A Study of Cell Wall Integrity Control in Transgenic Plants Expressing Polysaccharide-Modifying Enzymes Nathan T

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A study of cell wall integrity control in transgenic plants expressing polysaccharide-modifying enzymes

Nathan T. Reem

A dissertation submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Major: Plant Biology

Program of Study Committee: Olga A. Zabotina, Major Professor Steven Whitham Ling Li Gustavo MacIntosh Yanhai Yin

Iowa State University

Ames, Iowa

2017

TABLE OF CONTENTS

LIST OF FIGURES iv

LIST OF TABLES v

ABSTRACT vi

CHAPTER 1 INTRODUCTION 1 Research Objectives 1 CHAPTER 2 LITERATURE REVIEW 3 Cell wall composition & structure 3 Plant response to pathogen-associated molecular patterns 6 Plant-pathogen interactions 7 Cell wall integrity: polysaccharide-sensing PRRs 9 References 12 CHAPTER 3 DECREASED POLYSACCHARIDE FERULOYLATION 21 COMPROMISES PLANT CELL WALL INTEGRITY AND INCREASES SUSCEPTIBILITY TO NECROTROPHIC FUNGAL PATHOGENS Abstract 21 Introduction 22 Materials & Methods 26 Results 36 Discussion 45 Conclusions 52 References 53 CHAPTER 4 COMPREHENSIVE TRANCRIPTOME ANALYSES 65 CORRELATED WITH UNTARGETED METABOLOME REVEAL DIFFERENTIALLY EXPRESSED PATHWAYS IN RESPONSE TO CELL WALL INTEGRITY ALTERATIONS Summary 65 Introduction 66 Materials & Methods 73 iii

Results 77 Discussion 96 Conclusions 103 References 105 CHAPTER 5 TRANSGENIC ARABIDOPSIS THALIANA PLANTS 116 EXPRESSING FUNGAL PECTIN METHYLESTERASE EXHIBIT DWARFED PHENOTYPE AND ALTERATIONS IN STRESS RESPONSE Abstract 116 Introduction 117 Materials & Methods 122 Results 131 Discussion 138 Conclusions 143 References 144 CHAPTER 6 SPATIOTEMPORAL ANALYSIS OF CELL WALL INTEGRITY 157 CONTROL IN ARABIDOPSIS THROUGH POST-SYNTHETIC MODIFICATION OF THE CELL WALL Abstract 157 Introduction 158 Materials & Methods 162 Results 163 Discussion 167 Conclusions 169 References 170 CHAPTER 7 CONCLUSIONS AND FUTURE DIRECTIONS 177 References 181

LIST OF FIGURES

Figure 2.1. Model of the plant cell wall 3 Figure 2.2. Plant innate immunity 8 Figure 3.1. Ferulic acid content in cell walls 37 Figure 3.2. AnFAE cell wall digestibility 40 Figure 3.3. AnFAE plant response to pathogens 42 Figure 3.4. Gene expression in AnFAE plants 44 Figure 3.5. Extensin content in Arabidopsis AnFAE cell walls 45 Figure 4.1. Differentially expressed genes from RNA-seq analysis 79 Figure 4.2. Mapping of stress response genes from RNA-seq analysis 88 Figure 4.3. RT-qPCR confirmation of RNA-seq analysis 90 Figure 4.4. Significantly different metabolite abundances from 92 metabolome analysis Figure 5.1. AnPME plant phenotype and cell sizes 132 Figure 5.2. AnPME cell wall analyses 134 Figure 5.3. Immunofluorescence of plant stems 136 Figure 5.4. Plant response to stresses 138 Figure 6.1. Double transgenic response to B. cinerea 164 Figure 6.2. Gibson assembly scheme for double transgenes 166

LIST OF TABLES

Table 3.1. Monosaccharide composition of AnFAE cell walls 39 Table 4.1. Cell wall-related DE genes from RNA-seq analysis 83 Table 4.2. Stress-related DE genes from RNA-seq analysis 84 Table 4.3. Transcription factor DE genes from RNA-seq analysis 85 Table 4.4. Pathways enriched by correlation of transcriptome and 95 metabolome

ABSTRACT

Plants have developed specialized mechanisms for dealing with different stresses. For example, biotic stresses are sensed extracellularly, through Cell Wall

Integrity (CWI) control. CWI control is a complex system that works via a set of receptors and signaling networks that allow cells to sense pathogens and initiate defense responses. This dissertation aims to uncover cell wall-mediated mechanisms and underlying signaling of CWI using post-synthetic modification of plant cell walls by microbial cell wall degrading enzymes (CWDEs).

We first compared CWI in Arabidopsis thaliana and Brachypodium distachyon plants expressing a Ferulic Acid Esterase (AnFAE). Both species exhibited reduced cell wall recalcitrance and increased susceptibility to fungal necrotrophs. Changes in gene expression after fungal necrotroph infection indicated distinct CWI control mechanisms between Arabidopsis and Brachypodium plants. To determine underlying signaling, we analyzed the transcriptome and metabolome of AnFAE- expressing Arabidopsis, as well as two previously characterized acetylesterases,

AnAXE and AnRAE. Transcriptome analysis uncovered discrete cellular responses between all three genotypes, including candidate genes such as transcription factors and stress response genes. Correlation of transcriptome and metabolome data yielded enrichments in primary metabolic pathways that contribute to specialized metabolism for each transgenic line. Another Arabidopsis transgenic line expressing a pectin methylesterase (AnPME) was analyzed for phenotypic effects of cell wall de-esterification. AnPME plants have significantly reduced cell wall methylation and dramatic growth defects such as reduction of root and hypocotyl length as a result vii of decreased cell expansion. AnPME plants also exhibit changes in wall degradability and response to pathogens. Ongoing research focuses on reporter gene expression to explore spatiotemporal CWI control.

In these studies, we have shown that plants sense specific changes in the cell wall, and initiate discrete metabolic responses in response to extracellular changes.

These cell wall and metabolic changes have profound effects on plant phenotype and morphology, as well as defense responses.

CHAPTER 1

INTRODUCTION

Research Objectives:

This dissertation had four objectives pertaining to cell wall integrity and plant responses to cell wall modifications. Overall, the objectives were to determine genetic pathways involved in signaling induced by and/or responses to wall modifications, and the phenotypic responses elicited by such modifications. These responses were induced through transgenic expression of microbe-derived wall- degrading enzymes.

Objective 1 (Chapter 3):

This project sought to characterize the effects of expression of a ferulic acid esterase (AnFAE) in the model dicot plant Arabidopsis thaliana and model monocot

Brachypodium distachyon and determine what phenotypic and defense-related phenotypes were caused by reduction of cell wall ferulic acid.

Objective 2 (Chapter 4):

This objective was designed to understand cell wall integrity signaling and responses in Arabidopsis thaliana plants through correlation of transcriptome and metabolome datasets. Normalized RNA transcripts and metabolite abundance in plants expressing two acetylesterases (AnAXE and AnRAE) and AnFAE plants were compared to GFP-expressing Empty Vector (EV) plants.

Objective 3 (Chapter 5):

This objective examined the importance of pectin methylesterification to plant morphology and defense through expression of a pectin methylesterase

(AnPME) in Arabidopsis plants. Analysis consisted of stress response, cell wall composition and recalcitrance assays, and phenotypic measurements.

Objective 4 (Chapter 6):

The objective of this chapter was to extend analysis of three transgenic lines with known phenotypes and responses (AnAXE, AnRAE, AnFAE) through several means. First, double transgenic lines were created to help determine whether signaling overlaps or is distinct in each of these wall integrity events. Second, fluorescent reporter lines are being used to achieve a spatiotemporal characterization of cell wall integrity and defense response signaling in these plants.

This includes the reporter gene RFP driven by the PAD3 and WRKY40 promoters to assay for defense response.

CHAPTER 2

LITERATURE REVIEW

Cell wall composition & structure

The plant cell wall is a complex, dynamic structure that encapsulates the cell and defines its size and shape. It is composed primarily of polysaccharides, as well as lignin and proteins. The cell wall composition can vary between plant species, and within the same species the wall composition can vary depending on cell age, cell type, plant genotype, and environmental factors (Freshour et al., 1996;

Derbyshire et al., 2007; Pelletier et al., 2010; Roppolo et al., 2011). Cell wall polysaccharides are categorized into three distinct groups: cellulose, hemicelluloses,

FigureFigure 2.1 Model of the plant cell wall (Cosgrove et al., Nature Reviews 1. Model of the plant cell wall (Cosgrove et. al., Nature Reviews 2005) 2005) 4 and pectins. These polysaccharides are arranged in a complex matrix bound together by hydrogen bonding, covalent bonding, and ionic crosslinking (Fig. 1)

(Cosgrove, 2005). The 13 monosaccharides that make up the cell wall polysaccharides are grouped into several categories: Hexoses (D-glucose, D-

Galactose, D-mannose), deoxyhexoses (L-rhamnose, L-fucose), pentoses (L- arabinose, D-xylose, D-apiose), and acidic sugars (D-galacturonic acid, D-glucuronic acid, L-aceric acid, 3-deoxy-D-mannooctulosonic acid, 3-deoxy-D-lyxo-2- heptulosaric acid).

Cellulose is synthesized in complexes located on the plasma membrane (Fig.

1) (Paredez et al., 2006). It is composed entirely of unbranched β-1,4-glucose chains which hydrogen bond with other chains to form microfibrils (Cosgrove, 2005).

Microfibrils also hydrogen bond with other microfibrils to form a very rigid crystalline cellulose that makes up the bulk of the cell wall’s mass and are the main load-bearing polysaccharides in plant cell walls (Somerville, 2006).

The major hemicelluloses of dicot and monocot cell walls are xyloglucan and xylan, respectively, and are synthesized in the golgi apparatus (Fig. 1). Like cellulose, xyloglucan also has a β-1,4-glucose backbone. Unlike cellulose, a variety of sidechains rich in xylose, galactose, fucose, and arabinose can occur on the C6 carbon of glucose. Additionally, the sidechain galactoses can be acetylated (Scheller

& Ulvskov, 2010). Arabinoxylan, the main hemicellulose in poaceae cell walls, is composed of a β-1,4-xylan backbone that can be arabinosylated and acetylated.

Arabinose residues can also be crosslinked together with ferulic acid, the predominant hydroxycinnamate in poaceae cell walls (Vogel, 2008). 5

Pectins are divided into three main categories: homogalacturonan (HG), rhamnogalacturonan I (RG-I), and rhamnogalacturonan II (RG-II). All are synthesized in the golgi apparatus (Fig. 1). HG is an unbranched polymer of α-1,4- galacturonic acid (GalA) residues. HG can be acetylated, as well as methylesterified on the C6 carbon of GalA (Caffall & Mohnen, 2009). Removal of the methyl groups results in negatively charged pectate, which can then bind apoplastic Ca2+ ions to crosslink HG chains (Ridley et al., 2001). RG-I is composed of alternating GalA and rhamnose residues, with sidechains present on rhamnose. Sidechains in RG-I are highly variable, but are usually rich in galactose, fucose, arabinose, and rhamnose.

The RG-I backbone can also be acetylated, but not methylated (Caffall & Mohnen,

2009). RG-II is the most complex pectic polysaccharide. It has an α-1,4-GalA backbone that possesses both acetyl esters and complex sidechains. The sidechains in RG-II are elaborate, and contain apiose, which can bind boron to crosslink with other sidechains (Ridley et al., 2001).

Lignin is a hydrophobic polymer of aromatic compounds that reinforce wall polysaccharides in specialized tissues such as the vasculature. Lignin is produced by the polymerization of monolignols (cinnamyl alcohols), which are synthesized via phenylalanine (Cosgrove, 2005). While monolignols make up the bulk of lignin content, lignin has also been shown to incorporate other aromatic compounds. For instance, wall-bound hydroxycinnamic acids such as ferulic and coumaric acids can be added to the growing lignin polymer if pathway perturbations prevent adequate biosynthesis of monolignols (Sibout et al., 2005). Lignin binds to the cell wall through ether and carbon-carbon bonds (Vanholme et al., 2010). 6

There are numerous proteins present in the cell wall compartment as well.

Some have been well characterized, including expansins and extensins. Expansin proteins loosen the wall under acidic pH by disrupting hydrogen bonds between polysaccharides (Cosgrove, 2005; Yennawar et al., 2006; Thompson, 2008). This wall loosening allows the cell to expand and grow during development. Extensins are hydroxyproline-rich glycoproteins that also play a structural role in the cell wall.

Extensins are basic proteins which can interact with acidic pectin polysaccharides and crosslink them to prevent cell expansion (Lamport et al., 2011).

Composition of the cell wall varies between species, age of the tissue, and environmental conditions. Generally, however, poaceae primary cell walls are 20-

30% cellulose, 20-40% xylans, 5% pectins, and 1-5% phenolics. Primary cell walls of dicots are 15-30% cellulose, 20-25% xyloglucan, 20-35% pectins, 5% xylan, and trace amounts of phenolics. Some cell types possess a secondary cell wall, which is deposited beneath the primary wall. In poaceae, the secondary cell wall is 35-45% cellulose, 40-50% xylans, 0.1% pectin, and 20% lignin. The secondary cell wall of dicots in 45-50% cellulose, 20-30% xylans, trace amounts of xyloglucan, and 7-10% lignin (Vogel, 2008).

Plant response to pathogen-associated molecular patterns

The cell wall plays an important role as a structural component of the plant cell. It also plays an important role in detecting extracellular abnormalities, such as the presence of a pathogen, known as pathogen-associated molecular patterns

(PAMPs). After sensing a PAMP, a pattern-recognition receptor (PRR) transmits a 7 signal inward to the cytoplasm through signaling players such as phosphorylation cascades, ion fluxes, and transcription factor upregulation to ultimately induce a compensatory response. Perhaps the best-known example of these is FLAGELLIN-

SENSING 2 (FLS2), a receptor-like kinase with an extracellular leucine-rich repeat

(LRR) domain that can detect bacterial infection by binding bacterial flagellin

(Gómez-Gómez & Boller, 2000). Upon binding flagellin (or the flg22 epitope) FLS2 forms a co-receptor complex with BRI1-ASSOCIATED RECEPTOR KINASE 1 (BAK1), which induces transphosphorylation and begins a phosphorylation cascade through mitogen-activated protein kinases (MPKs) to upregulate expression of defense response genes (Asai et al., 2002; Navarro et al., 2004). Another well-studied example of PRRs sensing pathogen presence is another LRR-RLK, the EF-TU

RECEPTOR (EFR) (Shiu et al., 2004). EFR binds bacterial EF-Tu along with its co- receptor BAK1 (Kunze et al., 2004; Zipfel et al., 2006). A tyrosine on EFR is phosphorylated to activate defense response signaling mediated by BOTRYTIS-

INDUCED KINASE 1 (BIK1) (Macho et al., 2014).

Plant-pathogen interactions

Plants may encounter a variety of different pathogens throughout their lifetime. Different pathogens have different methods of infecting plant cells, but all must contend with the cell wall before successfully colonizing their host. Plants have co-evolved a system to detect and respond to pathogen stimuli that is known as plant innate immunity (Jones & Dangl, 2006). Plant innate immunity is frequently presented in a zig-zag model (fig. 2) in which pathogen-associated molecular 8 patterns (PAMPs) are sensed by the plant through pattern recognition receptors

(FLS2, for example) to activate PAMP-Triggered Immunity (PTI) as a broad, nonspecific defense against pathogens. Pathogens such as fungi, bacteria, and nematodes secrete effector proteins into cells which generally suppress PTI. Plant

Resistance (R) genes recognize effectors or the resulting molecular patterns from effector actions, and initiate Effector-Triggered Immunity (ETI), which is usually a more specific response tailored to the particular pathogen, and often results in

Hypersensitive Response (HR), or programmed cell death (Jones & Dangl, 2006).

Figure 2.2. The “zigFigure 2. the “zig-zag-zag” model of plant innate immunit” model of plant innate immunity (Jones & y (Jones & Dangl, Dangl, Nature Reviews 2006) Nature Reviews 2006)

Pathogens utilize an array of cell wall-degrading enzymes (CWDEs) when attacking plants in order to gain access to the cytoplasm. Plant-pathogenic fungi secrete a wide variety of CWDEs, including cellulases, hemicellulases, pectinases, and proteases (Colimer & Keen, 1986; de Vries et al., 2001; Lara-Márquez et al.,

2011; van den Brink & de Vries, 2011). These CWDEs macerate the tissue enough for fungal haustoria to penetrate the wall and begin manipulating the plant.

However, some cell wall fragments produced by CWDEs are bioactive, and can elicit defense responses as damage-associated molecular patterns (DAMPs), similarly to

PAMP perception.

Cell wall integrity: polysaccharide-sensing PRRs

Plants possess the ability to sense changes in the cell wall. This includes sensing PAMPs/DAMPs as described above, but also includes monitoring the cell wall itself in a process known as cell wall integrity (CWI) control. CWI signaling occurs in both normal growth and development, and when a plant is under stress.

The best example of the CWI system in plants involves the Wall-Associated Kinase

(WAK) family, which can sense the presence of DAMPs. WAKs are receptor-like kinases that possess epidermal growth factor-like repeats on their extracellular portion. WAKs monitor the integrity of pectic polysaccharides by directly binding them; their extracellular domains can bind both pectin and de-esterified pectate, as well as oligogalacturonides (OGs), small fragments of HG as a result of pathogenesis

(Decreux & Messiaen, 2005; Decreux et al., 2006; Kohorn et al., 2009; Brutus et al.,

2010). The signaling controlled by WAKs is partially overlapping, but distinct 10 depending on whether pectin or OGs are bound (Paparella et al., 2014; Gravino et al., 2015; Kohorn, 2016). WAKs regulate cell expansion under unstressed conditions by activating MPK3 and controlling vacuolar invertase activity (Wagner & Kohorn,

2001; Kohorn et al., 2006). Under pathogen stress, WAKs directly bind oligogalacturonides (OGs), breakdown products of pectins, to activate MPK6 and possibly MPK8 and upregulated defense response gene expression (Kohorn et al.,

2014). Overexpression of WAKs showed increased resistance to pathogens and increased production of ROS and callose (Brutus et al., 2010; Gramegna et al., 2016).

Another candidate for DAMP-based CWI is the Catharanthus roseus family of receptor-like kinases (CrRLKS), a 17-member gene family in Arabidopsis (Li et al.,

2016). They are characterized by having extracellular malectin-like domains

(Boisson-Dernier et al., 2011). The malectin domain, originally discovered in mammals, is capable of binding diglucose residues, and possesses a structure similar to that of the active sites of glycosyltransferases (Schallus et al., 2008).

Because of the malectin domain, there are several CrRLKs that have been studied extensively as potential wall-interacting proteins: FERONIA, THESEUS1, and

ANXUR1/2.

FERONIA (FER) is perhaps the most well-studied of the CrRLKs. FER has been shown to be involved in brassinosteroid (BR), ethylene (ET), auxin, and abscisic acid signaling (Guo et al., 2009; Deslauriers & Larsen, 2010; Duan et al.,

2010; Mao et al., 2015; Chen et al., 2016). Additionally, FER is involved in defense response as well as response to mechanical stresses (Kessler et al., 2010; Keinath et al., 2010; Shih et al., 2014). FER is bound in its extracellular moiety by RALF1, Rapid 11

Alkalinization Factor 1, to increase apoplast pH, increase cytoplasmic Ca2+ concentration, and suppress growth (Pearce et al., 2001; Haruta et al., 2008, 2014). fer1 mutants lack a biphasic Ca2+ burst characteristic for mechanical stress, and possess altered cell wall content (Shih et al., 2014; Yeats et al., 2016).

THESEUS1 (THE1) was discovered as a gene that recovered the dwarf phenotype observed in cesa6 mutant plants (Hematy et al., 2007). However, the the1 mutant also did not affect the low cellulose content seen in the cesa6 mutant, indicating that it is involved in sensing defects in the cell wall. The the1 mutant alone also does not show any obvious phenotypes, lending credence to this hypothesis (Hematy et al., 2007). Further investigation of THE1 demonstrated that it is a negative regulator of growth, and trigger oxidative bursts through respiratory burst oxidase homologue D (RBOHD) (Denness et al., 2011). Additionally, it was found that THE1 is also involved in glucosinolate biosynthesis and cell wall crosslinking (Hematy et al., 2007).

ANXUR1 and ANXUR2 are the closest homologues to FER in Arabidopsis

(Boisson-Dernier et al., 2009). They are both expressed in the male gametophyte and are important for fertilization (Miyazaki et al., 2009). anxur1/2 mutants are defective in pollen tube growth, and ANXUR1/2 overexpression results in pectin- rich pollen tube cell walls (Boisson-Dernier et al., 2013). Additionally, ANXUR1/2 control ROS production, similarly to THE1, as a potential tool for wall remodeling

(Boisson-Dernier et al., 2013).

Aside from our limited understanding of the CWI sensors mentioned above, relatively little is known about the CWI system. Many questions remain for CWI, 12 such as what signaling components make up the entire pathway of each CWI sensor, how or whether pathways share signaling components, and how many CWI sensors exist. It is likely that many more CWI sensors are present given that there are over

600 receptor-like kinases in Arabidopsis, the vast majority of which have not been characterized (Shiu et al., 2004). This dissertation attempts to gain understanding of

CWI signaling through transgenic expression of microbe-derived CWDEs.

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CHAPTER 3

DECREASED POLYSACCHARIDE FERULOYLATION COMPROMISES PLANT CELL

WALL INTEGRITY AND INCREASES SUSCEPTIBILITY TO NECROTROPHIC

FUNGAL PATHOGENS

Nathan T. Reem1, Gennady Pogorelko1, Vincenzo Lionetti2, Lauran Chambers1,

Michael A. Held3, Daniela Bellincampi2, Olga A. Zabotina1,*

1Roy J. Carver Department of Biochemistry, Biophysics & Molecular Biology, Iowa State

University, Ames, IA 50011

2Dipartmento di Biologia e Biotechnologie “Charles Darwin,” Sapienza Universita di

Roma, 00185 Rome, Italy.

3Department of Chemistry and Biochemistry, Ohio University, Athens, OH 45701.

(Published in Frontiers in Plant Science, 2016; DOI: 10.3389/fpls.2016.00630)

ABSTRACT

The complexity of cell wall composition and structure determines the strength, flexibility, and function of the primary cell wall in plants. However, the contribution of the various components to cell wall integrity and function remains unclear.

Modifications of cell wall composition can induce plant responses known as Cell

Wall Integrity control. In this study, we used transgenic expression of the fungal feruloyl esterase AnFAE to examine the effect of post-synthetic modification of

Arabidopsis and Brachypodium cell walls. Transgenic Arabidopsis plants expressing 22

AnFAE showed a significant reduction of monomeric ferulic acid, increased amounts of wall-associated extensins, and increased susceptibility to Botrytis cinerea, compared with wild type. Transgenic Brachypodium showed reductions in monomeric and dimeric ferulic acids and increased susceptibility to Bipolaris sorokiniana. Upon infection, transgenic Arabidopsis and Brachypodium plants also showed increased expression of several defense-related genes compared with wild type. These results demonstrate a role, in both monocot and dicot plants, of polysaccharide feruloylation in plant cell wall integrity, which contributes to plant resistance to necrotrophic pathogens.

INTRODUCTION

In the heterogeneous, complex, and highly dynamic plant cell wall, structural polysaccharides form a cross-linked macromolecular network consisting of cellulose, hemicellulose, pectin, glycoproteins, and (in some specialized tissues) lignin (Albersheim et al., 2010). Cell wall constituents function in regulation of plant growth, development, signal transduction, and responses to environmental stresses

(Somerville et al., 2004; Lionetti et al., 2012; Lionetti & Metraux, 2014; Tenhaken,

2015). In addition, plant biomass represents a valuable source of feed, fiber, and fuels, including a potential alternative to petroleum-based fuels. Cell wall lignification and the crosslinking of cell wall polysaccharides (Hatfield et al., 1999) hampers cell wall breakdown to simple sugars that can be used as an energy source by animals or be fermented to bioethanol (Himmel et al., 2007). 23

As plants are sessile, they have evolved a complex defense network to combat stresses, both biotic and abiotic, to survive in their environments. Many signaling pathways involved in plant stress responses and innate immunity have been identified and characterized (Jones & Dangl, 2006). Recent work has identified cell wall-related defense mechanisms, termed Cell Wall Integrity (CWI) control

(Ringli, 2010; Seifert & Blaukopf, 2010; Hamann & Denness, 2011; Pogorelko et al.,

2013a; Bellincampi et al., 2014). As the first line of defense for plants, the cell wall must be rigid enough to maintain cell turgor and prevent pathogen invasion, but accommodate cell expansion, division, and organogenesis. Hence, the cell wall must respond rapidly to environmental changes without compromising its essential functions. Different cell wall components function in controlling cell expansion

(Wolf et al., 2012) and defense responses (Nicaise et al., 2009; Tenhaken, 2015).

Certain phenolic compounds have key effects on cell wall structure, recalcitrance to degradation, and functions in defense (Buanafina et al., 2008;

Pogorelko et al., 2011; Lionetti et al., 2015). For example, hydroxycinnamic acids, such as ferulic, sinapic, and coumaric acids, have been implicated in structural integrity, and some participate in crosslinking of cell wall constituents (Grabber et al., 1998), due to their ability to form homodimers, either photo-induced (Ralph et al., 1994) or peroxidase-assisted (Hartley et al., 1990). In particular, ferulate crosslinking has been broadly investigated, especially in monocot species (Ishii,

1997; Buanafina, 2009). As the predominant hydroxycinnamic component of grass cell walls, ferulate dimers crosslink hemicellulosic polymers via an ester linkage to the arabinose side chain of arabinoxylan or can be ether-linked to lignin (Ralph et 24 al., 1995; Hatfield et al., 1999). In some dicots, by contrast, ferulic acid has been implicated in the crosslinking of pectic arabinans and galactans (Fry, 1982; Caffall &

Mohnen, 2009). It has also been suggested that ferulic acid may crosslink pectins with wall-bound extensins, to negatively regulate cell expansion (Qi et al., 1995).

Ferulate can form homo- and heterodimers in numerous ways, such as 8-O-4,

8-8, and 4-O-5 linkages and ferulates can also bind in 8-5 and 5-5 conformations

(Ralph et al., 2004). These dimers are considered an important structural aspect of the cell wall, but also hinder degradation for industrial purposes, such as biofuel production. Evidence indicates that ferulic acid (FA) affects plant-pathogen interactions, and that phenolic compounds are often induced in response to biotic stresses. FA is thought to play a role in fungal resistance and to be an important insect deterrent (Santiago & Malvar, 2010; Buanafina & Fescemyer, 2012). Apple leaves inoculated with the apple scab fungus Venturia inaequalis showed an increase in overall phenolic content, including FA (Mikulic Petkovšek et al., 2008). A negative correlation between FA concentration and disease severity was observed in maize exposed to Fusarium graminearum (Bily et al., 2003). Moreover, susceptibility to insect pathogens was negatively correlated with hydroxycinnamic acid content in maize (Bergvinson et al., 1994; García-Lara et al., 2004). Thus, these phenolic compounds may have key roles in cell wall structure and disease resistance.

Pathogens have evolved enzymatic mechanisms to target cell wall structure, including phenolic compounds; these enzymes have potential uses for improving digestibility of biomass. For example, some fungal species, such as Aspergillus nidulans, produce ferulic acid esterase (FAE), which hydrolyzes ester linkages 25 between FA and cell wall polysaccharides of the host. Several studies investigated the effects of the ectopic expression of fungal FAE on plant cell wall composition and phenolic function. Vacuolar-targeted expression of a fungal FAE in Lolium multiflorum induced auto-digestion of hemicellulose after cell death (Buanafina et al., 2006). Targeted expression of Aspergillus niger FAE to the vacuole (Buanafina et al., 2008) or to the apoplast, endoplasmic reticulum, and Golgi (Buanafina et al.,

2010) caused a reduction of cell wall feruloylation in Festuca arundinacea with a consequent improvement in cell wall digestibility. Aspergillus FAE, when added to fungal xylanase, improves the release of reducing sugars in oat hulls and in wheat bran (Faulds & Williamson, 1995; Yu et al., 2003). Arabinan-bound ferulic acid has been implicated in regulation of stomatal aperture of Commelina communis, and may confer flexibility in guard cells by preventing homogalacturonan (HGA) from binding calcium (Jones et al., 2003). Treatment with FAE, which hydrolyzes crosslinks between arabinans, allows HGA domains to associate through calcium crosslinked chain packing, thus reducing flexibility of the guard cell walls (Jones et al., 2003).

Arabidopsis plants expressing feruloyl esterase from A. nidulans have been previously generated and demonstrated to have reduced cell wall feruloylation and increased enzymatic saccharification of acid-pretreated plant biomass (Pogorelko et al., 2011). In this study, transgenic Brachypodium plants expressing the same microbial esterase were generated and characterized. Cell wall modifications in

Arabidopsis and Brachypodium transgenic plants caused by expressed feruloyl esterase were characterized. The effect of these cell wall modifications on plant 26 susceptibility to the necrotrophic fungi B. cinerea and B. sorokiniana was investigated and the results provide new insights into the relationship between the cell wall feruloylation, cell wall accessibility to degrading enzymes, and plant resistance to biotic stress. This study thus demonstrated that a reduction in cell wall cross-linking compromises plant resistance to pathogens.

MATERIALS AND METHODS

Plant growth conditions

Arabidopsis seeds were planted in wet LC-1 potting soil mix (Sun Gro Horticulture,

Agawam, MA, USA) and plants were grown in a growth chamber with controlled conditions: 16-h light/ 8-h dark at 21°C, with relative humidity of 65% and light intensity of 160 μmol s-1 m-2.

For the extensin quantification experiments, Arabidopsis seedlings were grown on plates in the same growth chamber as above. Seeds were sterilized with sequential treatments of 70% ethanol and 0.5% bleach, washed multiple times with sterile water and planted on ½-strength Murashige & Skoog medium (Murashige &

Skoog, 1962) with 2% sucrose and 0.3% Gelrite (Research Products International,

Mt. Prospect, IL, USA).

Brachypodium plants were grown in the same conditions as Arabidopsis.

After a vernalization period of 14 days in the dark at 4°C to maximize germination rate, pots were transferred to a growth chamber maintained at 21°C, 65% relative humidity, and 160 μmol s-1 m-2 light intensity.

Transformation of Brachypodium plants with AnFAE

Brachypodium transgenic plants were prepared as described previously (Pogorelko et al., 2013b). The Aspergillus nidulans AnFAE cDNA (AN5267.2) was amplified from

Pichia pastoris recombinant strains (Bauer et al., 2006), which were obtained from the Fungal Genetics Stock Center (http://www.fgsc.net). The cloned AnFAE sequence was amplified by PCR with primers AnFAE-F and AnFAE-R containing restriction sites KpnI and HindIII, respectively. After restriction digest of AnFAE, the fragment was ligated into a cassette containing (5’ to 3’) sequences encoding: a Zea mays β-expansin signal peptide, AnFAE, and a green fluorescent marker (smGFP), fused to the C-terminus of AnFAE. This cassette was then ligated into a pMLBart binary vector backbone, as described in (Fursova et al., 2012). A. tumefaciens- mediated transformation of Brachypodium callus was performed by the Plant

Transformation Facility at Iowa State University

(http://www.agron.iastate.edu/ptf). Diagrams of the transgenic expression cassettes for Arabidopsis and Brachypodium plants are shown in Supplementary

Figure S1.

Preparation of apoplastic fluid

Apoplast fluids were extracted from 6-week-old AnFAE and wild-type plants as described by Pogorelko et al (2011). Briefly, aerial parts of the plants (0.5 g) were cut into 3-6 mm segments and placed vertically into a 10 mL syringe sealed with parafilm. Five mL of pre-cooled buffer (25 mM Tris-HCl, 50 mM EDTA, 150 mM

Mg2Cl2, pH 7.4) was added and the syringe was placed under vacuum. After vacuum 28 infiltration, the buffer was drained and the syringe was placed into a 15 mL centrifuge tube and centrifuged at 1000 g for 10 min. Apoplast fluid was collected from the bottom of the tube, transferred to a new tube, and frozen at -20°C.

Feruloyl esterase activity assay

For activity assays, apoplastic total protein was quantified using Bradford reagent

(Bio-Rad Laboratories, Hercules, CA, USA). Then, equal amounts of protein per sample were incubated with 2 mM methyl ferulate (Sigma-Aldrich, St. Louis, MO,

USA) in sodium phosphate buffer pH 7.4 for 24 hours. The products of reaction were extracted with ethyl acetate, evaporated, dissolved in 100% methanol, and analyzed by reverse-phase HPLC on a Prevail C18 5μ column (4.6 x 50 mm; Grace Davison

Discovery Sciences, Deerfield, IL, USA) with UV detection at 290 and 320 nm.

Product and substrate were separated using a gradient of 0.1% trifluoroacetic acid in water (pH 2.8) and acetonitrile at 1 mL min-1 under following conditions: 0-3 min—95% water; 3-10 min—85% water; 10-20 min—70% water; 20-25 min—5% water; 25-30 min—95% water.

Cell wall extraction

Cell walls were isolated from plants grown on soil as described in Zabotina et al.,

2008. Whole aerial parts of plants were harvested and cut into 1-cm length segments. Tissue was frozen in liquid N2 and ground into a fine powder with a mortar and pestle. After homogenization, tissues were incubated in 80% ethanol at

80°C two times for one hour, and further homogenized with a PolyTron 29

(Kinematica, Inc., Bohemia, NY, USA) at 15,000 rpm for 5 minutes. The pellet was collected by centrifugation at 12,000 g and washed with 80% ethanol followed by several washes with 100% acetone until supernatant turned clear. Tissue was incubated in a solution of 20% SDS with 5 mM sodium metabisulfite at 4°C for 16 hours and washed five times with distilled water. Finally, samples were incubated in

1:1 chloroform:methanol solution at room temperature for 20 minutes, washed three times with 100% acetone, and air-dried at 50°C.

Analysis of cell wall phenolic acids

Phenolic acids and other hydroxycinnamates were extracted from prepared cell walls analyzed as described by Pogorelko et al., 2011. Briefly, each total cell wall sample was weighed, incubated twice for 24 hours in 2 ml 2M NaOH, and supernatants were combined. The supernatant mixture was acidified and phenolics were extracted with ethyl acetate, which was then evaporated with a stream of air.

Phenolics were then dissolved in 100% methanol and analyzed by reverse-phase

HPLC on a Prevail C18 5μ column (4.6 x 250 mm; Grace Davison Discovery Sciences,

Deerfield, IL, USA) with UV detection at 290 and 320 nm. Phenolic acids were separated using a gradient of 0.1% trifluoroacetic acid in water (pH 2.8) and acetonitrile at 1 mL min-1 under following conditions: 0-10 min—95% water; 10-30 min—85% water; 30-40 min—70% water; 40-47 min—5% water; 47-55 min—

95% water. To determine response factors, standard curves were created using mixtures of standard p-coumaric acid and ferulic acid, (all from Sigma-Aldrich, St.

Louis, MO, USA) at different concentrations. 30

Analysis of cell wall sugars

To determine monosaccharide composition, 1 mg of dry, de-starched cell wall was hydrolyzed with 2 N trifluoroacetic acid at 120°C for 2 h. The hydrolysates were dried at 50°C, re-dissolved in water, and analyzed by high-performance anion- exchange chromatography with pulsed-amperometric detection using a CarboPac

PA-20 column (3 x 150 mm; Dionex, Sunnyvale, CA, USA) as described earlier

Zabotina et al., 2008. Monosaccharides were separated using a gradient of 100mM

NaOH in water at 0.5 mL min-1 under following conditions: 0-0.05 min—12mM

NaOH; 0.05-26 min—0.65 mM NaOH; 26-46 min—300 mM NaOH; 46-55 min—

12mM NaOH. Monosaccharide standards included L-Fuc, L-Rha, L-Ara, D-Gal, D-Glc,

D-Xyl, D Man, D-GalA, and D-GlcA (all from Sigma-Aldrich, St. Louis, MO, USA). To determine response factors, standard curves were created using mixtures of all standard monosaccharides at different concentrations.

Reducing sugars were measured using the PAHBAH assay (Lever, 1972) with minor modifications. Briefly, 15 mL of supernatant was mixed with 135 mL of freshly prepared PAHBAH reagent (1 volume of 5% p-hydroxybenzoic acid hydrazide in 5% HCl mixed with 9 volumes of 1.25% trisodium citrate, 0.11% calcium chloride, and 2% sodium hydroxide) and heated at 95°C for exactly 6 min.

Absorbance was measured at 410 nm using a microplate reader (BioTek

Instruments, Inc., Winooski, VT, USA). Calculations were done using a standard curve prepared using different concentrations of Glc.

Cell wall extensin extraction and quantification

Wild-type and transgenic Arabidopsis cell wall samples from 2-week-old whole plants (20-35 mg) were deglycosylated with anhydrous hydrogen fluoride (HF), as described previously (Sanger & Lamport, 1983). HF reactions were quenched, dialyzed (3.5 kDa molecular weight cut-off) against distilled deionized water, and then lyophilized. Lyophilized samples were re-suspended in water and fractionated into water-soluble (HF-soluble) and water-insoluble (HF-insoluble) fractions by centrifugation. HF-insoluble pellets were washed with water (~10-15 mL) to further separate HF-soluble components. Wash supernatants were pooled with HF- soluble fractions. Both HF-soluble and HF-insoluble fractions were lyophilized and weight recoveries were recorded on a microbalance. Untreated cell wall, HF-soluble, and HF-insoluble fractions were assayed for hydroxyproline after acid hydrolysis

(constant boiling 6N HCl, 110°C, 24 h), as described earlier (Kivirikko & Liesmaa,

2009). Sample quantities permitting, analyses were performed in triplicate and error bars represent standard deviation.

Enzymatic digestions of cell wall

Digestion of hemicelluloses was done using 10 mg of dry cell wall material incubated with a mixture of 50 units of endo-1,4-β-xylanase M6 (rumen microorganism; Megazyme International, Wicklow, Ireland) and 5 units of endo-1,4-

β-xylanase M1 (Trichoderma viride; Megazyme) in a 0.3-mL total volume of sodium phosphate buffer (pH 6.0) for 24 h at 37°C. For the digestion of pectins, 10 mg of dry cell wall material was incubated with a mixture of 50 units of endo- 32 polygalacturonase (Megazyme International, Wicklow, Ireland) and 15 units of PME

(PROZOMIX LTD, Haltwhistle, United Kingdom) in a 0.3-mL total volume of sodium phosphate buffer (pH 6.0) for 24 h at 37°C.

Saccharification assays were performed as described in Pogorelko et al.,

2011 with some modifications. Stems of 6-week-old plants were cut into pieces approximately 0.3 cm long (5 mg of fresh tissue) and incubated in 0.1 ml of citrate buffer (pH 4.9) containing 4 units of cellulase (from Trichoderma reesei, Sigma-

Aldrich, C62730) and 1 unit of cellobiase (from A. niger, Sigma-Aldrich, C6105) on the shaker at 37°C. At each time point, the reaction was terminated by heating at

100°C for 15 min, supernatants were collected by centrifugation at 10,000 g, and the amount of reducing sugars released was analyzed by p-hydroxybenzoic acid hydrazide (PAHBAH) assay.

Inoculation of Arabidopsis with B. cinerea conidia

B. cinerea strain SF1 (Lionetti et al., 2007) was grown for 15 days on potato dextrose agar (PDA) at 39 g liter–1 at 23°C with a 12-h photoperiod before spore collection.

The spores were harvested by washing the culture surface of the agar and suspended in 5 mL of sterile distilled water. Spore suspensions were filtered through glass wool to remove residual mycelia and the concentration was determined using a Thoma chamber. Conidia, at a concentration of 5 × 105 conidia mL–1, were germinated in potato dextrose broth (PDB) at 24 g L–1 at room temperature for 3 h. Fully developed leaves were detached from four 6-week-old

Arabidopsis plants (3 leaves/plant), grown in a growth chamber maintained at 22°C 33 and 70% relative humidity, with a 12 h/12 h light-dark photoperiod. The detached leaves were placed in square petri dishes with petioles embedded in 0.8% agar. Six droplets of spore suspension (5 µL each) were placed on the surface of each leaf.

Mock inoculation was performed using PDB. Leaves were incubated at 24°C with a

12-h photoperiod and lesion diameter was measured 48 hours post inoculation.

Lesion sizes were measured using IMAGE-J software (Abràmoff et al., 2004).

Infection of Brachypodium with Bipolaris sorokiniana

Macroconidia of B. sorokiniana strain DSMZ 62608 (kindly provided by Prof. F.

Favaron, University of Padua) were produced by culturing the fungus on PDA before spore collection. The conidia were collected by washing the culture surface with 3 mL of sterile water, and conidia concentrations were estimated using a Thoma chamber. The infection of Brachypodium leaves was performed as described previously (Pogorelko et al., 2013b). Briefly, fully expanded leaves were detached from 60-d-old Brachypodium plants grown under a 16 h/8 h light/dark cycle in a climate-controlled chamber at 22°C with a relative humidity of 70%. The leaves were cut to 5-cm lengths and placed in square petri dishes containing 0.8% agar.

Four droplets (10 μL) of conidia suspension (1 × 106 conidia mL−1), with 0.05%

Tween 20, were deposited onto each leaf at a distance of about 2 cm from each other. Mock inoculation was performed using sterile distilled water with 0.05% +

Tween 20. The plates were incubated at 22°C under a 16-h/8-h light/dark cycle. 34

Disease symptoms were recorded at 48 h and lesion sizes were measured using

ImageJ (Abràmoff et al., 2004).

RNA extraction, cDNA synthesis, and Real-Time qPCR

Total RNA was extracted from the uninfected, infected, and mock-inoculated leaves of 6-week-old plants using the SV Total RNA Isolation kit (Promega Corp, Madison,

WI, USA), and cDNA synthesis was performed with the SuperScript III First Strand

Synthesis system (Invitrogen Corp, Carlsbad, CA, USA) following the manufacturer’s recommendations. The Maxima SYBR Green qPCR Master Mix (2X; Thermo

Scientific, Waltham, MA, USA) with appropriate primers (Supplementary Table S1) and the CFX-96 Thermal cycler (Bio-Rad) were used to determine relative expression of the genes. Relative expression levels were calculated in comparison with an appropriate control gene (for primer sequences, see Supplementary Table

S1) from wild-type plants, and the ACTIN2 gene (At3g18780; for Arabidopsis) whose expression level was not affected, was used as reference gene. Relative expression for Brachypodium samples was calculated by comparison with GAPDH. Gene expression levels in transgenic plants are presented relative to the expression of the same gene detected in wild-type plants (for which gene expression was set to 1).

The comparative threshold cycle method (Schmittgen & Livak, 2008) was used for determining differences between transcript copy numbers in wild-type and transgenic plants. For calculation of relative expression levels for B. cinerea genes, a fungal house-keeping gene ACTIN (for primer sequences, see Supplementary Table

S1) was used as a reference gene. 35

Chlorophyll Extraction and Quantification

Chlorophyll extraction was performed as described in Lolle et al., (1997). Whole rosette leaves were isolated from 4-week-old Arabidopsis plants, then carefully weighed and placed in a 24-well plate. Leaves were immersed in dimethyl sulfoxide at room temperature, covered in foil, and placed on a shaker for incubation. Aliquots of supernatant were taken from solution every 10 minutes for 80 minutes.

Absorption spectra at 664 and 647 nm were then measured. Chlorophyll was quantified as micromoles per mg tissue using the equation: chlorophyll

(micromoles) = 7.93(A664) + 19.53(A647).

Peroxide staining of Arabidopsis Leaves

Arabidopsis leaves were assayed for hydrogen peroxide accumulation according to the protocol outlined by Daudi and O’Brien (2012). An aqueous solution of 1 mg/mL

3,3’-diaminobenzidine (DAB)(Acros Organics, New Jersey, USA) was prepared and adjusted to pH 3.0 with HCl. Tween-20 and Na2HPO4 were added to the solution to final concentrations of 0.05% and 10 mM, respectively. Rosette leaves from different plants were harvested and placed in a 24-well plate, then immersed in DAB solution.

Samples were then vacuum infiltrated twice to ensure DAB solution penetrated the tissues. The 24-well plate was covered and placed on a shaker for 24 hours.

At the 24 hour time-point, leaf samples were placed in a bleaching solution of

3:1:1 ethanol: acetic acid: glycerol and heated to 95°C for 15 minutes. After boiling, 36 fresh bleaching solution replaced the boiled solution and leaves were stored at 4°C until ready for imaging.

RESULTS

Generation and characterization of transgenic Brachypodium plants expressing A. nidulans feruloyl esterase

To introduce A. nidulans feruloyl esterase (AnFAE), which we previously used to reduce the amount of ferulic acids in Arabidopsis plants (Pogorelko et al., 2011), to

Brachypodium plants, a construct harboring AnFAE was prepared using the binary vector described by Fursova et al. (2012). Two selected independent transgenic

Brachypodium lines were tested for production of AnFAE in the extracellular matrix by assaying enzymatic activity in their apoplastic fluids, with methyl ferulate as a substrate. All apoplastic fluids extracted from transgenic plants showed significantly higher feruloyl esterase activity in comparison with wild-type plants (Fig. 1A).

To demonstrate that AnFAE expressed in Brachypodium apoplast reduces the amount of ferulic acids (FA), we quantified the total contents of FA, di-FA, and p- coumaric acid in cell walls extracted from aerial parts of transgenic and wild-type plants. Amount of both hydroxycinnamic acids present in cell wall extracted from transgenic plants varied among different plants; however, both lines had significantly less FA in comparison with wild-type plants (Fig. 1B). In addition, cell walls from transgenic plants had lower amount of two types of di-FA (5-5 and 8-O-4 di-FA), whereas the content of two other di-FAs detected in Brachypodium cell wall

(8-5 and 8-5 benzofuran di-FA) did not significantly change (Fig. 1C). The total 37 content of mono- and di-FA was also significantly lower in transgenic plants in comparison with wild-type plants (Fig. 1D).

0.16 A 20 * C 18 0.14

16 0.12 14 0.1 12 * WT Bd21 0.08 10 * * AnFAE 8 8 * 0.06 * AnFAE 11 6 g Internal Standard/mg CW 0.04 4 μ g/ μ 0.02 2 Ac#vity (fold diﬀerence rela#ve to WT) 0 0 WT Bd21 AnFAE 8 AnFAE 11 5-5 DiFA 8-o-4 DiFA 8-5 DiFA (BF) 8-5 DiFA 5

4.5 B 4 D 4 3.5 3.5 8-5 DiFA 3 3 8-5 DiFA (BF) 2.5 WT Bd21 2.5 8-o-4 DiFA 2 * AnFAE 8 2 5-5 DiFA 1.5 * AnFAE 11 Ferulic g Internal Standard/mg CW 1.5 μ g Internal Standard/mg CW 1 g/ Coumaric μ

μ 1 g/ μ 0.5 0.5

0 0 Coumaric Ferulic WT Bd21 AnFAE 8 AnFAE 11 Fig 1. Analysis of AnFAE ac1vity and quan1fica1on of hydroxycinnamates in Brachypodium plants. A, Enzyme ac1vity assay from Brachypodium apoplast. Quan1fica1on was done by measuring quan1ty and calcula1ng the ra1o of product (ferulic acid) to substrate (methyl ferulate). This ra1o was then normalized to the average wild-type (WT) ra1o to calculate fold difference. B and C, Quan1fica1on of hydroxycinnamate monomers and dimers in the Brachypodium cell wall. Compounds were iden1fied under UV, then quan1fied based on peak area and normalized using an internal standard (Fig 3.1. Analysis of AnFAE activity and quantification of hydroxycinnamates in cinnamic acid). Micrograms of each sample were determined using standard curves of known compounds. D, Quan1fica1on of total hydroxycinnamates in Brachypodium cell wall. All peaks from quan1ta1ve analyses were added to determine overall reduc1on in total cell wall Brachypodium plants. A, Enzyme activity assay from Brachypodium apoplast. phenolics. Asterisks indicate data sets significantly differently between AnFAE and wild-type plants, according to a Student’s Quantification was done by measuring quantity and calculating the ratio of t-test (p<0.05). product (ferulic acid) to substrate (methyl ferulate). This ratio was then normalized to the average wild-type (WT) ratio to calculate fold difference. B and C, Quantification of hydroxycinnamate monomers and dimers in the Brachypodium cell wall. Compounds were identified under UV, then quantified based on peak area and normalized using an internal standard (cinnamic acid). Micrograms of each sample were determined using standard curves of known compounds. D, Quantification of total hydroxycinnamates in Brachypodium cell wall. All peaks from quantitative analyses were added to determine overall reduction in total cell wall phenolics. Asterisks indicate data sets significantly differently between AnFAE and wild-type plants, according to a Student’s t-test (p<0.05).

To investigate the effect of cell wall de-feruloylation on the polysaccharide composition, monosaccharide analyses of cell walls extracted from transgenic and wild-type plants were performed. For these analyses, Brachypodium transgenic lines AnFAE 8 and AnFAE 11, which showed strong reduction of FA in their cell walls, were also analyzed separately. A significant increase of xylose and reduction of glucose was observed in both transgenic lines in comparison with wild-type cell walls (Table 1A), indicating an increase in xylan content and a decrease in 1,3;1,4- mixed glucans in cell walls of Brachypodium transgenic plants, most likely in response to a reduction of polysaccharide cross-linking.

In addition, monosaccharide analysis was performed for cell walls extracted from one previously characterized line of transgenic Arabidopsis plants expressing the same fungal enzyme (AnFAE). Arabidopsis transgenic plants showed a reduction in mono-FA content (~50%), but no di-FA was detected in their cell walls

(Pogorelko et al., 2011). In contrast to Brachypodium, Arabidopsis transgenic plants did not display any alteration in monosaccharide composition (Table 1B).

Table 3.1. Monosaccharide composition (mol %) of cell walls from wild-type (WT) and AnFAE-expressing Brachypodium and Arabidopsis plants. A, Cell wall composition of Brachypodium non-cellulosic polysaccharides from WT and AnFAE plants. B, Cell wall composition of Arabidopsis non-cellulosic polysaccharides from WT and AnFAE plants. Numbers in bold represent statistical signiFicance (Student’s t-test, p<0.05, n=3-6)

A Fuc Rha Ara Gal Glc Xyl GalA GlcA WT Bd21 0.9±0.3 0.6±0.4 12.7±2.8 3.4±1.1 31.2±9.5 49.6±6.5 0.8±0.7 0.7±0.7

AnFAE 8 0.7±0.3 0.5±0.6 14.8±0.7 3.8±0.1 13.4±1.1 64.3±1.6 1.9±0.6 0.7±0.8

AnFAE 11 0.6±0.3 0.7±0.6 14.5±1.1 3.5±0.4 13.1±2.4 65.6±2.9 1.2±0.5 0.7±0.6

B Fuc Rha Ara Gal Glc Xyl Man GalA GlcA WT Col-0 1.2±0.3 4.6±0.4 5.3±1.7 8.8±2.5 9.0±0.1 55.2±3.2 6.9±0.9 7.6±1.7 1.5±0.8

AnFAE 1.5±0.5 5.3±2.1 4.5±1.2 8.7±2.2 8.7±0.4 56.0±5.6 6.5±0.3 7.1±1.4 1.6±0.6

AnFAE in the apoplast affects Arabidopsis and Brachypodium cell wall digestibility

To determine whether reduction of cell wall feruloylation alters cell wall digestibility, we measured the amount of reducing sugars released during treatment of cell walls extracted from Arabidopsis and Brachypodium transgenic and wild- type plants with either xylanase, pectin methyesterase plus polyglacturonase

(PME+PG) or a cellulase cocktail. Treatment of cell walls from Arabidopsis transgenic plants with xylanase and cellulases released significantly more reducing sugars in comparison with wild-type cell wall, whereas amount of sugars released by PME+PG treatment was not different (Fig. 2A). Cell walls extracted from

Brachypodium transgenic plants released higher amount of reducing sugars only after treatment with cellulases, but not after xylanase or PME+PG treatment (Fig.

2B). 40

* 10 300 400 * A 9 350 8 250 7 300 200 6 250 5 150 200 4 150 3 100 100

g reducing sugars/mg CW 2 g reducing sugars/mg CW g reducing sugars/mg CW

μ 50 μ 1 μ 50 0 0 0 WT Col-0 AnFAE WT Col-0 AnFAE WT Col-0 AnFAE

B 180 16 600 * 160 14 500 140 12 120 400 10 100 8 300 80 6 60 200 40 4 g Reducing sugars/mg CW g Reducing sugars/mg CW g Reducing sugars/mg CW 100 μ μ 20 2 μ 0 0 0 WT Bd21 AnFAE WT Bd21 AnFAE WT Bd21 AnFAE Xylanase Pec@nase Cellulase Fig 2. Amount of reducing sugars released aIer incuba@on of cell wall material from 8-week old plants with wall- degrading enzymes. A, Arabidopsis cell wall treated with Fig 3.2. Amount of reducing sugars released after incubation of cell wall material xylanase, pec@nase, and cellulase. B, Brachypodium cell wall treated with from 8-week old plants with wallxylanase, pec@nase, and cellulase. Asterisks indicate signiﬁcant diﬀerences according to Student’s t-test -degrading enzymes. A, Arabidopsis cell wall (p<0.05, n= 3-6). treated with xylanase, pectinase, and cellulase. B, Brachypodium cell wall treated with xylanase, pectinase, and cellulase. Asterisks indicate significant differences according to Student’s t-test (p<0.05, n= 3-6).

AnFAE-expressing plants have higher susceptibility to necrotrophic fungal pathogens

Since modification of cell wall composition, and specifically reduction of FA, may affect plant-pathogen interactions (Venkata et al., 2013), we next used pathogen infection to challenge the transgenic Arabidopsis generated previously (Pogorelko et al., 2011) and the Brachypodium plants generated in this study. We measured the susceptibility of Arabidopsis plants expressing AnFAE and wild-type Col-0 plants by 41 inoculating leaves with B. cinerea conidia and evaluating symptoms 48 h post inoculation (hpi). Similarly, leaves of two Brachypodium transgenic lines and wild- type plants were infected with B. sorokiniana and symptoms were evaluated at 48 hpi. Both Arabidopsis and Brachypodium transgenic plants showed a significant increase in the areas of lesions produced by the pathogens in transgenic plants compared with wild-type plants (Fig. 3A, B, D, E).

In Arabidopsis, higher accumulation of B. cinerea Actin transcripts was detected in infected transgenic leaves in comparison with infected wild-type leaves.

In Brachypodium, a slightly higher, though not statistically significant, amount of B. sorokiniana GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE-LIKE (GADPH) was detected in infected transgenic leaves in comparison with infected wild-type leaves

(Fig. 3C, F).

B. cinerea expresses a multitude of wall-degrading enzymes during pathogenesis and we also measured transcript levels of BcPG1, BcPG2, and BcPME3 during infection to investigate possible relationships between plant susceptibility, cell wall structural integrity, and fungal virulence. While the expression of PG genes did not change in transgenic plants, up-regulation of BcPME3 was observed in infected Arabidopsis transgenic leaves (Fig. 3G). These results indicate that the expression of AnFAE in Arabidopsis and Brachypodium can increase susceptibility to fungal necrotrophs. 42

A D WT AnFAE AnFAE Bd21 8 11 AnFAE WT Col-0

B E *

) 20

) 10 2

* 2 * 15 8 6 10 4 5 2 Lesion area (mm 0 Lesion area (mm 0 WT Col-0 AnFAE WT Bd21 AnFAE 8 AnFAE 11 * C 1.8 F 8 1.6 7 1.4 6 1.2 5 1 4 0.8 3 0.6 0.4 2 1 Rela9ve Expression Level Rela9ve Expression Level 0.2 0 0 WT Col-0 AnFAE WT Bd21 AnFAE 8 AnFAE 11 Fig 3.3. Analysis of Arabidopsis and G * 5 Brachypodium transgenic plants susceptibility to fungal necrotrophs. A 4 WT Col-0 and D, B. cinerea and B. sorokiniana symptoms on Arabidopsis and 3 AnFAE Brachypodium transgenic AnFAE and 2 wild-type leaves. B and E, Measurements of lesion areas on 1 Arabidopsis and Brachypodium Rela9ve Expression Level 0 BcPG1 BcPG2 BcPME3 leaves 48 hours post inoculation (HPI). C and F, Relative expression levels of B. cinerea-Actin in Arabidopsis and of B. sorokiniana GAPDH in Brachypodium AnFAE and wild-type leaves 48 HPI. G, Expression of B. cinerea virulence-related genes in Arabidopsis AnFAE and Col-0 plants. Asterisks indicate statistical signiNicance according to Student’s t-test (p<0.05, n=3). Scale bars = 1 cm.

De-feruloylation of cell walls alters the expression of pathogen-responsive genes during pathogenesis

Increased susceptibility to pathogens can be caused by the release and accumulation of ferulate in the apoplastic fluid of transgenic plants or by compromised cell wall integrity, which may induce plant-specific responses. Measurement of FA contents in apoplastic fluids of transgenic Arabidopsis plants did not reveal the presence of detectable free FA (Supp. Fig. S2).

To investigate whether the expression of fungal AnFAE and the consequent decrease of FA content in the cell wall affect the pathways involved in plant response to infection, we used RT-qPCR to measure the transcript levels of several known defense genes in infected and un-infected Arabidopsis and Brachypodium transgenic and wild-type plants. In healthy, un-infected transgenic plants, expression of these genes did not differ from their expression in wild-type plants

(Fig. 4A, B). However, several defense-related genes were significantly up-regulated in transgenic plants in comparison with wild-type plants upon infection (Fig. 4C, D).

Thus, in Arabidopsis transgenic plants, expression of PGIP1, bG2, and WRKY40 was significantly higher than in wild-type plants, whereas the level of PR1 transcript was significantly lower (Fig. 4C). Some increase of CYP81F2 was also observed in infected Arabidopsis plants but the difference was not statistically significant. In

Brachypodium, expression of WRKY40, WR3, and RetOX was higher in comparison with infected wild-type plants (Fig. 4D). A full list of genes assayed, including those 44 not significantly different from wild-type and not amplified in Brachypodium, is included in Supp. Fig. S3.

3 B A 5 2.5 4 WT Bd21 2 WT Col-0 3 AnFAE 8 1.5 AnFAE AnFAE 11 2 1

Rela%ve Expression Level 0.5 1 Rela%ve Expression Level

0 0 PR1 CYP bG2 PGIP WR3 RetO WRKY WRKY C 8 * D * 8 * 7 7 6 * * 6 WT Bd21 5 WT Col-0 5 * AnFAE 8 4 * AnFAE 4 3 3 AnFAE 11 2 2 Rela%ve Expression Level

* Rela%ve Expression Level 1 1

0 0 CYP PR1 bG2 PGIP WR3 RetO WRKY WRKY Fig 3.4. Real-time qPCR analysis of selected pathogen-inducible defense genes in mock-infected (A-Arabidopsis, B- Brachypodium) and 48 HPI (C-Arabidopsis, D-Brachypodium) plants. Gene expression levels in transgenic plants normalized to the expression of the same gene detected in wild-type plants (for which gene expression was set to 1), ACTIN2 was used as reference gene for Arabidopsis and GAPDH for Brachypodium expression analysis. The comparative threshold cycle method was used for determining differences between transcript copy numbers in wild-type and transgenic plants. Data represent average obtained for three independent transgenic lines. Asterisks indicate signiOicant differences between transgenic plants and wild-type plants (Student’s t-test, P < 0.05; n = 3).

Reduction of cell wall ferulic acid content affects extensin extractability in transgenic Arabidopsis plants

Previous work indicated that in dicots, FA may be involved in cross-linking pectins with extensins (Qi et al., 1995). Extensins are also induced during defense responses of Arabidopsis plants (Lamport et al., 2011). To investigate whether Arabidopsis plants expressing AnFAE have altered amounts of extensin in their cell walls, HF was used to deglycosylate cell walls. The HF-soluble fraction represents the pool of wall- associated extensins, while the HF-insoluble fraction represents the pool of 45 crosslinked extensins (Mort & Lamport, 1977). The amount of hydroxyproline was quantified as an indicator of extensin contents. We found that the total extensin content was unchanged in transgenic and wild-type cell walls (Fig. 5A). The amount of crosslinked extensin was slightly elevated in walls from AnFAE transgenic plants

(Fig 5B). However, the proportion of HF-soluble protein per mg cell wall was significantly reduced in cell walls from AnFAE transgenic plants (Fig. 5C). In the HF- soluble fraction, AnFAE cell wall samples contained lower amounts of hydroxyproline (Fig. 5D). This indicates that reduction of cell wall feruloylation affects extensin self-cross-linking.

A B C D 2.0 4.0 6.0 0.12

) * 3.5 Insol 5.0 0.1

1.5 3.0 g/mg HF- 4.0 g/mg CW) 0.08 μ 2.5 μ

1.0 2.0 3.0 0.06 per CW ( Content (μg/mg CW) 1.5 Hyp 2.0 0.04 Hyp 0.5 1.0 Total

1.0 HF-soluble 0.02 in HF-Insoluble Frac

DISCUSSION

Increasing evidence demonstrates that changes in cell wall composition can stimulate plant responses similar to stress responses (Hamann, 2012; Pogorelko et al., 2013a). For example, Arabidopsis and tobacco plants expressing an attenuated version of endopolygalacturonase II from A. niger had improved resistance to fungal 46 and bacterial pathogens and increased cell wall digestibility, but exhibited a dwarf phenotype (Capodicasa et al., 2004; Ferrari et al., 2007). Overexpression of a fruit- specific pectin methylesterase (PME) in wild strawberry induced defense-related gene expression and increased plant resistance to B. cinerea (Osorio et al., 2011).

Arabidopsis and Brachypodium plants expressing either acetylxylan esterase or rhamnogalacturonan acetylesterase from A. nidulans exhibited higher resistance to fungal necrotrophs and had increased transcript levels for some defense-related genes (Pogorelko et al., 2013b). Expression of a thermostable xylanase in rice induced upregulation of plant defense-related genes such as SOD, CAT, and the xylanase inhibitor RIXI (Weng et al., 2013). Cell wall structures and composition can also serve as a mechanical barrier to microbial penetration and thus influence plant resistance. Increased pectin methylesterification caused by overexpression of PME inhibitors (PMEI) decreased susceptibility to fungal and bacterial pathogens and viruses (Lionetti et al., 2007, 2012, 2014). Arabidopsis and wheat plants overexpressing PMEI had increased biomass and improved tissue saccharification

(Lionetti et al., 2010; Volpi et al., 2011).

By contrast, modifications that compromise cell wall mechanical properties can potentially have the opposite effect, reducing plant resistance to pathogens and other stresses. For example, reduction in lignin content in soybean Rpp2 plants was correlated with their loss of resistance to the soybean rust fungus Phakopsora pachyrhizi (Pandey et al., 2011). Therefore, such cell wall modifications require detailed characterization of plant fitness to be effective in applied crop biotechnology. 47

Earlier, we reported that Arabidopsis plants expressing the A. nidulans feruloyl esterase AnFAE exhibited significant reduction of cell wall feruloylation and increased biomass saccharification by fungal cellulases after acid pretreatment

(Pogorelko et al., 2011). In this study, we additionally generated the Brachypodium transgenic plants expressing the same AnFAE protein and confirmed reduction of monomeric and dimeric FA in their cell walls, which increased Brachypodium cell wall degradability by fungal cellulases. Using the Arabidopsis transgenic plants created earlier and the Brachypodium transgenic plants created in this study, we investigated the effect of cell wall deferuloylation on plant susceptibility to fungal necrotrophic pathogens and obtained new insights into the potential role of FA in plant cell wall integrity.

The increased degradability of cell walls observed in the plants expressing

AnFAE indicates that reduction of FA affects the accessibility of polysaccharides in both type I (dicots) and type II (grasses) cell walls. While the effect of monomeric and dimeric FA reduction on Brachypodium cell wall digestibility demonstrated in this study was not surprising and conforms to similar observations in other grasses

(Buanafina et al., 2010; Harholt et al., 2010), to the best of our knowledge, there are no reports about the effect of FA on the digestibility of the cell wall in dicots. Our results indicate that most likely, in the Arabidopsis cell wall, FA is esterified to fatty acids in the cutin (Rautengarten et al., 2012; Fich et al., 2016) as well as to the polysaccharides in the cell wall. It is possible that monomeric FA forms cross-links between those molecules creating a connection between the cell wall and cutin, affecting the accessibility of cell wall degrading enzymes or the integrity of the cutin. 48

However, these possible changes in cutin-cell wall connections do not seem to affect cutin permeability/integrity, since our experiments studying chemical leaching of chlorophyll showed no difference between AnFAE and wild-type plants (Supp. Fig.

S4). It cannot be excluded that the reduction of FA occurs exclusively on polysaccharides within the cell wall.

In dicots, FA may cross-link polysaccharides with extensins, as previously proposed (Qi et al., 1995), in response to pathogen attack (Deepak et al., 2010).

While in AnFAE-expressing plants, total extensin content remained unchanged in comparison with wild-type Arabidopsis plants (Fig. 5A), the amount of loosely associated HF-soluble extensin significantly decreased (Fig. 5D) due to the increased proportion of self-cross-linked extensin that became insoluble. This shift from loosely associated extensins, towards self-cross-linked extensins may occur in response to reduction of polysaccharide-extensin interconnections. It is plausible to propose that crossed-linked extensins contribute to recalcitrance of the type I cell wall in dicots somewhat similarly to diFA in monocot type II cell walls. Hence, the reduction of FA content in transgenic Arabidopsis plants expressing AnFAE can induce higher self-cross-linking of extensins as a compensatory response by the plants to fortify their cell walls.

Reduction of cell wall crosslinking and increase of their degradability in

AnFAE plants negatively affects the plant resistance to necrotrophic fungal pathogens. Both the Arabidopsis and Brachypodium transgenic plants showed significantly higher susceptibility to B. cinerea and B. sorokiniana, respectively, consistent with higher digestibility of their cell walls. It is plausible to expect that 49 mechanical strength of the wall with reduced di-FA cross-linking in Brachypodium plants is compromised, which makes it more accessible to the cell wall degrading enzymes secreted by fungus. Most likely, in Arabidopsis transgenic plants, the strength of cell walls is reduced as well, though perhaps due to reduction of polysaccharide-extensin connections. This notion will need further investigation in the future.

Transcript analysis of the known plant defense-related genes PR1, bG2, PR5,

PAD3, WR3, JR1, WRKY40, PGIP1, CYP81F2, and RetOx (Galletti et al., 2008; Raiola et al., 2011), as well as susceptibility genes PME3 (Raiola et al., 2011), PMR4

(Nishimura & Somerville, 2002), PMR5 (Vogel et al., 2004), PMR6 (Vogel et al.,

2002), and MYB46 (Ramírez et al., 2011), demonstrated that none of the investigated genes were constitutively up- or down-regulated in AnFAE plants. Also, peroxide staining did not show an alteration in the accumulation of hydrogen peroxide in the leaves of Arabidopsis transgenic plants with respect to wild-type plants. (Supp. Fig. S5). These results indicate that a perturbation of FA-mediated crosslinking in the cell wall does not induce defense responses in the absence of biotic stress, in contrast to what was observed in the case of post-synthetic cell wall de-acetylation (Pogorelko et al., 2013b) or pectin modification (Ferrari et al., 2008).

However, Arabidopsis plants expressing AnFAE showed higher expression of bG2

(PR2), PGIP1, and WRKY40, and repression of PR1 upon B.cinerea infection in comparison with wild-type plants. By contrast, Brachypodium plants expressing

AnFAE showed higher expression of genes homologous to Arabidopsis WRKY40,

WR3, and RetOx, in comparison with wild-type plants, upon infection with B. 50 sorokiniana. The pattern of affected defense-related genes in AnFAE plants was somewhat different from those that were differentially expressed in the plants with reduced cell acetylation or reduced homogalacturonan contents (Ferrari et al., 2008;

Pogorelko et al., 2013b). This could suggest that different alterations of cell wall structure initiate different cell wall integrity signaling pathways, which activate discrete defense pathways in response to pathogen infection.

The bG2 gene encodes a β-glucanase, which is up-regulated during the

Arabidopsis response to biotic stress (Dong et al., 1991). This gene was also constitutively up-regulated in Arabidopsis plants expressing rhamnogalacturonan acetylesterase in response to reduced acetylation of pectin and xyloglucan.

Moreover, basal β-1,3-glucanase activity was significantly higher in tobacco and

Arabidopsis lines expressing high levels of A. nidulans polygalacturonase (Ferrari et al., 2008). This indicates that despite the presence of specific responses, the activation of β-glucanase is a common response to the loss of cell wall integrity, regardless of the polysaccharide type in the cell wall being perturbed.

The accumulation of the cell wall associated PolyGalacturonase Inhibiting

Proteins (PGIPs) is considered to contribute to resistance against polygalacturonase-producing pathogenic fungi (De Lorenzo et al., 2001). A higher level of PGIP expression was observed in Arabidopsis AnFAE-expressing plants in response to fungal treatment. It is possible that although AnFAE plants try to defend themselves, the integrity of their cell walls is altered to the extent that it cannot be compensated by the activation of these defense genes. 51

The Arabidopsis WOUND RESPONSIVE 3 (WR3) encodes a high-affinity nitrate transporter, which was proposed to be involved in jasmonic acid- independent wound signal transduction (Titarenko et al., 1997) and was shown to be activated by treatment with fungal-derived oligosaccharide elicitor (Rojo et al.,

1999). WR3 was proposed to be involved in hypersensitive-like cell death induction

(Kim et al., 2008). Higher expression of the homologous gene in Brachypodium

AnFAE-expressing plants upon infection might suggest that reduction of FA- mediated cross-linking in their cell walls increases the response of the plant upon wounding associated with the action of necrotrophic microorganisms.

After fungal inoculation, Arabidopsis AnFAE-expressing plants showed lower expression of the salicylic acid (SA)-dependent PR1 gene, which was consistent with upregulation of the transcription factor gene WRKY40, considered to be a repressor of SA signaling (Xu et al., 2006; Zheng et al., 2006). This suggests that the weakening of cell walls due to reduction of FA-mediated crosslinks might affect either the SA metabolic pathway or activation of SA-dependent pathways. We did not observe higher accumulation of FA or any other phenolic acids in the apoplast of AnFAE plants in comparison with wild-type plants; therefore, we can eliminate the possibility that increased free FA in the apoplast contributes to repression of PR1.

The B. cinerea genome contains at least six endopolygalacturonase genes

(BcPGs) (Wubben et al., 1999), of which BcPG1 and BcPG2 are required for virulence

(Kars et al., 2005). At the same time, most pectinolytic enzymes cannot degrade highly methylated pectin. Therefore, the action of pectin methylesterase (PME), which de-methylesterifies pectin to pectate, is required. Although neither BcPME1 52 nor BcPME2 are required for fungal virulence, a possible involvement of BcPME3 was not excluded (Kars et al., 2005). Thus, we measured expression of fungal BcPG1,

BcPG2, and BcPME3 during infection to investigate possible relations between plant susceptibility, cell wall structural integrity and fungal virulence. Since different sets of cell wall degrading enzymes are secreted at different stages of fungal infection

(Laluk & Mengiste, 2010), the higher expression of BcPME3 but not of BcPG1 and

BcPG2 during growth of B. cinerea on AnFAE plants, in comparison with wild-type plants might reflect the faster development of fungal colonies at the stage that requires contribution of BcPME3.

Based on the results of this study, we propose that some improvements of feedstock biomass digestibility can negatively affect plant stress resistance, so a better understanding of this trade-off can help in finding optimal directions in plant biotechnology.

CONCLUSIONS

In this study, we demonstrated that alteration of plant cell wall feruloylation has a negative effect on plant fitness. While improving cell wall digestibility, reduction of ferulic acid content negatively affects plant resistance to biotic stress, most likely due to compromised cell wall integrity. Thus, in Brachypodium, reduction of FA- mediated cross-linking reduces cell wall strength, which leads to lower resistance against microbial penetration. Similarly, the cell wall in Arabidopsis becomes weaker, most likely due to changes in the polysaccharide-extensin network, but further detailed analyses are necessary to confirm this. 53

ACKNOWLEDGMENTS

This research was supported by Roy J. Carver Charitable Trust (#09-3384; 2010-

2013 to Olga Zabotina), NSF-MCB (#1121163; 2011-2016 to Olga Zabotina), and by

Ministero dell’Istruzione, dell’Università e della Ricerca (PRIN Grant #2010T7247Z, http://www.istruzione.it/; to Daniela Bellincampi).

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CHAPTER 4

COMPREHENSIVE TRANCRIPTOME ANALYSES CORRELATED WITH

UNTARGETED METABOLOME REVEAL DIFFERENTIALLY EXPRESSED

PATHWAYS IN RESPONSE TO CELL WALL INTEGRITY ALTERATIONS

Nathan T. Reem1, Han-Yi Chen5,6, Manhoi Hur2, Xuefeng Zhao3,4, Eve S. Wurtele2, Xu

Li5,6, Ling Li2,7, Olga Zabotina1,*

1Department of Biochemistry, Biophysics & Molecular Biology, Iowa State

University; 2Department of Genetics, Developmental & Cell Biology, Iowa State

University; 3Laurence H. Baker Center for Bioinformatics and Biological Statistics,

Iowa State University; 4Present address: Information Technology, College of Liberal

Arts and Sciences, Iowa State University; 5Plants for Human Health Institute, North

Carolina State University; 6Department of Plant and Microbial Biology, North

Carolina State University; 7Department of Biological Sciences, Mississippi State

University.

*- corresponding author

SUMMARY

Plant Cell Wall Integrity (CWI) control is a critical component of plant fitness, both for normal development and for response to pathogens. It has been shown that cell wall modifications in Arabidopsis thaliana have profound effects on defense response and gene expression, but the cell signaling mechanisms underlying these responses are not well understood. Three Arabidopsis transgenic lines, two with 66 reduced cell wall acetylation (AnAXE and AnRAE) and one with reduced feruloylation (AnFAE), were used in this study to investigate the plant responses to cell wall modifications. RNA-seq in combination with untargeted metabolome was employed to assess differential gene expression and metabolite abundance. RNA- seq results were correlated with metabolite abundances to determine the pathways involved in response to cell wall modifications introduced in each line. The resulting pathway enrichments revealed the deacetylation events, AnAXE and AnRAE, had similar responses, including upregulation of aromatic amino acid biosynthesis and changes in regulation of primary metabolic pathways that supply substrates to specialized metabolism including defense responses. In contrast, AnFAE plants were downregulated in lipid biosynthesis pathways and in peroxidases involved in lignin polymerization. These results elucidate the role that primary metabolism plays in response to extracellular stimuli. Correlating transcriptomics and metabolomics datasets increased the power of pathway prediction, and demonstrated the complexity of pathways involved in CWI signaling.

Keywords:

ARABIDOPSIS THALIANA, CELL WALL INTEGRITY CONTROL, METABOLOMICS,

SYSTEMS BIOLOGY, TRANSCRIPTOMICS,

INTRODUCTION

The plant cell wall is a dynamic structure that protects cells against environmental stresses and participates in signal transduction from external stimuli 67 to the cytoplasm. Due to the sessile nature of plants, their survival and reproduction directly depends on effective protection and constant surveillance for danger.

Complex cell wall structures evolved as a critical feature in enabling early plants to colonize the land and, since that time, to support a plant’s upright growth and defense (Popper & Fry, 2003). Many plant-pathogenic microorganisms actively penetrate the plant apoplast in order to access intracellular nutrients. Cell wall structure and composition change during pathogenesis, partially due to microbial cell wall-degrading enzymes (CWDEs) (Laluk & Mengiste, 2010) and partially due to cell wall remodeling that is induced in the plant as a defense reaction and directed towards wall fortification (Hamann, 2012; Underwood, 2012). The hundreds of

CWDEs secreted by pathogenic microbes into the plant apoplast vary depending on the microbe pathogen and the host species; these CWDEs are essential for successful pathogenesis (Kubicek et al., 2014).

In this constant battle with microorganisms, plants have developed a system for sensing pathogen penetration and monitoring cell wall integrity as a first layer of defense (Voxeur & Hofte, 2016). Plant cell walls are able to perform this surveillance-defense function because of their ability to dynamically remodel the cell wall in response to different types of stimuli, including non-self and damaged self.

Despite significant progress in understanding cell wall metabolism, knowledge about mechanisms regulating stimulus-induced changes in wall composition and structure is still limited (Engelsdorf & Hamann, 2014). Known mechanisms include perception and translation of external stimuli into quantitative 68 chemical signals, which induce responsive changes in cellular metabolism leading to specific modifications in wall organization (Engelsdorf & Hamann, 2014). Cell wall integrity (CWI) control is an example of such a mechanism; it monitors wall integrity and maintains the wall by stimulating modifications in cell wall metabolism and structure in response to the wall alterations that have been induced by external stimuli (Hamann & Denness, 2011). While different aspects of plant CWI signaling have been demonstrated, much remains to be understood about its precise mode of action and molecular components (Engelsdorf & Hamann, 2014; Voxeur &

Hofte, 2016). CWI signaling includes three major elements: (1) the perturbation of

CWI that serves as a stimulus; (2) the sensing of the specific features associated with these CWI perturbations; (3) the response via initiation of adaptive cell wall remodeling (Rodicio & Heinisch, 2010). During pathogenesis, plants perceive wall- derived molecules produced due to damage by microbial CWDEs. These damage- associated molecular patterns (DAMPs) together with microbial-associated molecular patterns (MAMPs) are recognized by membrane-bound pattern recognition receptors (PRR). The result is the induction of a variety of defense responses, including intracellular signaling, transcriptional reprogramming, synthesis of defense metabolites and cell wall remodeling (Ferrari et al., 2013;

Boller & He, 2016). For example, the leucine-rich repeat receptor-like kinase (LRR-

RLK) ERECTA and associated heterotrimeric G-protein are involved in cell wall remodeling and probably CWI signaling (Llorente et al., 2005; Sánchez-Rodríguez et al., 2009). In another example, oligogalacturonide DAMPs are sensed by the receptor Wall Associated Kinase 1 (WAK1) (Brutus et al., 2010); WAK1 is critical in 69 monitoring the pectin integrity disturbed during injury (De Lorenzo et al., 2011) and involved in plant immune responses (Ferrari et al., 2013). Several related CrRLKs monitor CWI and regulate growth in Arabidopsis: THESEUS1 (THE1), FERONIA

(FER), and HERCULES1 (HERK1). THE1 senses structural defects in the cell wall and its expression is downregulated in brassinosteroid-insensitive bri1 mutants

(Hematy et al., 2007; Tang et al., 2008). FER expression is also downregulated in bri1 mutants and FER-RNAi lines exhibited reduced cell elongation (Guo et al.,

2009). THE1 and FER also interact with HERK1 as part of a pathway influenced by brassinosteroids (BR) to regulate cell elongation (Guo et al., 2009).

After PRRs sense changes in CWI, multiple signaling pathways transmit the signal to the nucleus to induce compensatory gene expression. The signaling pathways involved in CWI are complex and not well understood, most likely due to their partially overlapping nature and sensitivity to common secondary messengers such as Ca2+, ROS production, and inositol triphosphate (Godfrey & Rathjen, 2012;

Ma et al., 2012). While individual signaling pathways are still being investigated, some downstream responses are better characterized. FLAGELLIN-SENSING 2

(FLS2) binds extracellular bacterial flagellin, then binds its co-receptor BRI1-

ASSOCIATED KINASE1 (BAK1) and initiates phosphorylation and a subsequent mitogen-activated protein kinase (MPK) cascade, which in turn upregulates expression of a variety of genes such as transcription factors, protein kinases, protein phosphatases, and protein-degradation proteins (Asai et al., 2002; Navarro et al., 2004). Wall-associated kinases (WAKs) are a family of well-characterized

PRRs that have significantly more complicated signaling components than FLS2. 70

WAKS directly bind pectic polysaccharides under unstressed conditions, and are thought to regulate cell expansion (Wagner & Kohorn, 2001). In the early stages of fungal pathogenesis, homogalacturonan is hydrolyzed to produce oligogalacturonans (OGA), which function as DAMPs. Upon binding OGA, WAKs

(which have higher affinity to OGA than intact homogalacturonan in vitro) activate

MPK signaling pathways to initiate transcription of defense response genes (Kohorn et al., 2014). WAK1 forms a complex with the apoplast-localized glycine-rich protein, GRP3; then cytoplasm-localized protein phosphatase (KAPP). In complex,

WAK1, GRP3, and KAPP negatively regulate defense response and have been proposed to return plants to baseline response after binding OGA (Gramegna et al.,

2016). It has also been shown that the Pseudomonas syringae effector AvrPto can abolish certain OGA signaling components, yet leave other components unaffected, further complicating the downstream signaling after WAK1 binds OGAs (Gravino et al., 2016).

The first evidence for the existence of CWI control mechanisms in plants was deduced from mutant physiology or pharmacological inhibition of cell wall biosynthetic processes (Hematy et al., 2007; Hamann et al., 2009; Ringli, 2010; Wolf et al., 2012). The recently proposed post-synthetic modification of cell walls by overexpressing hydrolytic enzymes targeted to the plant apoplast is a different way of CWI perturbation which occurs directly in muro and can potentially mimic the action of CWDEs secreted by microorganisms during pathogenesis (Pogorelko et al.,

2013; Bellincampi et al., 2014; Lionetti et al., 2014). Pathogenic microorganisms, in particular necrotrophs, produce and secrete a battery of diverse CWDEs, including 71 glycosidases, lyases, and esterases. The combination of secreted enzymes reflects the compositional complexity of the host cell walls as well as lifestyle of the pathogen (King et al., 2011). Induced post-synthetic modification of the cell wall through overexpression of CWDEs provides plants an opportunity for two extracellular sensing mechanisms: one via direct sensing of DAMPS liberated as a result of changes in the cell wall (Savatin et al., 2014), and another through the expressed microbial enzyme themselves that can be perceived as MAMPs (Wu et al.,

2014). Both DAMPs and MAMPs are sensed by RLKs to induce Pattern-Triggered

Immunity (PTI), the initial plant response when challenged with a pathogen. PTI is a well-studied system in which plants initially engage in broad defense responses, accompanied by more specialized responses depending on the pathogen involved

(Wu et al., 2014). Multiple MAMPs and DAMPs initiate PTI, which is often subsequently minimized by effector proteins secreted by the pathogen in a process called Effector-Triggered Susceptibility (ETS). If present in the plant, R genes such as Nucleotide-Binding Leucine Rich Repeat (NB-LRR) proteins will bind effectors in an attempt to neutralize them and gain Effector-Triggered Immunity (ETI) to the pathogen (Jones & Dangl, 2006). This complicated series of interactions between plants and pathogens involve numerous signaling pathways and it is difficult to determine which signaling pathways are activated by a specific M/DAMP.

Whole-transcriptome sequencing, known commonly as RNA-seq, and microarray technology have become important tools for discovering novel signaling pathways and their components induced in response to environmental stresses

(Guo et al., 2009; de Jonge et al., 2012; Rasmussen et al., 2013). Several studies have 72 successfully used RNA-seq to determine genes involved in CWI control and response to pathogens (Ehlting et al., 2008; De Cremer et al., 2013; Shen et al., 2014; Nafisi et al., 2015; Xu et al., 2017; Tsai et al., 2017). More recently, RNA-seq has been used in combination with global metabolomics or proteomics analyses where a systems biology approach has been applied for correlative analyses to increase the power of predictions (Strauch et al., 2015; Li et al., 2015; Liu et al., 2016).

Investigations of the effects of post-synthetic cell wall modification can facilitate the determination of the pathways responding to a specific M/DAMP, because specific signaling pathways will be activated in plants with targeted post- synthetically modified cell walls, even in the absence of pathogen. Therefore, in this study, we have applied transcript-metabolite correlations to evaluate which pathways are induced in response to cell wall post-synthetic modification. We compared control Arabidopsis and three lines that express three specific CWDEs from Aspergillus nidulans and display altered sensitivities to the Botrytis cinerea pathogen. We selected two acetylesterase lines, A. nidulans-derived

Acetylxylanesterase (AnAXE), and Rhamnogalacturonan Acetylesterase (AnRAE), because of the increased defense responses and reduced susceptibility to B. cinerea of these transgenic Arabidopsis lines (Pogorelko et al., 2013). We selected a third line based on the higher susceptibility of Arabidopsis plants expressing A. nidulans

Ferulic Acid Esterase (AnFAE) to B. cinerea (Reem et al., 2016). Here, RNA-seq analysis was performed in combination with untargeted metabolome profiling of

Arabidopsis plants expressing wall-degrading enzymes (AnAXE, AnRAE, and

AnFAE) and control plants expressing only an Empty Vector (EV). All differentially 73 abundant metabolites were correlated with differentially accumulated transcripts to determine the pathways most highly enriched in AnAXE, AnRAE, and AnFAE lines relative to the control EV plants.

MATERIALS AND METHODS

Plant materials and growth conditions

Arabidopsis seeds were sterilized with 70% ethanol and 0.5% bleach, washed with sterile water, and planted on petri plates containing ½-strength Murashige and

Skoog (Murashige & Skoog, 1962) medium containing 2% sucrose and 0.3% Gelrite

(Research Products International, Mt. Prospect, IL, USA). Plants were grown for 14 days in a growth chamber under the following conditions: 16-h light/ 8-h dark at 21

°C and 65% relative humidity, and light intensity of 160 μmol s-1 m-2. Plates with different transgenic lines and control plants were randomly distributed on the shelf to minimize the potential effects of small differences in light and temperature. At the time of harvest, plants were cut at the base of the hypocotyl and the entire aboveground portion of all plants were immediately placed in a 50 mL conical tube immersed in liquid nitrogen, and stored at -80 °C until analysis.

For RT-qPCR analyses, seeds were planted on autoclaved LC-1 potting soil mix (Sun Gro Horticulture, Agawam, MA, USA) and plants were grown in a growth chamber under 16-h light/8-h dark conditions at 21 °C, 65% relative humidity, and light intensity of 160 μmol s-1 m-2.

Preparation of RNA and RNA-seq

For RNA-seq, one gram of plant tissue was homogenized using RNase-free mortar and pestles, then transferred to tubes containing TRIZOL reagent (Invitrogen

Life Technologies, CA, USA). RNA was extracted according to the manufacturer’s protocol and solubilized in DEPC-treated water, then treated with DNase I for 30 minutes at 37 °C (Invitrogen Corp., Carlsbad, CA, USA). RNA was cleaned up using an

RNEasy Mini Kit (Qiagen, CA, USA). Sixty micrograms of total RNA was provided for sequencing, which was performed by BGI Americas (http://www.BGI.com).

For RT-qPCR, RNA was extracted using the same method as above. One microgram of total RNA was reverse-transcribed to cDNA using SuperScript III First

Strand Synthesis system (Invitrogen Corp., Carlsbad, CA, USA), then digested with

RNase H to purify the cDNA.

RNA-seq analysis: counting & mapping reads, statistical analysis for DE genes

For RNA-seq, total RNA from twenty seedlings was extracted for each biological replicate. Four biological replicates were analyzed for each transgenic line and control. Sequencing was conducted using an Illumina HiSeq 2000 system with

100-cycle paired-ends at BGI Americas (http://www.BGI.com). The cleaned reads were aligned to the reference genome of Arabidopsis thaliana using TopHat

(Trapnell et al., 2009), and the mapped reads were count using htseq-count

(http://www-huber.embl.de/users/anders/HTSeq/doc/count.html). Genes were tested for differential expression (DE) using the negative binomial QLShrink

(Lund et al., 2012) and the R package QuasiSeq (http://cran.r- project.org/web/packages/QuasiSeq).

RT-qPCR

Gene expression was conducted using cDNA from four biological replicates, with two technical replicates each. Expression was quantified using the Maxima

SYBR Green qPCR Master Mix (Invitrogen Corp) and the CFX-96 Thermal Cycler

(Bio-Rad) using primers appropriate for each gene (Supplementary Table 5).

Relative expression levels were calculated using the comparative threshold cycle method (Schmittgen & Livak, 2008), in which gene expression levels of wild-type plants were normalized to 1 and expression of transgenic lines was calculated relative to this level.

Metabolite extraction and LC/MS analysis

Metabolites were extracted from the same plants used from RNAseq analysis.

100 mg of plant tissue was finely ground with mortar and pestle, then incubated in

50% (v/v) methanol at 65 °C for 40 minutes. Samples were centrifuged at 16,000 g for 5 minutes and passed through a 0.2 µm regenerated cellulose filter.

Untargeted metabolite profiling was carried out on an Agilent G6530A Q-TOF

LC/MS system. Ten microliters of metabolite extract was injected onto an Agilent

Eclipse Plus C18 column (3 x 100 mm; 1.8 µm). Metabolites were separated using a binary gradient of solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in acetonitrile) at a flow rate of 0.6 mL min-1. The gradient starts at 2% solvent 76

B for 1 min, followed by a linear increase to 98% over 20 min. The acquisition of mass spectra was done in negative mode with the following parameters: drying gas temperature, 300 °C; drying gas flow rate, 7.0 L min-1; nebulizer pressure, 40 psi; sheath gas temperature, 350 °C; sheath gas flow rate, 10.0 L min-1; Vcap, 3500 V;

Nozzle Voltage, 500 V; Fragmentor, 150 V; Skimmer, 65 V; OctopoleRFPeak, 750 V.

The raw data were processed using Agilent Masshunter Profinder (Version

B.06.00) to extract mass peaks and align them across all the samples. The output files were imported into Agilent Mass Profiler Professional (Version B.13.11) for statistical analysis. Hierarchical clustering analysis was performed on log2 transformed and normalized data using Euclidean distance and Ward’s linkage rule.

Transcript-metabolite correlation

The entire transcriptome dataset, represented as Fragments Per Kilobase of transcript per Million mapped reads (FPKM), and the entire metabolome dataset, formatted in log2 abundance (peak area), along with their metadata, were uploaded to the Plant/eukaryotic and Microbial systems Resource (PMR) database (PMR: http://www.metnetdb.org/pmr)(Hur et al., 2013).

Statistical significance of metabolite abundances was calculated through the

PMR database by comparing the metabolite abundances of hydrolase-expressing line (AnAXE, AnRAE, AnFAE) with the EV control. Metabolites with q-values less than 0.1 were considered for further correlation analysis. For each metabolite, lists of genes were identified according to metabolite-transcript correlation (Pearson correlation coefficient >0.9). Genes meeting this cutoff were then used to determine 77 over-represented pathways through MetNet Online (http://www.metnetonline.org).

From the resultant enriched gene list, significantly enriched pathways (p<0.05) were determined for every metabolite, and then pooled together. The individual pathways and their relevant locusIDs were then ranked according to the number of metabolites associated with them. This yielded a final list of enriched pathways for each transgenic line, ranked according to occurrence along with their relevant gene expressions (Table 4).

RESULTS

Differentially expressed genes in transgenic plants expressing wall-modifying hydrolases

Total RNA was sequenced from rosettes of 2-week old AnAXE, AnRAE,

AnFAE, EV control, and wild-type (WT) control lines in a Col-0 background. Through the quasiSeq R package, q-values of genes are normally used to determine differential expression of genes. However, q-values were extremely high in all comparisons as determined by distribution of p-values within the dataset. A comparison of EV and WT gene expression revealed nine genes had q-values less than 0.2 (AT1G20160, AT1G21750, AT1G32350, AT1G47960, AT3G03341,

AT3G50630, AT4G00700, AT5G10760, AT5G58710), and an AnFAE-EV comparison had six genes with q-values less than 0.2 (AT1G20160, AT1G50110, AT3G50630,

AT3G54960, AT4G00700, AT4G14420). No other comparisons between genotypes yielded q-values in this range. Thus, DE gene expression was determined as p-values less than 0.05, acknowledging the potential for false positives present in this gene 78 list. Using this method, seventy-nine genes were differentially expressed between

EV and WT Col-0 plants. This is likely because, depending on its positional integration, transgene overexpression under the viral Cauliflower Mosaic Virus

(CaMV) 35S promoter can induce some responses in the plant (Zheng et al., 2007).

To minimize the impact of this background plant response on the transcriptome and metabolome comparisons among cell wall modified lines, the three hydrolase- expressing lines were compared only with EV plants, which were transformed with

Agrobacterium carrying the same plasmid only without a hydrolase cDNA. Fifty-nine genes were upregulated more than two-fold (P <0.05) in AnAXE, 60 genes in AnRAE, and 79 genes in AnFAE in comparison with the EV plants. One hundred genes were downregulated more than two-fold (P <0.05) in AnAXE, 127 genes in AnRAE, and

409 genes in AnFAE in comparison with the EV plants (Fig. 1A).

Most of the genes that were differentially regulated were unique to a particular transgenic line. The Venny online tool

(http://bioinfogp.cnb.csic.es/tools/venny/) was used to determine overlapping DE genes between the three transgenic lines. Among upregulated genes, 8 genes overlapped between AnAXE and AnRAE, 10 genes between AnAXE and AnFAE, 6 genes between AnRAE and AnFAE, and 7 genes between all three lines. Among downregulated genes, 10 genes were common between AnAXE and AnRAE, 25 between AnAXE and AnFAE, 25 between AnRAE and AnFAE, and 11 were common between all three lines (Fig. 1B). The entire transcriptome dataset is presented in

Supplementary Table 1, and is also available in the PMR database. All differentially expressed genes according to p-values are shown in Supplementary Table 2. 79

A Upregulated Downregulated 100 500

80 400

60 300 Fig. 2: DE genes from RNAseq. A: number of genes upregulated and downregulated in 40 200 AnAXE, AnRAE, and AnFAE plants rela?ve to EV control. B. Overlapping DE genes Number of genes 20 Number of genes 100 upregulated (leF) and downregulated (right) 0 0 rela?ve to EV control. C: GO term AnAXE vs. EV AnRAE vs. EV AnFAE vs. EV AnAXE vs. EV AnRAE vs. EV AnFAE vs. EV enrichment of DE genes sorted by molecular func?on and protein class B 34 8 39 54 10 81 7 11 10 6 25 25

56 348

Molecular Molecular Protein Class Protein Class Func?on C 18 Func?on 120 16 100 14

12 AnAXE 80 AnAXE 10 AnRAE 60 AnRAE 8 AnFAE AnFAE 6 40 Number of genes 4 Number of genes 20 2 0 0

Ligase Lyase Ligase Lyase Binding Binding Receptor Receptor Hydrolase Chaperone Isomerase Hydrolase Isomerase Transporter Transferase Transferase Transporter Chaperone Cataly?c ac?vity Receptor ac?vity Oxidoreductase Cataly?c ac?vity Oxidoreductase Structural molecul Membrane traﬃc Receptor ac?vity Structural protein Transporter ac?vity Enzyme modulator Signaling molecule Transcrip?on factor Enzyme modulator Signaling molecule Transla?on regulator Nucleic acid binding Cytoskeletal protein Transporter ac?vity An?oxidant ac?vity Nucleic acid binding Transcrip?on factor Cytoskeletal protein Calcium-binding protein Calcium-binding protein Transfer/carrying protein Membrane traﬃc protein Structural molecule ac?vity Defense/immunity protein Transmembrane regulatory Transla?on regulator ac?vity Fig. 4.1: DE genes from RNAseq. A. number of genes upregulated and downregulated in AnAXE, AnRAE, and AnFAE plants relative to EV control. B. Overlapping DE genes upregulated (left) and downregulated (right) relative to EV control. C. GO term enrichment of DE genes sorted by molecular function and protein class

Gene product enrichment by molecular function

To better understand the CWI response of each transgenic line, molecular functions and protein classes enriched in DE genes were determined using the

Panther Gene Ontology (GO) enrichment tool. Upregulated genes with known functions encode nucleic acid binding proteins, transporters, hydrolases, and receptors (Fig. 1C). Significant numbers of downregulated genes also encode nucleic 80 acid binding proteins, transporters, and hydrolases, as well as oxidoreductases and transferases, in addition (Fig. 1C).

In AnAXE plants, the upregulated DE genes included 11 genes encoding enzymes, 4 genes involved in binding, 4 transporters, and 1 receptor (Fig. 1C).

Downregulated genes in AnAXE included 30 genes involved in catalysis, 9 genes involved in binding, 6 transporters, 1 gene with receptor activity, and 1 gene encoding a structural protein. Protein classifications were also identified, including upregulation of 3 transporters, 3 hydrolases, 2 nucleic acid binding proteins, and 2 signaling molecules. Protein classification of downregulated genes included 12 genes encoding oxidoreductase activity, 6 transferases, 6 transporters, and 6 nucleic acid binding proteins.

Classification of gene functions revealed similarities between AnRAE plants and AnAXE plants, as well as some differences. Upregulated DE genes in AnRAE included a similar number of enzymes (catalytic activity) as in AnAXE (8 genes), as well as transporters (5 genes). In contrast with AnAXE, 10 genes with binding activity were upregulated in AnRAE. In addition, 8 genes with catalytic activity, 5 transporters, 4 receptors, and 2 genes with structural roles were upregulated (Fig.

1C). Downregulated genes in AnRAE included 40 enzymes with catalytic activity, 18 genes involved in binding (twice the amount of those in AnAXE), 9 transporters, 2 structural genes, and 1 receptor. Protein classifications in AnRAE included upregulation of 8 nucleic acid binding proteins (again, a higher number than in

AnAXE), 4 transporters, 4 receptors, and 2 hydrolases. Twelve genes with oxidoreductase activity, 11 nucleic acid binding proteins, 11 hydrolases, and 9 81 transferases were present among downregulated genes (Fig. 1C).

DE genes classified by molecular function for AnFAE plants included 16 enzymes (catalytic activity), 10 genes involved in binding, 5 transporters, 3 receptors, 1 structural protein, and 1 translation regulator. Downregulated genes in

AnFAE included 114 genes with catalytic activity, 41 genes involved in binding, 26 transporters, 9 genes with antioxidant activity, 2 receptors, 2 structural proteins, and 1 translation regulator. Enrichment of protein classes among upregulated genes included 5 nucleic acid binding proteins, 4 transporters, 4 hydrolases, and 4 oxidoreductases. Protein classes among downregulated AnFAE genes included 37 oxidoreductases, 27 transferases, 22 transporters, 17 nucleic acid binding proteins, and 16 hydrolases (Fig. 1C).

Stress response, cell wall remodeling, and transcription factor enrichments

To further investigate the plant responses to CW modifications introduced in the transgenic lines as well as defense responses induced by these CW modifications or by the overexpressed hydrolases, the DE genes were sorted according to known association with either cell wall modification, stress response, or transcriptional regulation (Tables 1, 2, and 3). The AnAXE plants differentially expressed several wall-related genes including upregulation of two glycosyl hydrolases (AT1G71380,

AT4G11050), and downregulation of several extensin proteins (AT5G35190,

AT5G06640, AT4G13390, AT2G24980) (Table 1). Several stress response genes were enriched, including upregulation of a tryptophan-rich membrane bound protein (AT2G47770) and chitinase A (AT5G24090), and downregulation of several 82 receptor-like kinases (AT4G23200, AT4G23210, AT4G11460), a WRKY62 transcription factor (AT5G01900), and a mildew-resistance locus (AT2G39200)

(Table 2). Upregulated transcriptional regulators include bZIP48 (AT2G04038),

MYB102 (AT4G21440), an ethylene-responsive transcription factor (AT1G33760) and an uncharacterized cys2/his2 transcription factor (AT4G16610), whereas

WRKY30 (AT5G24110) and two MYB transcription factors, MYB92 and MYB66

(AT5G10280, AT5G14750), were all downregulated in AnAXE plants (Table 3).

In the AnRAE plants, only one CW-related gene was significantly upregulated, the plant defensin 1.2b (AT2G26020). Downregulated CW-related genes included

XTH26 (AT4G28850) and two extensins (AT2G24980, AT4G01630) (Table 1). Stress responses included the upregulation of CYP81G1 (AT5G67310), the tryptophan-rich membrane protein (AT2G47770), and plant defensin 1.4 (AT1G19610), whereas the downregulated stress response genes included beta glucosidases 24 and 27

(AT5G28510, AT3G60120), and a glutathione peroxidase (AT2G48150) (Table 2).

Among transcriptional regulators bZIP48 as well as Homeobox 53 (AT5G66700) were upregulated, whereas the bZIP5 (AT3G49760), 2 basic helix-loop-helix proteins (AT4G21340, AT5G58010), and 2 MYB containing proteins (AT1G09540,

AT1G73410) were downregulated (Table 3). 83 1.79 1.14 2.46 2.33 0.07 1.68 1.79 1.19 1.14 1.02 0.49 1.20 2.46 2.33 1.49 0.07 1.68 1.19 1.02 0.49 1.20 1.49 -1.22 -0.55 -1.16 -1.36 -1.84 -2.33 -1.15 -2.46 -2.18 -2.37 -2.73 -1.63 -0.06 -1.00 -0.66 -1.71 -1.12 -1.08 -2.69 -2.59 -2.56 -2.49 -1.31 -1.02 -2.18 -1.10 -2.73 -2.01 -2.94 -2.71 -1.22 -1.12 -0.55 -1.16 -2.76 -1.36 -2.58 -1.84 -2.33 -2.74 -1.15 -2.33 -2.46 -3.68 -2.18 -2.37 -1.02 -2.73 -2.49 -1.63 -2.15 -0.06 -0.92 -1.00 -2.65 -0.66 -2.40 -1.71 -1.12 -1.47 -1.08 -3.08 -2.69 -1.95 -2.08 -2.70 -2.59 -0.88 -2.56 -1.18 -2.49 -1.03 -1.31 -1.02 -3.72 -2.18 -2.07 -1.10 -2.07 -2.73 -2.01 -2.94 -2.71 -1.12 -2.76 -2.58 -2.74 -2.33 -3.68 -1.02 -2.49 -2.15 -0.92 -2.65 -2.40 -1.47 -3.08 -1.95 -2.08 -2.70 -0.88 -1.18 -1.03 -3.72 -2.07 -2.07 AnFAE-EV AnFAE-EV 0.62 0.43 1.19 0.89 0.62 0.25 0.43 1.19 0.89 0.25 -0.41 -1.69 -1.40 -0.71 -0.48 -0.95 -1.87 -0.26 -0.68 -0.30 -0.33 -1.52 -1.18 -0.71 -1.22 -1.45 -0.47 -0.64 -0.75 -1.07 -1.55 -0.28 -0.37 -0.75 -0.19 -0.95 -0.01 -0.89 -0.49 -0.82 -0.81 -0.41 -1.77 -1.69 -1.11 -1.40 -1.05 -0.71 -0.96 -0.48 -0.95 -0.78 -1.87 -0.30 -0.26 -0.84 -0.68 -2.00 -0.30 -0.72 -0.33 -0.12 -1.52 -0.83 -1.18 -0.45 -0.71 -1.05 -0.87 -1.22 -1.25 -1.45 -0.68 -0.47 -0.64 -0.05 -0.75 -1.90 -1.07 -1.01 -0.63 -0.66 -1.55 -0.02 -0.28 -0.79 -0.37 -1.07 -0.75 -0.22 -0.19 -0.65 -0.95 -0.34 -0.01 -0.40 -0.89 -0.49 -0.82 -0.81 -1.77 -1.11 -1.05 -0.96 -0.78 -0.30 -0.84 -2.00 -0.72 -0.12 -0.83 -0.45 -1.05 -0.87 -1.25 -0.68 -0.05 -1.90 -1.01 -0.63 -0.66 -0.02 -0.79 -1.07 -0.22 -0.65 -0.34 -0.40 -Fold Change -Fold Change 2 2 AnRAE-EV AnRAE-EV Log Log 0.43 0.20 1.19 0.09 0.27 0.76 0.12 2.13 0.43 0.12 0.20 0.44 1.13 1.19 0.09 0.23 0.27 0.76 0.12 2.13 0.12 0.44 1.13 0.23 -0.62 -1.06 -1.29 -0.35 -0.20 -0.80 -0.59 -1.13 -0.83 -0.90 -0.99 -0.82 -0.95 -0.32 -0.38 -0.48 -1.24 -1.22 -0.52 -0.83 -0.54 -0.63 -0.16 -0.37 -1.29 -0.69 -1.25 -0.82 -0.62 -0.57 -1.06 -1.29 -0.68 -0.35 -1.14 -0.20 -0.80 -1.08 -0.59 -0.82 -1.13 -1.52 -0.83 -0.90 -0.32 -0.99 -0.41 -0.82 -0.79 -1.29 -1.46 -0.95 -1.07 -0.32 -0.38 -0.65 -0.48 -0.51 -1.24 -0.81 -1.07 -1.01 -1.22 -1.19 -0.52 -0.35 -0.83 -0.93 -0.54 -0.57 -0.63 -0.63 -0.16 -0.62 -0.37 -0.83 -1.29 -0.69 -1.25 -0.82 -0.57 -0.68 -1.14 -1.08 -0.82 -1.52 -0.32 -0.41 -0.79 -1.29 -1.46 -1.07 -0.65 -0.51 -0.81 -1.07 -1.01 -1.19 -0.35 -0.93 -0.57 -0.63 -0.62 -0.83 AnAXE-EV AnAXE-EV extensin 3 cellulase 3 extensin 6 extensin 3 cellulase 3 extensin 6 PDI-like 2-2 PDI-like 2-2 Description Description extensin 12 extensin 10 extensin 13 extensin 12 extensin 10 extensin 13 KORRIGAN 2 KORRIGAN 2 expansin A17 expansin A21 expansin A17 expansin A21 subtilase 4.12 subtilase 4.12 peroxidase 52 peroxidase 52 SKU5 similar 15 SKU5 similar 15 plant defensin 1.3 plant defensin 1.3 plant defensin 1.2 plant defensin 1.2 plant defensin 1.2b plant defensin 1.2b root hair specific 18 root hair specific 18 proline-rich protein 1 proline-rich protein 3 proline-rich protein 1 proline-rich protein 3 glycosyl hydrolase 9C1 glycosyl hydrolase 9C3 glycosyl hydrolase 9C1 glycosyl hydrolase 9C3 myb domain protein 54 myb domain protein 63 myb domain protein 54 myb domain protein 63 PHOSPHATE-INDUCED 1 PHOSPHATE-INDUCED 1 6-&1-fructan exohydrolase 6-&1-fructan exohydrolase arabinogalactan protein 30 Cellulose-synthase-like C12 purple acid phosphatase 25 arabinogalactan protein 30 Cellulose-synthase-like C12 purple acid phosphatase 25 leucine-rich repeat/extensin 1 leucine-rich repeat/extensin 1 RARE COLD INDUCIBLE GENE 3 RARE COLD INDUCIBLE GENE 3 DUF642 L-GalL responsive gene 1 DUF642 L-GalL responsive gene 1 xyloglucan endotransglycosylase 6 xyloglucan endotransglycosylase 6 SUPPRESSOR OF PHYTOCHROME B 5 SUPPRESSOR OF PHYTOCHROME B 5 L -gulono-1,4-lactone ( L -GulL) oxidase 5 L -gulono-1,4-lactone ( L -GulL) oxidase 5 Casparian strip membrane domain protein 3 Casparian strip membrane domain protein 1 Casparian strip membrane domain protein 2 Casparian strip membrane domain protein 5 Casparian strip membrane domain protein 3 Casparian strip membrane domain protein 1 Casparian strip membrane domain protein 2 Casparian strip membrane domain protein 5 plant glycogenin-like starch initiation protein 5 plant glycogenin-like starch initiation protein 5 xyloglucan endotransglucosylase/hydrolase 14 xyloglucan endotransglucosylase/hydrolase 26 xyloglucan endotransglucosylase/hydrolase 18 xyloglucan endotransglucosylase/hydrolase 13 xyloglucan endotransglucosylase/hydrolase 14 xyloglucan endotransglucosylase/hydrolase 26 xyloglucan endotransglucosylase/hydrolase 18 xyloglucan endotransglucosylase/hydrolase 13 REDUCED LEVELS OF WALL-BOUND PHENOLICS 1 REDUCED LEVELS OF WALL-BOUND PHENOLICS 1 RCI3 RCI3 BIP2 BIP2 LRX1 EXT3 PRP1 CEL3 EXT6 PRP3 LRX1 XTR6 EXT3 PRP1 CEL3 EXT6 PRP3 XTR6 PHI-1 KOR2 DGR1 PHI-1 sks15 KOR2 SOB5 DGR1 sks15 SOB5 Name CASP3 CASP1 CASP2 Name EXT12 XTH14 XTH26 XTH18 PAP25 PRX52 EXT10 CASP5 RHS18 EXT13 CASP3 RWP1 CASP1 XTH13 CASP2 EXT12 XTH14 XTH26 XTH18 PAP25 PRX52 EXT10 CASP5 RHS18 EXT13 RWP1 XTH13 PGSIP5 GH9C1 PDF1.3 AGP30 PGSIP5 GH9C3 GH9C1 PDF1.3 AGP30 PDF1.2 GH9C3 PDF1.2 PDIL2-2 MYB54 MYB63 GulLO5 EXPA17 CSLC12 PDIL2-2 MYB54 MYB63 cwINV6 EXPA21 GulLO5 EXPA17 CSLC12 cwINV6 EXPA21 PDF1.2b PDF1.2b SBT4.12 SBT4.12 AT1G02360 AT1G02460 AT1G20150 AT1G23720 AT1G44130 AT1G78860 AT2G18150 AT2G38380 AT2G45220 AT3G28550 AT3G52790 AT3G54580 AT1G02360 AT1G02460 AT4G08400 AT4G08410 AT1G20150 AT1G23720 AT1G44130 AT4G36430 AT5G04960 AT5G06630 AT1G78860 AT2G18150 AT5G17820 AT2G38380 AT2G45220 AT5G64100 AT3G28550 AT3G52790 AT3G54580 AT4G08400 AT4G08410 AT4G36430 AT5G04960 AT5G06630 AT5G17820 AT5G64100 Gene Gene AT1G02360 AT1G02460 AT1G04980 AT1G05260 AT1G08990 AT1G12040 AT1G20150 AT1G21310 AT1G23720 AT1G35140 AT1G44130 AT1G48930 AT1G54970 AT1G65610 AT1G71380 AT1G73410 AT1G78860 AT1G79180 AT1G80240 AT2G18150 AT2G24980 AT2G26010 AT2G26020 AT2G27370 AT2G33790 AT2G36100 AT2G38380 AT2G45220 AT2G46740 AT3G11550 AT3G28550 AT3G52790 AT3G54580 AT3G62680 AT1G02360 AT4G01630 AT1G02460 AT4G07960 AT1G04980 AT4G08400 AT1G05260 AT4G08410 AT1G08990 AT4G11050 AT1G12040 AT4G13390 AT1G20150 AT4G25810 AT1G21310 AT4G25820 AT1G23720 AT4G28850 AT1G35140 AT4G30280 AT1G44130 AT4G36350 AT1G48930 AT4G36430 AT1G54970 AT4G37160 AT1G65610 AT5G04960 AT1G71380 AT5G05340 AT1G73410 AT5G06630 AT1G78860 AT5G06640 AT1G79180 AT5G08150 AT1G80240 AT5G11920 AT2G18150 AT5G15290 AT2G24980 AT5G17820 AT2G26010 AT5G22410 AT2G26020 AT5G35190 AT2G27370 AT5G39260 AT2G33790 AT5G41040 AT2G36100 AT5G42020 AT2G38380 AT5G44420 AT2G45220 AT5G57540 AT2G46740 AT5G59090 AT3G11550 AT5G64100 AT3G28550 AT3G52790 AT3G54580 AT3G62680 AT4G01630 AT4G07960 AT4G08400 AT4G08410 AT4G11050 AT4G13390 AT4G25810 AT4G25820 AT4G28850 AT4G30280 AT4G36350 AT4G36430 AT4G37160 AT5G04960 AT5G05340 AT5G06630 AT5G06640 AT5G08150 AT5G11920 AT5G15290 AT5G17820 AT5G22410 AT5G35190 AT5G39260 AT5G41040 AT5G42020 AT5G44420 AT5G57540 AT5G59090 AT5G64100 , and AnFAE plants. Values in bold represent signi?icantly 1.79 1.14 2.46 2.33 0.07 1.68 1.19 1.02 0.49 1.20 1.49 -1.22 -0.55 -1.16 -1.36 -1.84 -2.33 -1.15 -2.46 -2.18 -2.37 -2.73 -1.63 -0.06 -1.00 -0.66 -1.71 -1.12 -1.08 -2.69 -2.59 -2.56 -2.49 -1.31 -1.02 -2.18 -1.10 -2.73 -2.01 -2.94 -2.71 -1.12 -2.76 -2.58 -2.74 -2.33 -3.68 -1.02 -2.49 -2.15 -0.92 -2.65 -2.40 -1.47 -3.08 -1.95 -2.08 -2.70 -0.88 -1.18 -1.03 -3.72 -2.07 -2.07 AnFAE-EV AnRAE , 0.62 0.43 1.19 0.89 0.25 -0.41 -1.69 -1.40 -0.71 -0.48 -0.95 -1.87 -0.26 -0.68 -0.30 -0.33 -1.52 -1.18 -0.71 -1.22 -1.45 -0.47 -0.64 -0.75 -1.07 -1.55 -0.28 -0.37 -0.75 -0.19 -0.95 -0.01 -0.89 -0.49 -0.82 -0.81 -1.77 -1.11 -1.05 -0.96 -0.78 -0.30 -0.84 -2.00 -0.72 -0.12 -0.83 -0.45 -1.05 -0.87 -1.25 -0.68 -0.05 -1.90 -1.01 -0.63 -0.66 -0.02 -0.79 -1.07 -0.22 -0.65 -0.34 -0.40 -Fold Change 2 AnRAE-EV Log 0.43 0.20 1.19 0.09 0.27 0.76 0.12 2.13 0.12 0.44 1.13 0.23 AnAXE -0.62 -1.06 -1.29 -0.35 -0.20 -0.80 -0.59 -1.13 -0.83 -0.90 -0.99 -0.82 -0.95 -0.32 -0.38 -0.48 -1.24 -1.22 -0.52 -0.83 -0.54 -0.63 -0.16 -0.37 -1.29 -0.69 -1.25 -0.82 -0.57 -0.68 -1.14 -1.08 -0.82 -1.52 -0.32 -0.41 -0.79 -1.29 -1.46 -1.07 -0.65 -0.51 -0.81 -1.07 -1.01 -1.19 -0.35 -0.93 -0.57 -0.63 -0.62 -0.83 AnAXE-EV extensin 3 cellulase 3 extensin 6 PDI-like 2-2 Description extensin 12 extensin 10 extensin 13 KORRIGAN 2 expansin A17 expansin A21 subtilase 4.12 peroxidase 52 SKU5 similar 15 plant defensin 1.3 plant defensin 1.2 plant defensin 1.2b root hair specific 18 proline-rich protein 1 proline-rich protein 3 glycosyl hydrolase 9C1 glycosyl hydrolase 9C3 myb domain protein 54 myb domain protein 63 PHOSPHATE-INDUCED 1 6-&1-fructan exohydrolase arabinogalactan protein 30 Cellulose-synthase-like C12 purple acid phosphatase 25 leucine-rich repeat/extensin 1 RARE COLD INDUCIBLE GENE 3 DUF642 L-GalL responsive gene 1 xyloglucan endotransglycosylase 6 SUPPRESSOR OF PHYTOCHROME B 5 L -gulono-1,4-lactone ( L -GulL) oxidase 5 Casparian strip membrane domain protein 3 Casparian strip membrane domain protein 1 Casparian strip membrane domain protein 2 Casparian strip membrane domain protein 5 plant glycogenin-like starch initiation protein 5 xyloglucan endotransglucosylase/hydrolase 14 xyloglucan endotransglucosylase/hydrolase 26 xyloglucan endotransglucosylase/hydrolase 18 xyloglucan endotransglucosylase/hydrolase 13 REDUCED LEVELS OF WALL-BOUND PHENOLICS 1 RCI3 BIP2 LRX1 EXT3 PRP1 CEL3 EXT6 PRP3 XTR6 PHI-1 KOR2 DGR1 sks15 SOB5 Name CASP3 CASP1 CASP2 EXT12 XTH14 XTH26 XTH18 PAP25 PRX52 EXT10 CASP5 RHS18 EXT13 RWP1 XTH13 PGSIP5 GH9C1 PDF1.3 AGP30 GH9C3 PDF1.2 PDIL2-2 MYB54 MYB63 GulLO5 EXPA17 CSLC12 cwINV6 EXPA21 PDF1.2b SBT4.12 AT1G02360 AT1G02460 AT1G20150 AT1G23720 AT1G44130 AT1G78860 AT2G18150 AT2G38380 AT2G45220 AT3G28550 AT3G52790 AT3G54580 AT4G08400 AT4G08410 AT4G36430 AT5G04960 AT5G06630 AT5G17820 AT5G64100 Gene Table 4.1. Cell wall-related DE genes in different gene expression relative to EV plants (p<0.05). AT1G02360 AT1G02460 AT1G04980 AT1G05260 AT1G08990 AT1G12040 AT1G20150 AT1G21310 AT1G23720 AT1G35140 AT1G44130 AT1G48930 AT1G54970 AT1G65610 AT1G71380 AT1G73410 AT1G78860 AT1G79180 AT1G80240 AT2G18150 AT2G24980 AT2G26010 AT2G26020 AT2G27370 AT2G33790 AT2G36100 AT2G38380 AT2G45220 AT2G46740 AT3G11550 AT3G28550 AT3G52790 AT3G54580 AT3G62680 AT4G01630 AT4G07960 AT4G08400 AT4G08410 AT4G11050 AT4G13390 AT4G25810 AT4G25820 AT4G28850 AT4G30280 AT4G36350 AT4G36430 AT4G37160 AT5G04960 AT5G05340 AT5G06630 AT5G06640 AT5G08150 AT5G11920 AT5G15290 AT5G17820 AT5G22410 AT5G35190 AT5G39260 AT5G41040 AT5G42020 AT5G44420 AT5G57540 AT5G59090 AT5G64100

84 1.16 1.02 0.41 2.46 2.33 1.45 1.89 1.52 1.97 1.08 1.18 1.14 1.41 0.69 0.06 1.49 1.06 1.36 0.91 1.16 1.02 0.41 2.46 2.33 1.45 1.89 1.52 1.97 1.08 1.18 1.14 1.41 0.69 0.06 1.49 1.06 1.36 0.91 -1.22 -1.16 -1.36 -1.61 -2.12 -4.30 -2.24 -1.41 -1.03 -1.03 -1.76 -1.94 -1.77 -1.38 -0.78 -1.57 -1.08 -1.46 -1.24 -1.08 -1.39 -1.65 -1.70 -1.31 -0.70 -2.39 -1.02 -3.17 -1.90 -1.40 -1.60 -1.73 -0.27 -1.28 -2.10 -2.50 -1.58 -1.88 -1.04 -1.30 -1.32 -2.85 -0.59 -2.69 -1.09 -0.05 -2.31 -1.80 -3.67 -1.02 -1.99 -1.00 -0.57 -0.92 -0.94 -1.95 -2.08 -1.11 -2.07 -0.82 -1.28 -1.03 -1.98 -0.72 -1.38 -1.50 -2.07 -2.05 -2.16 -1.22 -1.16 -1.36 -1.61 -2.12 -4.30 -2.24 -1.41 -1.03 -1.03 -1.76 -1.94 -1.77 -1.38 -0.78 -1.57 -1.08 -1.46 -1.24 -1.08 -1.39 -1.65 -1.70 -1.31 -0.70 -2.39 -1.02 -3.17 -1.90 -1.40 -1.60 -1.73 -0.27 -1.28 -2.10 -2.50 -1.58 -1.88 -1.04 -1.30 -1.32 -2.85 -0.59 -2.69 -1.09 -0.05 -2.31 -1.80 -3.67 -1.02 -1.99 -1.00 -0.57 -0.92 -0.94 -1.95 -2.08 -1.11 -2.07 -0.82 -1.28 -1.03 -1.98 -0.72 -1.38 -1.50 -2.07 -2.05 -2.16 AnFAE-EV AnFAE-EV 0.01 0.45 1.12 0.23 0.43 1.19 0.03 0.09 1.09 1.47 0.81 0.07 0.70 0.33 0.33 0.56 0.51 0.29 0.63 1.33 0.01 0.45 1.12 0.23 0.43 1.19 0.03 0.09 1.09 1.47 0.81 0.07 0.70 0.33 0.33 0.56 0.51 0.29 0.63 1.33 -0.41 -1.40 -0.71 -0.47 -1.10 -0.53 -0.98 -0.82 -0.65 -0.42 -0.52 -0.58 -0.58 -0.59 -0.50 -0.52 -0.75 -0.95 -0.58 -1.25 -1.00 -0.86 -0.75 -0.65 -0.70 -0.19 -2.20 -0.45 -0.46 -0.73 -0.34 -0.35 -1.23 -0.27 -1.37 -0.51 -0.62 -0.57 -0.65 -0.06 -0.08 -0.06 -0.84 -0.76 -0.13 -0.70 -0.83 -0.54 -0.99 -0.80 -0.87 -0.28 -3.27 -1.01 -0.63 -0.32 -3.44 -1.12 -0.49 -1.07 -0.22 -1.02 -0.01 -0.84 -0.28 -0.40 -0.55 -0.84 -0.41 -1.40 -0.71 -0.47 -1.10 -0.53 -0.98 -0.82 -0.65 -0.42 -0.52 -0.58 -0.58 -0.59 -0.50 -0.52 -0.75 -0.95 -0.58 -1.25 -1.00 -0.86 -0.75 -0.65 -0.70 -0.19 -2.20 -0.45 -0.46 -0.73 -0.34 -0.35 -1.23 -0.27 -1.37 -0.51 -0.62 -0.57 -0.65 -0.06 -0.08 -0.06 -0.84 -0.76 -0.13 -0.70 -0.83 -0.54 -0.99 -0.80 -0.87 -0.28 -3.27 -1.01 -0.63 -0.32 -3.44 -1.12 -0.49 -1.07 -0.22 -1.02 -0.01 -0.84 -0.28 -0.40 -0.55 -0.84 -Fold Change -Fold Change 2 2 AnRAE-EV AnRAE-EV Log Log 0.53 0.88 0.69 0.08 0.27 0.76 0.29 1.85 0.56 0.76 0.93 1.14 1.73 1.55 0.44 1.05 1.08 1.37 0.00 0.60 0.53 0.88 0.69 0.08 0.27 0.76 0.29 1.85 0.56 0.76 0.93 1.14 1.73 1.55 0.44 1.05 1.08 1.37 0.00 0.60 -0.62 -1.29 -0.35 -0.28 -0.40 -0.30 -1.82 -1.13 -0.25 -0.33 -0.23 -0.28 -1.02 -1.04 -0.31 -0.48 -0.87 -0.92 -0.80 -0.16 -0.57 -0.72 -0.54 -1.47 -0.07 -0.25 -0.63 -0.32 -1.10 -0.35 -0.78 -0.86 -0.61 -0.39 -0.62 -0.36 -1.29 -0.33 -0.35 -2.55 -0.28 -0.30 -0.81 -0.69 -1.16 -0.40 -1.66 -0.30 -0.18 -1.82 -1.13 -1.08 -1.34 -0.25 -0.92 -0.33 -0.56 -0.23 -0.59 -0.28 -0.32 -1.02 -0.27 -1.04 -1.09 -0.31 -0.48 -1.29 -0.87 -0.92 -0.80 -0.16 -0.88 -0.81 -1.07 -0.57 -0.05 -0.72 -0.52 -0.54 -0.34 -1.47 -1.05 -0.07 -0.93 -0.25 -0.57 -0.63 -0.73 -1.93 -0.32 -1.07 -1.10 -0.35 -0.71 -0.78 -0.86 -0.83 -0.28 -0.61 -0.75 -0.39 -0.36 -0.33 -2.55 -0.30 -0.81 -0.69 -1.16 -1.66 -0.18 -1.08 -1.34 -0.92 -0.56 -0.59 -0.32 -0.27 -1.09 -1.29 -0.88 -0.81 -1.07 -0.05 -0.52 -0.34 -1.05 -0.93 -0.57 -0.73 -1.93 -1.07 -0.71 -0.83 -0.28 -0.75 AnAXE-EV AnAXE-EV chitinase A chitinase A Description PDI-like 2-2 Description PDI-like 2-2 MYB-like 102 MYB-like 102 ACC oxidase 1 peroxidase 52 ACC oxidase 1 peroxidase 52 plant defensin 1.3 plant defensin 1.2 plant defensin 1.3 plant defensin 1.2 plant defensin 1.2b plant defensin 1.2b beta glucosidase 27 root hair specific 18 beta glucosidase 24 root hair specific 19 beta glucosidase 27 root hair specific 18 beta glucosidase 24 root hair specific 19 MLP-like protein 328 MLP-like protein 328 myb domain protein 47 myb domain protein 47 glutathione peroxidase 4 phospholipase D alpha 3 ROOT HAIR DEFECTIVE 2 glutathione peroxidase 4 phospholipase D alpha 3 ROOT HAIR DEFECTIVE 2 alcohol dehydrogenase 1 DBP-interacting protein 2 alcohol dehydrogenase 1 DBP-interacting protein 2 WRKY DNA-binding protein 62 WRKY DNA-binding protein 27 WRKY DNA-binding protein 62 WRKY DNA-binding protein 27 RARE COLD INDUCIBLE GENE 3 RARE COLD INDUCIBLE GENE 3 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 Arabidopsis toxicos en levadura 9 Arabidopsis toxicos en levadura 9 MILDEW RESISTANCE LOCUS O 12 MILDEW RESISTANCE LOCUS O 15 jasmonate-zim-domain protein 10 LOW-TEMPERATURE-INDUCED 65 MILDEW RESISTANCE LOCUS O 12 MILDEW RESISTANCE LOCUS O 15 jasmonate-zim-domain protein 10 LOW-TEMPERATURE-INDUCED 65 monodehydroascorbate reductase Late Embryogenesis Abundant 4-5 microtubule-associated protein 18 monodehydroascorbate reductase Late Embryogenesis Abundant 4-5 microtubule-associated protein 18 respiratory burst oxidase homolog B NOD26-like major intrinsic protein 1 respiratory burst oxidase homolog B NOD26-like major intrinsic protein 1 FLG22-induced receptor-like kinase 1 FLG22-induced receptor-like kinase 1 IMPAIRED OOMYCETE SUSCEPTIBILITY 1 IMPAIRED OOMYCETE SUSCEPTIBILITY 1 WALL ASSOCIATED KINASE (WAK)-LIKE 10 UDP-dependent glycosyltransferase 76B1 WALL ASSOCIATED KINASE (WAK)-LIKE 10 UDP-dependent glycosyltransferase 76B1 AT-hook motif nuclear-localized protein 19 AT-hook motif nuclear-localized protein 19 cysteine-rich RLK (RECEPTOR-like protein kinase) 36 cysteine-rich RLK (RECEPTOR-like protein kinase) 37 cysteine-rich RLK (RECEPTOR-like protein kinase) 30 cysteine-rich RLK (RECEPTOR-like protein kinase) 12 cysteine-rich RLK (RECEPTOR-like protein kinase) 13 cysteine-rich RLK (RECEPTOR-like protein kinase) 36 cysteine-rich RLK (RECEPTOR-like protein kinase) 37 cysteine-rich RLK (RECEPTOR-like protein kinase) 30 cysteine-rich RLK (RECEPTOR-like protein kinase) 12 cysteine-rich RLK (RECEPTOR-like protein kinase) 13 cytochrome P450, family 81, subfamily G, polypeptide 1 cytochrome P450, family 81, subfamily G, polypeptide 1 cytochrome P450, family 81, subfamily D, polypeptide 11 cytochrome P450, family 81, subfamily D, polypeptide 11 TSPO(outer membrane tryptophan-rich sensory protein)-related TSPO(outer membrane tryptophan-rich sensory protein)-related , and AnFAE plants. Bold values indicate RCI3 JAZ5 IOS1 JAZ7 RCI3 JAZ5 IOS1 JAZ7 BIP2 BIP2 FRK1 ATL9 TSPO PLP1 DIP2 CHIA FRK1 ATL9 TSPO PLP1 DIP2 CHIA ADH1 ACO1 GPX4 JAZ10 RHD2 LTI65 ADH1 ACO1 GPX4 JAZ10 RHD2 LTI65 Name AHL19 CRK36 CRK37 CRK30 NLM1 CRK12 CRK13 PRX52 RHS18 RHS19 Name AHL19 CRK36 CRK37 CRK30 NLM1 CRK12 CRK13 PRX52 RHS18 RHS19 PDF1.4 PDF1.3 LEA4-5 PDF1.2 PDF1.4 PDF1.3 LEA4-5 PDF1.2 PDIL2-2 RBOHB MYB47 MLO12 MLO15 MAP18 PDIL2-2 RBOHB MYB47 MLO12 MLO15 MAP18 BGLU21 BGLU22 MLP328 PDF1.2b MDHAR BGLU27 BGLU21 BGLU22 MLP328 PDF1.2b BGLU24 MDHAR BGLU27 BGLU24 WAKL10 MYB102 WRKY62 WRKY27 WAKL10 MYB102 WRKY62 WRKY27 UGT76B1 CYP81G1 UGT76B1 CYP81G1 CYP81D11 CYP81D11 AT1G02360 AT1G30870 AT1G34510 AT1G49570 AT1G58170 AT1G65690 AT1G68850 AT2G18150 AT2G18980 AT2G21100 AT2G35380 AT2G38380 AT2G42885 AT2G45220 AT3G01190 AT3G20340 AT3G22275 AT3G25510 AT3G25930 AT1G02360 AT3G49960 AT3G55230 AT4G10500 AT4G11170 AT1G30870 AT1G34510 AT1G49570 AT1G58170 AT1G65690 AT4G26010 AT4G30170 AT4G33730 AT1G68850 AT4G36430 AT2G18150 AT2G18980 AT5G16980 AT2G21100 AT5G17390 AT5G17820 PLDALPHA3 AT2G35380 AT2G38380 AT5G38000 AT5G38340 AT2G42885 AT2G45220 AT5G45220 AT3G01190 AT5G58400 AT5G64100 AT3G20340 AT5G66390 AT3G22275 AT3G25510 AT3G25930 AT3G49960 AT3G55230 AT4G10500 AT4G11170 AT4G26010 AT4G30170 AT4G33730 AT4G36430 AT5G16980 AT5G17390 AT5G17820 PLDALPHA3 AT5G38000 AT5G38340 AT5G45220 AT5G58400 AT5G64100 AT5G66390 AnRAE , Gene Gene AT1G02360 AT1G04980 AT1G05260 AT1G09090 AT1G17380 AT1G18710 AT1G19610 AT1G30870 AT1G34510 AT1G49570 AT1G51800 AT1G58170 AT1G65690 AT1G66270 AT1G66280 AT1G68850 AT1G77120 AT1G79680 AT2G01520 AT2G18150 AT2G18980 AT2G19190 AT2G19590 AT2G21100 AT2G26010 AT2G26020 AT2G34600 AT2G35000 AT2G35380 AT2G38380 AT2G39200 AT2G42885 AT2G44110 AT2G45220 AT2G47770 AT2G48150 AT3G01190 AT3G04570 AT3G09940 AT3G11340 AT3G20340 AT3G22275 AT3G25510 AT3G25930 AT3G28740 AT3G49960 AT3G55230 AT3G60120 AT4G04490 AT4G04500 AT4G10500 AT4G11170 AT4G11460 AT4G19030 AT4G21440 AT4G23200 AT4G23210 AT4G26010 AT4G30170 AT4G33730 AT4G36430 AT4G37070 AT5G01900 AT5G03210 AT5G05340 AT5G06760 AT5G13220 AT5G16980 AT5G17390 AT5G17820 AT5G22410 AT5G24090 AT5G25370 AT5G28510 AT5G38000 AT5G38340 AT5G42020 AT5G44420 AT5G44610 AT5G45220 AT5G51060 AT5G52300 AT5G52830 AT5G58400 AT5G64100 AT5G66390 AT5G67310 AT5G67400 AT1G02360 AT1G04980 AT1G05260 AT1G09090 AT1G17380 AT1G18710 AT1G19610 AT1G30870 AT1G34510 AT1G49570 AT1G51800 AT1G58170 AT1G65690 AT1G66270 AT1G66280 AT1G68850 AT1G77120 AT1G79680 AT2G01520 AT2G18150 AT2G18980 AT2G19190 AT2G19590 AT2G21100 AT2G26010 AT2G26020 AT2G34600 AT2G35000 AT2G35380 AT2G38380 AT2G39200 AT2G42885 AT2G44110 AT2G45220 AT2G47770 AT2G48150 AT3G01190 AT3G04570 AT3G09940 AT3G11340 AT3G20340 AT3G22275 AT3G25510 AT3G25930 AT3G28740 AT3G49960 AT3G55230 AT3G60120 AT4G04490 AT4G04500 AT4G10500 AT4G11170 AT4G11460 AT4G19030 AT4G21440 AT4G23200 AT4G23210 AT4G26010 AT4G30170 AT4G33730 AT4G36430 AT4G37070 AT5G01900 AT5G03210 AT5G05340 AT5G06760 AT5G13220 AT5G16980 AT5G17390 AT5G17820 AT5G22410 AT5G24090 AT5G25370 AT5G28510 AT5G38000 AT5G38340 AT5G42020 AT5G44420 AT5G44610 AT5G45220 AT5G51060 AT5G52300 AT5G52830 AT5G58400 AT5G64100 AT5G66390 AT5G67310 AT5G67400 AnAXE 1.16 1.02 0.41 2.46 2.33 1.45 1.89 1.52 1.97 1.08 1.18 1.14 1.41 0.69 0.06 1.49 1.06 1.36 0.91 -1.22 -1.16 -1.36 -1.61 -2.12 -4.30 -2.24 -1.41 -1.03 -1.03 -1.76 -1.94 -1.77 -1.38 -0.78 -1.57 -1.08 -1.46 -1.24 -1.08 -1.39 -1.65 -1.70 -1.31 -0.70 -2.39 -1.02 -3.17 -1.90 -1.40 -1.60 -1.73 -0.27 -1.28 -2.10 -2.50 -1.58 -1.88 -1.04 -1.30 -1.32 -2.85 -0.59 -2.69 -1.09 -0.05 -2.31 -1.80 -3.67 -1.02 -1.99 -1.00 -0.57 -0.92 -0.94 -1.95 -2.08 -1.11 -2.07 -0.82 -1.28 -1.03 -1.98 -0.72 -1.38 -1.50 -2.07 -2.05 -2.16 AnFAE-EV 0.01 0.45 1.12 0.23 0.43 1.19 0.03 0.09 1.09 1.47 0.81 0.07 0.70 0.33 0.33 0.56 0.51 0.29 0.63 1.33 -0.41 -1.40 -0.71 -0.47 -1.10 -0.53 -0.98 -0.82 -0.65 -0.42 -0.52 -0.58 -0.58 -0.59 -0.50 -0.52 -0.75 -0.95 -0.58 -1.25 -1.00 -0.86 -0.75 -0.65 -0.70 -0.19 -2.20 -0.45 -0.46 -0.73 -0.34 -0.35 -1.23 -0.27 -1.37 -0.51 -0.62 -0.57 -0.65 -0.06 -0.08 -0.06 -0.84 -0.76 -0.13 -0.70 -0.83 -0.54 -0.99 -0.80 -0.87 -0.28 -3.27 -1.01 -0.63 -0.32 -3.44 -1.12 -0.49 -1.07 -0.22 -1.02 -0.01 -0.84 -0.28 -0.40 -0.55 -0.84 -Fold Change 2 AnRAE-EV Log 0.53 0.88 0.69 0.08 0.27 0.76 0.29 1.85 0.56 0.76 0.93 1.14 1.73 1.55 0.44 1.05 1.08 1.37 0.00 0.60 -0.62 -1.29 -0.35 -0.28 -0.40 -0.30 -1.82 -1.13 -0.25 -0.33 -0.23 -0.28 -1.02 -1.04 -0.31 -0.48 -0.87 -0.92 -0.80 -0.16 -0.57 -0.72 -0.54 -1.47 -0.07 -0.25 -0.63 -0.32 -1.10 -0.35 -0.78 -0.86 -0.61 -0.39 -0.36 -0.33 -2.55 -0.30 -0.81 -0.69 -1.16 -1.66 -0.18 -1.08 -1.34 -0.92 -0.56 -0.59 -0.32 -0.27 -1.09 -1.29 -0.88 -0.81 -1.07 -0.05 -0.52 -0.34 -1.05 -0.93 -0.57 -0.73 -1.93 -1.07 -0.71 -0.83 -0.28 -0.75 AnAXE-EV chitinase A Description PDI-like 2-2 MYB-like 102 ACC oxidase 1 peroxidase 52 plant defensin 1.3 plant defensin 1.2 plant defensin 1.2b beta glucosidase 27 root hair specific 18 beta glucosidase 24 root hair specific 19 MLP-like protein 328 myb domain protein 47 glutathione peroxidase 4 phospholipase D alpha 3 ROOT HAIR DEFECTIVE 2 alcohol dehydrogenase 1 DBP-interacting protein 2 WRKY DNA-binding protein 62 WRKY DNA-binding protein 27 RARE COLD INDUCIBLE GENE 3 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 Arabidopsis toxicos en levadura 9 MILDEW RESISTANCE LOCUS O 12 MILDEW RESISTANCE LOCUS O 15 jasmonate-zim-domain protein 10 LOW-TEMPERATURE-INDUCED 65 monodehydroascorbate reductase Late Embryogenesis Abundant 4-5 microtubule-associated protein 18 respiratory burst oxidase homolog B NOD26-like major intrinsic protein 1 FLG22-induced receptor-like kinase 1 IMPAIRED OOMYCETE SUSCEPTIBILITY 1 WALL ASSOCIATED KINASE (WAK)-LIKE 10 UDP-dependent glycosyltransferase 76B1 AT-hook motif nuclear-localized protein 19 cysteine-rich RLK (RECEPTOR-like protein kinase) 36 cysteine-rich RLK (RECEPTOR-like protein kinase) 37 cysteine-rich RLK (RECEPTOR-like protein kinase) 30 cysteine-rich RLK (RECEPTOR-like protein kinase) 12 cysteine-rich RLK (RECEPTOR-like protein kinase) 13 cytochrome P450, family 81, subfamily G, polypeptide 1 cytochrome P450, family 81, subfamily D, polypeptide 11 TSPO(outer membrane tryptophan-rich sensory protein)-related RCI3 JAZ5 IOS1 JAZ7 BIP2 FRK1 ATL9 TSPO PLP1 DIP2 CHIA ADH1 ACO1 GPX4 JAZ10 RHD2 LTI65 Name AHL19 CRK36 CRK37 CRK30 NLM1 CRK12 CRK13 PRX52 RHS18 RHS19 PDF1.4 PDF1.3 LEA4-5 PDF1.2 PDIL2-2 RBOHB MYB47 MLO12 MLO15 MAP18 BGLU21 BGLU22 MLP328 PDF1.2b MDHAR BGLU27 BGLU24 WAKL10 MYB102 WRKY62 WRKY27 UGT76B1 CYP81G1 CYP81D11 AT1G02360 AT1G30870 AT1G34510 AT1G49570 AT1G58170 AT1G65690 AT1G68850 AT2G18150 AT2G18980 AT2G21100 AT2G35380 AT2G38380 AT2G42885 AT2G45220 AT3G01190 AT3G20340 AT3G22275 AT3G25510 AT3G25930 AT3G49960 AT3G55230 AT4G10500 AT4G11170 AT4G26010 AT4G30170 AT4G33730 AT4G36430 AT5G16980 AT5G17390 AT5G17820 PLDALPHA3 AT5G38000 AT5G38340 AT5G45220 AT5G58400 AT5G64100 AT5G66390 Gene Table 4.2. DE stress and defense response genes in signi?icantly different expression from EV plants (p<0.05). AT1G02360 AT1G04980 AT1G05260 AT1G09090 AT1G17380 AT1G18710 AT1G19610 AT1G30870 AT1G34510 AT1G49570 AT1G51800 AT1G58170 AT1G65690 AT1G66270 AT1G66280 AT1G68850 AT1G77120 AT1G79680 AT2G01520 AT2G18150 AT2G18980 AT2G19190 AT2G19590 AT2G21100 AT2G26010 AT2G26020 AT2G34600 AT2G35000 AT2G35380 AT2G38380 AT2G39200 AT2G42885 AT2G44110 AT2G45220 AT2G47770 AT2G48150 AT3G01190 AT3G04570 AT3G09940 AT3G11340 AT3G20340 AT3G22275 AT3G25510 AT3G25930 AT3G28740 AT3G49960 AT3G55230 AT3G60120 AT4G04490 AT4G04500 AT4G10500 AT4G11170 AT4G11460 AT4G19030 AT4G21440 AT4G23200 AT4G23210 AT4G26010 AT4G30170 AT4G33730 AT4G36430 AT4G37070 AT5G01900 AT5G03210 AT5G05340 AT5G06760 AT5G13220 AT5G16980 AT5G17390 AT5G17820 AT5G22410 AT5G24090 AT5G25370 AT5G28510 AT5G38000 AT5G38340 AT5G42020 AT5G44420 AT5G44610 AT5G45220 AT5G51060 AT5G52300 AT5G52830 AT5G58400 AT5G64100 AT5G66390 AT5G67310 AT5G67400

85 1.34 1.16 1.02 1.44 0.92 0.20 0.22 2.64 1.45 3.02 1.05 1.97 1.34 1.16 1.02 1.44 1.13 1.18 0.92 0.20 0.85 0.22 1.41 2.64 3.58 1.45 3.02 0.95 1.05 1.97 1.13 1.18 0.85 1.41 3.58 0.95 -1.88 -1.22 -1.17 -1.14 -0.40 -1.53 -1.59 -0.98 -0.47 -2.67 -1.00 -1.71 -2.09 -1.53 -0.40 -0.95 -0.97 -0.93 -1.35 -1.91 -1.65 -0.62 -1.40 -2.11 -2.23 -2.64 -1.39 -1.88 -0.18 -1.22 -1.17 -1.10 -2.12 -0.03 -1.17 -1.34 -1.10 -1.14 -0.40 -1.29 -1.53 -2.48 -1.59 -2.77 -0.98 -3.22 -0.47 -2.01 -1.00 -2.67 -2.12 -1.00 -1.46 -1.71 -0.34 -2.09 -1.53 -3.58 -0.40 -0.84 -0.95 -1.46 -0.97 -1.03 -2.97 -0.93 -1.50 -1.35 -1.74 -1.91 -1.93 -1.65 -3.28 -1.17 -0.62 -1.40 -2.03 -2.11 -2.23 -2.64 -1.39 -0.18 -1.17 -1.10 -2.12 -0.03 -1.34 -1.10 -1.29 -2.48 -2.77 -3.22 -2.01 -1.00 -2.12 -1.46 -0.34 -3.58 -0.84 -1.46 -1.03 -2.97 -1.50 -1.74 -1.93 -3.28 -1.17 -2.03 AnFAE-EV AnFAE-EV 1.59 0.01 0.45 1.46 0.07 2.56 0.03 3.16 0.33 0.13 1.19 0.81 0.39 0.83 1.19 1.70 0.32 1.32 1.59 0.01 0.45 1.46 0.07 2.56 0.03 3.16 0.33 0.13 1.19 0.81 0.39 0.83 1.19 1.70 0.32 1.32 -1.45 -0.69 -0.96 -3.07 -1.28 -0.36 -0.23 -0.80 -0.19 -2.15 -0.83 -1.22 -0.17 -0.47 -1.15 -0.82 -1.16 -3.35 -1.05 -1.89 -0.71 -0.81 -0.08 -2.74 -0.46 -1.09 -0.65 -1.45 -1.75 -0.69 -0.09 -2.53 -0.35 -0.18 -0.96 -0.23 -0.07 -3.07 -1.28 -3.37 -0.36 -0.06 -0.23 -0.80 -1.59 -0.24 -0.19 -1.68 -2.15 -0.99 -0.83 -1.20 -1.22 -0.17 -0.77 -0.47 -0.28 -0.66 -1.15 -0.82 -1.65 -1.16 -0.71 -3.35 -0.31 -1.05 -1.07 -0.47 -1.89 -0.28 -0.71 -0.09 -0.81 -1.53 -0.08 -0.59 -2.74 -0.46 -0.52 -1.09 -0.65 -1.75 -0.09 -2.53 -0.35 -0.18 -0.23 -0.07 -3.37 -0.06 -1.59 -0.24 -1.68 -0.99 -1.20 -0.77 -0.28 -0.66 -1.65 -0.71 -0.31 -1.07 -0.47 -0.28 -0.09 -1.53 -0.59 -0.52 -Fold Change -Fold Change AnRAE-EV AnRAE-EV 2 2 Log Log 1.80 0.53 0.88 1.33 1.03 0.05 0.09 3.09 0.29 3.00 0.95 0.76 1.80 0.53 0.88 1.10 1.33 0.18 1.14 1.03 0.05 0.09 0.44 3.09 3.55 0.29 0.03 3.00 0.86 0.95 0.76 1.10 0.18 1.14 0.44 3.55 0.03 0.86 -0.45 -0.98 -0.44 -0.56 -0.51 -0.41 -0.34 -1.92 -1.26 -0.16 -1.43 -0.32 -1.74 -1.60 -0.37 -0.94 -0.76 -0.51 -1.03 -1.44 -0.01 -0.84 -0.35 -0.87 -0.43 -0.69 -0.08 -0.45 -0.46 -0.98 -0.13 -0.25 -0.01 -0.44 -0.24 -0.51 -0.56 -0.51 -1.43 -0.41 -0.42 -0.34 -0.78 -1.92 -0.20 -1.26 -2.91 -1.09 -0.16 -0.67 -0.31 -1.43 -1.54 -0.32 -2.05 -1.74 -1.60 -1.10 -0.37 -1.51 -0.94 -0.58 -0.76 -0.93 -0.45 -0.51 -0.71 -1.03 -0.49 -1.44 -0.01 -0.12 -0.40 -0.84 -0.35 -0.56 -0.87 -0.43 -0.69 -0.08 -0.46 -0.13 -0.25 -0.01 -0.24 -0.51 -1.43 -0.42 -0.78 -0.20 -2.91 -1.09 -0.67 -0.31 -1.54 -2.05 -1.10 -1.51 -0.58 -0.93 -0.45 -0.71 -0.49 -0.12 -0.40 -0.56 AnAXE-EV AnAXE-EV RAD-like 5 RAD-like 5 Description Description MYB-like 102 LJRHL1-like 3 MYB-like 102 LJRHL1-like 3 homeobox 53 homeobox 53 AGAMOUS-like 6 AGAMOUS-like 6 PRESSED FLOWER AGAMOUS-like 21 PRESSED FLOWER AGAMOUS-like 21 response regulator 15 basic leucine-zipper 5 response regulator 15 basic leucine-zipper 5 ROOT SHORTENING 1 ROOT SHORTENING 1 basic leucine-zipper 48 basic leucine-zipper 48 myb domain protein 61 myb domain protein 47 myb domain protein 54 myb domain protein 63 myb domain protein 61 myb domain protein 47 myb domain protein 54 myb domain protein 92 myb domain protein 63 myb domain protein 66 myb domain protein 68 myb domain protein 92 myb domain protein 66 myb domain protein 68 TBP-associated factor 4B TBP-associated factor 4B nuclear factor Y, subunit B5 nuclear factor Y, subunit B5 CUP-SHAPED COTYLEDON 2 CUP-SHAPED COTYLEDON 2 RWP-RK domain-containing 5 ASYMMETRIC LEAVES 2-like 1 RWP-RK domain-containing 5 ASYMMETRIC LEAVES 2-like 1 WRKY DNA-binding protein 61 WRKY DNA-binding protein 65 WRKY DNA-binding protein 61 WRKY DNA-binding protein 65 LONG AFTER FAR-RED LIGHT 1 WRKY DNA-binding protein 62 WRKY DNA-binding protein 30 WRKY DNA-binding protein 27 LONG AFTER FAR-RED LIGHT 1 WRKY DNA-binding protein 62 WRKY DNA-binding protein 30 WRKY DNA-binding protein 27 ROOT HAIR DEFECTIVE 6-LIKE 2 ROOT HAIR DEFECTIVE 6-LIKE 2 FER-like regulator of iron uptake indole-3-acetic acid inducible 31 LIGHT SENSITIVE HYPOCOTYLS 9 FER-like regulator of iron uptake indole-3-acetic acid inducible 31 LIGHT SENSITIVE HYPOCOTYLS 9 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 jasmonate-zim-domain protein 10 jasmonate-zim-domain protein 10 NAC domain containing protein 42 NAC domain containing protein 58 NAC domain containing protein 90 NAC domain containing protein 42 NAC domain containing protein 58 NAC domain containing protein 90 MATERNAL EFFECT EMBRYO ARREST 3 TGACG (TGA) motif-binding protein 10 MATERNAL EFFECT EMBRYO ARREST 3 TGACG (TGA) motif-binding protein 10 AT-hook motif nuclear-localized protein 22 AT-hook motif nuclear-localized protein 19 AT-hook motif nuclear-localized protein 22 AT-hook motif nuclear-localized protein 19 ARABIDOPSIS TRITHORAX-RELATED PROTEIN 6 ARABIDOPSIS TRITHORAX-RELATED PROTEIN 6 HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY histone acetyltransferase of the TAFII250 family 2 histone acetyltransferase of the TAFII250 family 2 RL5 PRS RL5 PRS FRU B70 PEI1 FRU B70 PEI1 JAZ5 JAZ7 JAZ5 LAF1 RSL2 BIP2 JAZ7 LRL3 ASL1 LAF1 RSL2 BIP2 LRL3 ASL1 HRS1 TCP1 AGL6 HAF2 bZIP5 LSH9 IWS2 RKD5 CUC2 HB53 HRS1 TCP1 AGL6 HAF2 bZIP5 LSH9 IWS2 RKD5 CUC2 HB53 Name MEE3 IAA31 Name JAZ10 MEE3 IAA31 JAZ10 TAF4B ARR15 AHL22 AHL19 AGL21 TGA10 ATXR6 TAF4B ARR15 AHL22 AHL19 AGL21 TGA10 ATXR6 MYB61 MYB47 MYB54 MYB63 bZIP48 NF-YB5 MYB92 MYB66 MYB68 MYB61 MYB47 MYB54 MYB63 bZIP48 NF-YB5 MYB92 MYB66 MYB68 NAC042 NAC058 NAC090 NAC042 NAC058 NAC090 WRKY61 WRKY65 WRKY61 WRKY65 MYB102 WRKY62 WRKY30 WRKY27 MYB102 WRKY62 WRKY30 WRKY27 , and AnFAE plants. Bold values represent AT1G14686 AT1G26680 AT1G33760 AT1G49900 AT1G53690 AT1G54840 AT1G62490 AT2G20080 AT2G34210 AT2G39240 AT2G43140 AT3G10470 AT3G12977 AT3G19184 AT3G22275 AT3G46080 AT1G14686 AT4G12050 AT4G16610 AT4G17800 AT1G26680 AT1G33760 AT1G49900 AT1G53690 AT1G54840 AT1G62490 AT2G20080 AT5G21960 AT2G34210 AT5G43540 AT2G39240 AT2G43140 AT5G58280 AT3G10470 AT3G12977 AT3G19184 AT3G22275 AT3G46080 AT4G12050 AT4G16610 AT4G17800 AT5G21960 AT5G43540 AT5G58280 Gene Gene AT1G09540 AT1G13300 AT1G14686 AT1G17380 AT1G18710 AT1G18860 AT1G19510 AT1G26680 AT1G27720 AT1G29280 AT1G33760 AT1G49900 AT1G53690 AT1G54840 AT1G62490 AT1G67260 AT1G73410 AT1G74890 AT1G79180 AT2G04038 AT2G20080 AT2G21650 AT2G28160 AT2G28610 AT2G34210 AT2G34600 AT2G39240 AT2G43000 AT2G43140 AT2G45430 AT2G45650 AT2G47810 AT3G04570 AT3G10470 AT3G12977 AT3G17600 AT3G18400 AT3G19040 AT1G09540 AT3G19184 AT3G22275 AT1G13300 AT3G46080 AT1G14686 AT3G49760 AT1G17380 AT4G12050 AT1G18710 AT4G16610 AT1G18860 AT4G17800 AT1G19510 AT4G18610 AT1G26680 AT4G19000 AT1G27720 AT4G21340 AT1G29280 AT4G21440 AT1G33760 AT4G25560 AT1G49900 AT4G33880 AT1G53690 AT4G35590 AT1G54840 AT4G37940 AT1G62490 AT5G01900 AT1G67260 AT5G06839 AT1G73410 AT5G07500 AT1G74890 AT5G10280 AT1G79180 AT5G13220 AT2G04038 AT5G14750 AT2G20080 AT5G21960 AT2G21650 AT5G22380 AT2G28160 AT5G24110 AT2G28610 AT5G24330 AT2G34210 AT5G42020 AT2G34600 AT5G43540 AT2G39240 AT5G52830 AT2G43000 AT5G53950 AT2G43140 AT5G58010 AT2G45430 AT5G58280 AT2G45650 AT5G65790 AT2G47810 AT5G66700 AT3G04570 AT5G66870 AT3G10470 AT3G12977 AT3G17600 AT3G18400 AT3G19040 AT3G19184 AT3G22275 AT3G46080 AT3G49760 AT4G12050 AT4G16610 AT4G17800 AT4G18610 AT4G19000 AT4G21340 AT4G21440 AT4G25560 AT4G33880 AT4G35590 AT4G37940 AT5G01900 AT5G06839 AT5G07500 AT5G10280 AT5G13220 AT5G14750 AT5G21960 AT5G22380 AT5G24110 AT5G24330 AT5G42020 AT5G43540 AT5G52830 AT5G53950 AT5G58010 AT5G58280 AT5G65790 AT5G66700 AT5G66870 AnRAE , 1.34 1.16 1.02 1.44 0.92 0.20 0.22 2.64 1.45 3.02 1.05 1.97 1.13 1.18 0.85 1.41 3.58 0.95 -1.88 -1.22 -1.17 -1.14 -0.40 -1.53 -1.59 -0.98 -0.47 -2.67 -1.00 -1.71 -2.09 -1.53 -0.40 -0.95 -0.97 -0.93 -1.35 -1.91 -1.65 -0.62 -1.40 -2.11 -2.23 -2.64 -1.39 -0.18 -1.17 -1.10 -2.12 -0.03 -1.34 -1.10 -1.29 -2.48 -2.77 -3.22 -2.01 -1.00 -2.12 -1.46 -0.34 -3.58 -0.84 -1.46 -1.03 -2.97 -1.50 -1.74 -1.93 -3.28 -1.17 -2.03 AnAXE AnFAE-EV 1.59 0.01 0.45 1.46 0.07 2.56 0.03 3.16 0.33 0.13 1.19 0.81 0.39 0.83 1.19 1.70 0.32 1.32 -1.45 -0.69 -0.96 -3.07 -1.28 -0.36 -0.23 -0.80 -0.19 -2.15 -0.83 -1.22 -0.17 -0.47 -1.15 -0.82 -1.16 -3.35 -1.05 -1.89 -0.71 -0.81 -0.08 -2.74 -0.46 -1.09 -0.65 -1.75 -0.09 -2.53 -0.35 -0.18 -0.23 -0.07 -3.37 -0.06 -1.59 -0.24 -1.68 -0.99 -1.20 -0.77 -0.28 -0.66 -1.65 -0.71 -0.31 -1.07 -0.47 -0.28 -0.09 -1.53 -0.59 -0.52 -Fold Change AnRAE-EV 2 Log 1.80 0.53 0.88 1.33 1.03 0.05 0.09 3.09 0.29 3.00 0.95 0.76 1.10 0.18 1.14 0.44 3.55 0.03 0.86 -0.45 -0.98 -0.44 -0.56 -0.51 -0.41 -0.34 -1.92 -1.26 -0.16 -1.43 -0.32 -1.74 -1.60 -0.37 -0.94 -0.76 -0.51 -1.03 -1.44 -0.01 -0.84 -0.35 -0.87 -0.43 -0.69 -0.08 -0.46 -0.13 -0.25 -0.01 -0.24 -0.51 -1.43 -0.42 -0.78 -0.20 -2.91 -1.09 -0.67 -0.31 -1.54 -2.05 -1.10 -1.51 -0.58 -0.93 -0.45 -0.71 -0.49 -0.12 -0.40 -0.56 AnAXE-EV RAD-like 5 Description MYB-like 102 LJRHL1-like 3 homeobox 53 AGAMOUS-like 6 PRESSED FLOWER AGAMOUS-like 21 response regulator 15 basic leucine-zipper 5 ROOT SHORTENING 1 basic leucine-zipper 48 myb domain protein 61 myb domain protein 47 myb domain protein 54 myb domain protein 63 myb domain protein 92 myb domain protein 66 myb domain protein 68 TBP-associated factor 4B nuclear factor Y, subunit B5 CUP-SHAPED COTYLEDON 2 RWP-RK domain-containing 5 ASYMMETRIC LEAVES 2-like 1 WRKY DNA-binding protein 61 WRKY DNA-binding protein 65 LONG AFTER FAR-RED LIGHT 1 WRKY DNA-binding protein 62 WRKY DNA-binding protein 30 WRKY DNA-binding protein 27 ROOT HAIR DEFECTIVE 6-LIKE 2 FER-like regulator of iron uptake indole-3-acetic acid inducible 31 LIGHT SENSITIVE HYPOCOTYLS 9 jasmonate-zim-domain protein 5 jasmonate-zim-domain protein 7 jasmonate-zim-domain protein 10 NAC domain containing protein 42 NAC domain containing protein 58 NAC domain containing protein 90 MATERNAL EFFECT EMBRYO ARREST 3 TGACG (TGA) motif-binding protein 10 AT-hook motif nuclear-localized protein 22 AT-hook motif nuclear-localized protein 19 ARABIDOPSIS TRITHORAX-RELATED PROTEIN 6 HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY histone acetyltransferase of the TAFII250 family 2 RL5 PRS FRU B70 PEI1 JAZ5 JAZ7 LAF1 RSL2 BIP2 LRL3 ASL1 HRS1 TCP1 AGL6 HAF2 bZIP5 LSH9 IWS2 RKD5 CUC2 HB53 Name MEE3 IAA31 JAZ10 TAF4B ARR15 AHL22 AHL19 AGL21 TGA10 ATXR6 MYB61 MYB47 MYB54 MYB63 bZIP48 NF-YB5 MYB92 MYB66 MYB68 NAC042 NAC058 NAC090 WRKY61 WRKY65 MYB102 WRKY62 WRKY30 WRKY27 AT1G14686 AT1G26680 AT1G33760 AT1G49900 AT1G53690 AT1G54840 AT1G62490 AT2G20080 AT2G34210 AT2G39240 AT2G43140 AT3G10470 AT3G12977 AT3G19184 AT3G22275 AT3G46080 AT4G12050 AT4G16610 AT4G17800 AT5G21960 AT5G43540 AT5G58280 Gene AT1G09540 AT1G13300 AT1G14686 AT1G17380 AT1G18710 AT1G18860 AT1G19510 AT1G26680 AT1G27720 AT1G29280 AT1G33760 AT1G49900 AT1G53690 AT1G54840 AT1G62490 AT1G67260 AT1G73410 AT1G74890 AT1G79180 AT2G04038 AT2G20080 AT2G21650 AT2G28160 AT2G28610 AT2G34210 AT2G34600 AT2G39240 AT2G43000 AT2G43140 AT2G45430 AT2G45650 AT2G47810 AT3G04570 AT3G10470 AT3G12977 AT3G17600 AT3G18400 AT3G19040 AT3G19184 AT3G22275 AT3G46080 AT3G49760 AT4G12050 AT4G16610 AT4G17800 AT4G18610 AT4G19000 AT4G21340 AT4G21440 AT4G25560 AT4G33880 AT4G35590 AT4G37940 AT5G01900 AT5G06839 AT5G07500 AT5G10280 AT5G13220 AT5G14750 AT5G21960 AT5G22380 AT5G24110 AT5G24330 AT5G42020 AT5G43540 AT5G52830 AT5G53950 AT5G58010 AT5G58280 AT5G65790 AT5G66700 AT5G66870

Table 4.3. DE transcription factors expressed in statistically signiAicant gene expression relative to EV plants (p<0.05).

In AnFAE plants, the DE genes associated with CW included upregulation of plant defensins 1.2, 1.2b, and 1.3 (AT5G44420, AT2G26020, AT2G26010) and two xyloglucan endotransglycosylases (AT4G25810, AT4G30280), and downregulation of 6 extensin genes (AT1G21310, AT1G12040, AT5G06640, AT2G24980,

AT5G35190, AT4G13390), 2 proline-rich proteins (AT3G62680, AT1G54970), 2 xyloglucan endotransglucosylases (AT4G28850, AT5G57540), and a feruloyl transferase (AT5G41040) (Table 1). DE genes related to stress response and defense included upregulation of the tryptophan-rich membrane protein

(AT2G47770) and CYP81D11 (AT3G28740), and downregulation of 3 cysteine-rich

RLKs (AT4G04490, AT4G23200, AT4G04500), WRKY62 and WRKY27 (AT5G01900,

AT5G52830), a respiratory burst oxidase homolog B (AT1G09090), and a mildew- resistance locus (AT2G44110) (Table 2). Among DE transcription factors, the ethylene-responsive factor (AT5G21960), bZIP48 (AT2G04038), MYB47 and

MYB102 (AT1G18710, AT4G21440), and three JAZ proteins, JAZ7, JAZ10, and JAZ5

(AT2G34600, AT5G13220, AT1G17380), were upregulated. Downregulated transcription factors included WRKY62, WRKY61, WRKY27, and WRKY65

(AT5G01900, AT1G18860, AT5G52830, AT1G29280), 3 NAC domain-containing proteins (AT2G43000, AT3G18400, AT5G22380), and 5 MYB domain proteins

(AT1G73410, AT5G65790, AT5G10280, AT1G79180, AT1G09540) (Table 3).

Mapping stress responses in plants

To assist in identifying responses to cell wall modifications in AnAXE, ANRAE and AnFAE, MapMan software was used to map gene expression associated with 87 stress (Fig. 2). Mapping gene expression in AnAXE revealed a large number of genes involved in signaling and proteolysis. In addition, upregulation of WRKY transcription factors, and downregulation of MYB transcription factors was observed in AnAXE plants. Noticeable gene expression changes in relation to plant hormone signaling were also observed, e.g. mixed expression in auxin signaling, and upregulation of ethylene signaling (Fig. 2A). Like AnAXE, the AnRAE plants also possessed a large number of genes involved in signaling and proteolysis, as well as cell wall metabolism. WRKY and MYB transcription factors showed similar expression patterns to those observed in the AnAXE plants. Hormone signaling, however, was different in AnRAE plants; auxin and ethylene signaling were largely downregulated (Fig. 2B). As expected, fewer similarities were found in the AnFAE plants in comparison with AnRAE and AnAXE. While signaling, proteolysis, and cell wall metabolism were also among the most highly enriched stress responses, the

AnFAE plants exhibited downregulation of MYB transcription factors, and increased expression of ethylene response factors (ERF). In addition, the AnFAE plants showed downregulation of peroxidases (Fig. 2C).

Analysis of all DE genes highlights the similarities between AnAXE and

AnRAE, as well as their differences with AnFAE. MapMan was also utilized to construct a heat map of DE genes (Fig. 2D). While the expression pattern of cell wall- related genes was similar between AnAXE and AnRAE plants, with only a small number of genes downregulated, a large number of cell wall-related genes were downregulated in the AnFAE plants. In addition, significant downregulation of genes involved in lipid metabolism was found in AnFAE plants. A larger number of 88 signaling-related genes were differentially expressed in AnFAE plants in comparison with AnAXE and AnRAE plants. Some variations were observed among all three lines in DE genes related to stress response, secondary metabolism, and hormone metabolism (Fig. 2D).

A D AnFAE AnAXE AnRAE U D U D U D Photosystems Major CHO metabolism Minor CHO metabolism Glycolysis Gluconeogenesis/glyoxylate cycle FermentaPon OPP

Cell wall

Fig. 3. Overview of gene expression and stress responses visualized by Lipid metabolism Mapman so

Tetrapyrrole synthesis

Stress Redox NucleoPde metabolism

Miscellaneous

RNA

DNA C Protein

Signaling

Cell Development

Transport

Not assigned Fig. 4.2. Overview of gene expression and stress responses visualized by Mapman software. A Stress response enrichment among DE genes in AnAXE plants. B. Stress response enrichment among DE genes in AnRAE plants. C. Stress response enrichment among DE genes in AnFAE plants. D. Hierarchical clustering heat map of all DE genes showing enrichments across all lines

(U=upregulated vs. EV; D=downregulated vs. EV). Scale bars display log2-fold change in transgenic lines relative to EV. 89

Confirmation of gene expression through RT-qPCR

Real-Time Quantitative PCR (RT-qPCR) was used to confirm RNA-seq results.

A set of separately grown transgenic plants was used for these analyses. Eight genes were selected for RT-qPCR, some of which were classified as DE genes, and some which were not differentially expressed (Fig. 3). Expression of MLO12 was confirmed to be downregulated in AnAXE and AnFAE. Upregulation of JAZ5 was observed in AnFAE, and CAD2 expression in AnFAE plants remained slightly upregulated relative to EV, whereas no change was detected in AnAXE or AnRAE.

Upregulation of WRKY40 was observed in AnAXE plants, and no change was detected in expression of ICS1 or CYP94C1. AnRAE plants also exhibited upregulation of MPK14, and downregulation of ACS2, ICS1, and CYP71A13 (Fig. 3). 90

8 AnAXE

4 RT-qPCR RNAseq 2

0 MLO12 JAZ5 CYP94C1 CAD2 ICS1 CYP81F2 WRKY40 TSPO Rela%ve Expression Level

8 AnRAE 6 4 RT-qPCR 2 0 RNAseq

Rela%ve Expression Level bG2 CAD2 ACS2 ICS1 TSPO MPK14 CYP83B1 CYP94C1 CYP724A1 CYP71A13 AnFAE 10 8 6 RT-qPCR 4 RNAseq 2 0

Rela%ve Expression Level -2 MLO12 JAZ5 CYP94C1 CYP724A1 CAD2 TSPO WRKY40 Fig. 4.3. Comparison of gene expression between RNAseq and RT-qPCR. A, gene expression analysis of AnAXE plants. B. Gene expression analysis of AnRAE plants. C. Gene expression analysis of AnFAE plants. FPKM fold change relative to EV was used for RNAseq, and 2-∆∆Cq values were used for RT-qPCR.

Metabolome analysis of transgenic plants

Untargeted metabolomic analysis was used to characterize the global metabolome changes in AnAXE, AnRAE, and AnFAE plants in comparison with the

EV plants. Total metabolites were extracted from the same plant tissues used for transcriptome analysis, and were analyzed using LC/MS. In total, 482 metabolites were detected; some of these accumulated in at least one mutant to levels significantly different from the EV plants. In AnAXE plants, 46 metabolites were upregulated and 18 were downregulated in comparison with EV. AnRAE plants 91 possessed 26 upregulated and 18 downregulated metabolites. In AnFAE plants, 26 metabolites were upregulated and 13 were downregulated (Fig. 4A). All detected metabolites and their abundance are presented in Supplementary Table 3. Only 41 metabolites were annotated using available databases out of 482 metabolites detected in this study.

Compared to the transcriptome analysis, in which most differentially accumulated transcripts were unique to a given transgenic line, a large number of metabolites were co-enriched between the transgenic lines. Among upregulated metabolites, 16 were unique to AnAXE, but 6 were shared with AnRAE and 4 with

AnFAE. AnRAE plants possessed no unique upregulated metabolites, and only 2 upregulated metabolites were unique to AnFAE. 20 common metabolites were upregulated in all three lines. Among downregulated metabolites, 4 metabolites were unique to AnAXE, and 9 were shared with AnRAE. AnRAE plants had 2 unique downregulated metabolites, and shared 2 metabolites with AnFAE. AnFAE plants showed 6 unique downregulated metabolites. 5 metabolites were downregulated in all three lines (Fig. 4B).

All detected metabolites were arranged in a heat map using a hierarchical clustering algorithm based on normalized metabolite quantity. The abundances of all four replicates per line were averaged, and are presented in Supp. Fig. 1.

Metabolites with high correlation (Pearson correlation coefficient > 0.90) within

AnAXE, AnRAE, and AnFAE were clustered and compared to the same metabolites in

EV control plants (Fig. 4C). Distinct differences between each transgenic line and EV can be observed, suggesting changes in pathways in response to CWI disruption. 92

A Upregulated Downregulated 50 20

40 15 30 10 20 5 10 Number of metabolites Number of metabolites 0 0 AnAXE vs. EV AnRAE vs. EV AnFAE vs. EV AnAXE vs. EV AnRAE vs. EV AnFAE vs. EV

Fig. 4. Abundance of metabolites in B AnAXE, AnRAE, and AnFAE plants rela;ve to EV. A. Number of up- and downregulated metabolite abundances. 16 6 0 4 9 2 B. Venn diagrams comparing overlap of signiﬁcantly diﬀerent metabolites in each 20 5 transgenic line. C. Hierarchical clustering 4 0 0 2 heat map of highly correlated metabolites compared to EV controls. 2 Hierarchical Entity Tree on genotype (Non-averaged) Report 6 Experiment : New Experiment Active entity list : Fold change Hierarchical>= 2.0 Entity Tree on genotype (Non-averaged) Report

Experiment : New Experiment Active entity list : Fold change >= 2.0

AnAXE

AnFAE

AnRAE

Fig. 4.4. Abundance of metabolites in Condition dataset colors ConditionAnAXE, AnRAE, and AnFAE plants relative to EV. A. [AnAXE] [AnFAE] [AnRAE] [Col-0] [EV]

Number of up- and downregulatedCondition dataset colors genotype metabolite abundances. B. Venn diagrams comparing overlap of signiAicantly different metabolites in each transgenic line. C. Hierarchical clustering AnAXE AnFAE AnRAE Col-0 EV Description Created from Advanced Analysis operation: Clustering: Entity List: Fold change >= 2.0 heat map of highly correlated metabolites compared to EV controls. Interpretation: genotype (Non-averaged) Experiment: New Experiment Clustering Algorithm: Hierarchical Clustered By: Normalized intensity values Clustered On: Entities Similarity Measure: Euclidean Linkage Rule: Complete Correlation of transcriptome with metabolome increased sensitivity of analysis

To further increase the predictive power of the analyses, transcript abundance was correlated with metabolite abundance. To perform this correlation, the transcriptome and metabolome datasets were uploaded to the Plant/eukaryotic 93 and Microbial systems Resource (PMR; http://metnetdb.org/pmr)(Hur et al., 2013).

As described in the methods, the software correlated all transcripts with metabolite abundance. Genes exceeding the cutoff (Pearson correlation greater than 0.90) with each metabolite, and their associated pathways, were pooled together to provide a quantitative analysis of the pathways most perturbed in response to CW modification. The most highly enriched pathways (those associated with the highest number of metabolites) for each transgenic line are shown in Table 4. All co-analysis results, including pathways associated with fewer metabolites, are presented in

Supplementary Table 4.

The AnAXE plants displayed enrichments in several primary metabolism pathways that are known to provide substrate for specialized metabolism associated with glucosinolates and camalexin. These pathways include adenosine nucleotides de novo biosynthesis (9 genes upregulated), and methionine salvage

(two genes upregulated). The superpathway of phenylalanine, tyrosine, and tryptophan biosynthesis was also enriched (8 genes were upregulated and 3 genes were downregulated). One specialized metabolic pathway, glucosinolate biosynthesis from homomethionine was notably enriched (upregulation of 2 genes)

(Table 4).

The AnRAE plants, like the AnAXE plants, showed enrichment in primary metabolism pathways of adenosine nucleotides biosynthesis (8 genes upregulated, 2 genes downregulated), phenylalanine, tyrosine, and tryptophan biosynthesis (9 genes upregulated), and glucosinolate biosynthesis from homomethionine (2 genes upregulated). Distinct from the AnAXE plants, the S-adenosyl-methionine 94 biosynthetic pathway was significantly downregulated in AnRAE plants (11 genes); also, 13 genes involved in ethylene biosynthesis were downregulated in AnRAE

(Table 4). Like in AnAXE, 2 genes in the specialized metabolic pathway glucosinolate biosynthesis from homomethionine were upregulated.

The AnFAE plants also showed enriched primary metabolism, where adenosine nucleotide biosynthesis was upregulated (8 genes). In contrast to both

AnAXE and AnRAE, only one gene was upregulated involved in methionine salvage.

AnFAE plants showed enrichment in downregulation of lipid biosynthesis pathways: triacylglycerol biosynthesis, wax esters biosynthesis, CDP-diacylglycerol biosynthesis, and phospholipid biosynthesis were all downregulated. In addition, the ABA biosynthesis pathway (3 genes) and peroxidase/redox activity (15 genes) were shown to be downregulated in the AnFAE plants using enrichment analysis

(Table 4). 95 with 9 4 7 7 1 5 6 3 3 4 4 3 6 15 Genes Number of Downregulated 8 3 8 6 9 1 2 1 15 10 10 Genes transcriptome Number of Upregulated AnFAE plants) biosynthesis biosynthesis biosynthesis (ester formation) oxidase pathway) dephosphorylation Enriched Pathways peroxidase activity camalexin biosynthesis phosphate degradation oxygenic photosynthesis cytokinins 7-N-glucoside cytokinins 9-N-glucoside wax esters biosynthesis I abscisic acid biosynthesis triacylglycerol degradation triacylglycerol biosynthesis phospholipid biosynthesis II S-methyl-5-thio-α-D-ribose 1- photosynthesis light reactions adenosine nucleotides de novo aerobic respiration (alternative volatile benzenoid biosynthesis I NAD/NADH phosphorylation and pyruvate fermentation to lactate CDP-diacylglycerol biosynthesis I CDP-diacylglycerol biosynthesis II aerobic respiration (cytochrome c) methionine salvage I (bacteria and 1 2 5 4 1 1 7 8 9 1 1 1 1 13 10 10 11 13 11 12 Genes Number of Downregulated 8 9 3 1 7 8 9 2 1 1 1 1 2 2 7 16 10 13 Genes Number of Upregulated AnRAE dependent) biosynthesis biosynthesis biosynthesis (eukaryotic) tRNA charging homocysteine) (ester formation) oxidase pathway) homomethionine aminopelargonate dephosphorylation Enriched Pathways cysteine biosynthesis I camalexin biosynthesis cytokinins degradation phosphate degradation oxygenic photosynthesis ubiquinol-9 biosynthesis tryptophan biosynthesis tyrosine and tryptophan S-adenosyl-L-methionine cardiolipin biosynthesis II methenyltetrahydrofolate triacylglycerol degradation methionine degradation I (to S-methyl-5-thio-α-D-ribose 1- photosynthesis light reactions adenosine nucleotides de novo aerobic respiration (alternative seleno-amino acid biosynthesis ethylene biosynthesis I (plants) glucosinolate biosynthesis from 3-dehydroquinate biosynthesis I superpathway of phenylalanine, volatile benzenoid biosynthesis I S-adenosyl-L-methionine cycle II NAD/NADH phosphorylation and L-glutamine biosynthesis II (tRNA- biotin biosynthesis from 7-keto-8- aerobic respiration (cytochrome c) tetrahydrofolate salvage from 5,10- 9 7 7 5 4 5 5 4 3 20 Genes Number of Downregulated 9 9 3 3 2 2 3 8 3 2 17 12 17 11 10 Genes Number of Upregulated AnAXE datasets, with a correlation cutoff of r>0.90. plants) biosynthesis biosynthesis biosynthesis biosynthesis Rubisco shunt (ester formation) oxidase pathway) homomethionine dephosphorylation Enriched Pathways betanidin degradation camalexin biosynthesis phosphate degradation oxygenic photosynthesis cytokinins 7-N-glucoside cytokinins 9-N-glucoside tyrosine and tryptophan triacylglycerol degradation ascorbate glutathione cycle S-methyl-5-thio-α-D-ribose 1- photosynthesis light reactions adenosine nucleotides de novo aerobic respiration (alternative glucosinolate biosynthesis from volatile benzenoid biosynthesis I superpathway of phenylalanine, NAD/NADH phosphorylation and Table 4.4. The most highly enriched pathways of each transgenic line after correlation of metabolome aerobic respiration (cytochrome c) methionine salvage I (bacteria and

DISCUSSION

Transcriptome analysis reveals potential signaling components involved in defense responses and compensatory mechanisms

Previously, we have shown that Arabidopsis plants expressing AnAXE,

AnRAE, and AnFAE CWDEs exhibit changes in gene expression and defense response to pathogens. AnRAE and AnAXE plants have less cell wall acetylation and higher resistance to the fungal necrotroph B. cinerea in comparison with wild type plants (Pogorelko et al., 2013), whereas AnFAE plants have less cell wall feruloylation and show higher susceptibility to B. cinerea (Reem et al., 2016). We proposed that these changes in defense response are likely triggered by changes in cell wall integrity caused by the introduced CWDEs. Here, we combine transcriptome and metabolome analysis to reveal candidate signaling components in the plant response to specific cell wall modifications.

Transcriptome analysis demonstrated that each specific modification of the plant cell wall induces a relatively small but distinct set of genes, and that there is also a small common set of perturbed genes associated with each modification. DE genes have diverse metabolic functions, such as cell wall-related genes, stress response genes, and transcription factors, but many of these genes are involved in common pathways. AnAXE and AnRAE plants differentially expressed 19 cell wall- related genes, six of which were common to both lines. AnFAE plants differentially expressed 57 cell wall-related genes. Of genes involved in stress response, AnAXE had 25 DE genes, AnRAE had 17, and AnFAE possessed 74 DE genes. 22

97 transcription factors were differentially expressed in the AnAXE plants, 30 were differentially expressed in AnRAE, and 55 in AnFAE plants.

The AnAXE plants exhibited differential expression in some known stress- related genes, including the MYB102 transcription factor, two glycosyl hydrolases, downy mildew resistance locus, two WRKY transcription factors, and an ethylene response factor. MYB102 has been shown to be involved in both wounding and osmotic stresses, in particular during insect herbivory (Denekamp & Smeekens,

2003; De Vos et al., 2006). The upregulation in AnAXE plants of two glycosyl hydrolases, GH9C3 and CEL3, and downregulation of a xyloglucan endotransglucosylase XTH26 could reflect a wall remodeling event in response to deacetylation of hemicelluloses. The transmembrane protein MLO12, which is downregulated in AnAXE plants, is important for resistance to fungus via interaction with tryptophan-derived metabolites (Consonni et al., 2010). The expression of chitinase A, a gene which is induced specifically under wounding and salt stress

(TAKENAKA et al., 2009), was also upregulated in AnAXE, suggesting it plays a role in the enhanced disease resistance seen in these plants (Pogorelko et al., 2013).

Both the AnAXE and AnRAE line have upregulated PDF1.2b and PDF1.4, important defensins often upregulated during pathogenesis (Penninckx et al., 1998;

Thomma et al., 2002). TSPO, a tryptophan-rich membrane protein, and bZIP48 and

NAC090, two transcription factors, are also upregulated in both lines. Since both lines have reduced cell wall acetylation and increased resistance to B. cinerea, it is plausible that these genes are some of the key players in the defense responses induced in these plants by the cell wall modification. However, more analysis on 98 these genes must be done in the future to determine their role in defense response of AnAXE and AnRAE plants. The downregulation of transcription factors bZIP5,

MYB54, and MYB61 in AnRAE plants, but not in AnAXE plants, could reflect the subtle differences (Pogorelko et al., 2013) in defense responses between AnAXE and

AnRAE plants.

The AnFAE plants displayed very different gene expression patterns relative to AnAXE and AnRAE plants. This is not surprising since the AnFAE plants, in contrast with AnAXE/AnRAE, have compromised resistance to B. cinerea (Reem et al., 2016). However, some defense response are upregulated in AnFAE plants, indicating that the plants may compensate for the weakness of their cell walls associated with the reduction in cross-linking via ferulate (Reem et al., 2016). For example, the fungal defense response genes PDF1.2, 1.2B, and 1.3 (Thomma et al.,

2002; Pré et al., 2008) are upregulated in the AnFAE plants. The upregulation of JAZ genes in the AnFAE plants suggests an inhibition of JA response, consistent with the higher susceptibility of these plants to fungal necrotrophs.

Members of a large family of transcription factors, WRKY62, WRKY61,

WRKY26, and WRKY65 were all downregulated in the AnFAE plants. WRKY62 has been shown to interact with WRKY38 and histone deacetylase 19 in Arabidopsis, working as a transcriptional regulator of defense response (Kim et al., 2008). Since

WRKY transcription factors are involved in a variety of defense responses, it is possible that the downregulation of these genes reflects the compromised defense response seen in the AnFAE plants (Reem et al., 2016).

The downregulation of extensin and extensin-like genes in AnFAE (but not in

AnAXE or AnRAE) suggests a plant response associated with the reduced level of wall-bound ferulate, which has been hypothesized to interact with extensin proteins

(Qi et al., 1995; Reem et al., 2016). Downregulation of the feruloyl transferase

RWP1 (Gou et al., 2009; Molina et al., 2009) in the AnFAE plants is perhaps also associated with the reduction of wall feruloylation in this line.

Correlation of the transcriptome and metabolome datasets increases the power of the pathway prediction and shows enrichment of primary metabolism serving secondary metabolism

While RNA-seq alone is a powerful tool, we find that correlation of RNA-seq with metabolome datasets leads to increased sensitivity of DE gene selection and allows identification of genes that would not normally be considered significant through transcriptomics alone. Most of the differentially accumulated metabolic peaks in the three transgenic lines could not be assigned as specific compounds, due to the highly complex nature of metabolite identification. Clustering analysis of metabolites alone revealed several groups of metabolites correlated with each other. Each transgenic line displayed correlation of unique sets of up- and downregulated metabolites relative to EV, as well as some metabolites with altered accumulation that are common to all three transgenic lines (Fig. 4C). These results suggest that the correlated metabolites may be involved in CWI response pathways.

Despite the anonymity of many of the correlated metabolites, correlation of transcriptome with the metabolome datasets enabled us to reveal the most highly 100 enriched pathways up- or downregulated in each transgenic line. These co-analyses indicate that several pathways are consistently enriched in each transgenic line.

Notably, co-analyses revealed a substantial number of primary metabolic pathways, illustrating the significant shifts in cell metabolism associated with defense responses.

Correlation analysis reveals partially overlapping responses of the AnAXE and

AnRAE plants exhibiting decreased susceptibility to B. cinerea

The analyses of the AnAXE and AnRAE transcriptome and metabolome revealed similar patterns. Both exhibited upregulation in metabolites and genes of adenosine nucleotides de novo biosynthesis, glucosinolate biosynthesis, and aromatic amino acids biosynthesis.

Adenosine nucleotides biosynthesis is an important pathway for ATP production. Aromatic amino acids such as phenylalanine, tyrosine, and tryptophan are essential precursors of cell wall components and serve as substrates for the defense response compounds, the aromatic and indole glucosinolates and camalexin

(Grubb & Abel, 2006). Aliphatic glucosinolates are important defense metabolites derived directly from methionine (Field et al., 2004), and the methionine salvage pathway is also upregulated in AnAXE plants, while methionine degradation is downregulated in AnRAE plants. Upregulation of synthesis of adenosine nucleotides, aromatic amino acids, and glucosinolates suggests that the AnAXE and

AnRAE plants have increased production of ATP, which could serve as cofactor for the catalytic reactions including increased glucosinolate biosynthesis during 101 defense responses, and conversion of tryptophan to camalexin. The enrichment of these pathways illustrates the high demand that defense responses places on primary metabolism.

The AnAXE plants exhibited upregulation of genes in the methionine biosynthesis pathway, whereas AnRAE plants showed downregulation of genes involved in SAM and ethylene biosynthesis. Because SAM is a common one-carbon donor involved in many biochemical reactions, the significance of this finding is not clear. SAM is required for biosynthesis of the methyl jasmonate, and is a precursor for ethylene production (Fa Yang & Hoffman, 1984). Reduced expression of SAM biosynthetic genes in the AnRAE plants could affect the types and levels of defense metabolites formed in the cells. Additionally, the defense signaling induced by increased AnRAE expression might be modified by reduction of ethylene biosynthesis. In the AnAXE plants, an upregulation of genes in the methionine biosynthesis pathway (and no changes in SAM biosynthesis) indicates a more balanced ratio of SAM-dependent—SAM-independent metabolites. However, more experiments are necessary to confirm this hypothesis.

Correlation analysis provides insight into cell wall remodeling in the AnFAE plants as a result of reduced feruloylation

Correlation of metabolite abundance with gene expression in the AnFAE plants uncovered downregulation of 16 peroxidase enzymes related to lignin biosynthesis and of several extensin biosynthesis related genes. Usually, plants fortify their cell walls by accumulating wall-bound lignin and extensins in response 102 to pathogen invasions (Mikulic Petkovšek et al., 2008; Lamport et al., 2011). It was shown earlier that the AnFAE plants have significantly reduced content of loosely associated HF-soluble extensin, though no significant reduction of total extensin was observed (Reem et al., 2016). The reduction of soluble, non-cross-linked extensin shown in the AnFAE plants correlates with the downregulation of some extensin related genes observed in this study. Although we did not observe significant changes in total lignin content in AnFAE plants (Supp. Fig. 2), reduction of peroxidases might affect lignin degree of polymerization, thus weakening cell walls and decreasing resistance to fungal penetration in the AnFAE plants.

The correlation analysis also revealed downregulation of genes belonging to several pathways involved in fatty acid biosynthesis in the AnFAE plants. Among those are Wax esters biosynthesis I, CDP-diacylglycerol biosynthesis I & II, phosphatidylglycerol biosynthesis I & II, triacylglycerol biosynthesis, and phospholipid biosynthesis II. It has been shown that ferulic acid is covalently bound to cutin and suberin waxes in Arabidopsis and other species (Gou et al., 2009;

Molina et al., 2009). Downregulation of the wax ester biosynthesis pathway shown in AnFAE suggests possible feedback regulation and sensing of extracellular ferulic acid. In this case, an extracellular sensor might sense ferulate-lacking portions of cutin and downregulate biosynthesis of new cuticle until more ferulic acid can bind.

Lipids are also known to serve as signaling molecules, or precursors of signaling molecules. Perhaps the most well-known example, jasmonic acid, is derived from galactolipids which have been converted into alpha-linolenic acid

(Wasternack, 2007). Studies of fatty acid levels in the arbuscular-mycorrhizal fungi 103

Glomus intraradices and Gigaspora rosea have shown these fungi depend on host production of palmitic acid for fungal fatty acid elongation to occur (Trépanier et al.,

2005). Other studies have shown that an increase in 16:1 fatty acid in eggplant increased resistance to Verticillium dahlia (Xing & Chin, 2000). The downregulation of lipid biosynthesis observed in the AnFAE plants might be a mechanism intended to prevent specific fungal species from benefiting from plant fatty acids.

CONCLUSIONS

The combined transcriptome and metabolome analysis in plants altered in cell wall acetyl and feruloyl content has provided insight into the CWI control mechanism of Arabidopsis. Our data indicates that through the direct sensing of changes in cell wall components, plants are able to initiate compensatory responses.

Plants expressing AnAXE and AnRAE, both of which have reduced cell wall acetylation (Pogorelko et al., 2013), initiate partially overlapping defense responses.

AnFAE plants, which have decreased cell wall feruloylation (Reem et al., 2016), show distinct changes in defense responses. We have uncovered sets of transcription factors, wall-related genes, and stress response genes that are likely candidates in plant response to each cell wall alteration. Additionally, we observed the demand that secondary metabolism exerts on primary metabolism in order to produce metabolites associated with defense response. These results illustrate the complexity of CWI signaling and the robustness of extracellular sensing mechanisms in plants.

104

The results obtained in this study point to a potential utility of the post- synthetic modification of cell wall properties in elucidating key genes/pathways in cell wall integrity signaling induced in response to these modifications. Hydrolytic enzymes are the key components involved in cell wall remodeling, the main mechanism of cell wall adjustments during plant development and response to environmental cues. Therefore, employment of such enzymes with well characterized specificities, overexpression of which in the plant apoplast causes particular modifications in polysaccharide structures or their cross-linking, represents a promising approach for studying plant responses to these modifications. These modifications, mimicking the action of pathogen CWDEs, initiate responsive pathways potentially involved in CWI signaling during pathogenesis, and thus, impact plant resistance to biotic stresses. Therefore, action of CWDEs expressed in the plant apoplast can assist in dissecting the pathways usually initiated in response to complex cell wall modifications caused by the mixture of CWDEs secreted all together during pathogenesis. These results demonstrate that the correlation analysis of global transcriptome and metabolome data increases the power of the predictions in investigation and uncovering novel components involved in signaling induced by cell wall integrity alterations in response to environmental stresses.

ACKNOWLEDGMENTS

This research was partially supported by the NSF-MCB (#1121163 to OAZ) and

USDA-NIFA (#015227-00005 to OAZ). The authors thank Zebulun Arendsee (Iowa 105

State University) for his assistance in bioinformatics analysis.

AUTHOR CONTRIBUTIONS

NTR conducted all analyses of transcriptome and metabolome datasets, and wrote the paper. OZ and LL designed the experiments and wrote the paper. XZ cleaned and mapped reads, and applied statistical analysis to transcriptome data. HC and XL conducted metabolite analysis. MH and ESW maintained the PMR database and statistical analyses and contributed to the paper.

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CHAPTER 5

TRANSGENIC ARABIDOPSIS THALIANA PLANTS EXPRESSING FUNGAL PECTIN

METHYLESTERASE EXHIBIT DWARFED PHENOTYPE AND ALTERATIONS IN

STRESS RESPONSE

Nathan T. Reem, Lauran Chambers, Siti Farah Abdullah, Song Gao, Junmarie Soto-

Burgos, Marena Henkle, Gennady Pogorelko, Diane Bassham, Thomas Baum, Justin

Walley, Olga Zabotina

ABSTRACT

The plant cell wall is a complex matrix of polysaccharides, which is involved in controlling cell growth and protecting the cell against environmental stresses. Pectic homogalacturonan (HG) is one of the main constituents of plant cell walls. When de- esterified, HG can form complexes with divalent calcium ions and limit cell wall expansibility. These structures play an important role in determining cell wall biomechanics and in mediating cell-to-cell adhesion. Degree of HG methylesterification is controlled by endogenous pectin methylesterases (PME) or can be altered by action of microbial PME secreted during pathogenesis. Here, we show an Aspergillus nidulans pectin methylesterase (AnPME) expressed in the

Arabidopsis thaliana apoplast alters plant cell wall composition and suppresses cell growth, resulting in a dwarf phenotype. The AnPME plants were insensitive to salt stress, less susceptible to cyst nematode infection, but more susceptible to Botrytis cinerea. The results shown in this study demonstrates the critical importance of 117 pectin methylesterification to cell wall integrity that impacts plant growth and protection against stresses.

INTRODUCTION

The plant cell wall is an important, complex component of all plant cells, and changes in the wall structure can affect a plant’s fitness and defense responses. The cell wall is composed primarily of polysaccharides, as well as lignin, proteins, and ions that associate with or bind to the polysaccharides. The polysaccharides of the cell wall make up the bulk of its dry weight and are divided into three categories: cellulose, hemicelluloses, and pectins. Pectins constitute 20-35% of the primary cell wall, and also reside in the middle lamellae between cells. Pectins are heteropolymers of three distinct polysaccharides, all containing galacturonic acid: homogalacturonan (HG), rhamnogalacturonan I (RG-I), and rhamnogalacturonan II

(RG-II) (Caffall & Mohnen, 2009). HG, the most abundant pectic polysaccharide, is composed entirely of unbranched α-1,4-galacturonic acid (GalA) residues that can be methylesterified on the C6 carbon. HG is synthesized in the golgi stacks and delivered to the cell surface as a highly methylesterified polysaccharide, and as plant tissue ages, it is de-esterified to pectate by endogenous pectin methylesterases

(PMEs) localized in the apoplast (Micheli, 2001). RG-I is composed of alternating α-

1,4- and α-1,2-linked GalA and Rhamose (Rha) residues with varying sidechains on

Rha C4 carbons (Caffall & Mohnen, 2009). RG-II possesses an α-1,4-GalA backbone is the least abundant and most structurally complex pectin, thanks to its elaborate sidechain structures (Pellerin et al., 1996; Ndeh et al., 2017). These three pectic 118 polysaccharides exist as a continuous heteropolymer in muro with long stretches of

HG interspersed with shorter stretches of RG-I and RG-II (Wolf et al., 2012).

Pectin plays an important role in plant and organ morphology. Numerous studies have shown the morphological effects of defective pectin in plants. For example, it has been demonstrated that pectin is critical for cell-cell adhesion and cell wall degradability (Lionetti et al., 2010; Raiola et al., 2011). Arabidopsis plants defective in two GalA biosynthetic enzymes (GAE1 and GAE6) had lower levels of total pectin, more brittle leaves, and higher susceptibility to Botrytis cinerea in comparison with wild type plants (WT) (Bethke et al., 2016). Overexpression of a seed-specific pectin methylesterase (PME) in Arabidopsis resulted in altered embryo morphology as well as decreased cell size (Levesque-Tremblay et al., 2015).

Arabidopsis plants constitutively overexpressing an endogenous pectin methylesterase inhibitor (AtPMEI) showed increased seed methylesterification, faster germination rates, and an unusual growth phenotype: stunted growth and thick, twisted stems, particularly at points where cauline leaves or flowers would normally separate from the main stem (Müller et al., 2013b,a). Overexpression of

Arabidopsis PMEI1 and PMEI2 showed decreased cell adhesion and increased efficiency of protoplast isolation due to decreased wall recalcitrance to enzyme degradation (Lionetti et al., 2015).

PMEs are a large family of enzymes present in plants, fungi, and bacteria. All belong to the carbohydrate esterase class CE-8 as defined by CAZy (EC 3.1.1.11, ww.cazy.org; Markovič & Janeček, 2004). The Arabidopsis PME (AtPME) gene family is classified into subfamilies I and II, which are composed of 23 and 43 genes, 119 respectively (Wang et al., 2013b). The AtPME mode of action on HG is dependent on apoplast pH, but under normal apoplast conditions it most often results in blockwise de-esterification of consecutive GalA residues; 9 or more consecutive demethylated GalA residues allows for ionic Ca2+-mediated crosslinks between HG chains that rigidify the cell wall (Catoire et al., 1998; Denès et al., 2000; Lionetti et al., 2010). Fungal PMEs are also dependent on apoplast pH, but in contrast to

AtPMEs, they generally de-esterify HG in isolated, non-blockwise fashion (Limberg et al., 2000; Duvetter et al., 2006). This mode of action does not usually result in

Ca2+-mediated crosslinks; instead, fungal PMEs enhance the efficiency of polygalacturonases and pectate lyases and increase wall digestibility to facilitate pathogenesis (Micheli, 2001; Kars et al., 2005).

To regulate PME activity, the Arabidopsis genome contains 71 AtPMEIs

(Wang et al., 2013b). While the exact function of all AtPMEs and AtPMEIs is not known, PMEs and PMEIs are known to counteract each other and play important roles in plant growth & development and resistance to pathogens (Bellincampi et al.,

2014). AtPMEIs inhibit plant PMEs; most do not inhibit fungal PMEs due to their structure (Giovane et al., 2004; Di Matteo et al., 2005). However, recently it has been demonstrated that several AtPMEIs are critical for cell wall integrity (CWI) during pathogenesis; AtPMEI10, AtPMEI11, AtPMEI12 are induced during B. cinerea infection, and knockout mutants displayed increased susceptibility (Lionetti et al.,

2017).

Cell wall integrity (CWI) is the sensing of changes in the cell wall compartment through membrane-bound sensors and the subsequent responses 120 involved to compensate for these changes. This typically involves a growth-defense tradeoff controlled through cell signaling apparatuses. More specifically, hormone crosstalk is responsible for much of the growth-defense tradeoff (Huot et al., 2014).

For example, Pathogen-Associate Molecular Pattern (PAMP)-Triggered Immunity

(PTI) through the plasma membrane co-receptor complex FLS2 and BAK1 binding bacterial flagellin induces expression of the microRNA mir393, which represses auxin gene expression (Jones-Rhoades & Bartel, 2004; Sunkar & Zhu, 2004; Navarro et al., 2006). FLS2/BAK1 PTI also promotes ROS production, but overexpression of the brassinosteroid response protein BZR1 suppresses ROS (Lozano-Durán et al.,

2013). Jasmonic acid, a defense compound produced in plants in response to necrotrophic pathogenesis or insect herbivory, suppresses the auxin efflux transporter PIN2 (Sun et al., 2011), but can also be suppressed by brassinosteroid presence (Wasternack & Hause, 2013). Wall-Associated Kinase (WAK) sensors of pectin integrity also control the growth-defense tradeoff: under normal conditions,

WAKs bind pectin and signal for cell expansion through MAP Kinase 3 (MPK3)

(Kohorn et al., 2006, 2012). However, upon stress, WAKs signal through MPK6 and perhaps MPK8 to upregulate defense response (Kohorn et al., 2012; Kohorn, 2016).

This complicated tradeoff between growth and defense is still being determined, but it is clear that plants must carefully regulate growth and defense pathways for optimal fitness.

Pathogens must contend with the plant cell wall before successfully colonizing the plant. To do so, both biotrophic and necrotrophic pathogens secrete cell wall degrading enzymes (CWDEs) to macerate the wall matrix and gain access 121 to the cytoplasm (Kubicek et al., 2014). Pectin-degrading enzymes are among the first CWDEs secreted by pathogenic fungi (Colimer & Keen, 1986) and polygalacturonases, rhamnogalacturonan hydrolases, pectin lyases, and pectate lyases are present in their genomes (de Vries et al., 2001; Lara-Márquez et al., 2011; van den Brink & de Vries, 2011). Numerous studies have demonstrated that CWDE expression is induced in fungi during pathogenesis, and correlated with their virulence (Espino et al., 2005; Brito et al., 2006; Kema et al., 2008; Fernández-Acero et al., 2010). Thus, polygalacturonases and pectin methylesterases have been shown to be critical for pathogenesis (Ten Have et al., 1998; Valette-Collet et al., 2003).

Plant-parasitic nematodes also utilize CWDEs when forming syncytial feeding sites.

For example, cellulases, hemicellulases, and pectin hydrolases have all been identified in cyst-forming nematodes (Smant et al., 1998; De Meutter et al., 2001;

Gao et al., 2002, 2004; Vanholme et al., 2007). It has also been shown that nematodes secrete cellulose-binding proteins (CBP), one of which interacts with

Arabidopsis PME3 to facilitate syncytia formation (Hewezi et al., 2008).

Pectin and its degradation byproducts are important in CWI because they can be sensed by membrane-bound pattern-recognition receptors (PRRs) as Damage-

Associated Molecular Patterns (DAMPs) that induce defense response. As HG is fragmented during pathogenesis, oligogalacturonides (OGs) of various lengths are released into the apoplast and trigger defense responses (Hahn et al., 1981;

Nothnagel et al., 1983)). OGs are sensed by members of the WAK family, which initiate defense signaling through a different set of MAPKs than those involved in normal growth and development. Under normal unstressed conditions, WAKs bind 122 pectin and activate MPK3 to initiate cell elongation (Wagner & Kohorn, 2001;

Kohorn et al., 2006). After wall maceration WAKs bind OGs, activating MPK6 and possibly MPK8 to initiate defense response (Kohorn et al., 2014). Additionally, it has also been suggested that volatilized methanol released by pectin methylesterase has bioactivity and initiates defense response (Hann et al., 2014; Komarova et al., 2014).

This study explores the role of pectin methylesterification in CWI and impact of cell wall de-esterification on plant growth and stress response. Aspergillus nidulans pectin methylesterase (AnPME) was constitutively expressed in the apoplast of Arabidopsis thaliana plants. The transgenic plants showed a severe dwarf phenotype, reduced rate of growth, decreased cell size, and cell wall compositional changes. In addition, the AnPME plants lacked sensitivity to high concentration of NaCl, showed higher resistance to the biotrophic cyst-forming nematode Heterodera schachtii, but had higher susceptibility to the fungal necrotroph B. cinerea.

MATERIALS AND METHODS

Transgene construct cDNA from A. nidulans AnPME (AN3390) was amplified from Pichia pastoris recombinant strains (Bauer et al., 2006) from the Fungal Genetics Stock Center

(http://www.fgsc.net). The sequence was amplified by PCR with primers AnPME-F and AnPME-R containing restriction sites KpnI and HindIII, respectively. After restriction digest, the AnPME fragment was ligated into a cassette containing, from

5’ to 3’, sequences encoding: an Arabidopsis thaliana β-expansin signal peptide, 123

AnPME, and a green fluorescent marker (smGFP), fused to the C-terminus of AnPME.

This expression cassette was ligated into a pMLBart binary vector backbone, as described in Fursova et al. (2012). Agrobacterium tumefaciens-mediated floral dip transformation was performed, and the resulting seed was selected to a homozygous T3 generation using Basta herbicide (Clough & Bent, 1998).

Plant materials & growth conditions

Arabidopsis seeds were sterilized with sequential treatments of 70% ethanol and 0.5% bleach, washed multiple times with sterile water and planted on 1 /2 - strength Murashige and Skoog medium (Murashige & Skoog, 1962) with 2% sucrose and 0.3% Gelrite (Research Products International, Mt. Prospect, IL, USA) until two weeks of age. Plants were then transplanted into wet LC-1 potting soil mix (Sun Gro

Horticulture, Agawam, MA, USA) in a growth chamber with controlled conditions:

12-h light/ 12-h dark at 21 °C, with relative humidity of 65% and light intensity of

160 µmol s−1 m−2.

For B. cinerea inoculations, Arabidopsis seedlings were grown on plates in the same growth chamber as above, but transplanted to Murashige and Skoog medium with

0% sucrose after two weeks on 2% sucrose medium.

Cell wall extraction

Cell walls were isolated from plants grown on soil as described in Zabotina et al.

(2008). Whole aerial parts of plants were harvested and cut into 1-cm length segments. Tissue was frozen in liquid N2 and ground into a fine powder with a 124 mortar and pestle. After homogenization, tissues were incubated in 80% ethanol at

80 °C two times for 1 h, and further homogenized with a PolyTron (Kinematica, Inc.,

Bohemia, NY, USA) at 15,000 rpm for 5 min. The pellet was collected by centrifugation at 12,000 g and washed with 80% ethanol followed by several washes with 100% acetone until supernatant turned clear. The pellet was incubated in a solution of 20% SDS with 5 mM sodium metabisulfite at 4 °C for 16 h and washed five times with distilled water. Finally, the pellet was incubated in 1:1 chloroform:methanol solution at room temperature for 20 min, washed three times with 100% acetone, and air-dried at 50 °C.

Cell wall saccharification assays

For the digestion of pectins, 5 mg of dry cell wall material was incubated with a mixture of 50 units of endo-polygalacturonase (Megazyme International,Wicklow,

Ireland) and 15 units of PME (PROZOMIX LTD, Haltwhistle, UK) in a 0.3-mL total volume of sodium phosphate buffer (pH 6.0) for 24 h at 37 °C. Saccharification assays were performed as described in Pogorelko et al. (2011) with some modifications. Cell walls of 4-week old plants (5 mg of fresh tissue) were incubated in 0.1 ml of citrate buffer (pH 4.9) containing 4 units of cellulase (from Trichoderma reesei, Sigma–Aldrich, C62730) and 1 unit of cellobiase (from A. niger, Sigma–

Aldrich, C6105) on the shaker at 37 °C. The reaction was terminated by heating at

100 °C for 15 min, supernatants were collected by centrifugation at 10,000 g, and the amount of reducing sugars released was analyzed by p-hydroxybenzoic acid hydrazide (PAHBAH) assay. 125

PAHBAH assay of reducing sugars

Reducing sugars were measured using the PAHBAH assay (Lever, 1972) with minor modifications. Briefly, 15 µL of supernatant from each enzyme assay was mixed with 135 mL of freshly prepared PAHBAH reagent (1 volume of 5% p- hydroxybenzoic acid hydrazide in 5% HCl mixed with 9 volumes of 1.25% trisodium citrate, 0.11% calcium chloride, and 2% sodium hydroxide) and heated at 95 °C for exactly 6 min. Absorbance was measured at 410 nm using a microplate reader

(BioTek Instruments, Inc., Winooski, VT, USA). Calculations were done using a standard curve prepared using different concentrations of Glc.

Cell wall monosaccharide analysis

To determine monosaccharide composition, 1 mg of dry, de-starched cell wall was hydrolyzed with 2 N trifluoroacetic acid at 120 °C for 2 h. The hydrolysates were dried at 50 °C, re-dissolved in water, and analyzed by high-performance anion- exchange chromatography with pulsed-amperometric detection using a CarboPac

PA-20 column (3 mm× 150 mm; Dionex, Sunnyvale, CA, USA) as described earlier

(Zabotina et al., 2008). Monosaccharides were separated using a gradient of 100 mM

NaOH in water at 0.5 mL min−1 under following conditions: 0–0.05 min—12 mM

NaOH; 0.05–26 min—0.65 mM NaOH; 26–46 min—300 mM NaOH; 46–55 min—12 mM NaOH. Monosaccharide standards included L-Fuc, L-Rha, L-Ara, D-Gal, D-Glc, D-

Xyl, D Man, D-GalA, and D-GlcA (all from Sigma–Aldrich, St. Louis, MO, USA). To determine response factors, standard curves were created using mixtures of all 126 standard monosaccharides at different concentrations. Reducing sugars were measured using the PAHBAH assay (Lever, 1972) with minor modifications. Briefly,

15 µL of supernatant was mixed with 135 mL of freshly prepared PAHBAH reagent

(1 volume of 5% p-hydroxybenzoic acid hydrazide in 5% HCl mixed with 9 volumes of 1.25% trisodium citrate, 0.11% calcium chloride, and 2% sodium hydroxide) and heated at 95◦C for exactly 6 min. Absorbance was measured at 410 nm using a microplate reader (BioTek Instruments, Inc., Winooski, VT, USA). Calculations were done using a standard curve prepared using different concentrations of Glc.

Methylester content determination

Methylester content was determined by a method adapted from Klavons & Bennett

(1986). Five mg of total cell wall was saponified in 1 M NaOH for 24 hours, then centrifuged at 12,000 g for 10 minutes. The supernatant was pipetted off to a new tube and centrifuged again to remove any particulates. 50 μL of the supernatant was added to 50 μL of alcohol oxidase (0.6 U/mL) in 0.1 M sodium phosphate buffer pH

7.5, then incubated on a shaker for 15 minutes at 25 °C. Then, 100 μL of a solution containing 0.02 M 2,4-pentanedione, 2 M ammonium acetate, and 0.05 M acetic acid in sodium phosphate buffer pH 7.5 was added to the reaction. After 10 minutes of incubation at 68 °C, samples were cooled on ice and centrifuged. The solution was pipetted into a 96-well plate, then quantified in a spectrophotometer at 412 nm wavelength and compared to a standard curve of methanol concentrations to determine molar concentration.

127

Cell length measurements

One-week old plants were incubated in a solution of 10 μg/mL propidium iodide in distilled water for one minute, then washed briefly by soaking in distilled water three times for one minute per wash. Roots were then mounted under a cover slip and imaged under a confocal microscope at 617 nm wavelength (Iowa State

Confocal Microscopy Facility).

Sample fixation, sectioning, and antibody probing

Samples were fixed and probed according to the methods outlined in Avci et al.

(2012). Stems were cut 5 mm below the meristem in 5 mm sections, and roots were cut 1 cm above the root tip in 5 mm sections, then immediately submerged in cold

(4 °C) 1.6%paraformaldehyde and 0.2% glutaraldehyde in 0.05M phosphate buffer, pH 7.2. Samples were infiltrated in a vacuum for 30 minutes, then pressure was returned to normal and samples incubated at 4 °C for 2 hours. Samples were then washed in 0.05M phosphate buffer, 3 times 15 min. each and then dehydrated with a graded ethanol series: 25, 50, 70, 85, 95, and 100% using ultra pure ethanol for the final 100% changes (30 mins. each step). Samples were infiltrated with LR White resin (Electron Microscopy Sciences) and polymerized in gelatin capsules at 4 °C under UV light for 48 hours. Sections were made using a Leica UC6 ultramicrotome.

Sections were dried onto probe on plus slides (Fisher Scientific) for immuno labeling.

For antibody probing, slides were blocked for 30 minutes at room temperature in a solution of 3% milk protein in 10 mM potassium phosphate 128 buffered saline (KPBS). Slides were gently rinsed once with 10 mM KPBS, then primary antibody was applied at a 20-fold dilution in 10 mM KPBS for one hour at room temperature with gentle mixing. Samples were washed three times for 5 minutes with 10 mM KPBS, then secondary antibody was applied at a 100-fold dilution in 10 mM KPBS for one hour at room temperature. Slides were washed twice in 10 mM KPBS for 5 minutes apiece, then washed once with distilled water for 5 minutes. Citifluor AF1 (Electron Microscopy Sciences) was then applied to each sample and cover slips were applied. Samples were visualized under a FITC filter set at 20X and 60X magnifications.

NaCl stress assays

Plants grown for salt stress were germinated on 1/2MS medium plates grown vertically for 5 days until cotyledons had fully expanded. After 5 days of growth, seedlings were transplanted to new plates containing either 1/2MS with no salt stress or 1/2MS medium containing 100 mM NaCl. Root length was measured, then plants were grown vertically for 5 days, at which point root length was measured again to determine the growth rate for each seedling.

Cyst nematode inoculation

Arabidopsis seeds were surface sterilized and planted in 4-well rectangular dishes

(Thermo Fisher) containing modified Knop’s medium (Sijmons et al., 1991) with

0.8% Daishin agar (Brunschwig Chemie). Ten days after germination, plants were inoculated with 250 surface-sterilized J2 H. schachtii, and after 4 days the 129 nematodes were stained. Using a modified protocol from Grundler et al. (1991), nematodes were stained in 1 mL of staining solution (500 mL acetic acid, 500 mL

96% ethanol, and 17 mg acid fuschin) and incubated for 24 hours, then washed with water, and then 1 mL of destain solution containing 600 mL water, 200 mL glycerol, and 200 mL lactic acid. The number of penetrating nematodes in each root system was counted using a Zeiss Axiovert 100 microscope.

B. cinerea inoculation

B. cinerea was grown for 15 days on potato dextrose agar at 23 °C under a 12-hour photoperiod before collecting spores. Spores were collected by washing the plates with 5 mL sterile water, then filtered through glass wool to remove mycelia. Conidia were diluted to a stock concentration of 1 x 106 conidia/mL. Conidia were then further diluted to a working concentration of 1 x 105 conidia/mL in 25% grape juice, then sprayed onto 3-week old Arabidopsis seedlings grown on sucrose-free 1/2MS medium (described above). The inoculated plates were grown in a growth chamber as described above for 48 hours, then harvested for nucleic acid extraction.

DNA Extraction

DNA was extracted from total aboveground portion of 3-week old botrytis- inoculated plants using a modified CTAB method (Clarke, 2009). Plant tissue was homogenized and incubated in 700 μL CTAB buffer (100 mM Tris, pH 8.0, 20 mM

EDTA pH 8.0, 0.35 mM NaCl, 0.137 mM cetyltrimethyl ammonium bromide, 1.25 mM polyvinylpyrrolidone, 2% β-mercaptoethanol) and incubated at 60 °C for 30 130 minutes. Samples were then mixed with 700 μL of a solution containing 24:1 chloroform:isoamyl alcohol mixture, inverted to mix, and centrifuged at 12,000 x g for 10 minutes. The supernatant was pipetted to a new tube and mixed with an equal amount of isopropanol and mixed. The samples were centrifuged, the supernatant pipetted off, and 1 mL 70% ethanol added. Samples were mixed, centrifuged to pellet DNA, and supernatant removed. 300 μL of TE buffer (10 mM

Tris pH 8.0, 1 mM EDTA) was added to each sample and gently mixed to dissolve

DNA. 150 μL of 7.5 M ammonium acetate was then added and gently mixed, and 900

μL 100% isopropanol was then added to precipitate DNA. The samples were centrifuged at 12,000 x g to pellet DNA, then 70% ethanol was added, samples were vortexed, and centrifuged to pellet DNA. The supernatant was removed and samples dried at room temperature, at which point DNA was dissolved in 20 μL distilled water.

Real-Time Quantitative PCR

Quantification of genomic DNA extracted from botrytis-infected plants was performed using the Maxima SYBR Green qPCR Master Mix (2X; Thermo Scientific) and the CFX-96 thermal cyclter (Bio-Rad) with primers for A. thaliana ACTIN2

(AtActin2_F: GAAACCCTCGTAGATTGGCA; AtActin2_R:

CTCTCCCGCTATGTATGTCGC) and B. cinerea ACTIN (BC-Actin-F:

AAGTGTGATGTTGATGTCC; BC-Actin-R: CTGTTGGAAAGTAGACAAAG). Relative DNA quantity was calculated using the comparative threshold cycle method (Schmittgen

& Livak, 2008). 131

RESULTS

Arabidopsis plants expressing AnPME show dwarf phenotype and reduced cell expansion

Three independent transgenic events were selected for this study (AnPME 1-

1, 2-1, & 3-2). All three independent transgenic lines of AnPME-expressing

Arabidopsis plants exhibit a severe dwarf phenotype throughout their life cycle.

Cotyledons of seven-day old seedlings expanded normally, but after the first true leaves emerged, the growth of the plants was visibly reduced. Roots of AnPME plants were approximately 50% shorter in comparison with WT Col-0 (Fig. 1A, 1C).

Matured 5-week old plants had reduced rosette area, smaller leaves, and shorter stems, (Fig. 1B). Etiolated AnPME seedlings germinated and grown in the dark for 5 days also exhibited reduced hypocotyl length compared to WT (Fig. 1D). To further investigate this growth phenotype of AnPME plants, the roots of seven-day old seedlings were stained with propidium iodide and imaged with confocal microscopy. The cell size of two independent transgenic AnPME lines (AnPME 2-1 and 3-2) exhibited significant reduction in cell length relative to WT Col-0, whereas the cell size of AnPME 1-1 plants was not statistically different (Fig. 1E, 1F). AnPME

1-1, the least severe phenotype, was not significantly reduced in cell size. 132

A C 40 30 * * 20 * Fig. 1: A, 7-day old seedlings exhibit reduced 10 root growth and leaf

Root Length (mm) 0 expansion. B, 5-week old WT Col-0 AnPME AnPME AnPME AnPME plants have 1-1 2-1 3-2 reducMon in leaf and roseNe area, as well as 20 shorter stems. C, Root D * * length is reduced in 7-day 15 old AnPME plants. D, 10 Length of hypocotyls is 5 * reduced in eMolated AnPME seedlings. E & F, 0 Cell elongaMon is B Col-0 AnPME WT Col-0 AnPME AnPME AnPME inhibited in AnPME plants Hypocotyl Length (mm) 1-1 2-1 3-2 determined through confocal imaging of E propidium iodide stained 150 root Mssue. All asterisks indicate staMsMcal * * 100 signiﬁcance (p<0.05, student’s t-test). 50

Average cell size (um) WT Col-0 AnPME AnPME AnPME F 1-1 2-1 3-2 Col-0 AnPME 2-1

Fig. 5.1: A, 7-day old seedlings exhibit reduced root growth and leaf expansion. B, 5-week old AnPME plants have reduction in leaf and rosette area, as well as shorter stems. C, Root length is reduced in 7-day old AnPME plants. D, Length of hypocotyls is reduced in etiolated AnPME seedlings. E & F, Cell elongation is inhibited in AnPME plants determined through confocal imaging of propidium iodide stained root tissue. All asterisks indicate statistical signiKicance (p<0.05, student’s t-test).

Cell walls in AnPME plants have reduced methylester content and modified recalcitrance to CWDEs

Cell wall methylester content in AnPME plants was reduced by 30—50%, depending on the transgenic line, in comparison with WT Col-0 cell walls (Fig. 2A).

To determine the impact of the reduced methylesterification on cell wall 133 degradability, the transgenic and wild type cell walls were digested with cellulases.

Amount of reducing sugars released after cellulase treatment was not significantly different between AnPME plants and WT Col-0 (Fig. 2B). When cell wall from

AnPME and WT plants were treated with a pectinase cocktail (polygalacturonase + pectin methylesterase), a lower amount of reducing sugars was released from

AnPME cell walls than from WT cell wall (Fig. 2C). However when the cell walls were treated with polygalacturonase alone, amount of reducing sugars released from AnPME cell walls was significantly higher in comparison with WT (Fig. 2D).

Monosaccharide analysis of total cell walls demonstrated that all three transgenic lines have significantly reduced amounts of GalA and increased arabinose content

(Fig. 2E), whereas other monosaccharides were not significantly altered. 134

A C Average Cell Wall Methylester Content Pec>nase (PG/PME) Treatment Fig. 2: CW characterizaLon and 3 1 comparison between Col-0 and 0.8 AnPME. A, methylester content in 2 * content * * * * 0.6 * WT Col-0 and AnPME cell walls. B, /mg CW) amount of reducing sugars released sguars 0.4 ul 1 / into soluLon aSer treatment of cell

ug 0.2 ( wall with cellulase/cellobiase 0 0 Reducing Cell Wall Methanol (mM) soluLon. C, amount of reducing WT COL-0 AnPME 1-1 AnPME 2-1 AnPME 3-2 WT Col-0 AnPME 1-1 AnPME 2-1 AnPME 3-2 sugars released into soluLon aSer treatment of cell wall with B Cellulase Treatment D Polygalacturonase-Only Treatment polygalacturonase/pecLn methylesterase soluLon. D, amount 0.2 * of reducing sugars released into 0.6 * * content soluLon aSer treatment of cell wall 0.15 0.4 content with polygalacturonase. E, /mg CW) sguars

ul 0.1

/ monosaccharide composiLon of cell /mg CW) sguars ul ug 0.2 ( / 0.05 walls aSer treatment with ug ( triﬂuoroaceLc acid. Reducing 0 0 *: staLsLcal signiﬁcance (p<0.05, Reducing WT Col-0 AnPME 1-1 AnPME 2-1 AnPME 3-2 WT Col-0 AnPME 1-1 AnPME 2-1 AnPME 3-2 student’s t-test) E 35 *

30 * * 25

Col-0 20 * * AnPME 1-1 15 * AnPME 2-1 10 AnPME 3-2 5 Propor>on of Cell Wall (Percent of total)

Glc A Xylose Gal A Fucose Glucose Rhamnose Arabinose Galactose Mannose Fig. 5.2: CW characterization and comparison between Col-0 and AnPME. A, methylester content in WT Col-0 and AnPME cell walls. B, amount of reducing sugars released into solution after treatment of cell wall with cellulase/cellobiase solution. C, amount of reducing sugars released into solution after treatment of cell wall with polygalacturonase/pectin methylesterase solution. D, amount of reducing sugars released into solution after treatment of cell wall with polygalacturonase. E, monosaccharide composition of cell walls after treatment with triIluoroacetic acid. *: statistical signiIicance (p<0.05, student’s t-test)

135

Immunolocalization of methylated and non-methylated HG epitopes in stem and root tissues.

To investigate the spatial distribution patterns of HG methylation and confirm reduced degree of HG methylation in AnPME-expressing plants, the inflorescence stems and roots were sectioned and probed with two HG-specific antibodies, JIM 7 and CCRC-M 38 (Pattathil et al., 2010). JIM7 recognizes methylesterified HG, whereas CCRC-M38 binds to de-esterified parts of HG. In WT

Col-0 stems, the distribution of fluorescence observed for both JIM7 and CCRC-M38 antibodies was similar to what has been reported in other papers (Hall et al., 2013)

(Fig. 3). Stems were qualitatively analyzed for fluorescence intensity of both JIM7 and CCRC-M38 under a fluorescent microscope. WT Col-0 epidermal cells and the triangular cell-cell junctions showed the brightest fluorescence with JIM7, whereas the CCRC-M38 fluorescence was brightest in vascular tissues. In stem sections of the AnPME plants the JIM7 fluorescence showed lower intensity in epidermal cells, and the whole section showed slightly lower intensity overall. These results corroborate the reduced amount of methyl groups detected in AnPME cell walls

(Fig. 3). On the other hand, the CCRC-M38 fluorescence intensity was increased in

AnPME plants, particularly the fluorescence localized to the tricellular junctions, indicating increased de-esterification of pectins in transgenic cell walls (Fig. 3). 136

50 μm 50 μm

WT Col-0

Jim7 Col M38 Col

AnPME

JIM7 PME M38 PME

50 μm 50 μm JIM7 CCRC-M38 Fig. 5.3: Immuno.luorescence of stems incubated in monoclonal antibodies raised against homogalacturonan with different degree of methylesteri.ication. JIM7 binds highly methylesteri.ied HG, and CCRC- M38 binds lowly methylesteri.ied HG. Bars = 50 μM.

Plants expressing AnPME display different responses to abiotic and biotic stress.

To investigate the potential impact of reduced pectin methylesterification on plant stress responses, the AnPME and WT Col-0 plants were subjected to salt stress and two types of biotic stresses.

Plants were grown on 1/2MS media in the presence and absence of 100 mM

NaCl and length of their roots was compared. While WT Col-0 root length was significantly decreased under salt stress conditions, length of the AnPME roots was not different in comparison with the roots on media without salt (Fig. 4A). 137

To determine the effect of reduced pectin methylester content on plant resistance to cyst-nematode penetration, two transgenic lines of AnPME plants and

WT plants were inoculated with H. schachtii. One AnPME line, AnPME 3-2, showed a reduction in the number of J2 females infecting the plant. Another line, AnPME 1-1, did not show significant difference in comparison with WT plants (Fig. 4B). AnPME

2-1 were not tested because of constraints with experimental design.

To investigate the impact of cell wall modification on plant resistance to fungal necrotrophs, three transgenic lines of AnPME-expressing plants and WT plants were challenged with B. cinerea. Because leaves of AnPME plants do not expand properly, these plants were not suitable for standard detached-leaf lesion area assays. Thus, genomic DNA was extracted from WT Col-0 and AnPME plants sprayed with B. cinerea spores at 48 hours post-infection (HPI). Quantity of fungal

DNA (B. cinerea ACTIN) was compared to the quantity of plant DNA (A. thaliana

ACTIN2) as a proxy for host susceptibility to the pathogen. An increased quantity of

B. cinerea ACTIN was detected in AnPME plants relative to WT plants, indicating that AnPME plants are more susceptible to fungal necrotrophs (Fig. 4C). RNA was extracted from the same samples to determine any differential gene expression. 138

A 4.5 B 4 H. schach4i Penetra4on 0 mM NaCl 3.5 15 3 100 mM NaCl 2.5 * 10 * 2 1.5 5 Root length (cm) 1 0 0.5

Average females/plant WT Col-0 AnPME 1-1 AnPME 3-2 0 WT Col-0 AnPME C B. cinerea Ac4n Fig. 5.4: Plant responses to stresses. A, root length in plants grown in unstressed (0 mM 12 * NaCl) and stressed (100 mM NaCl) 10 * * conditions. B, number of H. schachtii females 8 attached to plants 10 days after germination. 6 C, relative quantity of B. cinerea ACTIN DNA 4 relative to A. thaliana ACTIN2 (normalized to diﬀerence) 2 WT Col-0 expression). *: statistical 0 signiOicance (student’s t-test, p<0.05).

Rela4ve gDNA amount (fold WT Col-0 AnPME 1-1 AnPME 2-1 AnPME 3-2

DISCUSSION

Pectins are important cell wall polysaccharides that are involved in critical Fig. 4: Plant aspects of plant growth, development and stress responses, including cell wall responses to stresses and hormones mechanical strength and stiffness, cell-cell adhesion, and stress responses

(Cosgrove, 2005; Lionetti et al., 2015). During the plant life cycle, pectins undergo methylesterification/de-esterification, which affects their cellular roles. Because calcium ions cross-link unmethylesterified or demethylesterified sites in HG, thus hardening the cell wall, the degree of HG methylesterification has a key role in cell wall plasticity with significant impact on wall expansibility and resistance to action of CWDEs during disease development. Pectin demethylation occurs within the cell wall as a result of plant or microbial PME activity localized or secreted to plant apoplast (Anderson, 2016). Thus, PME is frequently present among CWDEs secreted during pathogenesis and considered as a virulence factor for some fungal 139 necrotrophic pathogens, like B. cinerea, because demethylesterification of pectins is required for PG activity and sequential cell wall degradation (Colimer & Keen,

1986).

Constitutive expression of microbial polysaccharide hydrolytic enzymes in the plant apoplast proved to be useful approach to investigate the impacts of cell wall post-synthetic modification on CWI and plant fitness and stress responses

(Buanafina et al., 2010; Lionetti et al., 2010; Pogorelko et al., 2013, 2016; Reem et al.,

2016; Tsai et al., 2017). In addition, the constitutive expression of microbial PME in the cell wall, to some extent mimicking the action of PME secreted during pathogenesis, can provide the opportunity to understand the contribution of pectin esterification/de-esterification to plant stress response and defense. Therefore, the goal of this study was to express fungal PME in the apoplast of Arabidopsis plants and investigate the effects of reduced pectin methylesterification on plant growth and stress responses.

The AnPME enzyme introduced to the plant apoplast caused up to 50% reduction of pectin methylesterification in comparison with WT plants. This reduction in methylesterification resulted in a severe dwarf phenotype due to suppressed cell elongation. A negative impact of reduced HG methylesterification on plant growth was observed in several previous studies, where methylation of pectins was altered either through knockout of plant PME (Raiola et al., 2011) or overexpression of PMEI (Lionetti et al., 2007, 2014; Müller et al., 2013b) or methyltransferases CGR2 and CGR3 (Kim et al., 2015). The latter had reduced levels of pectin methylesterification and showed severe defects in plant growth and 140 development. The authors proposed that the stiffness of mutant cell walls increased due to reduced HG methylesterification and possible increase of Ca2+-dependent cross-linking, which limited cell wall expansion. The AnPME plants in the present study also have, most likely, less expandable cell walls resulting in less elongated cells.

The main difference between plant and fungal PMEs is that fungal PMEs have been shown to de-esterify HG in a non-blockwise manner (Limberg et al., 2000;

Duvetter et al., 2006), thus having less impact on formation of calcium–dependent cross-linking of HG within cell walls. Microbial PMEs more readily promote degradation of the cell wall by increasing accessibility of HG to action of PGs

(Micheli, 2001; Kars et al., 2005). Indeed, the cell walls from AnPME plants released significantly more reducing sugars than in WT Col-0 plants when treated with polygalacturonase, confirming that AnPME makes the wall less recalcitrant to PG degradation (Fig. 2D). It is possible that constitutively expressed microbial PME is able to demethylesterify the HG in long enough stretches to open them for Ca2+- dependent cross-linking, thus, inhibiting cell wall expansibility. It is worth noting the difference in reducing sugar availability between the two pectin-degrading treatments: in the PG-only treatment, WT Col-0 cell walls yielded roughly 8% of the sugars that were yielded in the PG+PME treatment. On the other hand, AnPME cell walls treated with PG-only yielded between 38-45% of the total sugar content observed in PG+PME treatments (Fig. 2C,D). This demonstrates that AnPME expressed in plants hastens wall degradation by facilitating hydrolysis by PG. 141

Interestingly, the cell walls from AnPME plants contain significantly less GalA and higher amount of Ara, which might suggest that either HG biosynthesis is downregulated or RG-I/RG-II biosynthesis is upregulated in AnPME plants as a response to HG de-esterification. It was shown that arabinose-containing side chains are involved in pectin-cellulose interaction, which can negatively impact cell wall flexibility, and would explain reduction of cell elongation in AnPME plants (Jones et al., 2003; Wang et al., 2013a, 2014). Another possibility is that the expressed PME increases accessibility of HG to the action of plant cell wall-localized PGs, resulting in reduction of the amount of HG and causing a dwarf phenotype similar to what was observed for Arabidopsis and tobacco plants expressing microbial PG

(Capodicasa et al., 2004) This question will require further investigation in the future.

The immunological assays shown here illustrate the difference in methylester content between WT and AnPME plants. It should be noted that limitations in epitopes exist; JIM7 binds partially methylesterified HG, while M38 only binds de-esterified HG with DP>4 (Pattathil et al., 2010). JIM7 fluorescence, while reduced in epidermal cells of AnPME plants, did not appear significantly reduced in the rest of the cells. M38 fluorescence was significantly brighter in the triangular cell-cell junctions in AnPME plants compared to WT. This suggests that

AnPME works in a non-random, non-blockwise mode of action that results in short fragmented (DP>4) of de-esterified HG. With continual activity, throughout the lifetime of the plant, AnPME could potentially de-esterify HG to a degree that would permit Ca2+-mediated crosslinking (DP>9). However, it appears that if this is 142 occurring, crosslinking may only occur in the pectin-rich middle lamella, rather than in other parts of the cell wall.

Degree of pectin methyesterification affects plant resistance to stresses

While WT Col-0 root growth was greatly suppressed under salt stress, the

AnPME roots did not exhibit a reduction in growth. There are two plausible explanations of the observed effect of reduced methylesterification of cell walls.

Either the increased stiffness of AnPME cell walls has already reduced cell size to the smallest possible amount, or since the free carboxyl groups on pectates hold a negative charge, they could potentially sequester more Na+ ions than in WT plants, minimizing the effect of high salinity on cell growth (De Lima et al., 2014).

We selected two AnPME transgenic lines to explore the impact of pectin deesterification on ability of nematode penetration. It has been shown that nematodes stimulate expression of wall-modifying proteins in order to create a more flexible cell wall, as well as secrete CWDEs during pathogenesis (Smant et al.,

1998; De Meutter et al., 2001; Gao et al., 2002, 2004; Vanholme et al., 2007; Hewezi et al., 2008; Hé et al., 2009; Aditya et al., 2015). Of the two AnPME lines, the AnPME

1-1 line had significantly less severe growth phenotype and showed no difference in nematode penetration assay in comparison with the WT Col-0 plants. The AnPME 3-

2 plants showed higher resistance to nematode penetration, most likely due to more stiffened cell walls. It has been shown that cyst-forming nematodes interact with plant PMEs (Ithal et al., 2007). Arabidopsis plants overexpressing endogenous

AtPME3 and nematode-derived cellulose-binding protein were more susceptible to 143

H. schachtii, and Atpme3 knockout lines were less susceptible to the nematode

(Hewezi et al., 2008). However, it is not known whether these interactions with

AtPMEs affect cell wall methylester content. Since cyst-forming nematodes recruit a plant PME, it is possible that the HG pattern de-esterified by microbial PME is not recognizable by CWDEs secreted by nematodes during penetration. On the other hand, a cell wall with higher stiffness might present a stronger barrier to nematode stylet secretion.

Since AnPME plants have significantly reduced leaf surface areas which prevented accurate measurements of lesion size in detached-leaf assays commonly used to evaluate fungal infection, we quantified fungal DNA relative to plant DNA to estimate disease progression. Using this approach it was shown that all three transgenic AnPME lines showed increased susceptibility to B. cinerea in comparison with WT Col-0 plants. Fungal AnPMEs de-esterify pectins in a random or non- blockwise manner to facilitate wall degradation by microbial PG. Thus, higher susceptibility of AnPME plants confirms that the cell wall became more accessible to fungal CWDEs. This conclusion is also supported by our results demonstrating that

AnPME cell walls are more digestible by PG.

CONCLUSIONS

In this study we show that expression of a fungal PME in transgenic

Arabidopsis plants modifies cell wall HG, plant growth, and plant stress responses.

We propose that reduction of pectin methylesterification increases cell wall stiffness that limits cell elongation and differently impacts plant resistance to fungal or 144 nematode infection. In addition, increased amount of positively charged GalA residues can positively affect plant resistance to salt, possibly by chelating ions. The observations reported here show that the esterified form of HG is a critical factor in plant growth and protection.

Recent cell wall engineering strategies to reduce cell wall recalcitrance for lignocellulosic biomass production make use of microbial CWDEs expressed directly in planta. As we demonstrated here, some cell wall modifications directed to improvement of cell wall digestibility can negatively impact plant fitness. Thus, this study contributes to the understanding of various cell wall components contribution to cell wall numerous functions and limitations in their in vivo manipulations.

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CHAPTER 6

SPATIOTEMPORAL ANALYSIS OF CELL WALL INTEGRITY CONTROL IN

ARABIDOPSIS THROUGH POST-SYNTHETIC MODIFICATION OF THE CELL WALL

Nathan T. Reem, Vincenzo Lionetti, Daniela Bellincampi, Olga Zabotina

ABSTRACT

Cell wall integrity (CWI) is an important part of plant life. It allows plant cells to sense abnormalities or presence of pathogens in the cell wall compartment and initiate early defense response. While several CWI sensors, signaling, and changes in gene expression are known, there are many gaps in our knowledge of CWI and the underlying signaling involved in it. This project aims to elucidate when and how

CWI signaling is initiated and which pathways are involved in different CWI mechanisms. First, plasmids expressing microbial hydrolases under the

UBIQUITIN10 promoter were constructed in order to transform and create double- transgenic Arabidopsis plants in order to determine any overlap in CWI signaling pathways. Then, constructs expressing a red fluorescent protein driven by the promoters of two defense-related genes, PAD3 and WRKY40, were created to determine location and timing of defense responses in hydrolase-expressing plants.

Preliminary results in double transgenic lines have shown changes in defense response according to the selected transgenes. Taken together, these experiments should provide a clearer picture of when and how CWI is signaled in plants, and which responses are activated at certain times of a plant’s life.

158

INTRODUCTION

The plant cell wall is an important component of every plant cell. It helps counteract turgor pressure exerted on it by the cytoplasm, maintains cell shape, and allows the cell to expand and divide as the plant grows (Cosgrove, 2005). The wall is composed primarily of polysaccharides cellulose, hemicellulose, and pectin, as well as proteins and lignin. Cellulose is a homopolymer of unbranched β-1,4-linked glucans. Xyloglucan, the main hemicellulose in Arabidopsis thaliana, is composed of a backbone of β-1,4-linked glucans with sidechains including xylose, galactose, and fucose. Xyloglucan can also be acetylated on the galactose side chain residues

(Scheller & Ulvskov, 2010). Pectin is a heteropolymer of three distinct polysaccharides: homogalacturonan (HG), rhamnogalacturonan I (RG-I), and rhamnogalacturonan II (RG-II). Pectic polysaccharides all contain galacturonic acid.

HG is unbranched, but both RG-I and RG-II possess complex branching structures with an assortment of other sugars (Caffall & Mohnen, 2009). Pectic polysaccharides can also be acetylated. The acetylation of cell wall polysaccharides has been shown as important for successful defense against pathogens (Pogorelko et al., 2013).

In addition to its structural role, the cell wall also participates in signaling through cell wall integrity (CWI). CWI allows the cell to properly expand and grow while maintaining wall rigidity and preventing pathogen invasion (Wolf, 2017).

Wall-associated kinase (WAK) proteins are one fine example of CWI. WAKs reside on the plasma membrane and are critical for cell expansion; their extracellular domains directly bind cell wall pectin (Wagner & Kohorn, 2001). Binding pectin under unstressed conditions controls signaling of MAP kinase 3 (MPK3) and 159 vacuolar invertase activity in cells to initiate cell expansion (Kohorn et al., 2006,

2009).

Catharanthus roseus receptor-like kinases (CrRLKs) are a family of membrane-associated proteins with cytoplasmic kinase domains and extracellular malectin-like domains, which have been shown to bind disaccharides (Li et al.,

2016). There are several CrRLKs that are most likely involved in CWI: FERONIA

(FER), THESEUS1 (THE1), ANXUR1 (ANX1), and ANXUR2 (ANX2). FER and ANX1/2 are involved in plant fertility; FER was shown to localize to the female gametophyte at the site where pollen tubes rupture; ANX1/2 are critical for pollen tube CWI

(Escobar-Restrepo et al., 2007; Boisson-Dernier et al., 2009). FER is associated with the extracellular RAPID ALKALINIZATION FACTOR, a protein involved in increased apoplastic pH in response to stresses (Haruta et al., 2014). FER signaling involves crosstalk with abscisic acid, auxin, ethylene, and brassinosteroid signaling, and fer mutants display a variety of phenotypes (Guo et al., 2009; Deslauriers & Larsen,

2010; Duan et al., 2010; Yu et al., 2012; Mao et al., 2015; Chen et al., 2016). ANX1/2 also are important for pollen tube cell wall composition, as mutants displayed increased pollen tube rupture, and overexpression of ANX1/2 resulted in thick, pectin-rich pollen tube cell walls (Boisson-Dernier et al., 2013). THE1 senses the status of cellulose: cesa mutants with defective THE1 did not exhibit the characteristic cesa dwarf phenotype or ectopic lignification (Hematy et al., 2007).

THE1 also affects expression of genes associated with defense response, glucosinolate biosynthesis, and cell wall crosslinking, as well as ROS production

(Hematy et al., 2007; Denness et al., 2011). 160

In addition to developmental regulation, CWI is also important for defense against pathogens. As stated above, WAKs normally bind pectin in unstressed conditions. However, as a pathogen macerates the cell wall to gain access to the cell,

WAKs will preferentially bind the breakdown products of pectic homogalacturonan, oligogalacturonides (OGs) (Decreux & Messiaen, 2005; Decreux et al., 2006; Kohorn et al., 2009; Brutus et al., 2010). Binding OGs initiates a different set of MPKs, MPK6 and perhaps MPK8, to initiate gene expression of defense responses and suppress cell expansion (Kohorn et al., 2014). Another receptor-like kinase, FLAGELLIN

SENSING 2 (FLS2), senses bacterial flagellin in its extracellular leucine-rich domain

(Gómez-Gómez & Boller, 2000). Upon binding flagellin, FLS2 forms a co-receptor complex with BRI1-ASSOCIATED KINASE 1 (BAK1) to initiate a MAP kinase cascade that upregulates defense response (Asai et al., 2002; Navarro et al., 2004).

Post-synthetic modification, the transgenic expression of microbe-derived

CWDEs, is a useful approach for dissecting CWI control in plants. The cell wall is produced normally, and then modified by the CWDE. An alternative to this approach is the use of mutant or overexpression lines for biosynthetic enzymes; however, some issues exist with the use of mutants for CWI investigations. First, many partial redundancies exist between wall biosynthesis enzymes, so this is usually not a very fruitful endeavor. Also, the cell wall is not fully formed in this case and may affect

CWI. Numerous studies have used post-synthetic modification, including the two acetylesterases and a ferulic acid esterase in this study, which possess increased and decreased resistance, respectively, to the fungal necrotroph Botrytis cinerea

(Pogorelko et al., 2011, 2013; Reem et al., 2016). Additionally, a fucosidase 161 expressed in Arabidopsis showed increased root length and decreased hypocotyl length as a result of defucosylation of wall-associated arabinogalactan proteins

(Pogorelko et al., 2016). Expression of a ferulic acid esterase in Italian ryegrass yielded increased wall digestibility (Buanafina et al., 2010).

This study sought to extend research on post-synthetic modification events described previously: two acetylesterases (AnAXE, AnRAE) and one ferulic acid esterase (AnFAE) expressed in Arabidopsis thaliana. Previously, it was shown that

AnAXE and AnRAE were less susceptible to B. cinerea. Both expressed an increased basal level of defense response, and in particular expression of WRKY40 and PAD3 were increased in both lines (Pogorelko et al., 2013). AnFAE, on the other hand, was more susceptible to B. cinerea and had no obvious changes in defense response when unchallenged (Reem et al., 2016). Here, we describe several efforts to build on this research: first, double transgenic events were created to determine if additive effects exist between responses to cell wall modifications. tagRFP-expressing reporter lines for WRKY40 and PAD3 were also created to determine spatiotemporal expression in AnAXE and AnRAE. Finally, crosses were made between 4xRSRE::Luciferase plants and AnAXE, AnRAE, and AnFAE plants to determine whether the DAMPs produced in these plants were involved in any rapid stress responses.

162

MATERIALS AND METHODS

Hydrolase constructs

Hydrolase constructs with basta resistance were created by cloning AnAXE,

AnRAE, and AnFAE cDNA sequences from Pichia pastoris stocks obtained from the

Fungal Genetics Stock Center (http://www.fgsc.net)(Bauer et al., 2006). The sequences were cloned into pENTR-D-TOPO entry vector, then transferred to the binary vectors pUBC-CFP using Gateway recombination (Grefen et al., 2010).

Hydrolase constructs with hygromycin resistance were created by cloning hydrolase sequences and ligating them into the vector pCAMBIA-1300-MCS. The coding sequence and hygromycin resistance gene were then transferred to pUBC-

CFP binary vector using Gibson assembly.

Fluorescent reporter constructs

Promoters for PAD3 and WRKY40 genes were cloned by amplifying 1.5kb of upstream sequence of the transcriptional start site using Platinum Taq Polymerase

(Thermo Fisher). The PCR fragment was ligated into the p5e-MCS entry vector using

In-Fusion cloning technology (Clontech), then transferred into binary vector

R4L1pGWB759 (supplied by the Nakagawa Lab, Shimane University) using Gateway recombination. The resulting vector was transformed into Agrobacterium tumefaciens.

163

Transformation of plants

Plants were transformed using the floral dip method (Clough & Bent, 1998).

A. tumefaciens was transformed with the appropriate plasmid vector, grown in 500 mL cultures at 28 °C, then centrifuged at 1,000 g to pellet the cells. The cells were then resuspended in a solution of 5% sucrose with 0.3% Silwet L-77 surfactant and diluted to an optical density of 0.8. Plants grown in soil were dipped into the solution for 5 seconds, then placed in a dark, humid chamber for 16 hours before being re-introduced to light.

RESULTS

Double transgene events using the 35S promoter

Previously, double transgenic events had been created by transformation of

Cauliflower Mosaic Virus (CaMV) 35S-driven hydrolase-expressing plants with a second 35S-driven construct through Agrobacterium-mediated floral dip. This resulted in plants overexpressing two hydrolase constructs driven by 35S promoters. After transformation, plants were selected through antibiotic resistance until homozygous. AnAXE/AnRAE double transgenic lines were created because both AnAXE and AnRAE plants exhibited increased basal defense response and resistance to B. cinerea. This was to determine whether these responses act in the same pathway or different pathways. AnFAE/AnRAE double transgenics were created to determine whether the increased resistance in AnRAE plants would be countered by the increased susceptibility in AnFAE plants. 164

Plants were inoculated with B. cinerea conidia and after 48 hours lesion area was measured (Fig. 1). AnAXE/AnRAE double transgenics showed a significant decrease in lesion area relative to wild-type (WT) and the AnAXE single transgenic.

No difference was detected between AnFAE/AnRAE and WT (Fig. 1).

B. cinerea Infec&on

Fig. 6.1. Lesion area measurements 48 hours after inoculation with B. cinerea spores. Labels a-e indicate statistical signi=icance: the same letter indicates no signi=icance between samples; different letters indicate statistically signi=icant differences (student’s t-test; p<0.05)

Apoplastic fluid was extracted from homozygous events, and a western blot was performed to attempt detection of both transgenes in AnAXE/AnRAE and

AnFAE/AnRAE. However, numerous attempts revealed one or both transgenes absent from apoplast samples. At this point it was determined that transgene silencing or protein misfolding was occurring. Thus, to minimize the risk of 165 transgene silencing, new constructs were produced using an endogenous constitutive promoter.

Creation of transgene constructs driven by the UBIQUITIN-10 promoter

The UBIQUITIN-10 promoter (pUBQ10) is a constitutively expressed endogenous promoter in Arabidopsis, and has been used as an alternative to the

CaMV 35S promoter (Norris et al., 1993). Recently, a set of Gateway-compatible binary vectors for Arabidopsis transformation were developed for expression of a transgene fused with fluorescent proteins. For the purposes of this study, a vector with a C-terminal cyan fluorescent protein (CFP) was chosen (pUBC-CFP) (Grefen et al., 2010). pUBC-CFP possesses resistance to the Basta herbicide in order to select plant transformants to homozygous genotypes. Hydrolase sequences of AnAXE,

AnRAE, and AnFAE were cloned, ligated into the pENTR-D-TOPO entry vector, then

Gateway-recombined into pUBC-CFP vectors.

To create double transgenic plants, two selection methods are necessary, one for each transgene. None of the vectors produced by Grefen et al., nor any other available source to our knowledge, possessed a Gateway-compatible pUBQ10 promoter with selection other than Basta resistance. Thus, it was necessary to create a vector with the necessary criteria. To achieve this, Gibson assembly (Gibson et al., 2009) was utilized to transfer the existing expression cassette from pUBC-CFP onto an existing backbone: pCAMBIA-1300-MCS (Fig. 2). Complementary overhanging primers for the cassette insert and plasmid backbone were designed, fragments were cloned via PCR, annealed together, and then transformed into E. coli 166

for propagation. Transgenic plants expressing basta-resistant pUBC-

[AnAXE/AnRAE/AnFAE]-CFP were then floral-dip transformed with Agrobacterium

carrying pCAMBIA-UBQ10-[AnAXE/AnRAE/AnFAE]-CFP. 5/27/2017 12:36:59 PM pUBC-AnFAE-CFP-pCAMBIA (11115 bp)

5/27/2017 12:40:24 PM R-Border

pCAMBIA-1300 (8958 bp) attR1

10 pUBQ

bom site attR2 AE 5/27/2017 12:39:05 PM nF S P A T S1-RE A pV r e Corrected pUBC-AnFAE-CFP (10708 bp) g pBR322-Rep i o n

RB P attR1 F C

pUBQ10 1 S K V T35S a p n - R A attR2 T ( S An a FA a E d

A pCAMBIA-1300 ) pCAMBIA-UBQ10-AnFAE-CFP pUBC-AnFAE-CFP-pCAMBIA 8958 bp 11115 bp P

C R a C - F M P 1 V S 3 V 5 p S

T35S L-Border p

V Corrected pUBC-AnFAE-CFP CaMV 3'UTR S 1 10708 bp II pt h h p R-Border t R I r CDS I a CaMV35S B pUC18 MCS PlacZ,CDS bom site

pBR322-REP B dA) L kanR (aa CaMV 3'UTR L-Border

R pBR pec 322 S Fig. 6.2. Gibson assembly scheme for production of the pCAMBIA-UBQ10- AnFAE-CFP plasmid. The expression cassette containing the pUBQ10 promoter, AnFAE-CFP fusion protein, and the 35S terminator were cloned https://benchling.com/nathanreem/f/ghykSqzvTb-my-sequences/seq-KyvVFdVH-pcambia-1300/edit 1/1 alongside the plasmid backbone from the pCAMBIA-1300 expression

https://benchling.com/nathanreem/f/UP9BAobU-pubq10-vectors/seq-PTcAZI43-corrected-pubc-anfae-cfp/edit 1/1 vector. The insert and backbone were ligated together using one-step https://benchling.com/nathanreem/f/U4h6nDRY-pubc-pcambia-gibson-assembly/seq-LYANQ3n9-pubc-anfae-cfp-pcambia/edit 1/1 Gibson assembly.

Fluorescent Reporter Lines

AnAXE and AnRAE plants exhibit upregulation of defense responses and

increased resistance to fungal necrotrophs (Pogorelko et al., 2013). Because this is a

response to cell wall modifications, and since the cell wall varies throughout age of

the plant, it is important to determine the location and timing of defense response in

these plants. Thus, fluorescent reporters were employed to determine

spatiotemporal activation of defense response, specifically expression of two genes

known to be involved in defense response: PHYTOALEXIN DEFICIENT 3 (PAD3),

and the WRKY40 transcription factor. 1.5 kilobases of promoter sequences of both 167 genes was amplified, then ligated into the p5e-MCS entry vector containing L4-R1

Gateway recombination sites. This vector was then Gateway-recombined with a binary vector containing R4 and L1 recombination sites complementary to the entry vector (R4L1pGWB759; Nakagawa Laboratory, Shimane University). Arabidopsis plants (AnAXE and AnRAE, along with wild-type Col-0) were transformed through

Agrobacterium-mediated floral dip and selected to T3 homozygous lines. The T3 plants are currently being evaluated for zygosity, and will be screened for fluorescence and gene expression across the lifetime of the plant.

DISCUSSION

Double transgenic plants to determine CWI signaling

Previously, it has been shown that AnAXE and AnRAE plants exhibit increased resistance to B. cinerea inoculation, and some defense responses are activated in the absence of pathogens (Pogorelko et al., 2013). AnFAE plants, on the other hand, do not show any specific gene expression in the absence of pathogens, and are more susceptible to B. cinerea. In order to determine whether these events are involved in the same CWI response pathways, it is useful to express both genes in plants and assay them for gene expression and response to pathogens. However, due to known issues with gene silencing in 35S-driven genes, it was necessary to change the promoter driving the expression of the hydrolases (Elmayan &

Vaucheret, 1996; Vaucheret et al., 1998; Mishiba et al., 2005). Double transgenic plants are currently being produced and will be selected for both transgenes using co-selection of Basta herbicide and hygromycin antibiotic. Because of the gene 168 silencing present in the 35S-driven events examined via western blot, it is unclear whether the results of Figure 1 are reliable. Thus, once T3 homozygous double transgene plants are obtained, lesion areas after B. cinerea inoculation must be redone. Additionally, apoplast will be extracted from these plants, and in vitro enzyme activity assays and western blots will confirm protein presence. To confirm in vivo activity, plant cell walls will be extracted and assayed for recalcitrance against cellulases, xylanases, and pectinases, in addition to acetyl and feruloyl content.

Fluorescent reporter lines for spatiotemporal examination of defense responses

PAD3 and WRKY40 are two genes previously known to be involved in CWI signaling of AnAXE and AnRAE plants, in addition to their roles in defense response

(Pogorelko et al., 2013). PAD3 was found to be upregulated in a basal level in AnRAE plants, and WRKY40 was upregulated in both AnAXE and AnRAE plants. PAD3 is necessary for production of camalexin, an effective defense compound against fungal necrotrophs (Schuhegger et al., 2006). Previously characterized OG-induced

CWI responses are also PAD3-dependent (Ferrari et al., 2007). It is not currently known how PAD3 is involved in signaling of AnRAE deacetylation events.

WRKY40 is also involved in defense response against fungal necrotrophs, and forms a complex with two other WRKY transcription factors to regulate ABA signaling (Xu et al., 2006; Shang et al., 2010). Recently, it was shown that WRKY40 interacts with WRKY18 after treatment with flg22 to regulate early MAMP-triggered 169 immunity and prevent overexpression of defense responses, including ethylene biosynthesis (Birkenbihl et al., 2016). However, it is not known at this time how

WRKY40 behaves in response to cell wall deacetylation or after treatment with a fungal necrotroph.

The use of fluorescent reporters to determine gene expression will provide us with valuable data showing the time and location of upregulation of PAD3 and

WRKY40 in AnAXE and AnRAE plants. T3 homozygous lines are being planted for spatiotemporal analysis of gene expression, where plants will be screened for gene expression analysis beginning at germination and continuing for the duration of their life cycle. Control plants, including untransformed WT Col-0 and

AnAXE/AnRAE plants, will be used to compare with the reporter plants. Early-stage seedlings will be grown in 96-well plants containing liquid 1/2MS medium for ease of microscopy. Plants for analysis of older tissues will be grown in soil and under sterile conditions in magenta boxes. Initial plans call for once-weekly expression analysis, with several timepoints throughout the day to control for any possible circadian effects on gene expression (Zhou et al., 2015).

CONCLUSIONS

CWI is a complicated network of receptors and signaling machinery that most likely have redundant or interdependent functions. This complicates efforts to uncover the signaling components in specific CWI events, because it is difficult to confirm that signaling components are indeed part of CWI, rather than an interdependent component on some other pathway. To gain a clearer picture of CWI 170 signaling, reporter lines and double transgene plants will be analyzed. We expect to confirm previous results from double transgenes, then leverage changes in gene expression to identify specific components of each CWI response pathway.

Fluorescent reporter lines will provide spatial and temporal data regarding expression of two key genes involved in these CWI responses.

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CHAPTER 7

CONCLUSIONS AND FUTURE DIRECTIONS

CONCLUSIONS

This dissertation contributed to our knowledge in plant cell wall integrity and the importance of cell walls in plant fitness. Through investigation of

Arabidopsis thaliana and Brachypodium distachyon plants expressing microbe- derived cell wall-degrading enzymes, we discovered unique CWI mechanisms and responses to wall modifications. Specifically, plants expressing AnFAE were more susceptible to fungal necrotroph attack and had weakened cell walls. Transcriptome and metabolome of plants expressing AnAXE, AnRAE, and AnFAE were correlated to determine primary metabolic pathways involved in each CWI response. A pectin methylesterase (AnPME) expressed in plants showed the importance of pectin in

CWI. Finally, several projects underway in furthering examination of these transgenic events will provide more details into the mechanism of CWI and cell wall in plants.

Cell wall integrity is important for plant fitness because it plays a key role in plant development, and it contributes to plant response to pathogens (Wolf, 2017).

For example, the wall-associated kinases are involved in both normal cell expansion and pathogen sensing (Kohorn, 2015). CrRLKs, such as THE1, FER1, and potentially others, detect defects in the cell wall and initiate signaling for defense responses (Li et al., 2016). Thus far, there have been few studies of cell wall integrity response to alterations of compounds decorating cell wall polysaccharides: acetyl, feruloyl, and 178 methyl groups. In this dissertation, we have shown the importance of these compounds in defense response and plant morphology.

Wall-bound ferulic acid affects defense response of both monocots and dicots

First, we addressed the importance of cell wall feruloylation in both monocot and dicot plants. Previously, it has been shown that in monocots, ferulic acid crosslinks accounted for about 5% of the cell wall dry weight, and were critical for defense responses. Our analyses in Brachypodium distachyon confirmed that ferulic acid was reduced in the cell wall, and plants were more susceptible to Bipolaris sorokiniana (Reem et al., 2016). Analysis of cell wall monosaccharide composition showed an increase in xylose, most likely in compensation for reduced ferulic acid crosslinking. Brachypodium cell walls were more degradable than WT under cellulase treatment.

In dicots, ferulic acid makes up less than 1% of the dry weight of the cell wall, and is considerably less well-studied. In some dicots, ferulic acid is associated with pectins; however, ferulic acid dimers are not present in dicot cell walls, so we sought to determine the significance of ferulic acid monomers in Arabidopsis. We determined that ferulic acid monomers are also important for defense, as

Arabidopsis AnFAE plants were found to be more susceptible to B. cinerea. Unlike

Brachypodium, no changes in cell wall monosaccharide composition were detected in AnFAE plants. Cell wall digestibility was also changed in AnFAE plants: cell walls were more digestible after cellulase treatment as well as pectinase, indicating that perhaps ferulic acid may associate with pectins in Arabidopsis. We also observed a 179 link between ferulic acid and extensin proteins, which are known to crosslink polysaccharides. In Arabidopsis AnFAE cell walls, while total amount of extensins was unchanged, they showed an increase in crosslinked extensins and decrease in

HF-soluble extensins, perhaps as a response to wall deferuloylation.

Correlation of metabolome and transcriptome reveals primary metabolism involvement in CWI

We assayed CWI signaling and plant responses to cell wall modifications through a correlation of transcriptome and metabolome from AnAXE, AnRAE, and

AnFAE Arabidopsis plants. The transcriptome alone showed potential players in

CWI signaling, including a variety of cell wall- and stress response-related genes. A set of transcription factors involved in each set of CWI was also determined. These candidate genes will be considered in the future for potential analysis as CWI- related genes.

Through correlation of transcriptome and metabolome, we discovered important players in CWI through an enrichment of primary metabolism. Both

AnAXE and AnRAE plants had upregulation of gene expression enriched in pathways including adenosine nucleotides de novo biosynthesis, glucosinolate biosynthesis, and aromatic amino acids biosynthesis. This suggests an increase in ATP production to power biosynthesis of secondary metabolites such as glucosinolates, jasmonate, and camalexin. AnRAE plants also were downregulated in s-adenosylmethionine and ethylene biosynthetic pathways, while no change was detected in AnAXE. Thus, it is likely that the subtle differences between AnAXE and AnRAE defense response 180 seen previously are a result of changes in ethylene or s-adenosylmethionine abundance. Pathway enrichments for AnFAE plants included a downregulation of 16 peroxidase-expressing genes related to lignin biosynthesis, as well as downregulation of lipid biosynthesis genes. It is not clear why lignin peroxidases are downregulated, but this may affect degree of lignin polymerization. Also, because lipids can serve as signaling molecules, the downregulation of these genes may be a plant response to prevent manipulation of the plant by pathogens. Together, the results obtained in this study indicate changes in primary metabolic pathways to affect secondary metabolism in response to cell wall modifications.

Pectin methylesterification is critical for plant morphology and affects response to pathogens

The importance of cell wall pectin methylesterification was demonstrated through expression of A. nidulans pectin methylesterase in Arabidopsis. Previously, it has been shown that pectin is important for cell expansion (Cosgrove, 2005). In this study, we have shown that the degree of pectin methylesterification is a key part of cell expansion, affecting the cell’s potential to increase in size. AnPME plants were dwarfed throughout their lifecycle as a result of reduced cell expansion.

Reduced methylester content in cell walls was confirmed by direct quantification from pure cell walls, and in situ immunolocalization.

Pectin methylesterification is also important for plant defense and response to stresses. AnPME plants showed no growth inhibition when grown under salt stress, indicating an enhanced tolerance to ionic stress. AnPME plants were also 181 more susceptible to B. cinerea. However, AnPME plants with significant pectin demethylesterification were also more resistant to H. schachtii nematode inoculation.

Future directions: double transgenic and fluorescent reporters

To further our examinations of CWI in Arabidopsis plants, we are in the process of creating double transgene plants. The double transgenics will provide information on the interaction between individual CWI signaling events. By assaying defense responses and gene expression associated with plant-pathogen interactions, we hope to connect DAMP recognition with CWI signaling to clarify the entire CWI signaling pathway for AnAXE, AnRAE, and AnFAE.

Plants expressing fluorescent reporters under the promoters for PAD3 and

WRKY40 will provide valuable knowledge pertaining to the initiation and duration of defense responses as they are induced in AnAXE and AnRAE plants. With this knowledge, we can attempt to correlate fluorescence with other cell functions such as ion flux, protein phosphorylation, and metabolite abundances.

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