.08 0.17 ± 0.17 cisZR 15.05 ± 1.68 5.94 ± 1.55 2.26 ± 0.83 1.52 ± 0.64 Nucleotide iPRP 48.66 ± 18.30 14.78 ± 5.99 7.63 ± 3.24 DHZRP transZRP 16.03 ± 14.83 61.33 ± 38.98 14.51 ± 2.75 2.90 ± 0.79 cisZRP 12.89 ± 4.73 17.99 ± 12.00 4.66 ± 2.20 3.29 ± 0.98 Glucoside iP7G iP9G DHZOG 28.43 ± 1.35 67.64 ± 13.34 93.02 ± 2.60 68.46 ± 11.66 DHZROG 623.22 ± 43.73 2128.40 ± 382.09 574.01 ± 368.45 175.16 ± 82.37 DHZ9G 43.12 ± 1.94 110.55 ± 17.98 156.54 ± 8.00 7.21 ± 1.46 transZOG 1.41 ± 0.13 1.71 ± 0.31 3.24 ± 1.22 1.71 ± 0.37 transZROG 2.66 ± 0.28 1.59 ± 0.03 1.32 ± 0.66 0.27 ± 0.27 trans/cisZ9G 300.69 ± 18.41 534.81 ± 80.08 942.71 ± 296.01 572.42 ± 58.60 cisZOG 4.91 ± 3.69 10.10 ± 2.78 1.88 ± 0.80 1.59 ± 0.71 cisZROG 263.49 ± 22.56 279.00 ± 16.98 125.98 ± 70.69 58.63 ± 16.41 Methylthiol 2MeSZR 2MeSZ 8.63 ± 2.69 2MeSiPR 2MeSiP

144

Table 4.4. Cytokinin concentrations (pmol g -1 FW) in SG200 infected Z. mays cob tissue, during the U. maydis- Z. mays infection time course. Values are means ± standard error (SE; n=3-9) at specific days post infection (dpi). The number of cobs from which samples were taken is presented. Empty cells indicate values of zero for those analytes. In cases where an analyte was detected in only one sample the presented mean concentration is equivalent to the SE. SG200 dpi 6 13 20 28 Cobs 1 3 4 5 n 3 4 6 9 Free base iP 1.51 ± 0.27 1.31 ± 0.07 1.75 ± 0.19 2.96 ± 1.11 DHZ 1.22 ± 0.37 transZ 9.69 ± 0.21 0.85 ± 0.43 4.18 ± 2.01 5.39 ± 1.84 cisZ 0.40 ± 0.04 0.20 ± 0.13 0.31 ± 0.16 0.70 ± 0.22 Riboside iPR 34.23 ± 33.65 2.42 ± 1.16 1.01 ± 0.76 15.81 4.55 DHZR 3.24 ± 0.20 0.13 ± 0.13 0.82 ± 0.49 0.12 0.08 transZR 12.21 ± 1.08 4.11 ± 1.85 1.00 ± 0.27 2.88 0.94 cisZR 27.44 ± 1.79 10.89 ± 1.09 11.60 ± 1.61 224.58 69.98 Nucleotide iPRP 7.75 ± 3.92 16.34 ± 7.91 16.41 ± 8.72 7.51 ± 1.05 DHZRP transZRP 7.41 ± 0.75 7.32 ± 2.45 3.26 ± 0.92 2.42 ± 0.53 cisZRP 16.44 ± 1.39 5.65 ± 0.42 45.07 ± 21.78 33.09 ± 6.46 Glucoside iP7G iP9G DHZOG 28.85 ± 1.39 17.37 ± 16.05 4.48 ± 3.11 0.75 ± 0.36 DHZROG 585.51 ± 45.47 150.08 ± 71.32 63.99 ± 13.19 59.22 ± 11.09 DHZ9G 45.46 ± 1.42 30.10 ± 28.08 7.54 ± 5.41 transZOG 4.53 ± 0.29 1.21 ± 1.21 0.05 ± 0.05 0.34 ± 0.18 transZROG 6.01 ± 1.05 0.48 ± 0.30 0.31 ± 0.12 0.35 ± 0.35 trans/cisZ9G 599.63 ± 56.21 435.85 ± 204.03 268.64 ± 70.57 444.76 ± 50.89 cisZOG 3.60 ± 0.67 0.66 ± 0.66 cisZROG 358.03 ± 41.39 239.79 ± 33.91 204.73 ± 34.36 263.48 ± 48.90 Methylthiol 2MeSZR 1.63 ± 0.36 15.16 ± 5.22 2MeSZ 2.02 ± 2.02 9.15 ± 1.31 2MeSiPR 2MeSiP

145

Table 4.5. Putative candidate CK signaling and biosynthesis orthologs identified in U. maydis through blastp analysis and reciprocal best blast hits. Further reference protein descriptions can be found in Table S4.3. Putative orthologs for all steps in CK signaling and biosynthesis are presented in Table S4.4. Schematics for proteins with conserved domains highlighted are found in Fig. S4.3. Protein Evalue for Functional category UMAG # length PEDANT DESC Reciprocal best blast hit Organism database reciprocal best (aa) blast hit Histidine kinase UMAG_02739 1356 probable nik-1 protein (Os- SLN1 Saccharomyces 2.0E-13 1p protein) cerevisiae Histidine phosphotransfer UMAG_10726 185 related to YPD1 - two- YPD1 Saccharomyces 3.0E-18

component phosphorelay cerevisiae intermediate Response regulator UMAG_03346 683 related to SKN7 - SKN7 Saccharomyces 2.00E-33

transcription factor (C- cerevisiae Signaling terminal fragment) Equlibrative nucleoside UMAG_11433 569 related to Inhibitor-sensitive AtENT8 Arabidopsis 7.0E-11 transporter equilibrative nucleoside thaliana transporter 1 tRNA-isopentenyltransferase UMAG_10043 491 related to tRNA AtIPT2 Arabidopsis 9.0E-20 isopentenylpyrophosphate thaliana

transferase

Phosphatase UMAG_04114 591 probable PHO8 - repressible Phosphatase (EC 3.1.3.1) Enterobacter 1.0E-27 alkaline phosphatase aerogenes vacuolar Adenosine nucleosidase UMAG_11846 580 related to nucleoside Adenosine nucleosidase Cordyceps militaris 3.0E-20 hydrolase (EC 3.2.2.7) Adenosine kinase UMAG_00797 345 probable adenosine kinase Adenosine Yarrowia lipolytica 3.0E-90 kinase:YALI0F23463p:EC 2.7.1.20 Adenine UMAG_10904 202 probable APT1 - adenine Adenine Burkholderia 2.0E-33 phosphoribosyltransferase phosphoribosyltransferase phosphoribosyltransferase rhizoxinica (EC 2.4.2.7) O-glucosyltransferase/N-glucosyl UMAG_06467 578 Ustilagic Acid glycosyl ZOG(trans: EC 2.4.1.203) Phaseolus lunatus 1.0E-11

Biosynthesis: Catabolism/ Biosynthesis:Anabolism Catabolism/ transferase transferase P. lunatus MiaC UMAG_05632 208 probable ISU1 - Iron-Sulfur MiaC: E. coli Escherichia coli 7.0E-67 cluster nifU-like protein aa:Amino acid 145

146

Fig. 4.1. Radial unrooted phylogenetic tree of IPT proteins. Branch lengths were inferred using MrBayes (Ronquist and Huelsenbeck 2003) based on MAFFT protein alignment of 52 representative members of the IPT family. A star highlights the U. maydis Ipt1 under investigation. Groupings are based on categories of IPTs previously presented by Frébort et al. (2011). Protein identifiers, species names and other descriptors are presented in Table S4.1.

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Fig. 4.2. Disease symptoms for U. maydis infected corn seedlings at 7, 14 and 21 days post infection (dpi). (a) Pathogenesis assay for corn seedlings infected with U. maydis strains: SG200, SG200∆ipt1 and SG200∆ipt1 progeny. Pathogenesis was scored using the disease symptoms presented in the legend. The percentage of symptom formation is indicated for each treatment. A non-parametric Mann-Whitney U test was conducted to assess statistical significance (p<0.05). Statistical significance is indicated by an asterisk (*). (b) Visual representation of disease symptoms from representative corn seedlings infected with U. maydis strains: SG200, SG200∆ipt1

147 and SG200∆ipt1 progeny at specific dpi.

148

Fig. 4.3. Representative time course of disease progression for Z. mays- U. maydis cob infection assay. Day post infection (dpi) appear above individual photographs for mock- infected controls, SG200∆ipt1 infected and SG200 infected.

149

Fig. 4.4. Abscisic acid concentration (pmol g-1 FW) for mock-infected control, SG200∆ipt1 and SG200 injected cob tissue at specific days post infection (dpi). n=3-9, error bars represent standard error (SE). Letters denote significant differences within time points (ANOVA and Tukey-Kramer post hoc analysis, p<0.05).

150

151

Fig. 4.6. cisZCK FBRNT concentration (pmol g-1 FW) for mock-infected control, SG200∆ipt1 and SG200 injected cob tissue at specific days post infection (dpi). The total cisZCK type is divided into cisZRP, cisZR and cisZ as indicated. n=3-9, error bars represent standard error (SE). The asterisk denotes a significant difference for total cisZCKs (ANOVA and Tukey-Kramer post hoc analysis, p<0.05). Letters denote significant differences within time points for the cisZR analyte (ANOVA and Tukey- Kramer post hoc analysis, p<0.05).

152

Fig. 4.7. Proposed U. maydis CK biosynthetic pathway. This is modified from Morrison et al. (2015a). The numbers represent inferred enzymes as follows: 2. tRNA- isopentenyltransferase (EC 2.5.1.8); 3.cytochrome P450 mono-oxygenase; 5. 5’ribonucleotide phosphohydrolase (EC 3.1.3.5); 6. adenosine nucleosidase (EC 3.2.2.7); 7. CK phosphoribohydrolase ‘Lonely guy: LOG’; 8. purine nucleoside phosphorylase (EC 2.4.2.1); 9. adenosine kinase (EC 2.7.1.20); 10. adenine phosphoribosyltransferase (EC 2.4.2.7); 19. cis-hydroxylase. Analytes denote detected CKs in U. maydis filamentous tissue grown in CK negative medium (minimal medium). Underlined analytes were not detected in U. maydis. Numbers denote putative CK biosynthetic enzyme orthologs identified based on searches in the current study (Table 4.5, Table S4.4). Underlined numbers indicate enzymes which are not well characterized and for which there are no reference sequences available. Grey boxes highlight pathways that are not well characterized, but inferred to be active in this system.

153

Fig. 4.8. Model of cytokinin involvement in tumour development in the Ustilago maydis – Zea mays pathosystem. The upper image represents tumour development before the ABA spike and the lower image represents tumour development after the ABA spike. Before the spike cisZCK production by U. maydis (blue) stimulates CK production by Z. mays either through receptor binding and signal transduction or direct uptake. In response Z. mays increases CK production and releases CKs (green) stimulating further fungal CK production. This results in the formation of a CK pool in the developing tumour to which the fungus and plant contribute (purple). This pool feeds back to the fungus and plant stimulating further CK production. After the ABA spike cisZCK levels increase such that after 13 days the physiological changes are dominated by response to cisZCK production (dark purple).

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SUPPLEMENTARY MATERIAL

Table S4.1. Summary of isopentenyltransferase proteins used for sequence alignment and phylogenetic tree creation. The groupings indicated in the tree (Fig. 4.1) appear along the left side of the table and protein classifications as identified in Kakimoto (2003) and / or Frébort et al. (2011) are indicated in the columns. Full original sequence lengths and trimmed lengths of the sequences which include only the conserved domains are also shown.

Length of NCBI Protein Listed in trimmed Classified in Kakimoto Classified in Frébort et Phylum Organism Accession NCBI Descriptor length Figure sequence (2003) al (2011) number (aa)a (aa)a

Actinobacteria Rhodococcus P46376 Rf_IPT RecName: Full=Isopentenyl transferase; 255 233 Bacterial adenylate IPTs fascians AltName: Full=Dimethylallyl transferase Cyanobacterium Anabaena WP_0113194 Av_IPT1 isopentenyl-diphosphate delta isomerase 244 216 DMAPP: AMP Bacterial adenylate IPTs variabilis 67.1 [Anabaena variabilis] isopentenyltransferases and their homologues Cyanobacterium Nostoc sp. BAB77744 No_IPT1 isopentenyl transferase [Nostoc sp. PCC 244 244 DMAPP: AMP Bacterial adenylate IPTs 7120] isopentenyltransferases and their homologues Proteobacteria Pantoea CAA86510 Pa_DMAPPT dimethylallyltransferase [Pantoea 236 234 DMAPP: AMP agglomerans agglomerans] isopentenyltransferases and their homologues Proteobacteria Ralstonia WP_0110045 Rs_tzs dimethylallyladenosine tRNA methylthiotr 238 233 DMAPP: AMP solanacearum 09.1 ansferase [Ralstonia solanacearum] isopentenyltransferases and their homologues

Bacterial adenylate IPTs adenylate Bacterial Proteobacteria Pseudomonas P06619 Ps_IPT IPT_PSESS RecName: Full=Isopentenyl 234 231 savastanoi transferase; AltName: Full=Dimethylallyl transferase; AltName: Full=Trans-zeatin producing protein Proteobacteria Agrobacterium NP_396682 At_tzs trans-zeatin secretion protein 243 232 DMAPP: AMP tumefaciens [Agrobacterium tumefaciens str. C58] isopentenyltransferases and their homologues Cyanobacterium Anabaena WP_0113192 Av_IPT2 tRNA dimethylallyltransferase [Anabaena 294 294 Bacterial tRNA IPTs variabilis 89.1 variabilis] Cyanobacterium Nostoc sp. WP_0109993 No_IPT2 tRNA dimethylallyltransferase [Nostoc sp. 295 294 DMAPP: tRNA Bacterial tRNA IPTs 90.1 PCC 7120] isopentenyltransferases and their homologues Cyanobacterium Acaryochloris WP_0121647 Am_IPT tRNA dimethylallyltransferase 302 298 Bacterial tRNA IPTs marina 89.1 [Acaryochloris marina] Firmicutes Bacillus CAB13617 Bs_tRNAIPPT tRNA isopentenylpyrophosphate 314 287 DMAPP: tRNA

Bacterial tRNA IPTs tRNA Bacterial subtilis transferase [Bacillus subtilis subsp. subtilis isopentenyltransferases str. 168] and their homologues

154

155

Firmicutes Staphylococcus WP_0015486 Sa_tRNAIPPT tRNA dimethylallyltransferase 311 308 DMAPP: tRNA aureus 13.1 [Staphylococcus aureus] isopentenyltransferases and their homologues Proteobacteria Escherichia AAC43396 Ec_tRNAIPPT tRNA delta-2-isopentenylpyrophosphate 216 199 coli (IPP) transferase, partial [Escherichia coli]

Streptophyta Zea mays ABY78881 Zm_IPT1 isopentenyl transferase IPT1 [Zea mays] 471 298 Eukaryotic origin plant tRNA IPTs Streptophyta Arabidopsis Q9ZUX7 At_IPT2 RecName: Full=tRNA 466 314 Eukaryotic origin thaliana dimethylallyltransferase 2; AltName: plant tRNA IPTs Full=Isopentenyl-diphosphate: tRNA

isopentenyltransferase 2; Short=AtIPT2; plant tRNA IPTs tRNA plant Eukaryotic origin origin Eukaryotic Short=IPP transferase 2; Short=IPPT 2 Ascomycota Claviceps CCE29200 Cp_tRNAIPT related to tRNA isopentenyltransferase 477 309 purpurea [Claviceps purpurea 20.1] Ascomycota Magnaporthe XP_00371233 Mo_tRNAIPT tRNA isopentenyltransferase 519 332 oryzae 6 [Magnaporthe oryzae 70-15] Ascomycota Saccharomyces NP_014917 Sc_Mod5 Mod5p [Saccharomyces cerevisiae S288c] 428 305 DMAPP: tRNA cerevisiae isopentenyltransferases and their homologues Ascomycota Schizosacchar- Q9UT75 Sp_IPPT RecName: Full=tRNA 434 301 DMAPP: tRNA omyces pombe dimethylallyltransferase, mitochondrial; isopentenyltransferases AltName: Full=Isopentenyl-diphosphate: and their homologues tRNA isopentenyltransferase; Short=IPP transferase; Short=IPPT; AltName: Full=tRNA isopentenyltransferase; Short=IPTase Ascomycota Fusarium CEF85538 Fg_tRNAIPT unnamed protein product [Fusarium 464 310 graminarium graminearum]: related to tRNA isopentenyltransferase Ascomycota Neurospera XP_958834 Nc_tRNAIPT tRNA isopentenyltransferase [Neurospora 471 326 crassa crassa OR74A] Ascomycota Aspergillus EAL85532 Af_tRNAIPT tRNA isopentenyltransferase, putative 488 330 fumigatus [Aspergillus fumigatus Af293]

Eukaryotic tRNA IPTs tRNA Eukaryotic Ascomycota Aspergillus EED51228 Afl_tRNAIPT tRNA isopentenyltransferase, putative 491 330 flavus [Aspergillus flavus NRRL3357] Basidiomycota Ustilago XP_01138663 Um_10043 hypothetical protein UMAG_10043 491 308 maydis 2 [Ustilago maydis 521] Basidiomycota Sporisorium CBQ67583 Sr_11516 related to tRNA isopentenylpyrophosphate 489 314 reilianum transferase [Sporisorium reilianum SRZ2] Basidiomycota Schizophyllum EFJ00160 Sco_hypoth hypothetical protein 334 270 commune SCHCODRAFT_40795, partial [Schizophyllum commune H4-8] Basidiomycota Cryptococcus AAW40861 Cn_tRNAIPT tRNA isopentenyltransferase, putative 551 381 neoformans [Cryptococcus neoformans var. neoformans JEC21] Chordata Homo sapiens AAG31324 Hs_tRNAIPPT tRNA isopentenylpyrophosphate 467 310 DMAPP: tRNA transferase [Homo sapiens] isopentenyltransferases

and their homologues 155

156

Nematoda Caenorhabditis T27538 Ce_hypoth hypothetical protein ZC395.6 - 344 321 DMAPP: tRNA elegans Caenorhabditis elegans isopentenyltransferases and their homologues Ascomycota Claviceps CCE30329 Cp_IPTLOG uncharacterized protein CPUR_04177 495 230

purpurea [Claviceps purpurea 20.1]

Fungal Fungal adenylate IPT adenylate Streptophyta Zea mays ABY78882 Zm_IPT2 isopentenyl transferase IPT2 [Zea mays] 322 271 Plant adenylate IPT Streptophyta Zea mays ABY78883 Zm_IPT4 isopentenyl transferase IPT4 [Zea mays] 364 272 Plant adenylate IPT Streptophyta Zea mays ABY78884 Zm_IPT5 isopentenyl transferase IPT5 [Zea mays] 337 291 Plant adenylate IPT Streptophyta Zea mays ABY78885 Zm_IPT6 isopentenyl transferase IPT6 [Zea mays] 338 295 Plant adenylate IPT Streptophyta Zea mays ABY78886 Zm_IPT7 isopentenyl transferase IPT7 [Zea mays] 352 279 Plant adenylate IPT Streptophyta Zea mays ABY78887 Zm_IPT8 isopentenyl transferase IPT8 [Zea mays] 388 285 Plant adenylate IPT Streptophyta Arabidopsis Q94ID3 At_IPT1 RecName: Full=Adenylate 357 317 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 1, chloroplastic; isopentenyltransferases Short=AtIPT1; AltName: Full=Adenylate and their homologues dimethylallyltransferase 1; AltName: Full=Cytokinin synthase 1; Flags: Precursor Streptophyta Arabidopsis Q93WC9 At_IPT3 RecName: Full=Adenylate 336 297 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 3, chloroplastic; isopentenyltransferases Short=AtIPT3; AltName: Full=Adenylate and their homologues dimethylallyltransferase 3; AltName: Full=Cytokinin synthase Streptophyta Arabidopsis Q9SB60 At_IPT4 RecName: Full=Adenylate 318 300 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 4; Short=AtIPT4; isopentenyltransferases AltName: Full=Adenylate and their homologues

Plant adenylate IPTs adenylate Plant dimethylallyltransferase 4; AltName: Full=Cytokinin synthase 4 Streptophyta Arabidopsis Q94ID2 At_IPT5 RecName: Full=Adenylate 330 267 Plant adenylate IPT thaliana isopentenyltransferase 5, chloroplastic; Short=AtIPT5; AltName: Full=Adenylate dimethylallyltransferase 5; AltName: Full=Cytokinin synthase Streptophyta Arabidopsis Q9C6L1 At_IPT6 RecName: Full=Adenylate 342 342 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 6, chloroplastic; isopentenyltransferases Short=AtIPT6; AltName: Full=Adenylate and their homologues dimethylallyltransferase 6; AltName: Full=Cytokinin synthase Streptophyta Arabidopsis Q94ID1 At_IPT7 RecName: Full=Adenylate 329 267 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 7, mitochondrial; isopentenyltransferases Short=AtIPT7; AltName: Full=Adenylate and their homologues dimethylallyltransferase 7; AltName: Full=Cytokinin synthase 156

157

Streptophyta Arabidopsis Q9LJL4 At_IPT8 RecName: Full=Adenylate 330 328 DMAPP: ATP/ADP Plant adenylate IPT thaliana isopentenyltransferase 8, chloroplastic; isopentenyltransferases Short=AtIPT8; AltName: Full=Adenylate and their homologues dimethylallyltransferase 8; AltName: Full=Cytokinin synthase 8; AltName: Full=Plant growth activator 22; Flags: Precursor Streptophyta Petunia AAL83819 Ph_SHO unknown [Petunia x hybrida] 350 307 DMAPP: ATP/ADP hybrida isopentenyltransferases and their homologues

Streptophyta Arabidopsis Q9C5J6 At_IPT9 RecName: Full=tRNA 463 340 Prokaryotic origin thaliana dimethylallyltransferase 9; AltName: plant tRNA IPTs Full=Isopentenyl-diphosphate: tRNA isopentenyltransferase 9; Short=AtIPT9; Short=IPP transferase 9; Short=IPPT 9 Streptophyta Physcomitrella ABP88738 Pp_IPT1 tRNA-isopentenyltransferase 557 317 DMAPP: tRNA Prokaryotic origin

patens [Physcomitrella patens] isopentenyltransferases plant tRNA IPTs and their homologues Streptophyta Physcomitrella XP_00177140 Pp_IPT2 predicted protein [Physcomitrella patens 892 263 Prokaryotic origin patens 7 subsp. patens] plant tRNA IPTs

Streptophyta Physcomitrella XP_00178049 Pp_IPT3 predicted protein [Physcomitrella patens 718 381 Prokaryotic origin patens 2 subsp. patens] plant tRNA IPTs

Streptophyta Physcomitrella XP_00176387 Pp_IPT4 predicted protein [Physcomitrella patens 717 469 Prokaryotic origin patens 0 subsp. patens] plant tRNA IPTs

Streptophyta Physcomitrella XP_00175459 Pp_IPT5 predicted protein [Physcomitrella patens 521 350 Prokaryotic origin

patens 4 subsp. patens] plant tRNA IPTs Prokaryotic origin plant tRNA IPTs tRNA plant origin Prokaryotic

Streptophyta Physcomitrella XP_00178278 Pp_IPT6 predicted protein [Physcomitrella patens 680 349 Prokaryotic origin patens 7 subsp. patens] plant tRNA IPTs

Streptophyta Selaginella XP_00298520 Sm_IPT hypothetical protein 426 341 Prokaryotic origin moellendorffii 1 SELMODRAFT_424359 [Selaginella plant tRNA IPTs moellendorffii] a: Amino acid (aa).

157

158

Table S4.2. Primers used in this study for SG200∆ipt1 creation and screening. Primera Primer sequence 5' to 3'b Creation and screening um10043LB3FLANK-F CAGACGAGTTTGTTGCGGCGGGTGAC

um10043LB3FLANK-RSfi1 CACGGCCTGAGTGGCCCCCGAAACGACCCACCCGACATGTAAC um10043RB5FLANK-FSfi1 GTGGGCCATCTAGGCCGCCCCCTCCCGATTCCCAAACCCAGAA um10043RB5FLANK-R CGCAGTTCACGGACACGCCTCGCTTC um10043&FLANK-L GACAAGCAGTTCCTCATCTCGTG um10043&FLANK-R GGTCTGGACAACTTCCTCCCTTAC um10043RT-ORF-F TGCGCTCGACCAGTTTCCTTGTACAC um10043RT-ORF-R GGTGGCGGTCCTGTGTGGAGGTAC pMF1-CARBseqF CGATGCAGGACGTGTACCTAG pMF1-CARBseqR TTTCCTTCATCTGGGTTTCG pMF1carb(1.8)F CCCGAATCACAAGAATTAGGC pMF1carb(1.8)R ACGTACGATTGTGGCGAATC Um10043 LB3OUT-F CAAAGAGCATGGCATGGCAGAATCAC Um10043 RB5OUT-R ACCTCGAGCGTCTATTGCTTC

UM10043F-BglII TGAGATCTATGCAGATTTACCGAGGCTTGGATAT

UM10043R-BglII GCAGATCTTTACATGTCGGGTGGGTCGTTTC Sequencing UM10043&FLANK-L GACAAGCAGTTCCTCATCTCGTG UM00169 RT-ORF F GACTGCATCATCACGTACGAC KOUM10043(1.8)F CGTATCGAGCGCTGTCAAGAG KOUM10043C1F CACGTACGATTGTGGCGAATC KOUM10043C2F AGGCATCGGTAGAGCGAAAAG KOUM10043C3F CTTGGTGTCATTCTGCTTGTCG KOUM10043C4F GTCGGAGAGCGGTACGAAGAC KOUM10043C5F CGGCTTTTTCCATTTTGCTTC pMF1-CARBseqR TTTCCTTCATCTGGGTTTCG KOUM10043(-0.3)F CCAAGATCCTGCAAAGCAAAG UM10044 RT-ORF F AAAACTTCATCCTGCCCTGTC KOUM10043(-1)F GTAGAGCCAAGCGTCCCAATC KOUM10043(2.4)R AGGCGCCAACTGATCTTCAC UM10043&FLANK-R GGTCTGGACAACTTCCTCCCTTAC KOUM10043C4R GAAACGGCAGGGACAATCAC a F:forward; R: reverse. b Lower-case letters in primer sequences represent nucleotides not homologous to the U. maydis genome.

159

Table S4.3. List of CK signaling and biosynthesis reference proteins used in searches. See Fig. S4.3 for a schematic representation of each protein. NCBI Protein Functional Category Protein Used in Search Organism Accession length NCBI Description number (aa) a Histidine kinase SLN1 Saccharomyces cerevisiae P39928 1220 RecName: Full=Osmosensing histidine protein kinase SLN1; AltName: Full=Osmolarity two-component system protein SLN1; AltName: Full=Tyrosine phosphatase-dependent protein 2 AtHK2 Arabidopsis thaliana Q9C5U2 1176 Full=Histidine kinase 2; AltName: Full=Arabidopsis histidine kinase 2; Short=AtHK2; AltName: Full=Protein AUTHENTIC HIS-KINASE 2 [Arabidopsis thaliana] AtHK3 Arabidopsis thaliana Q9C5U1 1036 Full=Histidine kinase 3; AltName: Full=Arabidopsis histidine kinase 3; Short=AtHK3; AltName: Full=Protein AUTHENTIC HIS-KINASE 3; AltName: Full=Protein ORESARA 12 [Arabidopsis thaliana] AtHK4 Arabidopsis thaliana Q9C5U0 1080 Full=Histidine kinase 4; AltName: Full=Arabidopsis histidine kinase 4; Short=AtHK4; AltName: Full=Cytokinin receptor CYTOKININ RESPONSE 1; Short=AtCRE1; Short=Cytokinin receptor CRE1; AltName: Full=Phosphoprotein phosphatase AHK4; AltName: Full=Protei.

Histidine phosphotransfer YPD1 Saccharomyces cerevisiae CAA98815 167 YPD1 [Saccharomyces cerevisiae] AtAHP1 Arabidopsis thaliana Q9ZNV9 154 two-component phosphorelay mediator 3 (AtAHP1/AtHP3)(Full=Histidine-

containing phosphotransfer protein 1 [Arabidopsis thaliana])

AtAHP2 Arabidopsis thaliana Q9ZNV8 156 two-component phosphorelay mediator 1 (AtAHP2/AtHP1)(Histidine- containing phosphotransfer protein 2 [Arabidopsis thaliana])

Signaling Response regulator SSK1 Saccharomyces cerevisiae Q07084 712 RecName: Full=Osmolarity two-component system protein SSK1 SKN7 Saccharomyces cerevisiae NP_012076 622 kinase-regulated stress-responsive transcription factor SKN7 [Saccharomycescerevisiae S288c] ARRs: CK response AtARR3 Arabidopsis thaliana Q9ZWS9 231 two-component response regulator / A-type response regulator 3 regulator (AtARR3)(Full=Two-component response regulator ARR3 [Arabidopsis thaliana]) AtARR4 Arabidopsis thaliana O82798 259 two-component response regulator / A-type response regulator 4 (AtARR4) / response reactor 1 (AtRR1) (Full=Two-component response regulator ARR4; AltName: Full=Response regulator 1 [Arabidopsis thaliana]) AtARR5 Arabidopsis thaliana Q9SB04 184 two-component response regulator / A-type response regulator 5 (AtARR5) / response reactor 2 (AtRR2)(Full=Two-component response regulator ARR5; AltName: Full=Response reactor 2 [Arabidopsis thaliana]) AtARR6 Arabidopsis thaliana Q9ZWS6 186 two-component response regulator / A-type response regulator 6 (AtARR6)(Full=Two-component response regulator ARR6 [Arabidopsis thaliana])

AtARR7 Arabidopsis thaliana Q9ZWS7 207 two-component response regulator / A-type response regulator 7 159 (AtARR7)(Full=Two-component response regulator ARR7 [Arabidopsis

160

thaliana])

AtARR8 Arabidopsis thaliana O80365 225 two-component response regulator / A-type response regulator 8 (AtARR8) / response reactor 3 (AtRR3)(Full=Two-component response regulator ARR8; AltName: Full=Response reactor 3 [Arabidopsis thaliana]) AtARR9 Arabidopsis thaliana O80366 234 two-component response regulator / A-type response regulator 9 (AtARR9) / response reactor 4 (AtRR4)(Full=Two-component response regulator ARR9; AltName: Full=Response reactor 4 [Arabidopsis thaliana]) AtARR15 Arabidopsis thaliana Q7G8V2 206 two-component response regulator / A-type response regulator 15 (AtARR15) (Full=Two-component response regulator ARR15 [Arabidopsis thaliana]) AtARR16 Arabidopsis thaliana Q9SHC2 164 two-component response regulator / A-type response regulator 16 (AtARR16)(Full=Two-component response regulator ARR16 [Arabidopsis thaliana]) AtARR17 Arabidopsis thaliana Q9FPR6 153 two-component response regulator / A-type response regulator 17 (AtARR17)( Full=Two-component response regulator ARR17 [Arabidopsis thaliana]) AtARR22 Arabidopsis thaliana Q9M8Y4 142 two-component response regulator / A-type response regulator 22 (AtARR22)(Full=Two-component response regulator ARR22 [Arabidopsis thaliana]) BRRs: CK response AtARR1 Arabidopsis thaliana Q940D0 690 two-component response regulator / B-type response regulator 1 regulator (AtARR1)(Full=Two-component response regulator ARR1 [Arabidopsis thaliana]) AtARR2 Arabidopsis thaliana Q9ZWJ9 664 two-component response regulator / B-type response regulator 2 (AtARR2)(Full=Two-component response regulator ARR2; AltName: Full=Receiver-like protein 5 [Arabidopsis thaliana]) AtARR10 Arabidopsis thaliana O49397 552 two-component response regulator / B-type response regulator 10 (AtARR10)(Full=Two-component response regulator ARR10; AltName: Full=Receiver-like protein 4 [Arabidopsis thaliana]) AtARR11 Arabidopsis thaliana Q9FXD6 521 two-component response regulator / B-type response regulator 11 (AtARR11/AtARP3)(Full=Two-component response regulator ARR11; AltName: Full=Receiver-like protein 3 [Arabidopsis thaliana]) AtARR12 Arabidopsis thaliana P62598 596 two-component response regulator / B-type response regulator 12 (AtARR12)(Full=Two-component response regulator ARR12 [Arabidopsis thaliana]) AtARR13 Arabidopsis thaliana Q9ZVD3 572 two-component response regulator / B-type response regulator 13 (AtARR13)(Full=Putative two-component response regulator ARR13 [Arabidopsis thaliana]_ AtARR14 Arabidopsis thaliana Q8L9Y3 382 two-component response regulator / B-type response regulator 14 (AtARR14)(Full=Two-component response regulator ARR14 [Arabidopsis thaliana]) 160

161

AtARR18 Arabidopsis thaliana Q9FGT7 635 two-component response regulator / B-type response regulator 18 (AtARR18)(Full=Two-component response regulator ARR18 [Arabidopsis thaliana]) AtARR19 Arabidopsis thaliana AEE32403 622 two-component response regulator / B-type response regulator 19 (AtARR19)(putative two-component response regulator ARR19 [Arabidopsis thalian) AtARR20 Arabidopsis thaliana Q9LZJ8 426 two-component response regulator / B-type response regulator 20 (AtARR20)(Full=Putative two-component response regulator ARR20 [Arabidopsis thaliana]) AtARR21 Arabidopsis thaliana Q9LYP5 613 two-component response regulator / B-type response regulator 21 (AtARR21)(Full=Putative two-component response regulator ARR21 [Arabidopsis thaliana]) AtARR23 Arabidopsis thaliana AED97566 145 two-component response regulator / B-type response regulator 23 (AtARR23)(protein response regulator 23 [Arabidopsis thaliana]) Equilibrative nucleoside AtENT3 Arabidopsis thaliana Q9M0Y3 418 putative equilibrative nucleoside transporter (AtENT3)(Full=Equilibrative transporter: CK transport nucleotide transporter 3; Short=AtENT3; AltName: Full=Nucleoside transporter ENT3; AltName: Full=Protein FLUOROURIDINE RESISTANT 1 [Arabidopsis thaliana]) AtENT8 Arabidopsis thaliana Q84XI3 389 putative equilibrative nucleoside transporter (AtENT8)(Full=Equilibrative nucleotide transporter 8; Short=AtENT8; AltName: Full=Nucleoside transporter ENT8 [Arabidopsis thaliana]) Adenylate AtIPT1 Arabidopsis thaliana Q94ID3 357 Full=Adenylate isopentenyltransferase 1, chloroplastic; Short=AtIPT1; isopentenyltransferase AltName: Full=Adenylate dimethylallyltransferase 1; AltName: Full=Cytokinin synthase 1; Flags: Precursor [Arabidopsis thaliana]

AtIPT3 Arabidopsis thaliana Q93WC9 336 Full=Adenylate isopentenyltransferase 3, chloroplastic; Short=AtIPT3; AltName: Full=Adenylate dimethylallyltransferase 3; AltName: Full=Cytokinin synthase 3; Flags: Precursor [Arabidopsis thaliana] AtIPT4 Arabidopsis thaliana Q9SB60 318 Full=Adenylate isopentenyltransferase 4; Short=AtIPT4; AltName: Full=Adenylate dimethylallyltransferase 4; AltName: Full=Cytokinin synthase 4 [Arabidopsis thaliana] AtIPT5 Arabidopsis thaliana Q94ID2 330 Full=Adenylate isopentenyltransferase 5, chloroplastic; Short=AtIPT5; AltName: Full=Adenylate dimethylallyltransferase 5; AltName: Full=Cytokinin synthase 5; Flags: Precursor [Arabidopsis thaliana]

AtIPT6 Arabidopsis thaliana Q9C6L1 342 Full=Adenylate isopentenyltransferase 6, chloroplastic; Short=AtIPT6; AltName: Full=Adenylate dimethylallyltransferase 6; AltName:

Full=Cytokinin synthase 6; Flags: Precursor [Arabidopsis thaliana] Biosynthesis: Catabolism/ Anabolism Catabolism/ Biosynthesis: AtIPT7 Arabidopsis thaliana Q94ID1 329 Full=Adenylate isopentenyltransferase 7, mitochondrial; Short=AtIPT7; AltName: Full=Adenylate dimethylallyltransferase 7; AltName: Full=Cytokinin synthase 7; Flags: Precursor [Arabidopsis thaliana]

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AtIPT8 Arabidopsis thaliana Q9LJL4 330 Full=Adenylate isopentenyltransferase 8, chloroplastic; Short=AtIPT8; AltName: Full=Adenylate dimethylallyltransferase 8; AltName: Full=Cytokinin synthase 8; AltName: Full=Plant growth activator 22; Flags: Precursor [Arabidopsis thaliana] tRNA- AtIPT2 Arabidopsis thaliana Q9ZUX7 466 Full=tRNA dimethylallyltransferase 2; AltName: Full=Isopentenyl- isopentenlytransferase diphosphate: tRNA isopentenyltransferase 2; Short=AtIPT2; Short=IPP transferase 2; Short=IPPT 2 [Arabidopsis thaliana] AtIPT9 Arabidopsis thaliana Q9C5J6 463 Full=tRNA dimethylallyltransferase 9; AltName: Full=Isopentenyl- diphosphate: tRNA isopentenyltransferase 9; Short=AtIPT9; Short=IPP transferase 9; Short=IPPT 9 [Arabidopsis thaliana] Cytochrome P450 CYP735A1 Arabidopsis thaliana Q9FF18 518 putative cytokinin trans-hydroxylase / cytokinin biosynthesis CYP735A1 monooxygenase (Full=Cytokinin hydroxylase; AltName: Full=Cytochrome P450 35A1 [Arabidopsis thaliana] CYP735A2 Arabidopsis thaliana NP_176882 512 putative cytokinin trans-hydroxylase / cytokinin biosynthesis CYP735A2 (cytokinin hydroxylase [Arabidopsis thaliana]) cytochrome P450 Streptomyces platensis CBX53644 402 cytochrome P450 monooxygenase [Streptomyces platensis] monooxygenase Phosphatase Phosphatase (EC 3.1.3.1) Enterobacter aerogenes CCG31503 471 Alkaline phosphatase (EC 3.1.3.1) [Enterobacter aerogenes EA1509E]

5'-ribonucleotide 5'-nucleotidase(EC Erwinia tasmaniensis CAO97506 556 UshA protein (UDP-sugar hydrolase and 5'-nucleotidase) (EC 3.6.1.45; EC phosphohydrolase 3.1.3.5) 3.1.3.5) [Erwinia tasmaniensis Et1/99] Adenosine nucleosidase Adenosine nucleosidase Cordyceps militaris XP_006671613 282 Adenosine nucleosidase [Cordyceps militaris CM01] (EC 3.2.2.7) Phosphoribohydrolase AtLOG6 Arabidopsis thaliana Q9LYV8 201 RecName: Full=Probable cytokinin riboside 5'- (LOG) monophosphatephosphoribohydrolase LOG6; AltName: Full=Protein LONELY GUY 6 [Arabidopsis thaliana] LOG Oryza sativa Q5ZC82 242 RecName: Full=Cytokinin riboside 5'-monophosphate phosphoribohydrolase LOG; AltName: Full=Protein LONELY GUY [Oryza sativa Japonica Group] Purine nucleoside Purine nucleoside Enterobacter aerogenes CCG31872 239 Purine nucleoside phosphorylase (EC 2.4.2.1) [Enterobacter aerogenes phosphorylase: CK phosphorylase EA1509E] biosynthesis (EC 2.4.2.1) Adenosine kinase Adenosine kinase Burkholderia rhizoxinica CBW73882 312 Adenosine kinase (EC 2.7.1.20) [Burkholderia rhizoxinica HKI 454] (EC 2.7.1.20) Adenosine Yarrowia lipolytica CAG78600 347 YALI0F23463p [Yarrowia lipolytica CLIB122] kinase:YALI0F23463p:EC 2.7.1.20 Adenine Adenine Burkholderia rhizoxinica CBW76115 188 Adenine phosphoribosyltransferase (EC 2.4.2.7) [Burkholderia rhizoxinica phosphoribosyltransferase phosphoribosyltransferase HKI 454] 162 (EC 2.4.2.7)

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Cytokinin dehydrogenase Cytokinin dehydrogenase Fusarium oxysporum ENH69814 484 Cytokinin dehydrogenase 3 [Fusarium oxysporum f. sp. cubense race 1] (CKX) (EC 1.5.99.12) AtCKX1 (EC 1.5.99.12) Arabidopsis thaliana AEC09992 575 cytokinin dehydrogenase 1 [Arabidopsis thaliana] AtCKX2 Arabidopsis thaliana Q9FUJ3 501 Full=Cytokinin dehydrogenase 2; AltName: Full=Cytokinin oxidase 2; Short=AtCKX2; Short=CKO 2; Flags: Precursor [Arabidopsis thaliana] AtCKX3 Arabidopsis thaliana Q9LTS3 523 Full=Cytokinin dehydrogenase 3; AltName: Full=Cytokinin oxidase 3; Short=AtCKX3; Short=CKO 3; Flags: Precursor [Arabidopsis thaliana] AtCKX4 Arabidopsis thaliana Q9FUJ2 524 Full=Cytokinin dehydrogenase 4; AltName: Full=Cytokinin oxidase 4; Short=AtCKX4; Short=CKO 4; Flags: Precursor [Arabidopsis thaliana] AtCKX5 Arabidopsis thaliana Q67YU0 540 Full=Cytokinin dehydrogenase 5; AltName: Full=Cytokinin oxidase 5; Short=AtCKX5; Short=AtCKX6; Short=CKO5; Flags: Precursor [Arabidopsis thaliana] AtCKX6 Arabidopsis thaliana Q9LY71 533 Full=Cytokinin dehydrogenase 6; AltName: Full=Cytokinin oxidase 6; Short=AtCKX6; Short=AtCKX7; Short=CKO6; Flags: Precursor [Arabidopsis thaliana] AtCKX7 Arabidopsis thaliana Q9FUJ1 524 Full=Cytokinin dehydrogenase 7; AltName: Full=Cytokinin oxidase 7; Short=AtCKX5; Short=AtCKX7; Short=CKO7 [Arabidopsis thaliana] N-glucosyl transferase AtZNG1 Arabidopsis thaliana Q9FI99 464 putative UDP-glycosyltransferase / cytokinin-N-glucoside synthesis UGT76C1(Full=UDP-glycosyltransferase 76C1; AltName: Full=Cytokinin- N-glucosyltransferase 1 [Arabidopsis thaliana]) Glucosyl transferase (EC Komagataella pastoris XP_002493240 578 Glucosyl transferase, involved in N-linked glycosylation [Komagataella 2.4.1.118) pastoris GS115] O-glucosyltransferase ZOG(trans: EC 2.4.1.203) Phaseolus lunatus Q9ZSK5 459 RecName: Full=Zeatin O-glucosyltransferase; AltName: Full=Trans-zeatin P. lunatus O-beta-D-glucosyltransferase [Phaseolus lunatus] cis: EC 2.4.1.215 Zea mays NP_001105017 467 cis-zeatin O-glucosyltransferase 1 [Zea mays] xylose: EC 2.4.2.40 Phaseolus vulgaris AAD51778 454 zeatin O-xylosyltransferase [Phaseolus vulgaris] AtZOG1 Arabidopsis thaliana Q9ZQ99 491 putative UDP-glycosyltransferase / cytokinin-O-glucoside synthesis UGT73C1( Full=UDP-glycosyltransferase 73C1; AltName: Full=Cytokinin-O-glucosyltransferase 1; AltName: Full=Zeatin O- glucosyltransferase 1; Short=AtZOG1 [Arabidopsis thaliana]) AtZOG2 Arabidopsis thaliana Q9SK82 489 putative trans-zeatin-O-ß-D-glycosyltransferase / cytokinin-O-glucoside synthesis UGT85A1 (Full=UDP-glycosyltransferase 85A1; AltName: Full=Cytokinin-O-glucosyltransferase 2; AltName: Full=Zeatin O- glucosyltransferase 2; Short=AtZOG2 [Arabidopsis thaliana]) AtZOG3 Arabidopsis thaliana Q9ZQ94 495 putative UDP-glycosyltransferase / cytokinin-O-glucoside synthesis UGT73C5 (AtDOGT1)(Full=UDP-glycosyltransferase 73C5; AltName: Full=Cytokinin-O-glucosyltransferase 3; AltName: Full=Deoxynivalenol- glucosyl-transferase 1; AltName: Full=Zeatin O-glucosyltransferase 3; Short=AtZOG3 [Arabidopsis thaliana])

ß-glucosidase ß-glucosidase (E. Enterobacter aerogenes CCG30299 456 Beta-glucosidase (EC 3.2.1.21); 6-phospho-beta-glucosidase (EC 3.2.1.86) 163 aerogenes EC 3.2.1.21) [Enterobacter aerogenes EA1509E]

164

ß-glucosidase (N. Neurospora crassa CAD71254 139 related to beta-glucosidase (EC 3.2.1.21) precursor [Neurospora crassa] crassaEC 3.2.1.21) MiaB: 2MeSZ pathway MiaB: E. coli Escherichia coli P0AEI1 474 RecName: Full=tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase; AltName: Full=(Dimethylallyl)adenosine tRNA methylthiotransferase MiaB; AltName: Full=tRNA-i(6)A37 methylthiotransferase [Escherichia coli K-12] MiaC: 2MeSZ pathway MiaC: E. coli Escherichia coli NP_417024 128 iron-sulfur cluster assembly scaffold protein [Escherichia coli str. K-12 substr. MG1655] MiaE: 2MeSZ pathway MiaE: S. enterica Salmonella enterica NP_463331 270 tRNA-(ms[2]io[6]A)-hydroxylase [Salmonella enterica subsp. enterica serovar Typhimurium str. LT2] a : Amino acid (aa).

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165

Table S4.4: Identified U. maydis candidate and possible putative CK signaling and biosynthesis. Reference sequences used to identify U. maydis proteins are listed in “Reference sequence identifying U. maydis protein”. The Evalue for the top reference protein in a reciprocal blastp search is listed. Schematics for proteins with conserved domains highlighted are found in Fig. S4.3.

Protein Reference sequence Functional NCBI Accession Evalue for top reference UMAG # length PEDANT DESC NCBI DESC identifying U. maydis category a number protein in reciprocal blastp (aa) protein

Histidine kinase UMAG_02739 1356 probable nik-1 protein putative nik-1 protein XP_011389101 SLN1c,AtHK2-4 SLN1: 2E-13 (Os-1p protein) (Os-1p protein) [Ustilago maydis 521] UMAG_11957 1526 related to histidine hypothetical protein XP_011389844 SLN1,AtHK2-4 SLN1: 5E-20 kinase UMAG_11957 [Ustilago maydis 521] UMAG_04773 2148 hypothetical protein hypothetical protein XP_011391642 AtHK3,2,4 AtHK3: 3E-19 UMAG_04773 [Ustilago maydis 521] Histidine UMAG_10726 185 related to YPD1 - hypothetical protein XP_011391532 YPD1c, AtHP1-2 YPD1: 3E-18 phosphotransfer two-component UMAG_10726 phosphorelay [Ustilago maydis 521] intermediate Response regulator UMAG_03346 683 related to SKN7 - hypothetical protein XP_011389736 SKN7c,AtARR1-2,10- SKN7: 2E-33 transcription factor UMAG_03346, partial 14,16-18,20-22

Signaling (C-terminal fragment) [Ustilago maydis 521] UMAG_11179 203 hypothetical protein hypothetical protein XP_011391946 SSK1,AtARR16,17,22 SSK1: 6E-12 UMAG_11179 [Ustilago maydis 521] UMAG_04506 495 hypothetical protein hypothetical protein XP_011390838 SSK1,AtARR10,12 SSK1: 5E-08 UMAG_04506 [Ustilago maydis 521] Equlibrative UMAG_11433 569 related to Inhibitor- hypothetical protein XP_011386760 AtENT8c AtENT8: 7E-11 nucleoside sensitive equilibrative UMAG_11433 transporter nucleoside transporter [Ustilago maydis 521] 1

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tRNA- UMAG_10043 491 related to tRNA hypothetical protein XP_011386632 AtIPT2c, AtIPT1,3-9 AtIPT2: 9E-20 isopentenyltransfer isopentenylpyrophosp UMAG_10043 ase hate transferase [Ustilago maydis 521] Cytochrome P450 UMAG_06459 535 Cytochrome P450 Cytochrome P450 XP_011392727 CYP735A1,2, CYP735A1: 9E-20 monooxygenase* monooxygenase monooxygenase cytochrome P450 mono involved in Ustilagic involved in Ustilagic oxygenase Acid production Acid production [Ustilago maydis 521] UMAG_01980 583 related to Cytochrome hypothetical protein XP_011387894 CYP735A1,2 CYP735A1: 1E-35 P450 4F8 UMAG_01980 [Ustilago maydis 521] UMAG_04189 652 related to Cytochrome hypothetical protein XP_011390676 CYP735A1,2 CYP735A1: 5E-29 P450 UMAG_04189 [Ustilago maydis 521] UMAG_05664 569 related to Cytochrome hypothetical protein XP_011391432 CYP735A1,2 P450 UMAG_05664 [Ustilago maydis 521] Phosphatase UMAG_04114 591 probable PHO8 - putative repressible XP_011390615 Phosphatase (EC Phosphatase (EC 3.1.3.1): repressible alkaline alkaline phosphatase 3.1.3.1)c 1E-27 phosphatase vacuolar vacuolar [Ustilago maydis 521] UMAG_10574 628 related to PHO8 - hypothetical protein XP_011390069 Phosphatase (EC Phosphatase (EC 3.1.3.1): repressible alkaline UMAG_10574 3.1.3.1) 2E-24 phosphatase vacuolar [Ustilago maydis 521] Biosynthesis: Catabolism/ Biosynthesis:Anabolism Catabolism/ 5'-ribonucleotide UMAG_11668 1058 related to 5`- hypothetical protein XP_011388064 5'-nucleotidase(EC phophohydrolase nucleotidase UMAG_11668 3.1.3.5) precursor [Ustilago maydis 521] Adenosine UMAG_11846 580 related to nucleoside hypothetical protein XP_011387459 Adenosine nucleosidase Adenosine nucleosidase nucleosidase hydrolase UMAG_11846 (EC 3.2.2.7)c (EC 3.2.2.7): 3E-20 [Ustilago maydis 521] UMAG_01783 426 related to Inosine- hypothetical protein XP_011387738 Adenosine nucleosidase Adenosine nucleosidase uridine preferring UMAG_01783 (EC 3.2.2.7) (EC 3.2.2.7): 9E-7 nucleoside hydrolase [Ustilago maydis 521] Phosphoribohydrol UMAG_03153 555 related to ATP- hypothetical protein XP_011389615 LOG, AtLOG6 LOG: 2E-40 ase (LOG) binding cassette UMAG_03153 (ABC) transporter [Ustilago maydis 521]

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Purine nucleoside UMAG_03504 330 related to Purine- hypothetical protein XP_011389949 Purine nucleoside Purine nucleoside phosphorylase nucleoside UMAG_03504 phosphorylase phosphorylase phosphorylase [Ustilago maydis 521] (EC 2.4.2.1) (EC 2.4.2.1): 2E-8

Adenosine kinase UMAG_00797 345 probable adenosine putative adenosine XP_011386569 Adenosine Adenosine kinase kinase [Ustilago kinase:YALI0F23463p: kinase:YALI0F23463p:EC maydis 521] EC 2.7.1.20c 2.7.1.20: 3E-90 UMAG_04561 359 related to RBK1 - hypothetical protein XP_011390877 Adenosine Adenosine putative ribokinase UMAG_04561 kinase:YALI0F23463p: kinase:YALI0F23463p:EC [Ustilago maydis 521] EC 2.7.1.20 2.7.1.20: 5E-6 Adenine UMAG_10904 202 probable APT1 - putative adenine XP_011390962 Adenine Adenine phosphoribosyltran adenine phosphoribosyltransfer phosphoribosyltransfer- phosphoribosyltransferase sferase phosphoribosyltransfe ase [Ustilago maydis ase (EC 2.4.2.7)c (EC 2.4.2.7): 2E-33 rase 521] Cytokinin UMAG_04533 527 hypothetical protein hypothetical protein XP_011390858 Cytokinin AtCKX2: 5E-12 dehydrogenase UMAG_04533 dehydrogenase (EC (CKX) [Ustilago maydis 521] 1.5.99.12), AtCKX1 (EC 1.5.99.12), 2-7 UMAG_11765 560 related to 6-hydroxy- hypothetical protein XP_011391004 Cytokinin D-nicotine oxidase UMAG_11765 dehydrogenase (EC [Ustilago maydis 521] 1.5.99.12), AtCK2-5,7 UMAG_02157 502 hypothetical protein hypothetical protein XP_011388510 AtCKX1 (EC AtCKX2: 9E-13 UMAG_02157 1.5.99.12), 2,3,5,7 [Ustilago maydis 521] UMAG_10861 527 related to Reticuline hypothetical protein XP_011392300 Cytokinin oxidase precursor UMAG_10861 dehydrogenase (EC [Ustilago maydis 521] 1.5.99.12), AtCKX3, 5 UMAG_11275 604 related to D-lactate hypothetical protein XP_011387398 Cytokinin dehydrogenase UMAG_11275 dehydrogenase (EC (cytochrome) [Ustilago maydis 521] 1.5.99.12)

O- UMAG_06467 578 Ustilagic Acid Ustilagic Acid XP_011392734 ZOG(trans: EC ZOG(trans: EC 2.4.1.203) glucosyltransferase glycosyl transferase glycosyl transferase 2.4.1.203) P. lunatusc, P. lunatus: 1E-11 /N-glucosyl [Ustilago maydis 521] AtZNG1, cis: EC transferase 2.4.1.215, xylose: EC 2.4.2.40, AtZOG1-3 UMAG_00605 744 related to hypothetical protein XP_011386428 Glucosyl transferase glucosyltransferase UMAG_00605 (EC 2.4.1.118)

[Ustilago maydis 521] 167

168

UMAG_02519 1220 related to ALG6 - hypothetical protein XP_011388934 Glucosyl transferase glucosyltransferase UMAG_02519 (EC 2.4.1.118) [Ustilago maydis 521] ß-glucosidase UMAG_06075 872 related to beta- hypothetical protein XP_011392435 ß-glucosidase (N. glucosidase UMAG_06075 crassa EC 3.2.1.21) [Ustilago maydis 521] UMAG_04032 804 probable beta- putative beta- XP_011390477 ß-glucosidase (N. glucosidase glucosidase [Ustilago crassa EC 3.2.1.21) maydis 521] UMAG_00446 819 probable beta- putative beta- XP_011386313 ß-glucosidase (N. glucosidase glucosidase [Ustilago crassa EC 3.2.1.21) maydis 521] MiaC UMAG_05632 208 probable ISU1 - Iron- putative iron-Sulfur XP_011391409 MiaC: E. colic MiaC: E. coli: 7E-67 Sulfur cluster nifU- cluster nifU-like like protein protein [Ustilago maydis 521] *Greater than five orthologs were detected, only the top four are listed. a : Amino acid (aa). C: candidate orthologs.

168

169

170

171

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Fig. S4.1. Protein MAFFT alignment of the conserved domain superfamily: P- loop_NTPase for select isopentenyltransferase proteins visualized using Jalview.2.8.2. Colour highlighting as per Clustalx default settings. Short forms are as listed in Table S4.1. Alignment was used for construction of an unrooted phylogenetic tree (Fig. 4.1).

173

Fig. S4.2. Amino acid sequence alignment of IPTs from S. cerevisiae (AC. NP_014917), Homo sapiens (AC. AAG31324) and U. maydis (AC. XP_011386632). Proteins were aligned using MAFFT and visualized using Jalview.2.8.2. Black underlined areas (1-4) indicate motifs highly conserved among IPTs (Golovko et al., 2000: 1. ATP/GTP motif, 3. putative dimethylallylpyrophosphate binding site). Additional underlines are based on regions identified in S. cerevisiae MOD5 using

http://www.uniprot.org/uniprot/P07884; and Kakimoto (2003). Coloured lines; blue hatched lines: interaction with substrate tRNA; 173 orange: core aggregation region; green dotted lines: DMAPP binding site/interaction with isopentenylpyrophosphate transferase.

174

175

176

Fig. S4.3. Schematic of CK signaling and biosynthesis reference proteins and their corresponding U. maydis ortholog, found in Table 4.5, Table S4.3 and Table S4.4. a-d:

177

CK signaling proteins, e-q: CK biosynthesis proteins. Conserved domain locations and descriptions were identified using NCBI-Batch-CD. Coloured boxes indicate conservation of specific conserved domains between proteins. Dashed line boxes show conserved domains that are unique to a particular protein and not found in the others presented. U. maydis orthologs are listed in order of likelihood. Bracketed numbers in e- q correspond to enzyme numbers found in Fig. 4.7 and Fig. S4.4.

178

Fig. S4.4. Predicted CK biosynthetic pathway of the U. maydis- Z. mays pathosystem. This figure represents the exchange of CK intermediates based on product detection and predicted product interconversion. Purple boxes indicate pathways that are likely targeted by U. maydis during infection. Grey boxes highlight pathways that are not well characterized, put predicted to be active in this system. Information from this pathway was inferred from the current study and plant and bacterial investigations (Persson and Bjork 1993, Persson et al., 1994, Sakakibara 2006, Frébort et al., 2011, Spichal 2012, Morrison et al., 2015a). Numbers represent inferred enzymes as follows: 1. adenylate isopentenyltransferase (EC 2.5.1.27); 2. tRNA-isopentenyltransferase (EC 2.5.1.8); 3.cytochrome P450 mono-oxygenase; 4. phosphatase (EC 3.1.3.1); 5. 5’ ribonucleotide phosphohydrolase (EC 3.1.3.5); 6. adenosine nucleosidase (EC 3.2.2.7); 7. CK phosphoribohydrolase ‘Lonely guy: LOG’; 8. purine nucleoside phosphorylase (EC 2.4.2.1); 9. adenosine kinase (EC 2.7.1.20); 10. adenine phosphoribosyltransferase (EC 2.4.2.7); 11. cytokinin dehydrogenase (CKX) (EC. 1.5.99.12); 12. N-glucosyl transferase (EC 2.4.1.118); 13. O-glucosyl transferase; 14. ß-glucosidase (EC 3.2.1.21); 15. zeatin reductase (EC 1.3.1.69); 16. zeatin isomerase; 17i. MiaB; 17ii. MiaC; 18. MiaE; 19. cis- hydroxylase. Bold and underlined enzyme numbers are found in the methylthiol CK pathway and have not been examined previously in the context of plant or fungal biosynthesis. Underlined enzyme numbers are predicted but not well characterized and no reference sequence was available. Underlined analytes were not detected in the current study but represent putative products of the presented pathway. Dashed lines

179 indicate predicted pathways that have not been fully investigated within the plant/ fungal system.

180

ACKNOWLEDGMENTS

The authors acknowledge the Natural Sciences and Engineering Research Council

(NSERC) of Canada for research funding and the Ontario Graduate Scholarship program for student support.

LIST OF AUTHOR CONTRIBUTIONS

E.N.M, R.J.N., B.J.S. designed the research; E.N.M. performed the research and analyzed the data; E.N.M, R.J.N., B.J.S wrote the article.

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CHAPTER 5

GENERAL DISCUSSION

INTRODUCTION

Phytohormone analysis of fungal plant interactions has often looked at phytohormone fluxes within the pathosystem without deciphering the individual hormone contribution by the fungus or the plant. This thesis sought to identify the dominant contributing CK biosynthetic pathway in fungi and examine the CK contribution of a plant host and fungal pathogen in a model pathosystem. Previous chapters were linked by the analysis of cytokinins and abscisic acid in fungi and their role in fungal development separate from, and in association with, a host plant. The main research objectives were to:

1. Assess the prevalence of cytokinins among a variety of fungi independent of host interaction and

2. Determine how fungal infection impacts phytohormone balance within a host plant.

To initially address these questions, an environmental survey was conducted in which twenty basidiomycete forest fungi were harvested and profiled for CKs and ABA

(Chapter 2). Previous in-depth environmental surveys had not been conducted on forest fungi. With these results a more targeted approach was carried out by manipulating and examining a model fungal plant pathogen Ustilago maydis and its interaction with its host

Zea mays (Chapters 3 and 4). Using this system the impact of stopping fungus-produced

CKs in this pathosystem was determined (Chapter 4). In this general discussion important findings will be highlighted and future research discussed.

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PHYTOHORMONE DETECTION IN FOREST FUNGI

While CKs and ABA are traditionally viewed as plant hormones recent evidence has indicated that these phytohormones may be present in a wider number of organisms including bacteria, algae and fungi (Hartung 2010, Tsavkelova et al., 2006, Stirk and van

Staden 2010). An environmental survey of basidiomycete forest fungi (Chapter 2) provided insight into the widespread presence of CKs and ABA in fungi. Although phytohormones have often been measured during fungal-plant interactions for insight into their role in disease development few have examined the production of CKs and ABA by non-plant pathogens. Chapter 2 presented an environmental survey in which, a variety of basidiomycete fungi with various modes of nutrition including ectomychorrizal, wood-rot and saprotrophy were profiled. This was one of the first studies to identify a common conserved CK biosynthetic pathway among fungi. Important findings included:

1. The widespread presence of ABA in fungi

2. The widespread presence of CKs in fungi

3. The presence of CKs consistent with the dominance of the tRNA degradation

pathway

4. The potential importance of CKs and ABA in fungal development.

Through this survey it was found that of the 27 potential CKs that were purified and scanned for, there were seven common CKs detected among all fungi, regardless of their mode of nutrition or phylogeny. ABA was also detected across all fungi with no connection to mode of nutrition or phylogeny. Because no relationship was identified between the mode of fungal nutrient acquisition and hormone presence or level, it was suggested that these phytohormones play a role in fungal development, separate from

190 plant interaction. The same seven CKs were detected across all fungi sampled (iPRP, iPR, iP, cisZRP, cisZR, 2MeSZR, and 2MeSZ) indicating that these fungi share a common CK biosynthetic pathway. Since no transZ CKs were detected among these samples it was concluded that the active CK pathway in fungi was likely the tRNA degradation pathway. Based on the detected CKs a common biosynthetic pathway was proposed for fungi which included a common initial analyte and branches leading to the synthesis of methylthiol CK derivatives, iP and cisZCK forms. Previous bacterial analysis had outlined the steps in methylthiol modification of specific tRNAs (Persson and Bjork 1993) however this had never been linked to current CK pathways. This study connected these pathways and presented a combined CK biosynthetic pathway in Fig.

2.4. These important findings were used to target a fungal-plant pathogen and examine the importance of the tRNA degradation pathway in fungal development and CK biosynthesis.

PHYTOHORMONES AND DISEASE DEVELOPMENT

Many organisms including fungi, bacteria and humans have CK-modified tRNA molecules that are important in translational efficiency (Golovko et al., 2000). Previous research stated that CK production from tRNA was at most a minor CK contributor and would not affect total hormone activity significantly (Golovko et al., 2002) so these modifications were rarely examined within the context of CK biosynthesis. However, many plant-pathogen infections show an increase in tRNA degradation derived CK products. Specifically cisZCKs predominated during infection as observed in, maize leaf infection by C. graminicola, corn seedling infection by U. maydis, and Arabidopsis

191 thaliana infection by the bacterium Rhodococcus fascians (Pertry et al., 2009, Bruce et al., 2011, Behr et al., 2012). In some cases these infections can yield differing disease symptoms associated with the level of CK accumulation. In cultured R. fascians, the pathogenic strains contained the same spectrum of CKs as their nonpathogenic counterpart yet with higher levels of 2MeScisZ, iP and cisZ (Pertry et al., 2009). This variability in virulence between different strains has also been seen in U. maydis with the comparison of the dikaryon and diploid infection of corn seedlings (Babu et al., 2005); however, no CK analysis had been conducted to detect any profile difference that may account for this difference in symptom development. Chapter 3 used solopathogenic and dikaryotic forms of U. maydis to compare virulence during cob infection and phytohormone profiles during an infection time course. Previous in lab observations noted a difference in disease development and symptom severity in corn seedling disease assays between these two strains, with the dikaryon being more virulent (Fig. S3.1). This chapter sought to determine if the difference in virulence and symptom development in seedlings would also occur in cob tissue and if these differences were related to phytohormone changes during disease development. Key findings included:

1. U. maydis infection of cob tissue specifically alters the CK balance within Z.

mays

2. There is a specific decrease in storage CK glucosides during infection

3. There are substantial increases in key CKs

4. CK accumulation and tumour manifestation are more dramatic in dikaryon

infected tissue

5. ABA accumulation may be important during tumour development.

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Findings indicated that cisZCKs, specificially cisZR, increased during tumour development. This increase was preceded by an increase in ABA. This increase in ABA was less dramatic in the dikaryon which accumulated more cisZCKs and showed an increased virulence during infection as compared to the solopathogen which showed a higher ABA spike and reduced accumulation of cisZCKs and virulence. This led to the conclusion that CKs, specifically cisZCKs, contribute to the virulence level observed during U. maydis infection of corn and a balance between CK and ABA is necessary for tumour development. This finding suggested a more complex interaction between phytohormone systems during infection. A fine balance and constraints may also be required on this system for tumour development. As suggested in Chapter 3 the level of

ABA accumulation past a certain level may lead to hindered growth in the developing tumour and lower virulence as seen in the solopathogen infected tissue.

CONTROL OF CK BIOSYNTHESIS IN U. MAYDIS

In the U. maydis-Zea mays model both the host plant and the pathogen are capable of producing cytokinins. In other systems this fact has lead to the inability to categorically assign the cytokinin contribution made by each (Ashby 2000). The attributes of U. maydis permitted the analysis of the U. maydis-Zea mays interaction without contribution of cytokinins from the fungus through the creation of gene deletion mutants. The sole tRNA-IPT gene was deleted in the solopathogenic U. maydis strain, SG200, and phytohormone profiles analyzed for these fungal strains separate from the host plant.

Pathogenesis assays were carried out in seedling and cob tissue for both SG200 and

193 tRNA-IPT deletion mutants and phytohormone profiles analyzed. Key findings in this study were:

1. The similarity of U. maydis tRNA-IPT to other DMAPP: tRNA-IPTs

2. That tRNA-IPT controls CK biosynthesis in U. maydis

3. Deletion of tRNA-IPT decreases virulence in seedlings and cob tissue

4. Typical CK accumulation in cob infected tissue is not seen in tRNA-IPT

deletion strains.

5. The ABA spike during U. maydis infection may be needed for tumour

development and CK accumulation.

6. Key enzyme steps in CK biosynthesis and signaling in U. maydis were

presented.

Deletion of the sole tRNA-IPT in U. maydis revealed the key step in CK biosynthesis in this fungus. Deletion mutants were no longer able to synthesize CKs and they were reduced in seedling virulence and hampered in cob tissue infection and tumour development. Furthermore it was suggested that U. maydis may be capable of taking up, processing and converting CKs from medium when not impaired in CK biosynthesis.

SG200 grown on medium that contained exogenous CKs had a different CK profile; a significant increase in cisZR and iPCKs when compared to SG200 grown on non CK containing medium (Table 4.1).

By removing fungal CK contribution it was found that cisZCK accumulation did not occur during the later stages of tumour development which was seen in the SG200 infection, suggesting that fungal CK production is necessary for this characteristic accumulation. ABA was also found to increase prior to cisZCK accumulation in the

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SG200 infection as well as in previous analysis in Chapter 3, this ABA accumulation was not present in SG200∆ipt1 infected tissue. This suggests that fungal presence without fungal CK production does not trigger other phytohormone responses (ABA) that are necessary in sustaining and continuing tumour development. The U. maydis CK biosynthesis and signaling pathways were also putatively outlined through blastp analysis and protein comparisons.

Findings from Chapters 2, 3 and 4 have produced a baseline in which to continue the analysis of the U. maydis- Zea mays interaction as well as further characterize the importance of the tRNA degradation pathway in fungal CK biosynthesis. The following outlines potential next steps in this area of research.

FURTHER CHARACTERIZATION OF tRNA-IPT

Chapter 4 functionally characterized the importance of the tRNA-IPT gene in U. maydis fungal CK biosynthesis. Protein alignments suggested conservation of key substrate binding domains when compared to S. cereviseae (Mod5) and Homo sapiens (tRNA-

IPPT; Fig. S4.2). This chapter further grouped the tRNA-IPT in U. maydis as a DMAPP: tRNA-IPT. To further analyze the importance of this key enzyme in CK biosynthesis targeted mutations directed at the identified substrate binding domains would reveal if disrupting these sites impacts CK biosynthesis in U. maydis and would identify key functional sites in this enzyme. Previous studies have looked at feeding experiments in which components of the MVA pathway have been added to medium to determine if fungal CK processing would occur (Behr et al., 2012). Behr et al. (2012) supplemented

Colletotrichum graminicola, grown in minimal medium, with DMAPP and CK

195 precursors to assess CK production. Linking MVA products with CK biosynthesis in U. maydis would strengthen the findings in Chapter 4. Other feeding experiments could also include supplementing U. maydis growth medium with different sidechain donours and performing CK analysis following incubation to determine if supplementing with increased precursor molecules impacts the total CKs produced by the fungus. This would include the separate addition of DMAPP as well as IPP. Although DMAPP and IPP can be isomerized between each other, as seen in Fig. 5.1 which outlines the initial stages of the MVA pathway in U. maydis, this may provide context for the preference of side chain donours for the initial steps of CK biosynthesis in U. maydis. To further assess the role of tRNA-IPT in CK biosynthesis overexpression strains should be created to analyze CK produced as well as evaluate any impact on pathogenicity that tRNA-IPT overexpression may have on this system.

THE ROLE OF CKS AT DIFFERENT FUNGAL LIFESTAGES

The ability of non-pathogenic U. maydis haploid cells to produce CKs suggests that CK synthesis may not be intended solely for infection of Z. mays (Bruce et al., 2011). While the production of CKs by other fungi has been noted (Cooper and Ashby 1998), the role of CKs in fungal development has not been examined. Precursor feeding experiments used to further characterize the role of tRNA-IPT could work in parallel to direct CK feeding experiments in U. maydis. Chapter 2 identified the likely role of CKs in fungal development separate from a host plant. Initial assessment of the various stages of fungal development have been conducted on U. maydis in Chapter 4 and previous research

(Bruce et al., 2011). A future experiment would examine how exogenous addition of

196

CKs can impact the growth of U. maydis at various stages of fungal development including haploid and dikaryotic growth forms. These CKs would include cisZR and iPR which are produced by this fungus. Labelled exogenous CKs could also be added in growth assays to see if exogenous CK addition impacts CK biosynthesis in the fungus.

By adding labelled CKs any changes in endogenous fungal produced CKs could be determined. Response to exogenous CK addition was suggested in Chapter 4 as increased detection of cisZR was found when U. maydis was grown on CK containing medium. It was also suggested that CK production in U. maydis may require a degree of

‘priming’ to maintain production, as no increased CK production was detected in ipt1 deletion strains grown on exogenous CK supplemented medium. This response to exogenous CKs has implications for the interaction and use of plant derived CKs in fungal CK production (Chapter 4).

PLANT AND PATHOGEN GENE EXPRESSION

Another experiment would involve assessing the expression of genes involved in CK biosynthesis by U. maydis to determine if the host plant or U. maydis has an influence on level of expression of any of these genes. Chapter 4 outlined potential U. maydis genes involved in CK biosynthesis and CK signaling based on similarity searches with proteins known to be involved in CK biosynthesis or signaling (Table 4.5 and Table S4.3).

Experiments would be conducted on U. maydis separate from the plant as well as during disease development to determine if the expression of these U. maydis genes correlate to response or changes in CK profiles. Separate from the host U. maydis CK feeding experiments could be done to assess if gene expression is influenced by exogenous CK

197 addition. Targeted gene deletions to genes identified in Table 4.5 and those that respond to CK addition would further assess their putative impact on CK biosynthesis and signaling. Gene expression analysis could also be conducted using infected tissue and transcript levels of identified genes compared between SG200, dikaryon and ∆ipt1 strain infections. Hinsch et al. (2015) examined Claviceps purpurea expression of three CK biosynthesis related genes during infection of rye. They found that although all were expressed at different levels, specifically cpipt-log, an isopentenyltransferase fused lonely guy gene, and cpp450, a cytochrome P450 monooxygenase, were induced during early stages of infection. Hinsch et al. (2015) indicated that the expression of cpipt-log may suggest fungal CK production at these stages of infection. By examining the expression of U. maydis identified genes during infection connections may be drawn to observed changes in CK levels during tumour development.

In addition to assessment of fungal gene expression, host gene expression during infection should be examined. Initial studies by Brefort et al. (2014) found that the cytokinin oxidase 3 gene in Z. maydis is likely suppressed by effectors during normal U. maydis seedling infection, suggesting that CK degradation is hampered and may thereby permit CK accumulation during infection as was seen in Chapter 3 and 4. The

SG200∆ipt1 strain provides an opportunity to assess the expression of key host CK genes that may be impacted by fungal derived CKs. Specific changes in host gene expression have been noted in microarray data from Doehlmann et al. (2008) during U. maydis infection. These changes included a >3 fold increase in Zea mays CK receptor: AHK4 histidine kinase receptor expression at 4 dpi in infected corn seedlings, this could suggest increased CK sensing potentially induced by U. maydis infection. Other Z. mays HKs

198 could also be examined including the ZmHK1 identifed by Yonekura-Sakakibara et al.

(2004). Doehlemann et al. (2008) also noted a decrease in a Zea mays potential glycosyltransferase at 2 dpi, this could suggest that during infection the conversion of

CKs to storage CK glucosides may be impacted. Brugiere et al. (2008) identified a Zea mays isopentenyltransferes, ZmIPT2, as most likely involved in CK production in developing kernels (Brugiere et al., 2008), this would be another target gene for examining host expression during infection. These changes in host gene expression profiles suggest that U. maydis is capable of manipulating the host’s CK signaling and storage pathways, using the SG200∆ipt1 we could examine the changes in host CK related gene expression and determine how this may alter CK profiles.

ABA AND CK INTERACTION

As discussed in Chapter 3 and 4 there is a dynamic interaction occurring between CKs and ABA during U. maydis infection of corn. It appears that CK production by the fungus is necessary to stimulate ABA accumulation in the plant-pathogen system which is then followed by the accumulation of cisZCKs (Fig. 4.8). Without these key phytohormone triggers, tumour formation in cob tissue does not occur normally. Fig. 5.1 outlines the MVA pathway in U. maydis and the shared IPP/DMAPP substrate between the ABA and CK pathways. This connection between the MVA pathway and the branch point to ABA and CK pathways has not been previously outlined in U. maydis. Steps in the MVA pathway have been previously identified in Lombard and Moreira (2010). This idea of a shared common substrate has been implied in Arabidopsis thaliana (Zd’árská et al., 2013) and can likely be further applied to corn. Fig. 5.1 presents the various genes

199 that are believed to be responsible for these steps in U. maydis. This interaction and shared common substrate may explain the dynamics of the fungal-plant system whereby an ABA increase would leave less substrate for CK production and vice versa as seen in the accumulation of cisZR in tumour tissue. Another reason for the offset of ABA followed by CK accumulation is the likely interaction and regulation that occurs between these phytohormone groups. Brugiere et al. (2003) found that, with exogenous application of ABA to maize kernels, there was an increase in the level of cytokinin oxidase 1 (Ckx1) transcript detected, which could hamper the characteristic CK increase in developing kernels. The authors suggested that ABA may act to control CK levels through its influence on Ckx1 expression (Brugiere et al., 2003). As discussed in Chapter

3 this peak in ABA, which is more dramatic in solopathogen infections, may act to control tumour development and reduce virulence in that system. Since U. maydis effectively hijacks a developing seed in order to grow, it is possible that initial CK production by the fungus is controlled through the ABA accumulation which triggers

Ckx1 expression in the plant which results in CK degradation and limits CK accumulation early in development. This is then overcome by the system following the

ABA spike and CK accumulation occurs in the tumour tissue. As described previously cisZ and 2MeSZ CKs were found to be poor substrates for 3 apoplastic CK oxidases

(Pertry et al., 2009) and therefore are more resistant to degradation. cisZCK accumulation following the ABA spike may be due to either decreased host CKX activity or that cisZCKs are poor substrates for CK oxidases. Other phytohormone networks may also be at work. ABA has been implicated in hampering the defense response of host plants during infection by Magnaporthe grisea (Jiang et al., 2010), Pseudomonas

200 syringae pv. tomato (Mohr and Cahill 2007), and Xanthomonas oryzae pv. oryzae (Xu et al., 2013) through the suppression of the salicylic acid (SA) pathway. The lack of ABA spike in SG200ipt1 infections may lead to increased SA response by the plant and heightened plant defense thereby attenuating disease development. SG200∆ipt1 strains are still capable of causing disease in seedling pathogenesis assays; however the virulence is reduced compared to SG200 infection.

CONCLUSIONS

The CK tRNA degradation pathway is still considered a minor contributor in some species but it appears to be very important in the production of CKs in certain fungi.

While tRNA derived CKs may be considered a byproduct of tRNA degradation they are a component of most organisms and their presence influences pathogen development within the host. Golovko et al. (2002) stated that, when made available through tRNA degradation, cisZ would not affect total hormone activity significantly. Unfortunately this statement has put the discovery of the impact of this pathway in the background for many years. Only recent research including this thesis has focused on the importance of the tRNA degradation pathway and its role in CK production.

The main findings in this thesis were the discovery of widespread CK and ABA production among fungi, the functional characterization of a tRNA-IPT in U. maydis which controls CK production in this fungus as well as the first comprehensive CK pathway for fungi and fungal-plant interaction. These findings can be applied to many other biotrophic fungal plant pathogens which hijack and mimic existing host sink systems in order to develop.

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Fig. 5.1. Proposed U. maydis MVA pathway leading to CK and ABA biosynthesis. Pathway is derived from findings in Lombard and Morieri (2011) and Wang et al. (2014). The U. maydis UMAG number corresponding to the various steps in the MVA pathway are presented. The enzyme abbreviations are as follows: acetoacetyl-CoA thiolase (AACT); 3-hydroxy-3-methylglutaryl-CoA synthase (HMGS); 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR); mevalonate kinase (MVK); phosphomevalonate kinase (PMK); mevalonate-6-decarboxylase (MDC); isopentenyl diphosphate isomerase (IDI1); farnesyl-pyrophosphate synthetase (FPS); tRNA- isopentenyltransferase (tRNA-IPT).

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205 action and differential regulation of hormonal homeostasis. Plant Physiology 161:918- 930.

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APPENDIX I

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CHAPTER 2: Detection of phytohormones in temperate forest fungi predicts consistent abscisic acid production and a common pathway for cytokinin biosynthesis. Published in: Mycologia (2015), 107(2): 245-257 doi: 10.3852/14-157

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CHAPTER 3: Phytohormone involvement in the Ustilago maydis– Zea mays pathosystem: relationships between abscisic acid and cytokinin levels and strain virulence in infected cob tissue. Published in: PlosOne (2015), 10(6): e0130945 doi:10.1371/journal.pone.0130945