FREE AMINO ACIDS IN ASIAN AND NORTH AMERICAN ASH ARE NOT A COMPONENT OF INDUCED RESISTANCE TO THE

Michael A. Falk1, David N. Showalter1, Amy L. Hill1, Paul L. Phelan2, Daniel A. Herms2, Pierluigi Bonello1

1Department of Pathology, The Ohio State University, 2021 Coffey Rd Columbus, OH

2Department of Entomology, The Ohio State University, OARDC, Wooster, OH

HONORS THESIS

Presented in partial fulfillment of degree of Bachelor of Science at The Ohio State University

By

Michael Falk Undergraduate Program in Environmental Science

The Ohio State University 2014

Defense Committee:

Dr. Pierluigi Bonello, Research Advisor

Dr. Roger Williams, Academic Advisor

Dr. Ronald Hendrick

1 Abstract

The emerald ash borer (EAB, Agrilus planipennis) is an invasive wood-boring insect responsible for the death of millions of North American ash ( spp.). While native ash species are susceptible to the pest, Manchurian ash (Fraxinus mandshurica), which shares a co-evolutionary history with the EAB in , is resistant. A 2012 study by Hill et al. investigated constitutive (pre-attack) nutritional components of ash phloem, the feeding substrate of EAB, and their relationship to resistance against the insect. No work, however, has looked into induced (post-attack) nutritional components. The main objective of this study was to test the hypothesis that EAB attack would induce decreases in free amino acid concentrations of resistant Manchurian ash compared to susceptible green and white ash. A fertilization treatment was implemented to elucidate interspecific differences in resource utilization. A secondary objective of this project was to investigate potential associations between free amino acid concentrations and host species-specific larval feeding efficiency patterns observed in a separate experiment

(Showalter unpublished), hypothesizing that free amino acid concentrations and larval feeding efficiency would share a direct relationship. Free amino acid concentrations decreased in response to attack but did not vary significantly between species and failed to explain species-specific larval feeding patterns.

Findings thus suggest that free amino acids do not play a significant role in induced ash defense against EAB.

2

Introduction

The emerald ash borer (EAB, Agrilus planipennis) is an exotic, invasive, wood-boring insect from Asia responsible for the death of millions of North

American ash trees (Fraxinus spp.) since its detection in 2002. EAB-induced ash mortality has caused extensive damage to the structure, composition, and function of forest ecosystems and threatens the availability of one of the most widely distributed timber resources in (MacFarlane & Meyer 2005). Larval feeding in the phloem creates serpentine galleries, disrupting resource translocation and killing the within 1-3 years. While all native North American ash species are susceptible to EAB, Manchurian ash (Fraxinus mandshurica), which shares a co- evolutionary history with EAB in Asia, is resistant (Smith et al. 2006; Rebek et al.

2008; Whitehill 2011).

Plant primary metabolites, such as amino acids, are widely recognized for their role in phytophagous insect nutrition. These compounds, however, are also thought to be involved in plant defense due to their profound effect on insect behavior and physiology (Berenbaum 1995). Furthermore, primary metabolites are likely to be more effective as components of defense against monophagous insects with limited mobility (Berenbaum 1995), such as EAB. Primary metabolite deficiencies can limit plant nutritional quality and act as a detriment to insect growth and physiology. Furthermore, there are 10 essential amino acids insects cannot synthesize and must obtain from an outside source. These include arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine,

3 tryptophan, and valine (House 1962). Deficiencies in any single essential amino acid can thus limit insect growth and survival (Liebig’s Law). Additionally, poor nutritional quality has been shown to trigger increased feeding in phytophagous insects to compensate for nutrient deficiencies, in turn causing increased consumption of toxic allelochemicals (Slansky & Wheeler 1992).

A recent study by Hill et al. (2012) found significant differences in constitutive (pre-attack) amino acid levels between Manchurian and North

American ash, suggesting nutritional differences may contribute to the resistance of

Manchurian ash to EAB. However, induced (post-attack) anti-nutrition responses, widely recognized as components of plant direct defense (Chen 2008), have yet to be investigated. Host-plant nutritional content has been shown to decrease in response to herbivory (Valentine et al. 1983; Haukioja et al. 1991). Additional evidence shows that insect feeding can induce changes in host-plant nutritional quality, in the form of free amino acid concentrations, that mediate patterns of interspecific resistance (Chiozza et al. 2010).

In this study, free amino acids were quantified before and after EAB inoculation in resistant Manchurian ash and two susceptible North American species, green and white ash. We hypothesized that inoculation would induce lower free amino acid concentrations in Manchurian ash. Half the trees within each species were subjected to a fertilization treatment. Fertilization has been known to enhance nutritional quality of trees and decrease concentrations of defense compounds

(Herms 2002). This study also attempted to use free amino acid concentrations to explain host species-specific patterns of EAB larval feeding. Unpublished data from a

4 study conducted on the same trees suggests larval feeding efficiency is significantly lower in resistant Manchurian ash (Showalter unpublished). We thus hypothesized that free amino acid concentrations determined in this study would share a direct relationship with larval feeding efficiency.

Materials & Methods

Experimental Plot Design and Fertilization Protocol

Trees were planted in a randomized complete block design, with four blocks, in 2004 at the Tollgate Research Facility (Michigan State University) in Novi,

Michigan. The four-year-old bare-root trees were obtained from Bailey Nurseries,

Inc. (St. Paul, MN). The plantation consisted of two susceptible North American ash species, green (Fraxinus pennsylvanica) cv. “Patmore”, and white ash (Fraxinus americana) cv. “Autumn Purple”, and one resistant Asian ash species, Manchurian ash (Fraxinus mandschurica) cv. “Mancana.” The resistance phenotypes of these have been confirmed in several prior common garden experiments (Smith et al. 2006; Rebek et al. 2008; Whitehill 2011).

In the fall of 2008, two levels of fertilization treatment were implemented: 0 and 200 kg N/ha/yr. The fertilizer used was 32:5:4 (N, P, K) with 33% N in slow release form (methylene urea), and 67% N in fast release form (50% ammonium nitrate and 17% water soluble urea). Starting May 12, 2011, ammonium nitrate was replaced with water-soluble urea due to changes in regulatory requirements. Half the annual fertilizer treatment was applied soon after budbreak in the spring, and

5 the other half was applied in the fall. Dates of application included: Sept. 28, 2008,

May 21, 2009, October 1, 2009, June 7, 2010, Oct. 12, 2010, May 12, 2011, Sept. 29,

2011, and April 24, 2012 (Herms personal contact).

Sample Collection and EAB Egg Application

24 ash trees belonging to the three separate species were selected for sampling, egg induction, and analysis. Each species was subjected to two fertilization treatments, totaling four trees per species x fertility combination. EAB eggs failed to hatch on 7 trees. 17 trees, in total, were thus sampled and analyzed.

On June 14, 2012, constitutive phloem samples were collected using a 15 mm diameter leather punch. Phloem samples were flash frozen in liquid nitrogen and stored at -80C. Eggs were applied to trees according to methods used in

Chakraborty et al. (2013). Eggs, on filter paper, were covered with gauze and attached to trees with duct tape. Each sampling region received two eggs at each of four locations for a total of eight eggs. Cage-reared EAB eggs were obtained from Dr.

Daniel Herms (OARDC, Wooster, OH) and Dr. Jonathan Lelito (USDA, APHIS,

Brighton, MI).

On July 11, 2012, the tape and gauze were peeled back to reveal the egg hatch sites. Eggs on the filter paper were observed for signs of hatching, and bark was peeled back with a razorblade near inoculation sites to look for initiated galleries.

Upon identifying a gallery, one to two 15 mm diameter phloem samples were collected from the areas immediately surrounding the galleries, including the gallery tissue, flash frozen, and stored at -80C.

6

Tree Harvest and Larval Colonization Measurements

On August 19-21, trees were cut down and transported to Wooster, OH where they were stored at 4C until processing. Larval colonization was quantified during October and November of 2012 by debarking 1 m sections of trunk areas that received egg application. Length and terminal width of feeding galleries were measured (Showalter unpublished).

Free Amino Acid Analysis

Ash phloem was ground in liquid nitrogen using a mortar and pestle. 0.5 mL of 0.01 N HCl was added to 50 mg of ground ash phloem in 1.5 mL centrifuge tubes and vortexed until all tissue was submerged. Samples were shaken at 700 rpm at room temperature for one hour, and then centrifuged for 5 min at 13.4 g.

Supernatants were transferred to new 1.5 mL centrifuge tubes and centrifuged again. The supernatant was collected a second time to ensure no residual plant tissue was present. Samples were stored at -20C to await further processing.

Samples were derivatized using an EZ:FAAST Amino Acid Sample Testing Kit

(Phenomenex, Torrance, CA) according to manufacturer recommendations. GC-MS analysis was conducted in the spring of 2013 using an Agilent 6890 series GC system with a 5973 Mass Selective Detector and a 7683 auto-sampler.

Concentrations of AA that were not present in standards were estimated using calibration curves of the nearest eluting AA or an AA known to produce similar MS response. Chromatograms of samples were also examined for significant levels of

7 other non-AA constituents. These non-AA peaks are either phenolic in nature and/or contain nitrogen and if not identified they were named using the designation

‘peak’ followed by their retention time in minutes. Concentrations of non-AA compounds were estimated by comparison of peak areas to the internal standard

(norvaline) (Phelan personal contact).

Statistical Analyses

A repeated measures analysis of variance (ANOVA) was used to identify significant interactions between and within factors. Inoculation was considered a within-subjects factor consisting of two levels: constitutive (pre-inoculation) and induced (post-inoculation). Between subjects factors consisted of block, species, and fertility treatment. Separate ANOVAs were run for each individual free amino acid and a summed total of all standard free amino acid concentrations detected. A feeding efficiency index (FEI) was calculated as the ratio of gallery terminal width to length. A Kruskal-Wallis test was performed on FEI. Associations between free amino acid concentrations and FEI were investigated using linear regression.

Results

EAB-inoculation induced significant decreases in the concentrations of 10 individual amino acids (glycine, valine, leucine, isoleucine, proline, asparagine, glutamic acid, phenylalanine, glutamine, and tryptophan), total amino acids (Fig 1), and three non-amino acid compounds (tyrosol, peak 0.4185, peak 0.4285) regardless of species (Table 1). This decreasing trend held for all compounds

8 detected by GC-MS analysis with the exception of peak 0.5594, which increased in response to inoculation (Table 2). Amino acid concentrations differed significantly between species for proline and glutamic acid, displaying a relationship similar to that described in Hill et al. (2010), in which amino acid concentrations were typically highest in green ash, intermediate in Manchurian ash, and lowest in white ash. Fertilization produced significant differences between species in aspartic acid, pyroglutamic acid, and glutamine. These three amino acids displayed a trend in which concentrations in fertilized green and white ash were lower than those of unfertilized green and white ash. Conversely, free amino acid concentrations of fertilized Manchurian ash were higher than those of unfertilized Manchurian ash.

This trend held for total free amino acid concentrations, but interactions between species and fertilization were not significant (p = 0.079). Significant interaction effects were observed between species and inoculation for tyrosol and peak 0.4185.

Concentrations of both compounds decreased with inoculation for all three species and were highest in green ash, intermediate in white ash, and lowest in Manchurian ash, regardless of inoculation. FEI was significantly lower in Manchurian ash compared to green and white ash, regardless of fertilization (Showalter unpublished) (Fig 2). No significant interactions were observed between total and individual amino acids and FEI (Fig 3).

Discussion

Contrary to our hypothesis, no significant interaction effects were observed between species and inoculation for any of the amino acids we have quantified

9 (Table 1). Inoculation alone, however, produced significant decreases in the concentrations of total free amino acids and 10 individual amino acids, regardless of species. This trend held for all amino acids, agreeing with overall trends observed in a study by Muilenburg et al. (2013) on wound response and larval homogenate application in birch (Betula spp.). These findings suggest that EAB-induced decreases in free amino acid concentrations are not unique to resistant phenotypes, but rather universal responses to insect attack or wounding. Wounding has been shown to induce synthesis of specific proteins in phloem exudate that are thought to play significant roles in plant defense (Dafoe et al. 2008). Attack-induced decreases in free amino acids observed in this study could thus suggest an increased demand for such proteins.

A separate larval performance experiment conducted on the same trees found that FEIs were significantly lower in Manchurian ash, regardless of fertilization (Showalter unpublished) (Fig 2). Lower FEIs suggest smaller larval size despite relatively high levels of phloem consumption and are thought to share a direct relationship with larval feeding efficiency, suggesting poor larval performance in resistant Manchurian ash. A secondary objective of the free amino acid study described in this paper was to see whether relationships existed between

FEIs and free amino acid concentrations. We hypothesized that free amino acid concentrations would be directly correlated with FEI, explaining species-specific patterns observed in the larval performance study. Contrary to our hypothesis, total and individual free amino acid concentrations did not share a significant relationship with FEI (Fig 3).

10 The findings of this study suggest that free amino acid concentrations, alone, do not play a direct independent role in induced ash resistance to EAB. Free amino acids, however, could be an important indirect component of induced ash defense.

Significant decreases in free amino acid concentrations were observed in resistant and susceptible species in response to inoculation (Table 1). These decreases, though similar in magnitude, do not necessarily serve identical purposes between species. Differential expression of proteins associated with defense has been documented in constitutive Manchurian ash tissue (Whitehill et al. 2011). Utilization of free amino acids for synthesis of unique defense proteins in Manchurian ash could perhaps explain observed differences in feeding efficiency despite relatively uniform constitutive and induced amino acid levels between species. For example, insect feeding has been shown to induce host plant synthesis of complex “post- ingestion” anti-nutritive compounds, such as digestive enzyme (e.g. protease) inhibitors, that hinder digestion of essential nutrients in insects regardless of host plant nutritional quality (Chen 2008). Unique synthesis of these compounds in

Manchurian ash could potentially explain observed discrepancies between nutritional quality and feeding efficiency documented in this experiment.

Quantification of more complex defense proteins, as well as proteinaceous amino acids, could thus provide more insight on ash resistance mechanisms to EAB, and should be a target of further research.

Acknowledgements

11 I would like to thank Dr. Pierluigi Bonello for his role as a mentor throughout my undergraduate career, providing unrelenting guidance, insight, and support. I would also like to thank David Showalter for allowing me to conduct this study within the design of his own research, providing help and opinion whenever needed, and acting as an overall role model. I thank Amy Hill for providing encouragement and assistance at every step. I thank Dr. Dan Herms for supplying the experimental plot used in this study, and Dr. Larry Phelan for conducting GC-MS analysis of my samples. I would also like to thank Dr. Ron Hendrick for serving on my defense committee. Lastly I would like to thank Dr. Roger Williams for providing essential direction while simultaneously allowing me to figure things out for myself. I could not be happier with where it all has led.

12

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16 Table 1. F-values and P-values from analysis of variance (ANOVA) of within and between-subjects effects for each compound detected by GC-MS analysis.

Variable Source F P Peak 4.185 Within-Subjects Effects Inoculation 21.282 0.002 Inoculation x Block 1.667 0.25 Inoculation x Species 5.327 0.034 Inoculation x Fertility 0.133 0.725 Inoculation x Species x Fertility 2.599 0.135 Between-Subjects Effects Intercept 24.523 0.001 Block 0.528 0.676 Species 2.474 0.146 Fertility 0.195 0.671 Species x Fertility 0.139 0.873 Peak 4.285 Within-Subjects Effects Inoculation 9.001 0.017 Inoculation x Block 0.369 0.778 Inoculation x Species 2.788 0.121 Inoculation x Fertility 0.4 0.545 Inoculation x Species x Fertility 2.678 0.129 Between-Subjects Effects Intercept 8.286 0.021 Block 0.382 0.769 Species 2.203 0.173 Fertility 0.456 0.519 Species x Fertility 0.471 0.64 Peak 4.606 Within-Subjects Effects Inoculation 2.72 0.138 Inoculation x Block 2.195 0.166 Inoculation x Species 1.275 0.331 Inoculation x Fertility 0 0.996 Inoculation x Species x Fertility 0.05 0.952 Between-Subjects Effects Intercept 34.58 0 Block 2.346 0.149 Species 0.339 0.722 Fertility 0.133 0.725 Species x Fertility 0.357 0.711 Peak 4.944 Within-Subjects Effects Inoculation 4.079 0.078 Inoculation x Block 3.342 0.077 Inoculation x Species 2.174 0.176 Inoculation x Fertility 0.424 0.533 Inoculation x Species x Fertility 0.001 0.999 Between-Subjects Effects

17 Intercept 5.096 0.054 Block 1.555 0.274 Species 2.035 0.193 Fertility 0.085 0.778 Species x Fertility 0.906 0.442 Peak 5.227 Within-Subjects Effects Inoculation 3.046 0.119 Inoculation x Block 0.211 0.886 Inoculation x Species 0.143 0.869 Inoculation x Fertility 1.665 0.233 Inoculation x Species x Fertility 0.872 0.454 Between-Subjects Effects Intercept 2.823 0.131 Block 1.886 0.21 Species 1.571 0.266 Fertility 0.285 0.608 Species x Fertility 0.838 0.467 Peak 5.594 Within-Subjects Effects Inoculation 1.23 0.3 Inoculation x Block 0.345 0.794 Inoculation x Species 3.245 0.093 Inoculation x Fertility 0.399 0.545 Inoculation x Species x Fertility 0.67 0.538 Between-Subjects Effects Intercept 14.193 0.005 Block 2.567 0.127 Species 3.387 0.086 Fertility 0.224 0.649 Species x Fertility 2.778 0.121 Alanine Within-Subjects Effects Inoculation 3.443 0.101 Inoculation x Block 1.231 0.36 Inoculation x Species 0.272 0.769 Inoculation x Fertility 1.319 0.284 Inoculation x Species x Fertility 1.525 0.275 Between-Subjects Effects Intercept 105.716 0 Block 1.093 0.406 Species 2.731 0.125 Fertility 1.142 0.316 Species x Fertility 1.641 0.253 Asparagine Within-Subjects Effects Inoculation 7.352 0.027 Inoculation x Block 0.323 0.809 Inoculation x Species 1.265 0.333 Inoculation x Fertility 0.463 0.515 Inoculation x Species x Fertility 0.547 0.599

18 Between-Subjects Effects Intercept 14.135 0.006 Block 0.169 0.914 Species 3.327 0.089 Fertility 0.003 0.956 Species x Fertility 0.203 0.821 Aspartic acid Within-Subjects Effects Inoculation 3.965 0.082 Inoculation x Block 0.713 0.571 Inoculation x Species 0.123 0.886 Inoculation x Fertility 0.29 0.605 Inoculation x Species x Fertility 0.61 0.567 Between-Subjects Effects Intercept 115.406 0 Block 0.749 0.553 Species 4.05 0.061 Fertility 2.89 0.128 Species x Fertility 5.141 0.037 Glutamic acid Within-Subjects Effects Inoculation 79.826 0 Inoculation x Block 0.77 0.542 Inoculation x Species 0.611 0.566 Inoculation x Fertility 0.761 0.408 Inoculation x Species x Fertility 0.827 0.472 Between-Subjects Effects Intercept 82.939 0 Block 1.904 0.207 Species 1.127 0.371 Fertility 1.279 0.291 Species x Fertility 2.583 0.136 Glutamine Within-Subjects Effects Inoculation 2.457 0.156 Inoculation x Block 0.383 0.769 Inoculation x Species 0.019 0.981 Inoculation x Fertility 0.074 0.793 Inoculation x Species x Fertility 0.599 0.572 Between-Subjects Effects Intercept 214.259 0 Block 2.287 0.155 Species 4.57 0.047 Fertility 1.976 0.197 Species x Fertility 6.814 0.019 Glycine Within-Subjects Effects Inoculation 19.461 0.002 Inoculation x Block 2.696 0.117 Inoculation x Species 2.355 0.157 Inoculation x Fertility 0.129 0.729

19 Inoculation x Species x Fertility 0.877 0.452 Between-Subjects Effects Intercept 36.369 0 Block 0.252 0.858 Species 1.213 0.347 Fertility 2.068 0.188 Species x Fertility 1.314 0.321 Isoleucine Within-Subjects Effects Inoculation 16.019 0.004 Inoculation x Block 2.052 0.185 Inoculation x Species 4.188 0.057 Inoculation x Fertility 0.264 0.621 Inoculation x Species x Fertility 1.874 0.215 Between-Subjects Effects Intercept 12.116 0.008 Block 0.592 0.637 Species 1.88 0.214 Fertility 1.368 0.276 Species x Fertility 0.75 0.503 Leucine Within-Subjects Effects Inoculation 7.282 0.027 Inoculation x Block 1.462 0.296 Inoculation x Species 0.879 0.452 Inoculation x Fertility 1.349 0.279 Inoculation x Species x Fertility 1.031 0.4 Between-Subjects Effects Intercept 52.273 0 Block 0.645 0.608 Species 3.086 0.102 Fertility 0.809 0.395 Species x Fertility 1.015 0.405 Lysine Within-Subjects Effects Inoculation 2.551 0.149 Inoculation x Block 0.707 0.574 Inoculation x Species 0.925 0.435 Inoculation x Fertility 0.906 0.369 Inoculation x Species x Fertility 0.849 0.463 Between-Subjects Effects Intercept 21.689 0.002 Block 1.825 0.221 Species 1.813 0.224 Fertility 2.172 0.179 Species x Fertility 1.629 0.255 Pyroglutamic Acid Within-Subjects Effects Inoculation 2.427 0.158 Inoculation x Block 0.292 0.83 Inoculation x Species 0.028 0.972

20 Inoculation x Fertility 0.441 0.525 Inoculation x Species x Fertility 0.653 0.546 Between-Subjects Effects Intercept 127.271 0 Block 3.489 0.07 Species 4.595 0.047 Fertility 2.929 0.125 Species x Fertility 6.044 0.025 Phenylalanine Within-Subjects Effects Inoculation 0.143 0.716 Inoculation x Block 1.008 0.438 Inoculation x Species 0.068 0.934 Inoculation x Fertility 0.057 0.817 Inoculation x Species x Fertility 2.204 0.173 Between-Subjects Effects Intercept 3.564 0.096 Block 1.024 0.432 Species 1.022 0.403 Fertility 0.04 0.847 Species x Fertility 1.273 0.331 Proline Within-Subjects Effects Inoculation 12.785 0.007 Inoculation x Block 0.493 0.697 Inoculation x Species 1.168 0.359 Inoculation x Fertility 0.08 0.785 Inoculation x Species x Fertility 0.811 0.478 Between-Subjects Effects Intercept 137.302 0 Block 0.346 0.793 Species 6.385 0.022 Fertility 0.007 0.934 Species x Fertility 1.578 0.264 Serine Within-Subjects Effects Inoculation 63.717 0 Inoculation x Block 0.559 0.657 Inoculation x Species 0.883 0.45 Inoculation x Fertility 0.192 0.673 Inoculation x Species x Fertility 0.181 0.838 Between-Subjects Effects Intercept 84.862 0 Block 0.293 0.829 Species 2.06 0.19 Fertility 0.001 0.971 Species x Fertility 1.296 0.325 Threonine Within-Subjects Effects Inoculation 31.987 0 Inoculation x Block 0.549 0.663

21 Inoculation x Species 0.989 0.413 Inoculation x Fertility 0.98 0.351 Inoculation x Species x Fertility 0.077 0.926 Between-Subjects Effects Intercept 71.514 0 Block 0.785 0.535 Species 1.948 0.205 Fertility 1.382 0.274 Species x Fertility 1.24 0.339 Tryptophan Within-Subjects Effects Inoculation 10.04 0.013 Inoculation x Block 0.212 0.885 Inoculation x Species 0.25 0.784 Inoculation x Fertility 0.127 0.731 Inoculation x Species x Fertility 0.038 0.962 Between-Subjects Effects Intercept 12.215 0.008 Block 0.298 0.826 Species 0.107 0.9 Fertility 0.111 0.748 Species x Fertility 0.004 0.996 Tyrosine Within-Subjects Effects Inoculation 4.712 0.062 Inoculation x Block 0.439 0.731 Inoculation x Species 0.288 0.757 Inoculation x Fertility 1.86 0.21 Inoculation x Species x Fertility 2.219 0.171 Between-Subjects Effects Intercept 34.768 0 Block 4.063 0.05 Species 0.884 0.45 Fertility 1.539 0.25 Species x Fertility 3.019 0.105 Tyramine Within-Subjects Effects Inoculation 2.018 0.193 Inoculation x Block 0.425 0.74 Inoculation x Species 2.223 0.171 Inoculation x Fertility 0.006 0.941 Inoculation x Species x Fertility 0.086 0.918 Between-Subjects Effects Intercept 5.827 0.042 Block 1.116 0.398 Species 2.53 0.141 Fertility 0.011 0.92 Species x Fertility 0.188 0.832 Tyrosol Within-Subjects Effects Inoculation 10.844 0.011

22 Inoculation x Block 2.793 0.109 Inoculation x Species 6.152 0.024 Inoculation x Fertility 0.045 0.837 Inoculation x Species x Fertility 2.854 0.116 Between-Subjects Effects Intercept 10.248 0.013 Block 0.305 0.821 Species 1.639 0.253 Fertility 0.149 0.709 Species x Fertility 0.215 0.811 Valine Within-Subjects Effects Inoculation 27.493 0.001 Inoculation x Block 1.01 0.437 Inoculation x Species 1.059 0.391 Inoculation x Fertility 0.564 0.474 Inoculation x Species x Fertility 1.35 0.312 Between-Subjects Effects Intercept 52.995 0 Block 0.722 0.566 Species 2.162 0.178 Fertility 1.908 0.204 Species x Fertility 1.526 0.275 Total Amino Acids Within-Subjects Effects Inoculation 9.812 0.014 Inoculation x Block 0.41 0.751 Inoculation x Species 0.163 0.853 Inoculation x Fertility 0.019 0.893 Inoculation x Species x Fertility 0.585 0.579 Between-Subjects Effects Intercept 146.474 0 Block 2.705 0.116 Species 2.047 0.191 Fertility 0.615 0.455 Species x Fertility 3.541 0.079

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Table 2. Concentrations (mean ± standard error) of compounds detected in GC-MS analysis for each species and attack status. Ash Species/Attack Status Green Manchurian White 1Variables Constitutive Induced Constitutive Induced Constitutive Induced Tyrosol 204.75 ± 166.73 181.40 ± 237.53 53.80 ± 76.35 28.09 ± 23.59 339.23 ± 199.49 116.37 ± 103.68 Amino Acids (nmol/g FW) Alanine 43.75 ± 16.63 37.45 ± 18.39 38.60 ± 20.22 18.11 ± 10.39 27.10 ± 6.33 28.13 ± 16.61 Asparagine 78.50 ± 56.40 10.85 ± 9.79 8.74 ± 8.84 1.23 ± 3.25 29.67 ± 24.86 3.47 ± 5.79 Aspartic acid 772.00 ± 344.18 535.55 ± 399.13 547.34 ± 285.53 329.34 ± 172.86 480.77 ± 130.61 388.97 ± 300.71 Glutamine 411.00 ± 149.80 134.00 ± 99.45 360.14 ± 134.74 64.17 ± 59.23 390.37 ± 121.98 72.43 ± 91.67 Glutamic acid 469.30 ± 153.90 414.85 ± 230.38 451.00 ± 169.60 326.51 ± 197.71 369.93 ± 75.29 274.63 ± 115.09 Glycine 3.25 ± 3.82 1.35 ± 2.7 9.91 ± 5.07 1.06 ± 2.80 5.53 ± 1.03 0.87 ± 2.12 Isoleucine 5.55 ± 4.88 0.00 ± 0.00 1.11 ± 1.91 0.00 ± 0.00 4.63 ± 1.82 2.40 ± 4.07 Leucine 5.30 ± 3.32 3.15 ± 0.64 2.74 ± 2.26 0.80 ± 1.39 4.63± 1.89 3.70 ± 2.04 Lysine 5.00 ± 5.78 6.40 ± 5.29 16.74 ± 8.65 3.49 ± 6.01 8.13 ± 3.78 5.87 ± 12.17 Pyroglutamic acid 135.75 ± 60.75 111.85 ± 68.95 126.03 ± 70.52 81.97 ± 65.92 95.80 ± 40.32 73.60 ± 22.84 Phenylalanine 2.20 ± 2.59 1.45 ± 2.90 4.51 ± 4.46 2.49 ± 4.25 1.67± 2.66 3.63 ± 8.90 Proline 13.15 ± 5.93 6.55 ± 2.27 5.89 ± 2.81 2.80 ± 2.34 8.80 ± 2.79 4.27 ± 1.55 Serine 124.50 ± 31.14 15.40 ± 11.62 87.06 ± 43.59 7.49 ± 12.79 87.37 ± 23.99 7.33 ± 11.64 Threonine 34.00 ± 13.13 8.75 ± 3.01 22.54 ± 11.23 3.49 ± 4.63 26.73 ± 11.60 9.23 ± 2.75 Tryptophan 20.20 ± 15.24 1.45 ± 1.00 16.34 ± 18.64 1.49 ± 2.70 23.63 ± 13.34 0.33 ± 0.82 Tyrosine 8.70 ± 3.63 5.75 ± 2.37 11.46 ± 7.82 6.97 ± 9.92 10.97 ± 6.53 5.80 ± 6.0 Valine 24.50 ± 11.42 9.30 ± 3.36 13.97 ± 7.99 2.46 ± 4.32 20.93 ± 8.81 11.63 ± 7.20 2919.90 ± 1975.00 ± 2175.49 ± 1127.80 ± 2558.60 ± 1346.57 ± Total free AA 737.91 862.16 1218.46 834.30 828.88 479.78 Non-Amino Acid Amines (nmol/g FW) Peak 4.185 346.70 ± 217.86 203.25 ± 204.54 117.74 ± 112.55 54.43 ± 43.38 460.27 ± 189.66 159.97 ± 112.47 Peak 4.285 188.50 ±89.40 94.20 ± 188.40 0.00 ± 0.00 0.00 ± 0.00 178.93 ± 109.47 76.63 ± 84.55 Peak 4.606 190.05 ± 141.51 184.30 ± 79.34 156.66 ± 166.04 76.66 ± 59.65 275.47 ± 162.25 98.17 ± 13.70 Peak 4.944 38.00 ± 44.39 15.90 ± 31.80 0.00 ± 0.00 0.00 ± 0.00 47.27 ± 58.87 11.47 ± 17.79 Peak 5.227 0.00 ± 0.00 98.25 ± 100.57 101.17 ± 134.07 119.95 ± 211.01 0.00 ± 0.00 81.47 ± 103.72 Peak 5.594 0.00 ± 0.00 75.00 ± 86.86 75.77 ± 88.89 22.91 ± 29.28 0.00 ± 0.00 22.57 ± 25.31 Tyramine 5.25 ± 1.25 9.50 ± 7.71 63.63 ± 61.48 2.40 ± 4.16 7.30 ± 4.11 1.87 ± 2.96 1Concentrations of SAR, ABA, BAIB, aILE, HIS, MET, HYP, AAA, ORN and C-C were below the detection limit in all ash species and were thus excluded from statistical analysis.

24 Figures

Figure 1.

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Figure 2.

26 Figure 3.

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Figure Legends

Figure 1. Mean total free amino acid concentrations between species before and after attack. Concentrations were significantly lower in induced samples. No other significant interactions were observed based on repeated measures ANOVA at P<0.05. Error bars = +/- 1 standard error.

Figure 2. Comparison of EAB larval feeding efficiency index between species. Feeding efficiency index is the ratio of the average gallery terminal width in millimeters to the average gallery length in centimeters for each individual tree. Letters indicate significant difference between species according to Kruskal-Wallis H test with all pairwise multiple comparisons, p <0.01. Manchurian and white n=12, green n=15. Figure 3. Comparison of induced mean total free amino acid concentration to FEI (gallery terminal width/length). No significant relationship was observed (P = 0.934).

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