Metabolite Profiling of Candidatus Liberibacter Infection in Hamlin

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Metabolite Profiling of Candidatus Liberibacter Infection in Hamlin Sweet Oranges Wei-Lun Hung, and Yu Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05866 • Publication Date (Web): 02 Apr 2018 Downloaded from http://pubs.acs.org on April 2, 2018

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Journal of Agricultural and Food Chemistry

Metabolite Profiling of Candidatus Liberibacter Infection in Hamlin Sweet Oranges

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Wei-Lun Hung,† Yu Wang,*†

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†Citrus Research and Education Center, Department of Food Science and Human Nutrition, University of Florida, Lake Alfred, 33850, USA

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*Please send all correspondence to:

14

Dr. Yu Wang

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Citrus Research and Education Center

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Department of Food Science and Human Nutrition

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University of Florida

18

700, Experiment Station Rd,

19

Lake Alfred, FL 33850 USA

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Phone: 863-956-8673

21

Fax: 863-956-4631

22

E-mail: [email protected]

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ABSTRACT

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Huanglongbing (HLB), also known as Citrus Greening Disease, caused by Candidatus

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Liberibacter asiaticus (CLas) is considered the most serious citrus disease in the world. CLas

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infection has been shown to greatly affect metabolite profiles in citrus fruits. However, due to

27

uneven distribution of CLas throughout the tree, and a minimum bacterial titer requirement for

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polymerase chain reaction (PCR) detection, the infected trees may test false negative. To prevent

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this, metabolites of healthy Hamlin oranges (CLas-) obtained from the citrus undercover

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protection systems (CUPS) were investigated. Comparison of the metabolite profile of juice

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obtained from CLas- and CLas+ (asymptomatic and symptomatic) trees revealed significant

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differences in both volatile and non-volatile metabolites. However, no consistent pattern could be

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observed in alcohols, esters, sesquiterpenes, sugars, flavanones and limonoids as compared to

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previous studies. These results suggest that CLas may affect metabolite profiles of citrus fruits

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earlier than detecting infection by PCR. Citric acid, nobiletin, malic acid and phenylalanine were

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identified as the metabolic biomarkers associated with the progression of HLB. Thus, the

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differential metabolites found in this study may serve as the biomarkers of HLB in its early

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stage, and the metabolite signature of CLas infection may provide useful information for

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developing a potential treatment strategy.

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Keywords: citrus, sweet oranges, metabolomics, Huanglongbing, Candidatus Liberibacter, greening

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1. Introduction

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Citrus Huanglongbing (HLB), also known as citrus greening disease, is the most destructive

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disease that affects all varieties of citrus. HLB is caused by the nonculturable bacteria of the

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genus Candidatus Liberibacter , which infects the phloem of the tree. The three species of this

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bacterium, including asiaticus (CLas), africanus and americanus, are known to cause HLB. The

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Asian citrus psyllid Diaphorina citri is the vector of HLB, which transports the disease-causing

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bacterium between trees1. Typical symptoms of HLB include yellow veins and adjacent tissues,

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blotchy and mottled leaf chlorosis, small green fruits, dieback of twigs, ultimately followed by

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the death of the entire plant. HLB was first discovered in south Miami-Dade County in 2005, and

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subsequently spread throughout the commercial production area in different counties in Florida.2

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In 2012, HLB was first detected in Texas and California.3-4 Florida accounted for approximately

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50% of the total U.S citrus production in the 2015-2016 season.5 Due to this devastating disease,

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citrus production in Florida decreased from 124 million boxes in the 2013-2014 season to 94.2

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million boxes in the 2015-2016 season.5-6 Over a five-year period (2006 – 2010), the presence of

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HLB has resulted in substantial losses of 1.7 billion of total revenue and 8,257 jobs.7 To date,

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although some treatments can delay the progression of HLB, there is no known cure to eliminate

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this disease.8

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Orange juice is one of the most popular fruit juices in the United States. Although human

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consumption of HLB-affected orange juice is harmless, both flavor and taste quality are

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profoundly affected.9 Previous studies have shown significant changes in the volatile and non-

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volatile metabolites of orange fruits as a response to CLas infection.10-13 Comparison of volatiles

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from HLB-symptomatic and control orange juices revealed that CLas infection increased the

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total terpenes and alcohol levels, while the levels of esters and sesquiterpenes decreased.10 In

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general, HLB-affected orange juice had lower soluble solids content (SSC) but higher titratable

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acidity (TA), resulting in a lower SCC/TA.10, 13 Descriptive sensory evaluation of orange juice

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also indicates HLB-affected orange juice is perceived as less sweet than healthy orange juice.9

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Limonin and nomilin are the two major limonoids responsible for the bitterness of orange juice.14

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HLB-affected juice tends to be more bitter than healthy orange juice due to high levels of

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limonin and nomilin.10 In addition, significant changes of flavonoid profiles in orange fruits by

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CLas infection have been described previously.15-16

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Along with genomics, transcriptomics and proteomics, metabolomics has emerged as an

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important tool, affording global understanding of biological systems. Plant metabolite profiling

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provides much useful information regarding the structure, function and biosynthetic pathway of

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these metabolites in understanding plant’s responses to biotic and abiotic stress. Recently,

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several studies have reported the impacts of CLas infection on the juice metabolome such as

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organic acids, amino acids, sugars, limonoids as well as flavonoids.11-12, 15, 17 Recently, a nuclear

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magnetic resonance (NMR)-based metabolomic analysis of sweet oranges revealed no clear

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differences between control and HLB asymptomatic Hamlin oranges in the PLS-DA score plot.11

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Moreover, the same research group has also reported decreased levels of proline and arginine in

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HLB symptomatic oranges.12 However, proline and arginine accumulation in stressed plants is

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considered a protective mechanism in response to biotic and abiotic stress, such as UV

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irradiation, droughts, oxidative stress and parasite infection.18-19 Failure to distinguish the

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metabolites between control and asymptomatic fruits and increased levels of proline and arginine

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found in healthy oranges suggest that some of the control trees possibly tested as false negatives

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due to the detection limit of polymerase chain reaction (PCR) methods or uneven distribution of

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CLas throughout the tree.11-12

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Detecting infection early is important in understanding how plant metabolites change once

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CLas infects the plant. Since HLB was first detected in 2005, the exact number of truly CLas-

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free trees remaining in Florida is unknown.11 To prevent a misjudgment of CLas infection due to

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the detection limits of PCR, or uneven distribution of bacteria,20-21 truly CLas-free citrus trees are

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warranted. In this study, Hamlin oranges were collected from the citrus undercover production

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systems (CUPS) to guarantee the fruits were truly CLas-free. CUPS physically prevents the trees

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from coming into contact with the Asian citrus psyllid.22 Meanwhile, the HLB asymptomatic and

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symptomatic Hamlin oranges were obtained from commercial groves in Florida. Then, liquid

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chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-

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MS) were employed to identify volatile and non-volatile metabolites in Hamlin orange juice. By

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comparing metabolite changes, this study will provide a fuller understanding into how CLas

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affects metabolite changes in Hamlin oranges in the early stage of HLB.

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2. Materials and Methods

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Chemicals and reagents

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All solvents were LC-MS grade and purchased from Fisher Scientific Co. (Waltham, MA,

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USA). All volatile authentic standards were purchased from Sigma Co. (St. Louis, MO,

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USA). β-Citronellol and nerol were purchased from TCI America (Portland, OR, USA).

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Amino acid and organic acid authentic standards were sourced from Sigma Co. Didymin,

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eriocitrin,

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tangeretin were purchased from Indofine Chemical Co. (Hillsborough, NJ, USA).

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Hesperidin,

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Heptamethoxyflavone was purchased from Yuanye Biotech (Shanghai, China).

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Plant Materials

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Citrus sinensis cultivar Hamlin fruits were used in this study. The healthy Hamlin fruits were

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obtained from CUPS at the University of Florida’s Citrus Research and Education Center

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(Lake Alfred, Florida) in January, 2017. The healthy trees in CUPS were approximately 2

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years old. The asymptomatic and symptomatic fruits were collected from the commercial

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groves in December, 2016 (Frostproof, FL) and January 2017 (Lake Wales, FL), respectively

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(Figure S1). The ages of asymptomatic and symptomatic trees were approximately 30 and 4

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years old, respectively. Fruits were collected from three replicate trees from CUPS (healthy

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fruits) and commercial groves (asymptomatic and symptomatic fruits). A total of 20-30 fruits

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were randomly collected from different trees in CUPS and commercial groves and then

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juiced by hand. The resulting juice was pooled, aliquoted, and stored at -20o C until analysis.

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The presence of CLas bacteria in asymptomatic and symptomatic trees, and its absence in

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healthy trees was confirmed by qPCR using the method described by Li et al.23 The leaves

5,6,7,3’,4’,5’-hexamethoxyflavone,

narirutin,

limonin

and

isosenesetin,

nomilin

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were

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nobiletin,

purchased

sinensetin

from

Sigma

and

Co.

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from healthy, asymptomatic and symptomatic trees were collected for qPCR detection at the

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same time as the fruit collection.

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Measurement of Brix and total titratable acidity

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Soluble solids content (SSC), generally expressed in o Brix, reflects sugar concentrations in

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orange juice, as most soluble solids in orange juice are sugars. The SSC of orange juice was

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measured using the Brix-Acidity Meter designed for citrus juice (Atago, Tokyo, Japan). For

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total titratable acidity (TAA), the juice sample was diluted 49:1 (w/w) with water prior to

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acidity determination. The TAA was also determined using the Brix-Acidity Meter.

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Volatile analysis

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The volatile compounds from orange juice were extracted using headspace solid-phase

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microextraction (HS-SPME). The procedure was modified from Dagulo et al.10 Briefly, 5 mL

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of whole juice was thoroughly mixed with 5 µL benzyl alcohol (2000 µg/mL in methanol) in

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a 20 mL glass vial. After addition of 1.8 g NaCl, the juice sample was gently stirred using a

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stirring bar in a 40o C water bath for 45 min. After the equilibration period, a Stableflex fiber

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(2 cm, 50/30 µm, Divinylbenzene/CarboxenTM/polydimethylsiloxane, Supelco, Bellofonte,

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PA, USA) was exposed in the vial headspace at 40o C for 45 min. The volatile compounds

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were identified using a PerkinElmer Clarus 680 gas chromatograph (PerkinElmer, Waltham,

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MA) equipped with a PerkinElmer Clarus SQ 8T mass spectrometer (PerkinElmer). The

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mass spectrometer was operated in the electron impact ionization mode with an ionizing

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energy of 70 eV. A constant pressure of helium, the carrier gas was set at 30 psi as

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calculating using the PerkinElmer Swafer utility software (PerkinElmer). Chromatographic

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separation of volatile compounds was carried out using a TR-FFAP column (30 m x 0.25

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mm, 0.25 µm film thickness, Thermo Scientific). Column temperature program was initially

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set at 40o C for 2 min, followed by a ramp of 5o C/min to 230o C with a 10-min hold. The

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temperature of injector and transfer line were set at 250o C. The scan range of the mass

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spectrometer was m/z 50 to 300. Peak identification of volatile compounds was achieved by

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comparing the linear retention index (LRI) values and mass spectra with the NIST library

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(National Institute of Standards and Technology, Gaithersburg, MA, USA). A mixture of n-

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alkane standards (C7-C30, Sigma Co) was also analyzed to calculate retention indices.

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Authentic standards of volatiles listed in Table 1 were also run on a TR-FFAP column and

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their retention time confirmed compound identity. The concentration of volatile compounds

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is relative to the concentration of internal standard.

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Sugar analysis

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The analytical method used for determination of glucose, fructose and sucrose in orange juice

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was modified from Cerdan-Calero et al.24 In brief, whole juice was centrifuged at 2000 g for

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5 min and supernatant was filtered through a 0.22 µm nylon filter. Then, 10 µL of filtered

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juice was mixed with 40 µL adonitol as an internal standard (1 mg/mL in methanol) and the

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moisture and solvent were removed using a SpeedVac evaporator (Thermo Scientific,

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Waltham, MA). The dried juice was mixed with 30 µL methoxyamine hydrochlorie (20

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mg/mL in pyridine) and then shaken vigorously for 2 h at room temperature. Finally, 80 µL

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N-methyl-N-(trimethylsily)trifluoracetamide was added into the mixture and vigorously

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shaken for an additional 30 min. Glucose, fructose and sucrose were determined using a

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Agilent 7890 gas chromatograph coupled with a Agilent 5975C mass spectrometer (Santa

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Clara, CA, USA) in electron impact mode with 70 eV. Helium was the carrier gas and a

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constant flow rate was set at 1.1 mL/min. The injector and transfer line temperature were set

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at 230o C. One µL of each sample was injected into an Rxi-5 MS column (30 m x 0.25 mm;

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0.25 µm film thickness, Restek, Bellefonte, PA, USA) using a split mode (1:10). The oven

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temperature program was initially set at 70o C for 5 min, and then ramped up by 4o C/min to

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270o C, followed by 20o C/min to 320o C and held for 5 min. A solvent delay of 5 min was

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applied. The scan range of mass spectrometry was from m/z 60 to 650. Compound

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identification was confirmed according to the retention time of authentic standards and the

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NIST library. Relative concentrations of glucose, fructose and sucrose were semi-quantified

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based on the concentration of the internal standard.

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Organic acid analysis

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The analytical method used for determining organic acids in orange juice was modified from

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Flores et al.25 In Brief, 100 µL filtered juice sample was mixed with 100 µL gallic acid (10

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µg/mL, internal standard) and 800 µL water (LC-MS grade). The mixture was filtered

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through a 0.22 µm nylon filter prior to LC-MS quantification. A Thermo Ultimate 3000

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HPLC equipped with a Thermo Quantiva triple quadrupole electrospray ionization tandem

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mass spectrometer (Thermo Scientific, Waltham, MA, USA) was used. Chromatographic

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separations were performed using a Phenomenex Gemini C18 column (3 µm, 3 x 150 mm,

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Phenomenex, Torrance, CA, USA), and a mobile phase consisting of 0.1% formic acid

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

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as follows: 0-13 min, 2% B, 13-17 min, ramped to 95% B; 17-24 min, 95% B. The flow rate

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was set at 0.2 mL/min. The column temperature was maintained at 25o C. The injection

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volume was 5 µL. The spray voltage in negative mode was set at 2,500 V. Other MS

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parameters were as follows: sheath gas, 35 Arb; Aux gas, 10 Arb, Sweep gas, 1 Arb; CID

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gas, 2 mTorr, Ion transfer tube temp: 325o C, vaporizer temp: 350o C. Authentic standards of

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organic acids were directly infused into the mass spectrometry at a flow rate of 200 µL/min

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and product ions, collision energy and RF lens of each standard were optimized using TSQ

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

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and retention time of the analytes and internal standard are given in Table S1. Although citric

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acid and isocitric acid had the same product ion, they still could be differentiated from each

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other based on their retention time.

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Amino acid analysis

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One hundred µL of filtered juice was mixed with 100 µL theanine (10 µg/mL, internal

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standard) and 800 µL water (LC-MS grade). The mixture was filtered through a 0.22 µm

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nylon filter prior to LC-MS quantification. Chromatographic separations were performed

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using a Tosoh TSKgel Amide-80 column (3 µm, 2 x 150 mm, Tokyo, Japan) with a mobile

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phase consisting of 5 mM ammonium acetate and 5 mM ammonium formate aqueous

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solution containing 0.15% formic acid (A) and 2.5 mM ammonium acetate and 2.5 mM

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ammonium formate in 90% acetonitrile containing 0.15% formic acid (B). The gradient

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program was set as follows: 0-10 min, 100-90% B; 10-16 min, 90-80% B; 16-20 min, 80-

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50% B; 20-24 min, 50% B. The flow rate was set at 0.2 mL/min. The column temperature

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was maintained at 35 oC. The injection volume was 5 µL. The spray voltage in positive mode

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was set at 3,500 V. Other MS parameters were as follows: sheath gas, 35 Arb; Aux gas, 10

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Arb, Sweep gas, 1 Arb; CID gas, 2 mTorr, Ion transfer tube temp: 325o C, vaporizer temp:

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350o C. The SRM transitions, collision energy, RF lens and retention time of the analytes and

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internal standard are given in Table S2. Although leucine and isoleucine had the same

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product ion, they still could be differentiated from each other based on their retention time.

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Flavonoid and limonoid analysis

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Five hundred µL of filtered juice was mixed with 5 µL catechin (1 mg/mL, internal

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standard) and then extracted with 500 µL ethyl acetate using a shaker for 5 min. After

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centrifugation at 3000 g for 5 min at 4o C, the supernatant was collected and then the juice

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extracted again with an additional 500 µL ethyl acetate. Solvent from the supernatant was

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removed by a stream of nitrogen gas. Dried supernatant was reconstituted in 500 µL

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methanol and then filtered through a 0.22 µm filter prior to LC-MS analysis.

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Chromatographic separations were performed using a Phenomenex Gemini C18 column (3

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µm, 3 x 150 mm) with a mobile phase consisting of 0.1% formic acid aqueous solution (A)

225

and 0.1% formic acid in acetonitrile (B). The gradient program was set as follows: 0-20 min,

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5-75% B, 25-26 min, ramped up to 95% B; 26-33 min, 95% B. The flow rate was set at 0.2

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ml/min. The column temperature was maintained at 25o C. The injection volume was 10 µL.

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The spray voltage in both positive and negative modes were set at 3,500 and 2,500 V,

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respectively. Other MS parameters were as follows: sheath gas, 45 Arb; Aux gas, 20 Arb,

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Sweep gas, 1 Arb; CID gas, 1.5 mTorr, Ion transfer tube temp: 325o C, vaporizer temp: 275o

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C. The SRM transitions, collision energy, RF lens and retention time of the analytes and

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internal standard are given in Table S3.

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Statistical analysis

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The concentrations of volatiles and non-volatiles were semi-quantified based on the

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concentrations of internal standards. Data are expressed as means of relative concentrations

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of the metabolites compared to that of healthy fruits. Significant differences were statistically

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detected by one-way analysis of variance (ANOVA), followed by Tukey’s test using

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Statistical Analysis System (SAS) software (Cary, NC, USA) for each metabolite. The

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ANOVA was performed on the relative concentrations of metabolites. The result was

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considered as a significant difference when p < 0.05. Partial-squares-discriminant analysis

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(PLS-DA) was performed using SIMCA-P (Umea, Sweden) with mean centering and unit

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variance scaling. The confidence of tolerance ellipse based on Hotelling’s T2 was 95%. The

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goodness-of-fit parameter (R2X and R2Y) and predictive ability parameter (Q2) were used to

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judge the quality of the model. Also, the PLS-DA model was validated by the R2Y and Q2

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from a random permutation test (n=100). In the PLS-DA model, variable influence in

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projection (VIP) value, weight sum of squares of the PLS loading weights, greater than 1.5

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were selected for further discussion. The VIP value was determined using SIMCA-P. The

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heat map was performed using MetaboAnalyst 3.0 (http://www.metaboanalyst.ca). Before

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constructing a heat map, the raw data were normalized by median, followed by log

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transformation. The Ward hierarchical clustering algorithm and Euclidean distance metrics

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were used for constructing a heat map.26

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Results and Discussion

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In the aroma profile of citrus fruits, aldehydes are known to contribute citrus-like, grassy and

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soapy odor in the juice.27-28 In Hamlin juice, a previous study showed decreased levels of

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aldehyde compounds, including acetaldehyde, octanal and hexanal, in the HLB symptomatic

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orange fruits as compared to healthy fruits.13 Similar to those results, this study shows

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decreased levels of hexanal, (E)-2-hexanal, octanal and decanal in symptomatic juice as

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compared to healthy fruits (Table 1). On the contrary, Dagulo et al. suggest that aldehyde

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compounds including octanal, nonanal and decanal were higher in concentration of HLB

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asymptomatic and symptomatic Valencia orange juice, whereas Baldwin et al. have found

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that alcohol compounds in symptomatic Valencia oranges were similar to that from control

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fruits.10, 13. In the terpene profile, levels of α-pinene, β-myrcene, d-limonene, γ-terpinene and

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4-terpineol were higher in concentration of HLB symptomatic juice as compared to healthy

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fruits (Table 1). Consistent with our findings, previous studies also found that β-myrcene, d-

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limonene as well as total amounts of terpenes were higher in concentration of HLB

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symptomatic Hamlin juice as compared to healthy fruits.10, 13

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The fruity odor in orange juice is attributed to ester compounds.27 The levels of methyl

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butanoate, ethyl butanoate and ethyl hexanoate in HLB asymptomatic and symptomatic juice

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were higher than those from the healthy juice (Table 1). However, previous studies have

270

found that ethyl butanoate and total amounts of esters were higher in concentration of healthy

271

Hamlin fruits.10,

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hexanol, 1-octanol, β-citronellol, nerol and geraniol, had lower levels in both asymptomatic

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and symptomatic fruits compared to controls (Table 1). On the contrary, Dagulo et al. have

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reported that CLas infection resulted in accumulation of alcohol compounds in Hamlin

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orange juice, while Baldwin et al. has shown that CLas infection did not significantly affect

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accumulation of alcohol compounds in Hamlin orange juice.10, 13 In the sesquiterpene profile,

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valencene, α-humulene, β-elemene, and nootkatone had the lowest levels in the healthy juice,

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while asymptomatic juice had the highest concentration of total sesquiterpenes (Table 1). In

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contrast to our results, a higher concentration of total sesquiterpenes accumulated in healthy

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Hamlin orange juice was observed.10 Our current findings together with volatile profiles of

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Hamlin fruits reported from previous studies indicate that no apparent pattern can be

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observed regarding the changes of ester, alcohol and sesquiterpene compounds in response to

283

CLas infection.10, 13 Since our healthy fruits collected from CUPs were truly CLas-free, one

284

possible explanation is CLas may alter metabolite profiles in citrus earlier than detection of

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CLas by PCR.20-21,

13

In the alcohol profile, most of the alcohol compounds, including 1-

29

PCR is prone to false negatives due to a minimum bacterial titer

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requirement and uneven distribution of bacteria throughout the tree. A NMR-based

287

metabolomic analysis of Hamlin juice showed no clear differences between control and HLB

288

asymptomatic fruits in the PLS-DA score plot suggesting that some controls possibly tested

289

false negative by PCR.11 Furthermore, in CLas-inoculated Valencia oranges, leaves from

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certain inoculated trees were PCR positive after 13 weeks. Whereas leaves from different

291

sections of the same tree were still PCR negative after 21 and 29 weeks, indicating that the

292

bacterium was not evenly distributed throughout the tree.21 Meanwhile, PLS-DA was

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employed to further determine whether the fruits could be discriminated on the basis of

294

infection status. As shown in Figure 1(A), the PLS-DA score plot showed a clear separation

295

among control, asymptomatic and symptomatic fruits. R2X, R2Y and Q2 were 0.838, 0.415

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and 0.289, respectively. After the permutation test was performed, y-intercepts for R2 and Q2

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were 0.389 and -0.186, respectively, indicating a valid model. The clusters of asymptomatic

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and symptomatic samples were located far from the control samples suggesting that volatile

299

profiles of Hamlin oranges were changed after CLas infection. In the loadings plot (Figure

300

1B), d-limonene, valencene and linalool were considered to be the most influential in

301

separation of healthy, asymptomatic and symptomatic fruits.

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Balance of sweetness and sourness is a key factor providing a desirable taste quality of

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orange juice. In general, HLB Valencia oranges had lower concentrations of glucose,

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fructose and sucrose, but higher concentrations of organic acids, contributing a lower

305

SCC/TA ratio compared to healthy Valencia juice.11, 13, 16, 30 In this study, asymptomatic and

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symptomatic juice had higher concentrations of citric acid, ascorbic acid, isocitric acid and

307

quinic acid, but lower levels of malic acid (Table 2). Similar to these findings, NMR analysis

308

of metabolites in Hamlin and Valencia fruits revealed higher concentrations of citric acid and

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ascorbic acid in HLB symptomatic juice, but a lower concentration of malic acid.11-12 In the

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sugar profile, both asymptomatic and symptomatic juice had higher levels of glucose and

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fructose, while the level of sucrose in symptomatic juice was similar to healthy juice (Table

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2). Fructose and glucose have been shown to increase in Hamlin asymptomatic oranges

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compared to the control fruits.11 Similarly, accumulation of glucose and fructose by CLas

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infection could be observed in citrus leaves.31 However, lower levels of sucrose, glucose and

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fructose in HLB-infected orange juice have been reported by Baldwin et al.,13 whereas

316

research from Raithore et al. suggests CLas infection did not significantly affect

317

accumulation of glucose and fructose.30 In addition, a higher SSC/TAA ratio in

318

asymptomatic and symptomatic juice could be observed in this study (Table 3) and these

319

results were similar to the Hamlin oranges harvested in 2008.13 However, lower SSC/TA

320

ratio in HLB-affected Hamlin orange juice has been reported previously.10-11 Again, similar

321

to the results from ester, alcohol and sesquiterpene compounds, no consistent trend could be

322

observed in sugar and SSC/TA from Hamlin orange juice in response to CLas infection when

323

compared to previous studies.11,

324

orange juice may be affected earlier than detection of CLas by PCR. However, it should be

325

noted that the variations in SSC/TA due to environment factors, such as harvest date and

326

growing region, might be greater than that due to HLB.13, 32

13, 30

Based on these results, organic acid and sugars of

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Amino acids are essential for primary metabolism in plants. Biosynthesis of amino acids

328

in citrus plants has been shown to be affected by CLas infection.11-12, 31, 33 In this study, most

329

amino acids in symptomatic juice were lower than those in healthy juice (Table 4). Similarly,

330

an NMR-based metabolomics study of Valencia orange juice has also reported that alanine,

331

leucine, isoleucine, threonine and valine in symptomatic orange juice had lower levels when

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compared to the healthy juice.12 Meanwhile, phenylalanine in symptomatic juice was

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significantly lower compared to that from healthy juice (Table 4). This is in contrast to the

334

studies previously reported.11-12 Phenylalanine is a crucial precursor responsible for

335

secondary phenylpropanoid metabolism in higher plants.34 In the phenylpropanoid

336

biosynthetic pathway, phenylalanine is converted to trans-cinnamic acid by phenylalanine

337

ammonia-lyase (PAL) through a deamination reaction. Synthesis of PAL is stimulated due to

338

pathogen attack, tissue wounding, UV irradiation and low temperature.35 Moreover,

339

transcriptomic data has identified the gene expression of phenylpropanoid biosynthesis was

340

significantly affected by CLas infection.36 Biotic stress induced by infestation of Asian citrus

341

psyllid Diaphorina citri also decreased the accumulation of phenylalanine in Satsuma orange

342

leaves.37 Therefore, lower concentrations of phenylalanine found in symptomatic fruits could

343

be partly due to activation of PAL by CLas. Proline is the one of the most abundant amino

344

acids in Hamlin juice and CLas infection significantly elevated proline accumulation in

345

Hamlin oranges (Table 4).12 Studies have shown that proline accumulates in many plant

346

species under different environment stressors, such as drought, UV irradiation and pathogen

347

attack.18 Similar to proline accumulation, arginine was also higher in concentration of

348

symptomatic juice when compared to the healthy juice (Table 4). Environment stress also

349

causes arginine accumulation in citrus plants.19,

350

investigation of orange juice have found higher levels of proline and arginine accumulated in

351

healthy juice.12 These results are in contrast to what they expected. A possible explanation

352

from their study was uneven distribution of CLas in citrus plants.

38

However, NMR metabolomics

353

In flavonoid composition, the most abundant flavonoids present in orange juice are

354

flavanone-O-glycosides including hesperidin, narirutin, didymin and eriocitrin.39 Besides,

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different polymethoxyflavones in orange juice have been also described. Previously,

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increased levels of flavanone-O-glycosides, including hesperidin, didymin and narirutin were

357

observed in HLB symptomatic Hamlin juice.13,

358

defense against pathogen attack has been summarized.40 Additionally, transcriptome and

359

proteome analyses confirmed that gene expression involved in flavonoid biosynthesis was

360

regulated by CLas infection.41 However, in this study, most flavanone-O-glycosides

361

including didymin, hesperidin and narirutin were higher in concentration of healthy juice

362

when compared to HLB symptomatic juice (Table 5). This is in contrast to what was

363

expected. A possible explanation could be related to the high temperature in CUPS. It should

364

be noted that the average temperature in CUPS is higher than that in the open air, but the

365

wind gust is lower. Temperature, water, radiation, chemical and mechanical stress are abiotic

366

stressors that may influence the production of secondary metabolites in plants.42-43. In the

367

polymethoxyflavone (PMF) profile, nobiletin, sinensetin and isosinensetin had higher levels

368

in symptomatic juice compared to healthy juice (Table 5). Similarly, higher levels of

369

nobiletin and tangeretin found in HLB-infected Valencia and Hamlin juice have been

370

reported.15-16 Similar studies have also demonstrated that pathogen infection facilitates

371

accumulation of PMFs in citrus plants.44-45 Limonin and nomilin are the two major limonoids

372

that contribute to the bitterness of citrus fruits. In general, CLas-infected orange juice had

373

higher levels of limonin and nomilin.10, 13, 15 On the contrary, this study shows lower levels of

374

limonin and nomilin in symptomatic juice compared to healthy juice, whereas the highest

375

concentrations are seen in asymptomatic juice. Currently, it is not clear why low levels of

376

limonin and nomilin are present in HLB symptomatic juice. Regulation of limonoid UDP-

377

glucosyltransferase by HLB infection may partly explain these findings. A transcriptional

17

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study identified the groups of citrus genes involved in CLas infection and gene expression

379

profiles show that the expression level of a limonoid UDP-glucosyltransferase with sinapate

380

1-glucosyltransferase activity increased after CLas infection.46 Their findings imply that

381

CLas infection may increase expression of the limonoid UDP-glucosyltransferase responsible

382

for conversion of limonoids into their corresponding glucosides. Consistent with our

383

findings, chemical analysis of Valencia oranges from Plotto et al. also showed higher

384

concentrations of limonin and nomilin in the healthy fruits when compared to HLB

385

symptomatic fruits.9

386

To further understand whether non-volatile profiles were significantly changed after

387

CLas infection, a PLS-DA plot was constructed. As shown in Figure 1 (C), the PLS-DA

388

score plot showed a clear separation among control, asymptomatic and symptomatic fruits.

389

R2X, R2Y and Q2 were 0.641, 0.494 and 0.317, respectively. The permutation test (n=100)

390

was performed and y-intercepts for R2 and Q2 were 0.158 and -0.297, respectively,

391

suggesting a valid model. In the loadings plot (Figure 1D), proline, nobiletin, phenylalanine

392

and glutamine, were considered to be the most influential in separation of healthy,

393

asymptomatic and symptomatic fruits. Previously, non-volatile metabolite profiles in healthy

394

and HLB-asymptomatic metabolites of Hamlin oranges have been analyzed and the PLS-DA

395

plot score showed that some of the control and asymptomatic fruits were clustered together

396

due to uneven distribution of bacteria and/or false detection by PCR.11 Since the control

397

fruits in this study were collected from CUPS, and a clear separation was found between

398

control and asymptomatic fruits, CLas infection may significantly alter non-volatile profiles

399

of Hamlin oranges before infection is detected by PCR.

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The PLS-DA score plot of all metabolites is given in Figure 1(E). R2X, R2Y and Q2

401

were 0.656, 0.493 and 0.362, respectively. The y-intercepts of R2 and Q2 in the permutation

402

test (n=100) were 0.157 and -0.343, respectively, indicating a valid model. A clear separation

403

among these three groups could be observed and the loading plot revealed several

404

metabolites that were higher in symptomatic fruits, including proline, citric acid, arginine and

405

nobiletin (Figure 1F). In this model, the VIP score of each metabolite was determined (Table

406

6). In theory, the compounds above threshold (VIP >1) are considered to be significant

407

among treatments.47 However, a limited number of samples may result in overfitting of the

408

model.48 Thus, the metabolites with a VIP value ≥ 1.5 were selected in the study. These

409

metabolites include proline, citric acid, nobiletin, d-limonene, glutamine, malic acid and

410

phenylalanine (Table 6). In order to clearly visualize the stage-dependent variations, a heat

411

map with mean intensities of differential metabolites was constructed (Figure 2). Three major

412

clusters could be observed based on the intensity of metabolites. Cluster I consists of three

413

metabolites with increased levels in symptomatic fruits, while cluster II showed decreased

414

levels in the asymptomatic fruits. Glutamine and malic acid in cluster III progressively

415

decreased along with the progression of HLB. Among the metabolites with VIP value ≥ 1.5,

416

no significant differences were found in the levels of proline and d-limonene between control

417

and asymptomatic fruits, while the level of glutamine in asymptomatic fruits also did not

418

show significant differences when compared to the symptomatic fruits (Table 6). Thus, citric

419

acid, nobiletin, malic acid and phenylalanine were identified as potential markers not only for

420

discriminating the CLas-free fruits from CLas-infected fruits, but also for discriminating the

421

HLB asymptomatic fruits from HLB asymptomatic fruits (Table 6). Although metabolic

422

signatures at the different stages of HLB could be discriminated, and the potential metabolic

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biomarkers were identified, one limitation of this study is the sample size. Therefore, a larger

424

sample size and the comprehensive evaluation of environmental factors on potential

425

biomarkers, such as age, harvest region, harvest date and climate impacts, still needs to be

426

further investigated.

427

Overall, metabolite profiling of Hamlin orange juice in this study has shown

428

significant changes in the concentrations of volatile compounds, sugars, organic acid, amino

429

acid, flavonoids and limonoids in response to CLas infection. However, no consistent pattern

430

could be observed in alcohols, sesquiterpenes, esters, sugars, flavanone-O-glycosides, as well

431

as limonoids when compared to previous studies.9-10, 13, 15 Since the healthy Hamlin oranges

432

collected from CUPS were guaranteed CLas-free, this discrepancy suggest CLas may alter

433

metabolite profiles in citrus earlier than detection of CLas by PCR. Four differential

434

metabolites, citric acid, nobiletin, malic acid and phenylalanine, were identified as the

435

metabolic biomarkers associated with the progression of HLB. This study is the first to show

436

the alternations in volatile and non-volatile metabolites of Hamlin orange fruits from truly

437

CLas-free, HLB symptomatic, and HLB symptomatic fruit. Therefore, the differential

438

metabolites found in this study may not only serve as the biomarkers of HLB in its early

439

stage, but also provide useful information for developing potential treatment strategies.

440

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3. ASSOCIATED CONTENT

442 443 444 445 446 447

Supporting information is available free of charge on ACS Publications website

448

Citrus HLB on Hamlin oranges (Figure S1).

449

SRM transitions, collision energy, RF lens and retention time for organic acids (Table S1),

450

amino acids (Table S2) and flavonoids and limonoids (Table S3).

https://urldefense.proofpoint.com/v2/url?u=http3A__pubs.acs.org&d=DwIFaQ&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=fzf5PIRnHimIP EUph6KM6A&m=fRhalqXnXiwgseuwH2VVJSESDOqC93WuABn_i_02248&s=s9LPCcepi9LDyrZlDU2DYKs0c ZdKDSydF6q-zKsm2LQ&e=.

451 452

4. AUTHOR INFORMATION

453

Corresponding Author

454

Telephone: +1-863-956-8673

455

E-mail:[email protected]

456

ORCID:

457

Wei-Lun Hung: 0000-0002-1932-3112

458

Yu Wang: 0000-0002-2003-270X

459

Notes:

460

The authors declare no competing financial interest.

461 462

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463 464

5. ACKNOWLEDGEMENTS

465

We thank Tony Trama (Florida Department of Citrus, FL) for providing the GC-MS

466

instrument for sugar analysis. We thank Dr. Arnold Schumann and Brandon Page for

467

providing Hamlin oranges.

468 469

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6. REFERENCES

471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516

1. Grafton-Cardwell, E. E.; Stelinski, L. L.; Stansly, P. A., Biology and Management of Asian Citrus Psyllid, Vector of the Huanglongbing Pathogens. Annu Rev Entomol 2013, 58, 413-432. 2. Halbert, S. E.; Manjunath, K.; Ramadugu, C.; Lee, R. F., Incidence of Huanglongbing-Associated 'Candidatus Liberibacter Asiaticus' in Diaphorina Citri (Hemiptera: Psyllidae) Collected from Plants for Sale in Florida. Fla Entomol 2012, 95, 617-624. 3. da Graca, J. V.; Kunta, M.; Setamou, M.; Rascoe, J.; Li, W.; Nakhla, M. K.; Salas, B.; Bartels, D. W., Huanglongbing in Texas: Reports on the first detection in commercial citrus. J Citrus Pathol 2015, 2, 1-6. 4. Kumagai, L. B.; LeVesque, C. S.; Blomquist, C. L.; Madishetty, K.; Guo, Y.; Woods, P. W.; RooneyLatham, S.; Rascoe, J.; Gallindo, T.; Schnabel, D.; Polek, M., First Report of Candidatus Liberibacter asiaticus Associated with Citrus Huanglongbing in California. Plant Dis 2013, 97, 283-283. 5. Florida Citrus Statistics 2015-2016. Florida Department of Agriculture and Consumer Services https://www.nass.usda.gov/Statistics_by_State/Florida/Publications/Citrus/Citrus_Statistics/201516/fcs1516.pdf, March, 2017. 6. Florida Citrus Statistics 2013-2014. Florida Department of Agriculture and Consumer Services https://www.nass.usda.gov/Statistics_by_State/Florida/Publications/Citrus/Citrus_Statistics/201314/fcs1314.pdf, February, 2015. 7. Hodges, A.; Spreen, T., Economic impacts of citrus greening (HLB) in Florida, 2006/07-2010/11. Institute of Food and Agricultural Sciences, University of Florida http://www.crec.ifas.ufl.edu/extension/greening/PDF/FE90300.pdf, January, 2012. 8. Tansey, J. A.; Vanaclocha, P.; Monzo, C.; Jones, M.; Stansly, P. A., Costs and benefits of insecticide and foliar nutrient applications to huanglongbing-infected citrus trees. Pest Manag Sci 2017, 73, 904-916. 9. Plotto, A.; Baldwin, E.; McCollum, G.; Manthey, J.; Narciso, J.; Irey, M., Effect of Liberibacter Infection (Huanglongbing or "Greening" Disease) of Citrus on Orange Juice Flavor Quality by Sensory Evaluation. J Food Sci 2010, 75, S220-S230. 10. Dagulo, L.; Danyluk, M. D.; Spann, T. M.; Valim, M. F.; Goodrich-Schneider, R.; Sims, C.; Rouseff, R., Chemical Characterization of Orange Juice from Trees Infected with Citrus Greening (Huanglongbing). J Food Sci 2010, 75, C199-C207. 11. Chin, E. L.; Mishchuk, D. O.; Breksa, A. P.; Slupsky, C. M., Metabolite Signature of Candidatus Liberibacter asiaticus Infection in Two Citrus Varieties. J Agric Food Chem 2014, 62, 6585-6591. 12. Slisz, A. M.; Breksa, A. P.; Mishchuk, D. O.; McCollum, G.; Slupsky, C. M., Metabolomic Analysis of Citrus Infection by 'Candidatus Liberibacter' Reveals Insight into Pathogenicity. J Proteome Res 2012, 11, 4223-4230. 13. Baldwin, E.; Plotto, A.; Manthey, J.; McCollum, G.; Bai, J. H.; Irey, M.; Cameron, R.; Luzio, G., Effect of Liberibacter Infection (Huanglongbing Disease) of Citrus on Orange Fruit Physiology and Fruit/Fruit Juice Quality: Chemical and Physical Analyses. J Agric Food Chem 2010, 58, 1247-1262. 14. Hasegawa, S.; Bennett, R. D.; Herman, Z.; Fong, C. H.; Ou, P., Limonoid Glucosides in Citrus. Phytochemistry 1989, 28, 1717-1720. 15. Kiefl, J.; Kohlenberg, B.; Hartmann, A.; Obst, K.; Paetz, S.; Krammer, G.; Trautzsch, S., Investigation on Key Molecules of Huanglongbing (HLB)-Induced Orange Juice Off-flavor. J Agric Food Chem 2018, 66, 2370-2377 16. Massenti, R.; Lo Bianco, R.; Sandhu, A. K.; Gu, L. W.; Sims, C., Huanglongbing modifies quality components and flavonoid content of 'Valencia' oranges. J Sci Food Agr 2016, 96, 73-78. 17. Freitas, D. D.; Carlos, E. F.; Gil, M. C. S. D.; Vieira, L. G. E.; Alcantara, G. B., NMR-Based Metabolomic Analysis of Huanglongbing-Asymptomatic and -Symptomatic Citrus Trees. J Agric Food Chem 2015, 63, 7582-7588.

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18. Szabados, L.; Savoure, A., Proline: a multifunctional amino acid. Trends Plant Sci 2010, 15, 89-97. 19. Nemec, S.; Meredith, F. I., Amino-Acid Content of Leaves in Mycorrhizal and Non-Mycorrhizal Citrus Rootstocks. Ann Bot-London 1981, 47, 351-358. 20. Cevallos-Cevallos, J. M.; Rouseff, R.; Reyes-De-Corcuera, J., Untargeted metabolite analysis of healthy and Huanglongbing-infected orange leaves by CE-DAD. Electrophoresis 2009, 30, 1240-1247. 21. Hijaz, F. M.; Manthey, J. A.; Folimonova, S. Y.; Davis, C. L.; Jones, S. E.; Reyes-De-Corcuera, J. I., An HPLC-MS Characterization of the Changes in Sweet Orange Leaf Metabolite Profile following Infection by the Bacterial Pathogen Candidatus Liberibacter asiaticus. Plos One 2013, 8. 22. Schumann, A.; Singerman, A., The economics of citrus undercover production systems and whole tree thermotherapy. Citrus Industry 2016, Jan, 14-18. 23. Li, W. B.; Hartung, J. S.; Levy, L., Quantitative real-time PCR for detection and identification of Candidatus Liberibacter species associated with citrus huanglongbing. J Microbiol Meth 2006, 66, 104115. 24. Cerdan-Calero, M.; Sendra, J. M.; Sentandreu, E., Gas chromatography coupled to mass spectrometry analysis of volatiles, sugars, organic acids and aminoacids in Valencia Late orange juice and reliability of the Automated Mass Spectral Deconvolution and Identification System for their automatic identification and quantification. J Chromatogr A 2012, 1241, 84-95. 25. Flores, P.; Hellin, P.; Fenoll, J., Determination of organic acids in fruits and vegetables by liquid chromatography with tandem-mass spectrometry. Food Chem 2012, 132, 1049-1054. 26. Ward, J. H., Hierarchical Grouping to Optimize an Objective Function. J Am Stat Assoc 1963, 58, 236-244. 27. Buettner, A.; Schieberle, P., Evaluation of aroma differences between hand-squeezed juices from valencia late and navel oranges by quantitation of key odorants and flavor reconstitution experiments. J Agric Food Chem 2001, 49, 2387-2394. 28. Seideneck, R.; Schieberle, P., Comparison of the key aroma compounds in hand-squeezed and unpasteurised, commercial NFC juices prepared from Brazilian Pera Rio oranges. Eur Food Res Technol 2011, 232, 995-1005. 29. Tatineni, S.; Sagaram, U. S.; Gowda, S.; Robertson, C. J.; Dawson, W. O.; Iwanami, T.; Wang, N., In planta distribution of 'Candidatus Liberibacter asiaticus' as revealed by polymerase chain reaction (PCR) and real-time PCR. Phytopathology 2008, 98, 592-599. 30. Raithore, S.; Dea, S.; Plotto, A.; Bai, J. H.; Manthey, J.; Narciso, J.; Irey, M.; Baldwin, E., Effect of blending Huanglongbing (HLB) disease affected orange juice with juice from healthy orange on flavor quality. Lwt-Food Sci Technol 2015, 62, 868-874. 31. Cevallos-Cevallos, J. M.; Garcia-Torres, R.; Etxeberria, E.; Reyes-De-Corcuera, J. I., GC-MS Analysis of Headspace and Liquid Extracts for Metabolomic Differentiation of Citrus Huanglongbing and Zinc Deficiency in Leaves of 'Valencia' Sweet Orange from Commercial Groves. Phytochem Analysis 2011, 22, 236-246. 32. Bai, J. H.; Baldwin, E. A.; McCollum, G.; Plotto, A.; Manthey, J. A.; Widmer, W. W.; Luzio, G.; Cameron, R., Changes in Volatile and Non-Volatile Flavor Chemicals of "Valencia" Orange Juice over the Harvest Seasons. Foods 2016, 5, 4. 33. Cevallos-Cevallos, J. M.; Futch, D. B.; Shilts, T.; Folimonova, S. Y.; Reyes-De-Corcuera, J. I., GC-MS metabolomic differentiation of selected citrus varieties with different sensitivity to citrus huanglongbing. Plant Physiol Bioch 2012, 53, 69-76. 34. Jones, D. H., Phenylalanine Ammonia-Lyase - Regulation of Its Induction, and Its Role in Plant Development. Phytochemistry 1984, 23, 1349-1359. 35. Dixon, R. A.; Paiva, N. L., Stress-Induced Phenylpropanoid Metabolism. Plant Cell 1995, 7, 10851097.

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36. Martinelli, F.; Ibanez, A. M.; Reagan, R. L.; Davino, S.; Dandekar, A. M., Stress responses in citrus peel: Comparative analysis of host responses to Huanglongbing disease and puffing disorder. Sci HorticAmsterdam 2015, 192, 409-420. 37. Malik, N. S. A.; Perez, J. L.; Kunta, M.; Patt, J. M.; Mangan, R. L., Changes in free amino acids and polyamine levels in Satsuma leaves in response to Asian citrus psyllid infestation and water stress. Insect Sci 2014, 21, 707-716. 38. Rabe, E.; Lovatt, C. J., Increased Arginine-Biosynthesis during Phosphorus Deficiency - a Response to the Increased Ammonia Content of Leaves. Plant Physiol 1986, 81, 774-779. 39. Gattuso, G.; Barreca, D.; Gargiulli, C.; Leuzzi, U.; Caristi, C., Flavonoid composition of citrus juices. Molecules 2007, 12, 1641-1673. 40. Treutter, D., Significance of flavonoids in plant resistance and enhancement of their biosynthesis. Plant Biology 2005, 7, 581-591. 41. Zhong, Y.; Cheng, C. Z.; Jiang, N. H.; Jiang, B.; Zhang, Y. Y.; Hu, B. M. L.; Zeng, J. W.; Yan, H. X.; Yi, G. J.; Zhong, G. Y., Comparative Transcriptome and iTRAQ Proteome Analyses of Citrus Root Responses to Candidatus Liberibacter asiaticus Infection. Plos One 2015, 10. 42. Ramakrishna, A.; Ravishankar, G. A., Influence of abiotic stress signals on secondary metabolites in plants. Plant Signal Behav 2011, 6, 1720-31. 43. Mittler, R., Abiotic stress, the field environment and stress combination. Trends Plant Sci 2006, 11, 15-19. 44. Del Rio, J. A.; Gomez, P.; Baidez, A. G.; Arcas, M. C.; Botia, J. M.; Ortuno, A., Changes in the levels of polymethoxyflavones and flavanones as part of the defense mechanism of Citrus sinensis (Cv. Valencia late) fruits against Phytophthora citrophthora. J Agric Food Chem 2004, 52, 1913-1917. 45. Ballester, A. R.; Lafuente, M. T.; de Vos, R. C. H.; Bovy, A. G.; Gonzalez-Candelas, L., Citrus phenylpropanoids and defence against pathogens. Part I: Metabolic profiling in elicited fruits. Food Chem 2013, 136, 178-185. 46. Xu, M. R.; Li, Y.; Zheng, Z.; Dai, Z. H.; Tao, Y.; Deng, X. L., Transcriptional Analyses of Mandarins Seriously Infected by 'Candidatus Liberibacter asiaticus'. Plos One 2015, 10. 47. Cho, H. W.; Kim, S. B.; Jeong, M. K.; Park, Y.; Miller, N. G.; Ziegler, T. R.; Jones, D. P., Discovery of metabolite features for the modelling and analysis of high-resolution NMR spectra. Int J Data Min Bioin 2008, 2, 176-192. 48. Ramautar, R.; Nevedomskaya, E.; Mayboroda, O. A.; Deelder, A. M.; Wilson, I. D.; Gika, H. G.; Theodoridis, G. A.; Somsen, G. W.; de Jong, G. J., Metabolic profiling of human urine by CE-MS using a positively charged capillary coating and comparison with UPLC-MS. Mol Biosyst 2011, 7, 194-199.

597

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FIGURE CAPTIONS

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Figure 1. Comparison of metabolite composition of Hamlin orange juice obtained from healthy,

600

asymptomatic and symptomatic fruits. PLS-DA score plot of (A) volatile metabolites, (C) non-

601

volatile metabolites and (E) all metabolites in healthy (green), asymptomatic (blue) and

602

symptomatic (red) fruits. Loadings plot of (B) volatile metabolites, (D) non-volatile metabolites

603

and (F) all metabolites.

604

Figure 2. Heat map of intensity of differential metabolites (VIP ≥ 1.5) in healthy, asymptomatic

605

and symptomatic Hamlin orange fruits. Heat map scale bar indicates log2-fold changes. Shades

606

of blue to red represent increasing intensity of a metabolite. Asterisks (*) denote significant

607

differences (ANOVA, followed by Tukey’s test) between healthy fruits vs. asymptomatic fruits,

608

healthy fruits vs. symptomatic fruits and asymptomatic fruits vs. symptomatic fruits.

609

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(A)

611 612

(B)

t[2]

610

613

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(C)

t[2]

614

615 616

(D)

617

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(E)

619 620

(F)

t[2]

618

621 622

Figure 1.

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624 625 626

Figure 2.

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Table 1. Relative amounts of volatile compounds of HLB-asymptomatic and HLB-symptomatic Hamlin fruits as compared to healthy fruits Asymptomatic

Symptomatic

methyl butanoate

6.78±1.58a

1.96±0.40b

ethyl butanoate

2.88±0.19a

1.72±0.25ab

ethyl hexanoate

2.98±1.04a

1.56±0.34b

total

3.10±0.50a

1.72±0.21ab

hexanal

1.47±0.18a

0.83±0.13b

(E)-2-hexenal

0.77±0.10

0.12±0.09ab

octanal

1.23±0.22

0.33±0.05ab

nonanal

1.93±0.05

2.27±0.96

decanal

1.51±0.29

0.52±0.24b

perillaldehyde

1.00±0.12

1.18±0.11

total

1.26±0.13

0.65±0.08ab

α-pinene

0.97±0.34

1.84±0.31ab

β-mycene

0.81±0.49

1.38±0.22

d-limonene

1.02±0.29

1.51±0.18ab

γ-terpinene

1.43±0.83

2.48±1.00ab

terpinolene

1.11±0.15

1.41±0.21ab

4-terpineol

1.24±0.26

2.08±0.50ab

neral

1.77±0.37a

0.59±0.11ab

α-terpineol

0.53±0.28a

0.44±0.05a

total

1.02±0.29

1.51±0.18ab

1-hexanol

0.40±0.09a

0.35±0.10a

linalool

0.43±0.08a

0.91±0.06b

1-octanol

0.62±0.14a

0.41±0.26a

β-citronellol

0.25±0.08a

0.55±0.05ab

nerol

0.28±0.06a

0.30±0.04a

geraniol

0.83±0.16

0.50±0.20a

total

0.46±0.09a

0.78±0.09b

Esters

Aldehydes

Terpenes

Alcohols

Sesquiterpenes

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valencene

8.02±1.08a

5.74±1.00a

β-elemene

4.32±0.43a

5.06±0.70a

α-humulene

3.62±1.05a

6.54±1.65a

nootkatone

11.52±2.63a

6.04±1.24ab

total

7.70±1.01a

5.69±0.97a

629

Data are expressed as means ± SDs.

630

Means are calculated from three triplicates.

631

Statistical difference was assessed by ANOVA and Tukey’s test (p < 0.05)

632

a

denotes statistical significance compared to healthy fruits

633

b

denotes statistical significance compared to asymptomatic fruits

634

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Table 2. Relative amounts of organic acids and sugars of HLB-asymptomatic and HLBsymptomatic Hamlin juice as compared to healthy juice Asymptomatic

Symptomatic

quinic acid

1.51±0.06a

1.83±0.13ab

ascorbic acid

1.19±0.08

1.69±0.07ab

malic acid

0.70±0.02a

0.43±0.02ab

isocitric acid

2.43±0.33a

3.98±0.37ab

citric acid

1.48±0.09a

1.66±0.08ab

total acids

1.23±0.06a

1.29±0.06a

glucose

1.43±0.03a

1.48±0.04a

fructose

1.27±0.03a

1.28±0.02a

sucrose

1.14±0.04a

0.95±0.02b

total sugars

1.27±0.02a

1.22±0.03a

Organic acids

Sugars

637

Data are expressed as means ± SDs.

638

Means are calculated from three replicates.

639

Statistical difference was assessed by ANOVA and Tukey’s test (p < 0.05)

640

a

denotes statistical significance compared to healthy fruits

641

b

denotes statistical significance compared to asymptomatic fruits

642

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643 644

Table 3. Soluble solids content and titratable acidity in healthy, HLB-asymptomatic and HLBsymptomatic Hamlin orange juice SSC(o Brix)

TAA (%)

SSC/TA

control

7.43±0.06a

0.87±0.03a

8.51±0.19a

asymptomatic

9.93±0.15b

0.92±0.02b

10.76±0.19b

symptomatic

8.93±0.06c

0.96±0.01b

9.34±0.06c

645

Data are expressed as means ± SDs.

646

Means are calculated from three replicates.

647

Statistical difference was assessed by ANOVA and Tukey’s test (p < 0.05)

648

Different letters on online within a column represent statistical significance.

649

SSC: soluble solids content; TA: titratable acidity.

650

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Table 4. Relative amounts of amino acids of HLB-asymptomatic and HLB-symptomatic Hamlin juice as compared to healthy juice Asymptomatic

Symptomatic

phenylalanine

0.23±0.02a

0.70±0.09ab

leucine

0.13±0.01a

0.23±0.02a

isoleucine

0.30±0.03a

0.71±0.07ab

methionine

0.11±0.02a

0.24±0.08a

tyrosine

0.27±0.04a

0.44±0.07a

valine

0.34±0.01a

0.55±0.06a

proline

0.95±0.02

2.29±0.23ab

alanine

0.59±0.04a

0.94±0.08

threonine

0.41±0.04a

0.73±0.07ab

glutamic acid

0.73±0.10

1.00±0.16

glutamine

0.09±0.01a

0.13±0.01a

serine

0.47±0.06a

0.73±0.07

asparagine

0.45±0.05a

0.74±0.07

aspartic acid

0.84±0.10a

1.48±0.14

histidine

0.45±0.10a

1.03±0.08

arginine

1.09±0.21

1.33±0.09

lysine

0.71±0.15

1.01±0.08

653

Data are expressed as means ± SDs.

654

Means are calculated from three replicates.

655

Statistical difference was assessed by ANOVA and Tukey’s test (p < 0.05)

656

a

denotes statistical significance compared to healthy fruits

657

b

denotes statistical significance compared to asymptomatic fruits

658

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659 660

Table 5. Relative amounts of flavonoids and limonoids of HLB-asymptomatic and HLBsymptomatic Hamlin juice as compared to healthy juice Asymptomatic

Symptomatic

eriocitrin

0.66±0.04a

0.91±0.02ab

narirutin

0.74±0.06a

0.63±0.07ab

hesperidin

0.54±0.02a

0.61±0.03ab

didymin

0.55±0.05a

0.38±0.09a

isosinensetin

0.22±0.01a

1.42±0.15ab

sinensetin

0.40±0.01a

1.40±0.06ab

limonin

1.28±0.01a

0.57±0.01ab

5,6,7,3’,4’,5’hexamethoxyflavone

0.38±0.01a

1.08±0.04b

nobiletin

0.36±0.01a

1.18±0.03ab

nomilin

3.67±0.01a

0.16±0.00ab

3,5,6,7,8,3’,4’heptamethoxyflavone

0.42±0.01a

0.99±0.04b

tangeretin

0.36±0.01a

0.99±0.05b

661

Data are expressed as means ± SDs.

662

Means are calculated from three replicates.

663

Statistical difference was assessed by ANOVA and Tukey’s test (p < 0.05)

664

a

denotes statistical significance compared to healthy fruits

665

b

denotes statistical significance compared to asymptomatic fruits

666

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Table 6. List of altered metabolites identified in the PLS-DA model.

Metabolites

Healthy vs. Asy

Healthy vs. Sym

Asy vs. Sym

(FC)

(FC)

(FC)

VIP

proline

3.99

0.95±0.02

2.29±0.23ab *

2.41±0.20*

citric acid

3.13

1.48±0.09*

1.66±0.08*

1.12±0.09*

nobiletin

2.36

0.36±0.01*

1.18±0.03*

3.26±0.12*

d-limonene

2.26

1.02±0.29

1.51±0.18*

1.48±0.25*

glutamine

2.17

0.09±0.01*

0.13±0.01*

1.44±0.06

malic acid

1.84

0.70±0.02*

0.43±0.02*

0.61±0.04*

phenylalanine

1.50

0.23±0.02*

0.70±0.09*

3.04±0.39*

668

Variable importance in the projection (VIP) value was obtained from the PLS-DA model with

669

threshold of 1.5. Fold changes (FC) of the mean concentrations in healthy vs. asymptomatic and

670

healthy vs. symptomatic groups were calculated by comparing those metabolites in CLas-

671

infected fruits to healthy fruits. Fold changes in asymptomatic vs. symptomatic group was

672

calculated by comparing those metabolites in symptomatic fruits to asymptomatic fruits. *

673

denotes statistical significance compared to healthy or asymptomatic fruits (p