A Targeted Mass Spectrometry-based Metabolomics Approach toward

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A Targeted Mass Spectrometry-based Metabolomics Approach toward the Understanding of Host Responses to Huanglongbing Disease Wei-Lun Hung, and Yu Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b04033 • Publication Date (Web): 16 Sep 2018 Downloaded from http://pubs.acs.org on September 18, 2018

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Journal of Agricultural and Food Chemistry

A Targeted Mass Spectrometry-based Metabolomics Approach toward the Understanding of Host Responses to Huanglongbing Disease

Wei-Lun Hung,†‡ and Yu Wang*†

†Citrus Research and Education Center, Department of Food Science and Human Nutrition, University of Florida, Lake Alfred, FL 33850, USA ‡School of Food Safety, Taipei Medical University, 250 Wu-Hsing Street, Taipei, 11031, Taiwan

*Please send all correspondence to: Dr. Yu Wang Citrus Research and Education Center Department of Food Science and Human Nutrition University of Florida 700, Experiment Station Rd, Lake Alfred, FL 33850 USA Phone: 863-956-8673 Fax: 863-956-4631 E-mail: [email protected]

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ACS Paragon Plus Environment


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ABSTRACT

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Candidatus Liberibacter asiaticus (CLas) is the major culprit of Huanglongbing (HLB), the most

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destructive citrus disease worldwide. Polymerase chain reaction (PCR) is the most common

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method for detecting the presence of CLas in the tree. However, due to uneven distribution of

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bacteria and a minimum bacterial titer requirement, an infected tree may test false negative. Thus,

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our current study profiled primary and secondary metabolites of CLas-free leaves harvested from

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citrus undercover protection system (CUPS) to prevent a misjudgment of CLas infection.

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Functional enrichment analysis revealed several metabolic pathways significantly affected by

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CLas infection, mainly biosynthesis of amino acids and secondary metabolites. Comparisons of

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CLas-infected metabolite alterations among oranges, mandarins and grapefruits revealed that

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host responses to CLas were different. The metabolite signature highlighted in this study will

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provide a fuller understanding into how CLas bacteria affects biosynthesis of primary and

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secondary metabolites in different hosts.

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Keywords: citrus, metabolomics, Huanglongbing, Candidatus Liberibacter, metabolic pathway

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INTRODUCTION

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Huanglongbing, also known as citrus greening disease, is a devastating disease affecting all

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varieties of citrus worldwide. This destructive disease is associated with infection of the gram-

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negative bacteria Candidatus Liberibacter asiaticus (CLas) transmitted by the Asian citrus

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psyllid (ACP) Diaphorina citri, the vector of HLB. HLB was first reported in southern China in

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1919, and subsequently has spread throughout to different countries in Africa, Asia, South and

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North Americas.1 In the United States, HLB was first confirmed in south Miami-Dade County in

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2005, and it is present in all citrus-growing areas including Texas and California.2-3 Different

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symptoms can be found in all parts of the tree including leaves, twigs and fruits. In leaves, the

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typical symptoms include blotchy mottles, yellow veins and green islands, ultimately followed

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by the death of the entire plant (Figure S1).4 Furthermore, HLB also profoundly affects flavor

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and the taste quality of citrus fruits. Several studies have found that HLB-affected oranges had a

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lower soluble solids content (SSC)/titratable acid (TA), resulting in the HLB-affected juice being

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perceived as less sweet than the juice from healthy trees.5 Meanwhile, descriptive sensory

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evaluation from 16 panelists indicated that HLB-affected orange juice was perceived as more

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bitter than healthy orange juice due to high contents of limonoids and flavonoids.5-6 Recently,

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sensory descriptions of active taste compounds of orange juice isolated from centrifugal partition

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chromatography and preparative high performance liquid chromatography (HPLC) suggested

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that hydroxycinnamic acids and other compounds may also contribute to the bitterness of HLB-

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affected Valencia orange juice in addition to limonoids and flavonoids.7

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Since HLB is one of the most destructive diseases in citrus, different strategies have been

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developed to delay the progression of HLB, including antimicrobials, thermotherapy and

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nonantimicrobial compounds.8 For example, a recent study documented the effects of

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oxyteracycline hydrochloride trunk injections on HLB-affected Hamlin orange trees.9 The

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population density of CLas remained significantly lower in treated trees compared to that from

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untreated controls for 9 months. In addition, thermotherapy appears to be a potential strategy to

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suppress phytopathogen titer, at least, in the green house and growth chamber.10-11 Combined

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with applications of broad-spectrum insecticides and foliar nutrients, fruit yield increased

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significantly.12 Although these treatments could delay the progression of HLB, there is no cure to

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eliminate this disease. Therefore, according to the latest statistical report from the Florida

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Department of Agriculture and Consumer Services, citrus production in Florida decreased from

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94.2 million boxes in the 2015-2016 season to 78.1 million boxes in the 2016-2017 season.13

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Over the last decade, metabolomics has emerged as a comprehensive approach to achieve

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a global view of biological systems through the profiling of metabolites from bodily fluids, cells

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and tissues. Among different methodologies used for metabolite discovery, mass spectrometry is

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an excellent analytical platform for metabolomics analysis due to its high sensitivity and

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versatility.14 In recent years, liquid chromatography or gas chromatography coupled with mass

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spectrometry has been employed to understand plant’s responses to HLB. For example, a

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targeted metabolomics approach using high performance liquid chromatography-mass

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spectrometry (LC-MS) was carried out to profile alterations of secondary metabolites in sweet

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orange leaves infected with CLas.15 In flavoromics, changes of key aroma compounds in citrus

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fruits after CLas infection have been characterized using gas chromatography-mass spectrometry

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(GC-MS).6, 16 Our recent research revealed a positive link between lipid oxidation products and

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long-chain fatty acids in response to HLB using a targeted metabolomics approach.17

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Polymerase chain reaction (PCR) technique is the most common method used to detect

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the presence of CLas in citrus trees.18 However, limitations of PCR such as requirement of a

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minimum bacterial titer and uneven distribution of bacteria throughout the tree make PCR prone

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to false negatives, especially at early stages of infection. A nuclear magnetic resonance (NMR)-

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based metabolomics study revealed that healthy Hamlin oranges could not be completely

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separated from asymptomatic fruits in the partial least squares discriminant analysis (PLS-DA)

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model, suggesting that some of the healthy fruits were possibly false negatives due to uneven

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distribution of bacteria.19 Our recent metabolomics study has also compared volatile and

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nonvolatile profiles of healthy Hamlin orange fruits collected from citrus undercover protection

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systems (CUPS) with HLB asymptomatic and symptomatic fruits.16 CUPS, consisting of a pole

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and cable frame architecture, physically prevents the trees from coming into contact with ACP.20

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However, no consistent pattern could be observed in both volatile and nonvolatile metabolites as

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compared to previous studies, indicating that the metabolite profile of Hamlin orange fruits

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significantly changed earlier than detecting CLas infection by PCR. To better understand how

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CLas infection affects metabolite changes in the different hosts and prevent a misjudgment of

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health status due to uneven distribution of CLas and detection limits of PCR, our current study

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profiled primary and secondary metabolites of CLas-free leaves from Hamlin oranges, Murcott

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mandarins and Ray Ruby grapefruits, harvested from CUPS. Comparisons of metabolite profiles

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of truly CLas-free trees and their corresponding CLas-infected trees will provide a fuller

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understanding of the host responses to CLas bacteria in different citrus species as well as acquire

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useful information for developing potential treatments against HLB.

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MATERIALS AND METHODS

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Chemical and reagents

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All solvents used in this study were LC-MS grade and purchased from Fisher Scientific

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(Waltham, MA, U.S.A). Authentic standards of organic acids, amino acids, sugars and sugar

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alcohols were purchased from Sigma Co. (St. Louis, MO, U.S.A). Authentic standards of

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eriocitrin, narirutin, hesperidin, didymin, hesperetin, isosinensetin, sinensetin, 5,6,7,3’,4’,5’-

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hexamethoxyflavone, nobiletin, isosakuranetin and neoeriocitrin were purchased from Indofine

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Chemical Co. (Hillsborough, NJ, U.S.A). Rutin, apigenin, diosmetin, limonin, luteolin, naringin,

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neohesperidin and poncirin were sourced from Sigma Co. Meranzin, isomeranzin, tetramethoxy-

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o-isoscutellarein, tetramethoxy-o-scutellarein and 3,5,6,7,8,3’,4’-heptamethoxyflavone were

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purchased from Yuanye Biotech (Shanghai, China). Scopoletin was purchased from ChromaDex

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(Irvine,

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hydrochloride were purchased from Sigma Co.

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Plant materials

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Leaf samples from Hamlin orange (Citrus sinensis (L.) Osbeck), Murcott mandarin (Citrus

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reticulata Blanco) and Ray Ruby grapefruit (Citrus paradisi Macf.) used in this study were

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grown at the University of Florida’s Citrus Research Education Center (CREC, Lake Alfred,

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Florida). All trees were planted in August 2014 and leaf samples were harvested in June 2016.

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The healthy samples were collected from CUPS to guarantee the tree was truly CLas-free,20

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while the CLas-infected samples were collected from the field. CUPS and the field are located at

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CREC. Three plants (n=3) from each species were sampled from CUPS (healthy, CLas-free) and

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the field (CLas-infected). The CLas-free and Clas-infected leaves were from the same rootstock.

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The rootstocks of Hamlin oranges, Murcott mandarins and Ray Ruby grapefruits were Swingle,

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Kuharske and Sour orange, respectively. Several leaves were collected from different locations

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(top, middle and bottom) of each tree. Typical symptoms of HLB could be found in CLas-

CA,

U.S.A).

N-methyl-N-(trimethylsily)trifluoacetamide

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and

methoxyamine

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infected leaves, including blotchy mottles, green islands and yellow veins (Figure S1). Leaf

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samples were immediately frozen in liquid nitrogen and then stored at -80

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Leaves from different locations of each tree were pooled and ground before metabolite extraction.

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The presence of CLas in the infected trees and its absence in healthy trees were confirmed by

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qPCR.18 The qPCR data of CLa-infected leaves revealed average cycle threshold values of

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26.91±0.49 for Hamlin oranges, 27.51±1.02 for Murcott mandarins and 26.81±2.74 for Ray

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Ruby grapefruits. Generally, Ct values under 30 are considered confidently positive, while

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higher numbers are considered ambiguous.21

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Sugar, sugar alcohol and organic acid analysis

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Thirty three milligrams of ground leaves were extracted with 470 µL 80% methanol containing

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20 µL adonitol as internal standard (1 mg/mL in methanol) by agitation for 10 min. After

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centrifugation at 1000g for 10 min at 4 o C, the supernatant was collected and the solvent and

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moisture were removed by a SpeedVac evaporator (Thermo Scientific, Waltham, MA). The

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dried residue was mixed with 30 µL of methoxyamine hydrochloride (20 mg/mL in pyridine)

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and

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(trimethylsily)trifluoacetamide was added to the mixture and then shaken for an additional 30

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min prior to GC-MS analysis. A 7890 gas chromatograph coupled with an Agilent 5975C mass

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spectrometer (Santa Clara, CA, U.S.A) was employed to analyze sugar, sugar alcohols and

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organic acids. The carrier gas was helium and a split ratio was 1:20 with a 1.1 mL/min flow rate.

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The temperature of the ion transfer line and injection port was set at 230 oC. An Rxi-5 MS

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column (30 m Χ 0.25 mm; 0.25 µm film thickness, Restek, Bellefonte, PA, U.S.A) was carried

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out to separate analytes. The oven temperature was initially set at 70 oC for 5 min, and then

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ramped up by 4 oC /min to 270 oC, followed by 20 oC /min to 320 oC and held for 5 min. A

then

shaken

for

2

h

at

room

temperature.

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Finally,

80

o

C until analysis.

µL

N-methyl-N-


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solvent delay of 5 min was applied. Scan of mass spectrometry was ranged from m/z 60 to 650.

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Compound identification was confirmed by the retention time of authentic standards and the

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NIST library. Relative concentrations of sugars, sugar alcohols and organic acids were semi-

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quantitated based on the concentration of the internal standard.

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Amino acid analysis

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Fifty milligrams of ground leaves were extracted with 1mL 80% methanol containing 10 µL

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theanine (1 mg/mL, internal standard) by sonication for 30 min. After centrifugation at 5,000g

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for 5 min at 4 o C, the supernatant was filtered through a 0.22 µm nylon filter prior to LC-MS

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analysis. The analytical method was performed as described by our previous work.16 In brief, a

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Thermo Ultimate 3000 HPLC equipped with a Thermo TSQ Quantiva triple quadrupole

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electrospray ionization tandem mass spectrometer (Thermo Scientific) was carried out for

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analyzing amino acids. Chromatographic separations were achieved using a Tosoh TSKgel

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Amide-80 column. The mobile phase consisted of 2.5 mM ammonium formate and 2.5 mM

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ammonium acetate in 90% acetonitrile aqueous solution containing 0.15 % formic acid (A) and

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2.5 mM ammonium formate and 2.5 mM ammonium acetate in 90% acetonitrile containing

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0.15% formic acid (B). The gradient program was set as follows: 0-10 min, 100-90% B; 10-16

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min, 90-80% B; 16-20 min, 80-50% B; 20-24 min, 50% B. The injection volume was 5 µL.

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Authentic standards were directly infused into the mass spectrometer at a flow rate of 0.2

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mL/min. The product ions, collision energy and RF lens of each analyte were optimized using

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TSQ Quantiva Tune software (Thermo Scientific).The SRM transitions, collision energy, RF

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lens and retention time of amino acids are given in Table S1. Relative concentrations of amino

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acids were semi-quantitated based on the concentration of the internal standard

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Flavonoid, coumarin and limonoid analysis 8


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One hundred milligrams of ground leaves were extracted with 1 mL methanol containing 10 µL

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catechin (1 mg/mL, as internal standard) by sonication for 15 min. After centrifugation at 5000g

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for 10 min, the supernatant was collected and solvent was evaporated by a speedVac evaporator.

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The dried residue was reconstituted in 500 µL methanol and then subjected to a C18 solid phase

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extraction cartridge (100 mg, Restek, Bellefonte, PA, U.S.A) and then eluted with 500 µL

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methanol. The eluents were combined and 10 µL was injected into LC-MS (TSQ Quantiva,

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Thermo Scientific). The analytical method was modified from our previous work.16 In brief,

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chromatographic separations were carried out using a Phenomenex Gemini C18 column (3 µm, 3

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Χ 150 mm, Phenomenex, Torrance, CA. U.S.A) with a mobile phase consisting of 0.1% formic

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acid in water (A) and 0.1% formic acid in acetonitrile (B). The gradient program was set as

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follows: 0-20 min, 5-75% B, 25-26 min, 75-95% B, 26-33 min, 95% B. The flow rate and

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injection volume were set at 0.2 mL/min. The SRM transitions, collision energy, RF lens and

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retention time of the analytes are given in Table S2. Relative concentrations of the analytes were

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semi-quantitated based on the concentration of the internal standard.

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Statistical Analysis

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Data are expressed as means of relative concentrations of the metabolites compared to that of

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healthy leaves. Significant differences were statistically detected by Student’s t test using MS

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Excel (Version 2016, Microsoft, Redmond, Washington, U.S.A). A significant difference was

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considered when p < 0.05. PLS-DA was performed using SIMCA-P software (Umea, Sweden)

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with mean centering and unit variance scaling. The confidence of tolerance ellipse in the PLS-

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DA model was 95% based on Hotelling’s T-squared distribution. The quality of the PLS-DA

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model was described in terms of three parameters. R2X and R2Y were used to quantitate the

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good-of-fit and Q2 was used to assess the predictability of the model. To rule out the non-

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randomness of separation between groups, a 100-iteration random permutation test was also

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carried out to validate the PLS-DA model. After a log transformation, the heat map was

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performed using MetaboAnalyst 4.0 (http://www.metaboanalyst.ca/). Metabolic pathways were

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constructed using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database

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(https://www.genome.jp/kegg/) as a reference.

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RESULTS

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Alterations of organic acids, sugar, and sugar alcohols in citrus leaves by CLas-infection

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GC-MS was employed to analyze organic acids, sugars and sugar alcohols in citrus leaves after

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metabolite derivatization. A total of 10 organic acids, 6 sugars and 3 sugar alcohols were

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analyzed. In CLas-free Hamlin oranges and Murcott mandarin, no significant changes could be

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found in most of organic acids as compared to the CLas-infected leaves (Table 1). The levels of

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fumaric acid and malic acid in CLas-free Hamlin oranges were significantly higher than that

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from CLas-infected oranges, while the level of citric acids in Murcott mandarins and Ray Ruby

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grapefruits significantly increased after CLas infection. In Ray Ruby grapefruit, levels of maleic

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acid, succinic acid, glyceric acid and quinic acid significantly decreased after CLas infection. In

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the sugar profile, the concentration of melibiose significantly increased in both CLas-infected

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Hamlin oranges and Murcott mandarins. In grapefruits, CLas-infected leaves had lower levels of

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glucose, fructose, galactose and myo-inositol as compared to CLas-free leaves (Table 1).

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Alterations of amino acids in citrus leaves by CLas-infection

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Amino acids are crucial primary metabolites directly involved in plant growth and metabolism.

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Here, we used hydrophilic interaction chromatography coupled with MS to determine amino

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acids in leaves. The results of amino acids in citrus leaves are given in Table 2. The levels of

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most of amino acids generally increased after CLas infection regardless of citrus species. In

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Hamlin orange leaves, phenylalanine, leucine, isoleucine, methionine, valine, alanine, threonine

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and glycine in CLas-free leaves were significantly higher than that from CLas-infected leaves.

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Similarly, CLas infection significantly elevated production of several amino acids in Ray Ruby

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grapefruit leaves, including leucine, methionine, proline, glutamine, asparagine, arginine and

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lysine. Only isoleucine and valine of Murcott mandarin leaves significantly increased after CLas

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infection (Table 2).

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Alterations of flavonoids, coumarins, furanocoumarins and limonoids in citrus leaves by CLas-

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infection

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LC-MS was used to identify different classes of flavonoids, including flavanones, flavones and

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flavonols, in which both flavonoid aglycones and their corresponding glycosides were analyzed

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in this study. CLas infection increased accumulation of most of flavonoids in Hamlin oranges

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and Murcott mandarins (Table 3). Levels of naringenin, apigenin, diosmetin, 3,5,6,7,8,3’,4’-

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heptamethoxyflavone and rutin in Hamlin oranges significantly increased after CLas infection.

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Similarly, eriocitrin, hesperidin, hesperetin, isosakuranetin, diosmin, diosmetin, nobiletin,

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tangeretin, rutin and quercetin in CLas-infected Murcott mandarins were significantly higher

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than that from CLas-free leaves. Conversely, CLas infection decreased accumulation of many

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flavonoids in Ray Ruby grapefruits, especially flavanones. Levels of neoeriocitrin, narirutin,

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naringin, didymin, poncirin and isosakuranetin in Ray Ruby grapefruits significantly decreased

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after CLas-infection. It should be noted that neohesperidin, naringin, poncirin, neodiosmin could

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be only found in Ray Ruby grapefruits. In coumarins, CLas infection significantly increased

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scopoletin accumulation in Hamlin oranges. Furanocoumarins are specific groups of secondary 11



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metabolites commonly present in grapefruits.22 Our results showed that both 6’,7’-

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epoxybergamottin and bergamottin had higher levels in CLas-free Ray Ruby grapefruits as

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compared to CLas-infected leaves. Limonin is one of the major limonoids that contribute to the

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bitterness of citrus fruits.6 Limonin accumulation was significantly elevated in CLas-infected

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Hamlin oranges (Table 3).

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Multivariate analysis of metabolites

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First, Venn diagrams were constructed to illustrate the overlapping metabolites significantly

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altered after CLas infection (Figure 1). In total, CLas infection significantly altered 21, 15 and 26

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metabolites in Hamlin oranges, Murcott mandarins and Ray Ruby grapefruits, respectively. A

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total of 6 metabolites, including melibiose, valine, isoleucine, diosmetin, tangeretin and rutin,

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were significantly altered in both Hamlin oranges and Murcott mandarins after Clas infection,

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while only two metabolites were significantly changed in both Hamlin oranges and Ray Ruby

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grapefruits. However, once CLas infected, no metabolites were simultaneously altered in Hamlin

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oranges, Murcott mandarins and Ray Ruby grapefruits. Similarly, 16 and 14 metabolites

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significantly accumulated in Hamlin oranges and Murcott mandarins, respectively, while only 9

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metabolites significantly increased in Ruby Ray grapefruits. It is noteworthy that CLas infection

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significantly decreased accumulation of 17 metabolites in Ray Ruby grapefruits, while only 5

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and 1 metabolites in Hamlin oranges and Murcott mandarins significantly decreased (Figure 1).

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Meanwhile, PLS-DA was employed to determine whether metabolite profiles significantly

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changed by CLas infection. First, the clusters of Hamlin oranges, Murcott mandarins, and Ray

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Ruby grapefruits were separated from each other (Figure 2), indicating that metabolite profiles

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were significantly different depending on the citrus species. R2X, R2Y and Q2 values were 0.907, 12


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0.982 and 0.800, respectively. Y-intercepts of R2 and Q2 in the permutation test (n=100) were

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0.719, -0.567, respectively, suggesting a valid model. Importantly, the healthy leaves were

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clustered together and separated from the CLas-infected leaves in Hamlin oranges, Murcott

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mandarins and Ray Ruby grapefruits (Figure 2). These results suggest that metabolite profiles of

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citrus leaves significantly altered after CLas infection regardless of citrus species. To identify the

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most relevant metabolic pathways involved in metabolic reprogramming after CLas infection,

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metabolites significantly changed by CLas infection (p

A Targeted Mass Spectrometry-based Metabolomics Approach toward

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