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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
8 9 10 11 12 13
*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
17
University of Florida
18
700, Experiment Station Rd,
19
Lake Alfred, FL 33850 USA
20
Phone: 863-956-8673
21
Fax: 863-956-4631
22
E-mail:
[email protected] 1
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ABSTRACT
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Huanglongbing (HLB), also known as Citrus Greening Disease, caused by Candidatus
25
Liberibacter asiaticus (CLas) is considered the most serious citrus disease in the world. CLas
26
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
28
polymerase chain reaction (PCR) detection, the infected trees may test false negative. To prevent
29
this, metabolites of healthy Hamlin oranges (CLas-) obtained from the citrus undercover
30
protection systems (CUPS) were investigated. Comparison of the metabolite profile of juice
31
obtained from CLas- and CLas+ (asymptomatic and symptomatic) trees revealed significant
32
differences in both volatile and non-volatile metabolites. However, no consistent pattern could be
33
observed in alcohols, esters, sesquiterpenes, sugars, flavanones and limonoids as compared to
34
previous studies. These results suggest that CLas may affect metabolite profiles of citrus fruits
35
earlier than detecting infection by PCR. Citric acid, nobiletin, malic acid and phenylalanine were
36
identified as the metabolic biomarkers associated with the progression of HLB. Thus, the
37
differential metabolites found in this study may serve as the biomarkers of HLB in its early
38
stage, and the metabolite signature of CLas infection may provide useful information for
39
developing a potential treatment strategy.
40 41 42
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
47
genus Candidatus Liberibacter , which infects the phloem of the tree. The three species of this
48
bacterium, including asiaticus (CLas), africanus and americanus, are known to cause HLB. The
49
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-
99
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
6
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
185
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
188
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
190
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
224
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
227
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,
229
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
231
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
235
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
243
goodness-of-fit parameter (R2X and R2Y) and predictive ability parameter (Q2) were used to
244
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
246
projection (VIP) value, weight sum of squares of the PLS loading weights, greater than 1.5
247
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
249
constructing a heat map, the raw data were normalized by median, followed by log
250
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
254
soapy odor in the juice.27-28 In Hamlin juice, a previous study showed decreased levels of
255
aldehyde compounds, including acetaldehyde, octanal and hexanal, in the HLB symptomatic
256
orange fruits as compared to healthy fruits.13 Similar to those results, this study shows
257
decreased levels of hexanal, (E)-2-hexanal, octanal and decanal in symptomatic juice as
258
compared to healthy fruits (Table 1). On the contrary, Dagulo et al. suggest that aldehyde
259
compounds including octanal, nonanal and decanal were higher in concentration of HLB
260
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-
265
limonene as well as total amounts of terpenes were higher in concentration of HLB
266
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
268
butanoate, ethyl butanoate and ethyl hexanoate in HLB asymptomatic and symptomatic juice
269
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,
272
hexanol, 1-octanol, β-citronellol, nerol and geraniol, had lower levels in both asymptomatic
273
and symptomatic fruits compared to controls (Table 1). On the contrary, Dagulo et al. have
274
reported that CLas infection resulted in accumulation of alcohol compounds in Hamlin
275
orange juice, while Baldwin et al. has shown that CLas infection did not significantly affect
276
accumulation of alcohol compounds in Hamlin orange juice.10, 13 In the sesquiterpene profile,
277
valencene, α-humulene, β-elemene, and nootkatone had the lowest levels in the healthy juice,
278
while asymptomatic juice had the highest concentration of total sesquiterpenes (Table 1). In
279
contrast to our results, a higher concentration of total sesquiterpenes accumulated in healthy
280
Hamlin orange juice was observed.10 Our current findings together with volatile profiles of
281
Hamlin fruits reported from previous studies indicate that no apparent pattern can be
282
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
285
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
290
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
293
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
296
and 0.289, respectively. After the permutation test was performed, y-intercepts for R2 and Q2
297
were 0.389 and -0.186, respectively, indicating a valid model. The clusters of asymptomatic
298
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.
302
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,
304
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
306
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
311
fructose, while the level of sucrose in symptomatic juice was similar to healthy juice (Table
312
2). Fructose and glucose have been shown to increase in Hamlin asymptomatic oranges
313
compared to the control fruits.11 Similarly, accumulation of glucose and fructose by CLas
314
infection could be observed in citrus leaves.31 However, lower levels of sucrose, glucose and
315
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
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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
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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
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profiles show that the expression level of a limonoid UDP-glucosyltransferase with sinapate
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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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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
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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.
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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
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differences (ANOVA, followed by Tukey’s test) between healthy fruits vs. asymptomatic fruits,
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healthy fruits vs. symptomatic fruits and asymptomatic fruits vs. symptomatic fruits.
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(A)
611 612
(B)
t[2]
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t[2]
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615 616
(D)
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619 620
(F)
t[2]
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Figure 1.
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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