Metabolic Response of Strawberry (Fragaria x ananassa) Leaves

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Metabolic response of strawberry (Fragaria x ananassa) leaves exposed to the Angular leaf spot bacterium (Xanthomonas fragariae) Min-Sun Kim, Jong Sung Jin, Youn-Sig Kwak, and Geum-Sook Hwang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.5b05201 • Publication Date (Web): 18 Feb 2016 Downloaded from http://pubs.acs.org on February 19, 2016

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Journal of Agricultural and Food Chemistry

Metabolic response of strawberry (Fragaria x ananassa) leaves exposed to the Angular leaf spot bacterium (Xanthomonas fragariae)

Min-Sun Kim†, Jong Sung Jin≠, Youn-Sig Kwak§, and Geum-Sook Hwang*†,‡

†Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 120-140, Republic of Korea ≠Busan

§

Center, Korea Basic Science Institute, Busan 609-735, Republic of Korea

Department of Plant Medicine & RILS, Gyeongsang National University, Jinju 52828,

Republic of Korea ‡

Chemistry & Nanoscience, Ewha Womans University, Seoul 120-750, Republic of Korea

* Corresponding Authors Geum-Sook Hwang: Korea Basic Science Institute, Seoul 120-140, Korea. Phone: +82-26908-6200. Fax: +82-2-6908-6239. E-mail:[email protected].

ACS Paragon Plus Environment


ABSTRACT 1

Plants have evolved various defense mechanisms against biotic stress. The most common mechanism

2

involves the production of metabolites that act as defense compounds. Bacterial angular leaf spot

3

disease (Xanthomonas fragariae) of the strawberry (Fragaria x ananassa) has become increasingly

4

destructive to strawberry leaves and plant production. In this study, we examined metabolic changes

5

associated with the establishment of long-term bacterial disease stress using UPLC-QTOF mass

6

spectrometry. Infected leaves showed decreased levels of gallic acid derivatives and ellagitannins,

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which are related to the plant defense system. The levels of phenylalanine, tryptophan, and salicylic

8

acid as precursors of aromatic secondary metabolites were increased in inoculated leaves, whereas

9

levels of coumaric acid, quinic acid, and flavonoids were decreased in infected plants, which are

10

involved in the phenylpropanoid pathway. In addition, phenylalanine ammonia-lyase (PAL) activity, a

11

key enzyme in the phenylpropanoid pathway, was decreased following infection. These results

12

suggest that long-term bacterial disease stress may lead to down-regulation of select molecules of the

13

phenylpropanoid metabolic pathway in strawberry leaves. This approach could be applied to explore

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the metabolic pathway associated with plant protection/breeding in strawberry leaves.

15 16

KEYWORDS: Metabolic profiling, defense mechanism, strawberry leaves, bacterial angular

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leafspot, UPLC-QTOF/MS


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INTRODUCTION

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Plants are constantly exposed to various biotic and abiotic environmental challenges throughout

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their life cycle. To compensate for their lack of mobility, plants have to develop efficient and

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polyvalent biochemical defense mechanisms to cope with these continuous threats1. Infection by a

22

pathogen is the most-studied inducer of plant defense responses. Plants produce a variety of

23

metabolites, and many metabolic pathways have evolved to confer selective advantages during

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pathogen attacks2.

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The strawberry (Fragaria × ananassa) is the most widely cultivated fruit plant in the world,

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consumed for both its pleasant flavor and nutritional content.3,4 Strawberries are an important source

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of health-promoting compounds.5 However, this crop originates from a plant species susceptible to a

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large variety of phytopathogenic organisms.4,6 The strawberry angular leaf spot disease, caused by the

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bacterium X. fragariae, is the only important bacterial disease that affects the strawberry.7 The disease

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was first reported in Minnesota in 1960 and has since spread to strawberry-growing areas

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worldwide.7,8 The disease has been responsible for major strawberry production losses.8 Strawberry

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plants that are systemically inoculated have bacteria present in their vascular system. Infection is

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generally symptomless when the bacterium is first introduced; however, the bacteria become active in

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systemically infected plants, leading to the development of disease symptoms under high relative

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humidity, moderate daytime temperatures (~68°F), and night time temperatures near freezing.9

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Metabolite profiling is an essential part of plant science, because it can analyze simultaneously

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primary and secondary compounds related to plant defense mechanisms10. In general, metabolomics

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concerns both the qualitative and quantitative analysis of all metabolites in organisms.11 Changes in

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the levels of metabolites are indicators of biotic or abiotic stress related to specific environmental

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circumstances.12

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Plants produce a large variety of compounds that are chemically diverse and present in a wide range

42

of concentrations.10 To analyze as many metabolites as possible simultaneously in a single step, an

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optimized method for sample analysis is required. Mass spectrometry (MS) combined with

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chromatography has become a typical analytical approach for metabolomics.10,13 Mass analyzer



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quadrupole-time-of-flight MS (QTOF/MS) provides high resolution and mass accuracy in both MS

46

profiling and MS/MS analysis.14 Ultra-performance liquid chromatography (UPLC) has been applied

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to improve the resolution, peak efficiency, and separation speed for complex matrices.15 For

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quantitative analysis of targeted metabolites, UPLC-QTOF/MS-multiple reaction monitoring (MRM)

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mode is applied, and specific transition ions were selected to reduce any potential matrix effects.16

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Recently, various studies have been conducted concerning metabolic changes in plants in response

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to plant pathogens, such as Vitis vinifera/Plasmopara viticola,17 tomato/Pseudomonas syringae,18

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Arabidopsis thaliana/Pseudomonas syringae,19 soybean/Colletotrichum gloeosporioides,20 and

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soybean/Fusarium tucumaniae.21 However, less is known regarding changes in the metabolic profile

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of the strawberry in response to X. fragariae. In addition, most of plant-pathogen interaction studies

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have focused on short-term infection (less than 7 days post-infection). The most common feature is

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the induction of metabolites, such as phenolic compounds, by defense mechanisms.19, 20, 22 Here, we

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hypothesized that different changes in metabolites related to the plant defense system may occur in

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infected plants that have visible symptoms caused by long-term bacterial inoculation (over 2 weeks

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post-infection). Thus, the current study evaluated the metabolome of strawberry leaves and identified

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variations in the levels of important metabolites in response to long-term infection with X. fragariae.

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This study included (a) identification of diverse metabolites present in strawberry leaves, based on the

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interpretation of high-resolution mass value and MS/MS spectra from UPLC-QTOF/MS, (b)

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quantification of significant metabolites involved in bacterial infection, using QTOF/MS-MRM mode,

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and (c) interpretation of these data to identify pathogen-responsive pathways in strawberry leaves.


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MATERIALS AND METHODS

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Chemicals. Organic solvents of HPLC grade (acetonitrile, methanol, and ethanol) were purchased

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from Burdick & Jackson (Muskegon, MI, USA). Formic acid, bicinchoninic acid (BCA) protein assay,

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and PAL activity reagents were obtained from Sigma Chemical (St. Louis, MO, USA). Distilled water

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was obtained from a Milli-Q system (Millipore, Bedford, MA, USA). All other chemicals and

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solvents were of the highest analytical grade available.

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All authentic standards and catechin-13C3, used as a recovery internal standard, were provided by

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Sigma Chemical (St. Louis, MO, USA). The purities of these compounds were greater than 95%.

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Stock solutions were prepared by dissolving the chemical in water or methanol at a concentration of 1

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mg/mL and diluting with ethanol/water (70:30, v/v) when necessary. All stock solutions were stored

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at −20°C until analysis.

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Plant materials. Strawberries (Fragaria x ananassa) were cultivated for 3 months in several

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commercial farm greenhouses (Garden K, A, B, and C) in the Republic of Korea. Same age nursery

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plants were transplanted to the greenhouse in late August. The following growth conditions were

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used: relative humidity 85-95% (night-day), daylight 16 h, and temperature 18-20°C (night-day).

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Strawberry angular leaf spot disease, caused by X. fragariae, occurred by natural infection at the

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greenhouse. It is predicted that initial infections progressed from nursey plants through runners and

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irrigation water treatment. The strawberry leaves were harvested at maturity and divided into three

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groups (DI 0, DI 1-2, and DI 3-4) according to the angular leaf spot disease severity. To reduce leaf

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aging bias, we collected similarly sized leaves and many leaves for technical replication with three

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biological replications. Inoculation sites were evaluated and rated using the following criteria: DI 0 =

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no symptoms of angular leaf spot disease; DI 1 = water-soaking evident in one leaf; DI 2 = slight

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chlorosis or necrosis in one leaf; DI 3 = water soaking spreading to three or five leaves; DI 4 =

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necrosis spreading to three or five leaves and/or secondary infections evident; DI 5 = necrosis and a

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change in leaf color from chlorotic yellow to reddish-brown.23 Briefly, DI 0 is the non-symptomatic

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sample group and DI 1-2 and 3-4 are the infected sample groups. After harvesting, pooled whole-leaf



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samples were placed on ice immediately and frozen as soon as possible. Strawberry leaves were

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stored at -70°C until further processing.

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Sample preparation. Freeze-dried strawberry leaves (50 mg) were placed in a 1.5 mL microfuge tube

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to which 1 mL ethanol/water (70:30, v/v) was added. The sample was vortexed for 1 min and

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ultrasonicated for 30 min. The extract was then centrifuged at 13000 rpm for 20 min at 4°C. The

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supernatants were filtered through a 0.22 µm PTTE syringe filter (Millipore). The filtered extract was

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analyzed using UPLC-QTOF/MS.

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UPLC-QTOF/MS analysis and data processing. All UPLC-QTOF/MS analyses were performed

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using an ACQUITY UPLC I-Class system (Waters Corporation, Milford, MA, USA) coupled with an

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Impact HD mass spectrometer (Bruker Daltonik, Bremen, Germany), equipped with an electrospray

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ionization (ESI) source. Chromatographic separation analysis was carried out using an Acquity UPLC

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HSS T3 column (2.1 mm × 100 mm, 1.7 µm; Waters) at 40°C; a binary gradient separation was

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performed at a flow rate of 0.45 mL/min. The mobile phases consisted of solvent A (0.1% formic acid

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in water) and solvent B (0.1% formic acid in acetonitrile). The gradient profile was a 0–2 min linear

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increase in B from 1% to 5%; 2-10 min linear increase in B from 5% to 30%; 10-14 min linear

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increase in B from 30% to 50%; 14-16 min linear increase in B from 50% to 99%; 16–18 min held at

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99% B, and 18-20 min (post-acquisition time) starting mobile phase 1% B to re-equilibrate the

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column. The total run-time for each injection was 18 min, and the injection volume was 5 µL. The

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mass spectrometer was operated in negative and positive ionization modes and acquired data in the

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mass range from 50 to m/z 1100 with a sampling rate of 2 Hz. In negative mode, the capillary was set

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at +4500 V, the end plate offset at −500 V, the nebulizer gas at 1 bar and the dry gas at 12 L/min at

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200°C. The MS/MS analyses were acquired by automatic fragmentation, in which the five most

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intense mass peaks were fragmented. Collision energy values for MS/MS experiments were adjusted

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as follows: m/z 100, 12 eV; m/z 300, 20 eV; m/z 500, 30 eV; m/z 1000, 45 eV. Nitrogen was used as

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the drying, nebulizing, and collision gas.

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External calibration was performed using 10 mM sodium formate solution. The calibration solution

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was injected at the beginning of the run, and all spectra were calibrated prior to carrying out


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compound identification. Data acquisition and processing were performed using Hystar 3.2 and

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DataAnalysis 4.2 (Bruker Daltonik) software. Peaking finding, peak alignment, and peak filtering of

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raw data were carried out using Progenesis QI (NonLinear Dynamics, NC, USA) software.

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For targeted analysis, UPLC-QTOF/MS-MRM mode was used to quantify 12 compounds

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selectively. Chromatographic separation was performed using an Acquity UPLC HSS T3 column (2.1

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mm × 5 mm, 1.7 µm; Waters). The flow rate and injection volume were set at 0.45 mL/min and 5 µL,

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respectively. Mobile phase A consisted of 0.1% formic acid in water, and phase B consisted of 0.1%

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formic acid in acetonitrile. The linear gradient elution was as follows: 0-6 min, 1-50% B; 6-7 min, 50-

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99% B; 1 min, isocratic 99%; 8-9 min, 99-1% B; 1 min, isocratic 1% B. In the case of gallic acid and

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quinic acid, a 100-mm-length Acquity UPLC HSS T3 column was used for quantification to

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accommodate the short retention time.

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The MRM conditions were optimized by infusion of each of the standards (100 ng/mL in 50%

131

methanol) into the ESI source in positive and negative ion modes. The selection criteria of the product

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ions were set to choose the most intense ions, to increase the specificity of product ions, and to

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minimize the level of background signals. The retention times and MRM transitions of the compounds

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are summarized in supporting information Table S1.

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Statistical methods. Differences among the strawberry leaf samples were analyzed by ANOVA

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(SPSS 12.0. SPSS Inc., H, Chicago, IL USA. The Bonferroni test and Mann-Whitney test were

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performed to determine differences between specific groups. Differences were considered significant

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at the 95% probability level (p < 0.05).

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Phenylalanine ammonia-lyase activity. Enzyme activity was measured as described by Phimchan et

140

al.24 Briefly, 0.5 g fresh frozen leaf was extracted with 1.5 mL 50 mM Tris-HCl buffer (pH 8.8)

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containing 1 mM EDTA, 15 mM β-mercaptoethanol, and 50 mM ascorbic acid. The mixture was

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centrifuged at 13000 rpm for 30 min at 4°C. The protein concentration of the sample was measured

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using the BCA assay, with bovine serum albumin (BSA) as the standard.25 Reaction mixtures,

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containing 0.1 mL enzyme extract, 1 mL 100 mM Tris-HCl buffer (pH 8.8), 0.5 mL 10 mM L-

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phenylalanine, and 0.4 mL deionized water were incubated for 1 h at 37°C. The enzyme reaction was



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stopped by adding 0.5 mL 6 M HCl. The sample absorbance was measured at 290 nm using an

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Infinite® 200 PRO spectrophotometer (Tecan, Männedorf, Switzerland). The calibration curve was

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generated using cinnamic acid, and the blank had the same constituent mixture as the sample.

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RESULTS AND DISCUSSION

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The disease severity indicated by the infected leaves was classified and rated according to Maas et

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al. (2000). In our model, DI 1-2 and DI 3-4 indicate inoculation periods of around 2 weeks and over 3

154

weeks, respectively. The disease-processing period of our infected samples was consistent with long-

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term infection.

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Identification of metabolites in strawberry leaves. To identify differences in metabolite

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composition between non-symptomatic and infected strawberry leaves, non-targeted metabolite

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profiling of extracts was conducted. The extracts of the leaves were analyzed by high-resolution

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UPLC-QTOF/MS. Principal components analysis (PCA) was performed on MS spectra to assess the

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intrinsic variation between the non-symptomatic and infected leaves. The PCA score plots derived

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from positive (supporting information Figure S1A) and negative (supporting information Figure S1B)

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modes showed clear separation along the first principal component of non-symptomatic and infected

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leaves (positive, R2 = 0.664, Q2 = 0.246; negative, R2 = 0.738, Q2 = 0.538). However, the difference in

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disease severity was negligible with respect to PCA score plots, in both polarity modes.

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The identification of metabolites related to infection was confirmed by high-resolution MS analysis

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using QTOF/MS, allowing elucidation of the corresponding molecular formulae. Metabolites were

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identified as phenolic acids, amino acids, and kynurenic acid by comparing their retention times and

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MS/MS spectral data to those of authentic standards. Other phenolic classes, such as gallic acid

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derivatives, ellagitannins, and flavonoids, were tentatively identified by performing exact mass

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measurement of molecular ions and fragment ions, with reference to previously published data.26-29 A

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retention time closely matching the expected value was also needed for tentative identification of

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these metabolites. The assigned peaks observed in the total ion chromatograms (TIC, both positive

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and negative mode) are indicated in Figure 1, and the metabolite names corresponding to each number

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are presented in Table 1.

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Gallic acid conjugates, ellagitannins, and flavonoids were mainly identified in TICs of strawberry

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leaves. Mass measurement error (difference between observed mass and theoretical mass) of [M+H]+



177

or [M-H]- ions were within 12.2 ppm.

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Peaks 1, 2, and 3 in strawberry leaf extracts were identified as galloyl glucose, gallic acid, and

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trigalloyl glucose, respectively. The largest peak was gallic acid, which is characterized by the

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presence of a product ion at m/z 125, resulting from the loss of carboxylic acid. The characteristic ion

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of galloylglucose is observed at m/z 169 and is formed by the loss of a hexose moiety. Trigalloyl

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glucose is identified by the presence of a product ion at m/z 465, representing the loss of gallic acid

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moieties from the [M-H]- ion. All of these compounds have been detected previously in the

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strawberry.26 The relative levels of galloyl compounds in infected samples were lower than in non-

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symptomatic samples (below 0.47-fold).

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Ellagitannins are polyphenolic compounds with a sugar core that exhibit typical features. Four

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ellagitannins (peaks 4-7) were detected in strawberry leaves. These compounds were reported in

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strawberries in previous studies.30,31 Each compound was tentatively identified based on the loss of

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gallic acid moieties, a hexahydroxydiphenyl (HHDP) unit, and a sugar unit.30 The MS/MS spectrum

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of galloyl-HHDP-glucose exhibited fragment ions at m/z 463 and m/z 301, corresponding to [M-H-

191

gallic acid]- and [M-H-gallic acid-hexose]-, respectively. The most characteristic ions of bis-HHDP-

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glucose and casuarictin are formed by the loss of a HHDP unit at m/z 481 and 633, respectively.31

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Ellagic acid yielded fragment ions at m/z 257 and 229 in negative mode. The relative levels of

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ellagitannins were significantly decreased in inoculated leaves compared with non-symptomatic

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leaves (0.41- to 0.72-fold) (Table 1). In previous reports, a strong positive correlation between gallic

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acid and ellagitannins was observed, which is consistent with the fact that these compounds are

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produced through the same biosynthesis pathway.27

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In agreement with previous reports, various flavonoids were detected in strawberry leaves.27,28

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Flavonoids in plants are commonly substituted with one or several sugar moieties. In this study, the

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flavonols kaempferol and quercetin were observed to be conjugated with several sugars in strawberry

201

leaves. Sugar moieties were identified and classified as hexose, glucuronide, and pentose sugar. The

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9-14 peaks in positive ion mode and 15-21 peaks in negative ion mode were identified as derivatives

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of kaempferol and quercetin, respectively. The most prevalent ions of kaempferol and quercetin


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conjugates were produced by the loss of a sugar moiety. The aglycones of kaempferol and quercetin

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were detected as the predominate ions at m/z 287 and m/z 301, respectively. Kaempferol coumaroyl

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hexose is formed via acylation of the sugar moiety with hydroxycinnamic acid.26 The characteristic

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ions of the loss of kaempferol and the coumaroyl hexose moiety from [M+H]+ were detected at m/z

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309 and 287 in positive ion mode, respectively. Also, a common product ion at m/z 147 was observed

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for coumaroyl moieties.27,32 Catechin, a flavan-3-ol, was tentatively identified based on the presences

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of a m/z 139 ion in positive mode, which is thought to represent the loss of a galloyl moiety.33 In

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infected leaf samples, almost all kaempferol and quercetin derivative levels were decreased. However,

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some quercetin derivatives, such as quercetin dihexose and quercetin pentose glucuronide, were

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increased (1.46- and 1.23-fold, respectively) in infected leaves. Catechin was remarkably decreased

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(below 0.49-fold) after inoculation.

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Metabolite quantification in strawberry leaves. Based on global profiling data, the quantities of

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important metabolites related to bacterial infection of the strawberry leaf were determined

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quantitatively by UPLC-QTOF/MS. Targeted analyses of quinic acid, gallic acid, coumaric acid,

218

ellagic acid, and salicylic acid as phenolic acids; of catechin, quercetin, quercetin hexose, and

219

kaempferol as flavonoids; of phenylalanine and tryptophan as an amino acid and kynurenic acid were

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conducted for non-symptomatic and infected leaf samples.

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Quantification of analytes was performed using MRM mode for high selectivity and sensitivity of

222

acquisition data. Based on the MS/MS fragment pattern, the MRM ion transitions were selected to

223

provide the best signal-to-noise ratio for individual metabolites (supporting information Table S1).

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The quantitative ions of quinic acid, ellagic acid, salicylic acid, and kaempferol were selected with

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their precursor ions because of their higher intensity relative to the product ions. The chemical

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structure and product ion mass spectra of targeted metabolites are presented in supporting information

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Figure S2.

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Calibration standards with the appropriate range of each compound were generated using a

229

combined standards solution. Supporting information Table S2 shows the equations for the calibration

230

curves and the linear regression coefficients for the targeted metabolites. The calibration curves were



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generated using a linear least squares regression analysis of the analyte/IS peak area ratio. The

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correlation coefficients (R2) for all of the compounds were greater than 0.99, indicating excellent

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linearity.

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A total of 12 metabolites in strawberry leaf samples were quantitated using the established method.

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Typical total ion chromatograms and MRM chromatograms of the targeted metabolites extracted from

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strawberry leaves obtained by UPLC-QTOF/MS-MRM mode are shown in Figure 2. Quinic acid and

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gallic acid were detected using a 100 mm column due to their fast elution pattern. Consequently, their

238

compounds were not assigned in the TIC of negative mode. The targeted metabolites in strawberry

239

leaf extract with complicated matrices were clearly detected and accurately quantified without any

240

interfering peaks. To quantify the metabolites, the most abundant transition ion in the MRM mode

241

was selected for integration of the peak area against the internal standard. The Catechin-13C3

242

compounds were used as internal standards for both positive and negative mode, which improved the

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precision and accuracy of the quantification.

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The levels of metabolites affected by the infection are shown in supporting information Table S3.

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Confirmation of metabolite identity was achieved on the basis of retention times and the MRM

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transition ions, compared with those of standards in UPLC-QTOF/MS-MRM mode.

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Changes in metabolite levels associated with X. fragariae infection. Figure 3 depicts the

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variation in the levels of significant metabolites in strawberry leaves upon X. fragariae infection. The

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levels of tryptophan, kynurenic acid, salicylic acid and phenylalanine were increased in the infected

250

leaves. This correlation was expected, because these compounds are formed from the same

251

biosynthetic pathway, which depends on the metabolic flux of shikimic acid (Figure 4). Phenylalanine

252

and tryptophan serve as precursors of a wide variety of aromatic secondary metabolites, such as

253

alkaloids, flavonoids, and lignins, which play crucial roles in plant defense against bacterial attack.34

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Increased levels of phenylalanine and tryptophan are commonly reported in plant leaves following

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pathogen attacks.19,35 Kynurenic acid is formed along the tryptophan–kynurenine pathway. Through

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the kynurenine pathway, tryptophan may be partly metabolized to kynurenic acid and kynurenine

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pathway metabolites, which serve as an indirect plant defense mechanism against fungi, pathogens,


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and herbivorous parasites.36,37 Salicylic acid is derived from the shikimate pathway and is an

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important signaling molecule in the induction of plant disease resistance.38 Furthermore, salicylic acid

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activates the production of reactive oxygen species and other defensive processes, such as

261

hypersensitive response and cell death.39 Therefore, accumulation of tryptophan, kynurenic acid,

262

salicylic acid, and phenylalanine is expected as part of the strawberry’s defense response.

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In the shikimate pathway, a major branch point occurs at 3-dehydroshikimic acid. Through one

264

branch, shikimic acid is produced via dehydration and reduction steps, whereas through the other

265

branch, gallic acid is formed by dehydrogenation. Gallic acid is antimicrobial and is frequently the

266

starting material for hydrolysable tannin synthesis, which inhibits herbivore activity.40 In our study,

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shikimic acid and gallic acid metabolism followed a different pattern. While gallic acid and the

268

ellagitannins were significantly decreased in infected leaf samples (0.23- to 0.72-fold), shikimate

269

pathway compounds were increased (1.28- to 4.97-fold) (Figure 3 and Table 1). Thus, there may be

270

competition between the synthesis of shikimic acid and gallic acid41, which could explain the weaker

271

induction of gallic acid derivatives and ellagitannins.

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Ellagic acid is a natural phenolic antioxidant and antiviral compound found in numerous fruits and

273

vegetables.42,43 Most of the ellagic acid content of plant cells exists in vacuoles as hydrolysable

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ellagitannins.44 Ellagitannins yield ellagic acid upon hydrolysis of the HHDP group.44 In our study,

275

ellagic acid levels were correlated positively with ellagitannins in response to bacterial infection.

276

In the phenylpropanoid pathway, the content of phenolic compounds, such as coumaric acid and

277

quinic acid, were found to be reduced in infected plants. The synthesis of coumaric acid starts with the

278

removal of phenylalanine to produce cinnamic acid (Figure 4). Cinnamic acid can be hydroxylated to

279

produce coumaric acid. A wide variety of chemically diverse phenylpropanoids are generated from

280

coumaric acid, including flavonoids involved in plant defense mechanisms.45 Furthermore, coumaric

281

acid and quinic acid are associated with the production of chlorogenic acid.46 In plants, chlorogenic

282

acid has strong antibacterial activity by triggering the loss of important barrier functions in

283

pathogens47 and by reducing the effects of melanin production on the growth of fungus.48 Thus,

284

decreasing coumaric acid and quinic acid could seriously compromise local disease resistance.



285

Flavonoids represent one of the largest classes of phenylpropanoids, which are involved in a

286

multitude of physiological functions.4 Flavonoids are very important in plant resistance against

287

pathogenic bacteria and fungi.49 Flavonoid compounds are transported to the site of inoculation to

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induce the hypersensitivity reaction, which is the earliest defense mechanism employed by infected

289

plants.50 In our study, the concentration of catechin, a flavan-3-ol, was strongly decreased in infected

290

leaves (about 70% less). Supporting information Table S3 shows that the levels of quercetin and

291

kaempferol were reduced in response to bacterial infection in strawberry leaves (about 30% less).

292

These effects are assumed to be connected to downregulation of the phenylpropanoid pathway in

293

strawberry leaves after X. fragariae inoculation.

294

To probe the potential down-regulation of the phenylpropanoid pathway further, PAL enzyme

295

activity was assayed in non-symptomatic and infected leaves. PAL is a key enzyme of the

296

phenylpropanoid pathway that plays an important regulatory role in controlling the biosynthesis of all

297

phenylpropanoid products.51-53 In a previous study, transgenic tobacco with suppressed levels of PAL

298

was associated with inhibition of the accumulation of phenylpropanoid products.54 In our study, the

299

PAL activity of infected plants was demonstrated to be lower than that in non-symptomatic leaves

300

(Figure 5). This suggests that the reduction in concentration of phenylpropanoid products is related to

301

the down-regulation of PAL activity in strawberry leaves.

302

In our study, although strawberry leaves were infected by a bacterial pathogen, the levels of PAL

303

and phenylpropanoids were decreased following X. fragariae infection. We suggest that one of the

304

factors influencing the down-regulation of phenylpropanoid metabolism is the inoculation period. As

305

we described, leaf samples infected by X. fragariae for over 2 weeks can be considered to be

306

experiencing long-term. In a previous study, the accumulation of chlorogenic acid and rutin in tomato

307

leaves upon introduction of the bacterial pathogen Pseudomonas syringae was increased until 48 h

308

and was decreased remarkably until 5 days after infection. Visible symptoms, such as necrotic brown

309

spots and the death of inoculated tissues did not appear until 72 h after infection.22 In another study,

310

induction of PAL activity was detected in inoculated plants within 50 h, a short inoculation period.55 In

311

plant passive defense mechanisms, phenolic compounds build biological barriers and act locally


Page 14 of 37

Page 15 of 37


312

during the very early stages of pathogen invasion.2 Taken together, our data suggest that the

313

mechanism of action of phenylpropanoid in the context of long-term infection might be different from

314

that of short-term infection.

315

To confirm the changes in metabolite levels in strawberry leaves in response to long-term bacterial

316

exposure, plants were sampled from several different regions. The leaf levels of significant

317

metabolites related to X. fragariae infection (supporting information Figure S3 and supporting

318

information Table S4) were quantified for each garden. In gardens A, B, B1, and C, the cultivated

319

strawberry species was the same as that in garden K, and the plants were naturally infected with

320

bacterial pathogen X. fragariae in the greenhouse. Following disease scoring, the leaves were divided

321

and collected into two groups, DI 0 and DI 3-4. In all of the gardens, the levels of gallic acid,

322

coumaric acid, catechin, and quinic acid decreased after infection; however, phenylalanine, salicylic

323

acid, tryptophan, and kynurenic acid were accumulated in infected strawberry leaves in all cases. The

324

levels of metabolites were consistent with the levels observed in strawberry leaves in garden K. These

325

data support the conclusion that long-term bacterial infection leads to down-regulation of the

326

phenylpropanoid pathway, even though their precursor compounds are induced.

327

In this study, we conducted metabolite profiling of strawberry leaves using UPLC-QTOF/MS to

328

examine the effects of angular leaf spot disease. The characterization of metabolites related to

329

infection was confirmed by high-resolution MS/MS analysis, complemented by the calculation of the

330

corresponding molecular formulae. Quantification of compounds was performed using MRM mode

331

for high selectivity and sensitivity of acquisition data. Bacterial infection leads to the synthesis of

332

precursors of aromatic secondary metabolites related to the plant defense system; however, levels of

333

phenolic compounds in the phenylpropanoid pathway were decreased in infected leaves. A

334

corresponding reduction in the activity of the PAL enzyme was observed in infected leaves. These

335

data are indicative of down-regulation of select elements of phenylpropanoid metabolism in the

336

strawberry in response to long-term bacterial infection. To the best of the authors’ knowledge, this is

337

the first report to provide information concerning metabolic changes triggered by long-term X.

338

fragariae infection in strawberry leaves. The present study increases our understanding of the



339

metabolic pathway involved in plant protection and breeding, supporting the possible application of

340

metabolomics analysis to determine a wide range of pathogen-induced plant metabolites.


Page 16 of 37

Page 17 of 37


ASSOCIATED CONTENT 341

Supporting Information

342

Additional figures and tables. This material is available free of charge via the Internet at

343

http://pubs.acs.org.

344 345

AUTHOR INFORMATION

346

Corresponding Author

347

*(G.-S.H.) Phone: +82-2-6908-6200, fax: +82-2-6908-6239, email: [email protected].

348 349

Funding

350

This study was supported by the National Research Foundation of Korea (NRF) funded by the

351

Ministry of Science, ICT & Future Planning, Korea (2013M3A9B6046418), the National Research

352

Council of Science and Technology (DRC-14-3-KBSI and the Creative Allied Project (CAP)), and the

353

Korea Basic Science Institute (C36705 and T35622).

354 355

Notes

356

The authors declare no competing financial interest.



357

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Figure captions

506 507

Figure 1. Total ion chromatograms in (A) ESI-positive and (B) ESI-negative modes from

508

UPLC-QTOF/MS of strawberry leaves.

509

Figure 2. Total ion chromatograms and MRM chromatograms of strawberry leaf extracts under

510

(A) positive ionization and (B) negative ionization.

511

Figure 3. Variation in metabolite levels in non-symptomatic strawberry leaves and strawberry

512

leaves infected with X. fragariae in Garden K. (A) gallic acid, (B) coumaric acid, (C) catechin,

513

(D), quinic acid, (E) phenylalanine, (F) salicylic acid, (G) L-tryptophan, and (H) kynurenic acid.

514

Vertical lines indicate standard deviation (n = 6). Significance levels on pairwise comparisons

515

compared with the non-symptomatic samples are defined as * p < 0.05, **p < 0.01, ***p

Metabolic Response of Strawberry (Fragaria x ananassa) Leaves

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