NMR-Based Metabolomic Analysis of Huanglongbing-Asymptomatic

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NMR-BASED METABOLOMIC ANALYSIS OF HUANGLONGBINGASYMPTOMATIC AND SYMPTOMATIC CITRUS TREES Deisy dos Santos Freitas, Eduardo Fermino Carlos, Márcia Cristina Soares de Souza Gil, Luiz Gonzaga Esteves Vieira, and Glaucia Braz Alcantara J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.5b03598 • Publication Date (Web): 19 Aug 2015 Downloaded from http://pubs.acs.org on August 20, 2015

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Journal of Agricultural and Food Chemistry

NMR-BASED METABOLOMIC ANALYSIS OF HUANGLONGBINGASYMPTOMATIC AND SYMPTOMATIC CITRUS TREES

Deisy dos Santos Freitas1, Eduardo Fermino Carlos2, Márcia Cristina Soares de Souza Gil3, Luiz Gonzaga Esteves Vieira4, Glaucia Braz Alcantara1*

1

Universidade Federal de Mato Grosso do Sul (UFMS), Instituto de Química,

CP 549, CEP 79.074-460, Campo Grande, MS, Brazil 2

Instituto Agronômico do Paraná (IAPAR), Laboratório de Biotecnologia

Vegetal, CP 481, CEP 86.001-970, Londrina, PR, Brazil 3

Instituto Agronômico de Campinas (IAC), Laboratório de Biotecnologia, CP 04,

CEP 13.490-970, Cordeirópolis, SP, Brazil 4

Universidade do Oeste Paulista (UNOESTE), Rodovia Raposo Tavares, km

572, CEP 19.067-175, Presidente Prudente, SP, Brazil

*Corresponding author: Glaucia Braz Alcantara Universidade Federal de Mato Grosso do Sul, Instituto de Química, Av. Filinto Muller, 1555, CP 549, CEP 79074-460, Campo Grande, MS, Brazil Tel.: +55 67 3345-3577; Fax: +55 67 3345-3552. e-mail: [email protected]

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Abstract

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Huanglongbing (HLB) is one of the most severe diseases that affects citrus

3

trees worldwide and is associated with the yet uncultured bacteria

4

Candidatus Liberibacter spp. To assess the metabolomic differences

5

between HLB-asymptomatic and symptomatic tissues, the extracts from leaf

6

and root samples taken from a uniform 6-year-old commercial orchard of

7

Valencia trees were subjected to Nuclear Magnetic Resonance (NMR) and

8

chemometrics. Our results show that the symptomatic trees had higher

9

sucrose content in their leaves and no variation in their roots. In addition,

10

proline betaine and malate were detected in smaller amounts in the HLB-

11

affected symptomatic leaves. The changes in metabolic processes of the

12

plant in response to HLB are corroborated by the relationship between the

13

bacterial levels and the metabolic profiles.

14 15

Keywords: Huanglongbing (HLB), Candidatus Liberibacter, NMR, chemometrics,

16

plant response, citrus greening disease.

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Journal of Agricultural and Food Chemistry

1 Introduction

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Huanglongbing (HLB), which is also known as the citrus greening disease, is one

20

of the most serious and destructive diseases to the citrus industry and is

21

responsible for large economic losses in all major citrus-producing areas

22

worldwide, with the exception of Europe up to this moment. The disease has

23

been reported in China for more than two centuries and was first detected on the

24

American continent in Brazil in 20041,2 and in the USA in 2005.3 The infection is

25

associated with three yet-uncultured Candidatus Liberibacter species, which are

26

named after the places in which they were first identified: Ca. L. africanus, Ca. L.

27

asiaticus and Ca. L. americanus. These Gram-negative bacteria inhabit the

28

phloem of the HLB-affected plants and have a typical membrane structure.4 In

29

the early stages of disease progression, the infected trees are asymptomatic and

30

visually indistinguishable from healthy ones. In the well-developed symptomatic

31

stages, there are leaf blotchy mottle, small and lopsided fruits, a reduction in

32

plant vigor and a decline in production.5,6 However, for the early assessments

33

that require a definitive diagnosis of HLB, the polymerase chain reaction (PCR) is

34

commonly used.7 The disease is spread by flying insect vectors (psyllids

35

Diaphorina citri in America and Asia and Trioza erytreae in Africa) and the

36

grafting of contaminated buds.5 In addition, HLB has been found in all

37

commercial citrus species, which makes it notably difficult to enforce effective

38

controlling measures.7,8 Despite the spread of the disease, Fan et al. (2013)8 and

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Folimonova et al. (2009)9 reported the existence of citrus species with different

40

levels of susceptibility to the disease.

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The large geographical distribution and severity of the disease have stimulated

42

diverse approaches to understanding the mechanisms of the plant-pathogen

43

interaction and will eventually provide alternative concepts to explain the ongoing

44

progression of HLB.

45

As expected, the HLB bacterium triggers various responses, which range from an

46

altered cellular metabolism to differential gene expression. One informative study

47

performed by Etxeberria et al. (2009)10 found abnormally high levels of starch in

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the HLB-affected Valencia orange trees. The development of HLB in plants

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causes the collapse of regular phloem flow, triggering an abnormal accumulation

50

of starch in the affected source tissues, such as leaves, and a depletion in the

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sink tissues, such as roots. Starch is a natural product of carbon fixation in

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plants; however, Ca. Liberibacter spp. induces significant modifications in the

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phloem transport of photo-assimilates, which results in the excessive

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accumulation of starch granules,10 beyond the sucrose accumulation due to the

55

carbohydrate imbalance.11

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Gas Chromatography - Mass Spectrometry applied to the study of citrus cultivars

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showed varying metabolic profiles in response to HLB.12 A metabolomic analysis

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of the juice from HLB-affected fruits revealed significant changes in several

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compounds,13 which may be associated with the effect of the pathogen on the

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plant defense mechanisms.14

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Understanding how HLB changes the overall metabolism of plants, even in the

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asymptomatic stages, may provide important information about the plant-

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pathogen interactions. This knowledge may prove fundamental for finding new

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methods to control the disease. Nuclear Magnetic Resonance (NMR) has been

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widely used in metabolomic analyses via different applications because this

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robust technique enables the identification and quantification of metabolites.15 In

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most cases, the samples are easily prepared, and the analysis is rapid and

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reproducible. The combination of NMR and chemometrics can help to identify

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metabolic patterns in plants under stress conditions such as those caused by

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diseases.

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In this context, the present work aimed to apply NMR and chemometrics to the

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metabolomic evaluation of HLB-affected leaves and roots in the asymptomatic

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and symptomatic stages of the disease.

74 75

2 Materials and methods

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2.1 Plant material

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The leaf and secondary root samples of symptomatic (SYM) and asymptomatic

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(ASY) HLB-affected trees were collected in August 2012 from a 6-year-old grove

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with Valencia sweet orange (Citrus sinensis L. Osbeck) on Rangpur Lime

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rootstock (Citrus limonia Osbeck) in a commercial citrus orchard near

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Taquaritinga in the central part of São Paulo State. All trees received normal

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grove management, pest control and fertilization.

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The SYM plants showed the typical yellowish asymmetrical chlorosis of the

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leaves, as well as small and lopsided fruits, whereas the ASY plants showed

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normal shoots, leaves, and fruits. Samples from roots were collected of the same

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side of the canopy where leaf samples were taken. All samples (the SYM and

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ASY groups) were subjected to a titer estimation of Ca. Liberibacter asiaticus

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using quantitative real-time PCR (qPCR).

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A total of ten neighboring orange trees in the same planting row were collected:

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five SYM and five ASY biological samples. About forty leaves and a piece of

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secondary roots per tree were sampled. Among five ASY biological samples, one

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plant did not show a detectable level of bacterium in the leaves by qPCR

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analysis, but it showed a detectable level of bacterium in roots (in this study) and

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fruits (data not shown). The same case occurred for one root. As reported by

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Chin and coworkers (2014),13 the bacteria are not evenly distributed throughout

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the tree, thus false negatives can occur in qPCR. Therefore, the negative

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samples for Ca. Liberibacter asiaticus are highlighted in the PCA figures (Figures

100

2A and 3A) as ASY-ND (non-detected HLB in the ASY samples), but they belong

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to the ASY group.

102 103

2.2 Sample preparation and qPCR analysis

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The sample preparation and analysis of qPCR were performed according to the

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procedure outlined by Coletta-Filho et al. (2010).7 The qPCR data showed

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averaged cycle threshold (Ct) values of 23.6 ± 1.3 for the SYM leaves and 36.3 ±

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2.3 for the ASY leaves, whereas the Ct values for roots were 31.6 ± 3.9 for the

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SYM and 38.8 ± 0.7 for the ASY samples. Samples with Ct value ≥ 40 were

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negative for Ca. Liberibacter asiaticus.

111 112

2.3 Sample preparation and NMR analysis

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Each biological sample was independently analyzed, with three technical

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replicates. For each replicate, 80 mg of leaves or roots were manually macerated

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for 2 min. Extractions were performed with 1 mL of TMSP-D4/D2O 0.05% solution

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in phosphate buffer (KH2PO4/Na2HPO4) at pH 5.4 and sonicated for 20 min. The

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extracts were centrifuged, filtered and maintained at approximately 1 ºC until the

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NMR analyses were performed. The extracts were directly inserted into 5 mm

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NMR tubes.

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The 1H NMR measurements were obtained using a Bruker DPX 300 (7.05 T)

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spectrometer, which operated at 300.13 MHz for 1H. The 1H NMR spectra were

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acquired at 20ºC using a composite pulse presaturation sequence to suppress

123

the solvent signal (D2O), with 128 scans, 65,536 points, an acquisition time of

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3.64 s, a relaxation delay of 2 s and a spectral window of 30 ppm. The spectra

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were processed with 65,536 points in the Fourier transformation and subjected to

126

exponential multiplication of 0.30 Hz with manual phase and baseline corrections.

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Two-dimensional experiments (gHSQC, gHMBC and gTOCSY) were conducted

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at the default parameters to further support compound identification.

129 130

2.4 Principal Component Analysis (PCA) and statistical analysis

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The 1H NMR spectra were introduced into the AMIX program (3.8 Bruker) and

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subjected to exploratory analyses using PCA. The 0.75-8.26 ppm proton region

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of the leaf extracts and the 0.70-8.10 ppm proton region of root extracts were

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evaluated; the region between 4.60-5.20 ppm was excluded, which corresponds

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to the deuterated water signal. Buckets were constructed through a simple

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rectangular format with 0.04 ppm of width and integrated normalizing by the sum

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of the absolute intensities. The samples were mean-centered and Pareto scaling

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pre-processing was applied for leaves and roots.

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Statistical analyses were performed using the integration values from the signals

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with high loadings in PCA relative to the TMSP-D4 signal in the 1H NMR spectra.

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The Student's t test was applied to assess the differences between the means of

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the ASY and SYM groups. PCA and statistical analyses were performed with a

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95% confidence level. A P-value below 0.05 was used to indicate statistical

145

significance.

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3 Results and Discussion

148 149

3.1 Identification of metabolites in the leaves and roots

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The ASY and SYM leaves and roots had similar spectral profiles but different

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signal intensities (Fig. 1). The

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dimensional experiments and the literature16-19 supported the identification of

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carbohydrates, amino acids, organic acids and other compounds. The identified

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metabolites and their chemical shifts are reported in Table 1.

1

H NMR spectra associated with the two-

156 157

3.2 Multivariate analysis by PCA in the leaves and roots

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The changes caused by HLB in the leaves and roots of the citrus plants were

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evaluated using PCA, which enabled the observation of the natural clustering of

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the samples and unsupervised pattern recognition. The ASY and SYM leaves

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were distinguished on the score plot (Fig. 2-A). The characteristic spectral region

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of carbohydrates was responsible for the disposition of the SYM samples in the

164

negative PC1 values, which included the signals related to sucrose (Fig. 2-B).

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The loadings that corresponded to malate and proline betaine were important for

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allocating the ASY samples to the more positive values of PC2. The ASY-ND

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scores are close to those of the ASY leaves, although they were allocated to the

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positive PC2 axis because of the greater contribution of proline, proline betaine

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and malate, and the smaller contribution of sucrose.

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In Fig. 3-A, the roots of the asymptomatic plants were indistinguishable from

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those of symptomatic ones. However, there was a tendency of separation

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between these groups of samples. The ASY-ND roots were detached from the

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HLB-affected ones on the PC1 axis. The sucrose signals were the variables

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responsible for allocating the ASY-ND roots to the more negative values of PC1

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(Fig. 3-B).

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Fig. 4 illustrates the relative proportion of highlighted metabolites in the loading

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plots (sucrose, proline betaine, malate and proline), which are responsible for the

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separation of the ASY and SYM samples. The SYM leaves had a higher sucrose

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content than the ASY ones (Fig. 4-A1; P=4.77e-5), although the ASY and SYM

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roots were not significantly different in terms of sucrose content (Fig. 4-A2;

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P=0.086). The SYM leaves showed a significant decrease in the proline betaine

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and malate content (Figs. 4-A3 and 4-A4; P=3.71e-9 and P=2.18e-6,

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respectively), whereas the proline content was not significantly different between

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the ASY and SYM leaves (Fig. 4-A5; P=0.65).

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3.3 Role of sucrose, proline betaine, proline, and malate in HLB-affected citrus

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Our results indicate that sucrose is an important metabolite for evaluating HLB-

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affected leaves. Sucrose is the principal source of energy that is transported by

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the phloem in plants, whereas starch is a stable source of energy that can be

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stored in the plants. Several reports have indicated the accumulation of starch in

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HLB-affected trees.8,10,20,21 However, starch accumulation is detrimental to the

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plants because of the large volume that it occupies, which disintegrates the

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thylakoid membrane and causes chlorosis of the leaves.9

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The starch and sucrose formations occur simultaneously, so an increase in

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sucrose concentration may cause a source-sink metabolic imbalance. The 10 ACS Paragon Plus Environment

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transcriptome data from young HLB-infected leaves also show that the genes

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involved in both sucrose metabolism and starch biosynthesis were upregulated.22

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Fan et al. (2010) found no significant difference in sucrose content between

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asymptomatic and symptomatic leaves; however, both types of leaves were

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sampled from infected plants with HLB symptoms.11 In our case, the

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asymptomatic leaves were collected from asymptomatic plants; thus, we

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observed a sucrose accumulation in the SYM leaves (Fig. 4-A1). The high

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concentration of sucrose in the SYM leaves suggests that this metabolite cannot

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be normally transported to other parts of the plant. For the roots, this

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accumulation was not observed (Fig. 4-A2) because the phloem vessel was

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blocked by the Ca. Liberibacter spp. bacteria, which alters the transport of

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sucrose to all parts of the plant.

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Proline betaine is commonly found in the Rutaceae species and can be formed

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by consecutive methylations of proline.23 Proline and proline betaine are

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traditionally considered non-toxic compatible osmolytes24 and are generally

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associated with the osmotic adjustment and protection of subcellular structures

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during abiotic 23,25-28 and biotic stresses.29

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We detected a decrease in proline betaine content in the SYM leaves (Fig. 4-A3),

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whereas no significant variation was observed for proline (Fig. 4-A5). Proline

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betaine has not been reported in HLB-affected citrus leaves,30 but it has been

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observed in juices of HLB-affected oranges with negligible variation.12,13 As noted

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by Seifi et al. (2013),31 the redox-regulating potential of proline may be important

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in its defense against pathogens, but the pathogens can also exploit these

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mechanisms to induce susceptibility. Lower proline levels were found in the

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juices from asymptomatic and symptomatic fruits.13 These results are different

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from the findings of Cevallos-Cevallos et al. (2011),30 who reported significantly

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higher concentrations of this amino acid in HLB-affected leaves.

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Despite the observed accumulation of proline in response to the abiotic and biotic

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stresses in many plant species, the metabolic alterations in proline and proline

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betaine content in the HLB-symptomatic leaves remain unclear and may indicate

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a specific plant-pathogen relationship that specifically modifies this metabolic

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pathway. Therefore, further studies on the precursors, co-factors, expression and

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activities of the key enzymes in the metabolism and catabolism of proline and

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proline betaine are necessary to understand and characterize the role of these

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amino acids in the citrus response to HLB infection in different tissues and stages

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of disease development.

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Malate is reported to be a substrate that performs various functions in the cells,32

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which include supplying carbon skeletons for the biosynthesis of amino acids.33 It

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is an important intermediary component in the citric acid cycle,34 and variations in

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malate content have been associated with the plant response to stress

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conditions.35 Malate can be formed from phosphoenolpyruvate, which is a

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product of glycolysis. Phosphoenolpyruvate is carboxylated by the action of the

239

PEP carboxylase enzyme to produce oxaloacetate, which is reduced to malate

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by the action of malate dehydrogenase.36 An important functionality in plants is

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the action of the NAD-malic enzyme, which converts malate to pyruvate.

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Consequently, malate plays an important role in maintaining the activities of the

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citric acid cycle and in the production of some amino acids.37

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In our study, a decrease in malate content was observed in the SYM leaves (Fig.

245

4-A4). This result suggests that HLB significantly changes the essential metabolic

246

processes and affects the normal plant development. The change in malate

247

content may indicate the greater consumption of this metabolite to maintain the

248

normal functions of the citric acid cycle, which suggests that other substrates

249

may be consumed for the plant defense.

250 251

3.4 Relationship between NMR metabolic profiles and qPCR

252 253

It is possible to relate the observed changes in metabolic profiles with the

254

quantity of bacteria in the samples (Fig. 4). The performed NMR analyses in this

255

work show that greater sucrose content in the leaves (Fig. 4-A1) is observed

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when the symptoms are observable, i.e., when there is a high bacterial

257

concentration (Ct value 23.6 ± 1.3 for the SYM leaves, Fig. 4-B). Thus, the HLB-

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affected leaves with a low quantity of bacteria and therefore do not show any

259

symptoms (Ct value 36.3 ± 2.3 for the ASY leaves, Fig. 4-B) do not display

260

sucrose accumulation, although they are already infected with the disease.

261

Meanwhile, equivalent sucrose content was detected in both the ASY and SYM

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HLB-affected roots (Fig. 4-A2). Therefore, even in the ASY roots (Ct value 38.8 ±

263

0.7, Fig. 4-B), HLB sufficiently alters the phloem to inhibit the transport of sucrose

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from the leaves to the roots, as expected for the SYM roots (Ct value 31.6 ± 3.9,

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Fig. 4-B).

266

The proline betaine and malate content (Figs. 4-A3 and 4-A4) shows an inversely

267

proportional decrease with the level of bacteria in the leaves (Fig. 4-B). The plant

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response can be observed in the SYM leaves because of a reduction in content

269

of these compounds, which may be associated with their catabolism for plant

270

defense.

271

In summary, our data show modifications in the metabolic profiles of the leaves

272

and less pronounced changes in the roots, which proves that NMR and

273

chemometrics approaches are effective techniques for the metabolomic study of

274

HLB-affected plants. An increase in sucrose content in the leaves and the

275

negligible changes of this metabolite in the roots demonstrate the collapse of the

276

phloem transportation, which is caused by Ca. Liberibacter asiaticus. The

277

decrease in proline betaine and malate content suggests that these compounds

278

are associated with response mechanisms. This study provides important results

279

to further the understanding of the progression of HLB in citrus trees, which can

280

be helpful in developing strategies to control HLB in the future.

281 282

Abbreviations Used

283

ASY: Asymptomatic; ASY-ND: non-detected HLB in the ASY samples; Ct:

284

averaged cycle threshold from qPCR data; gHMBC: gradient Heteronuclear

285

multiple bond correlation; gHSQC: Gradient heteronuclear single quantum

286

coherence;

gTOCSY:

Gradient

total

correlation

spectroscopy;

HLB:

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Huanglongbing; NMR: Nuclear magnetic resonance; PCA: Principal component

288

analysis; qPCR: Quantitative Real Time Polymerase Chain Reaction; SYM:

289

Symptomatic; TMSP-D4: 2,2,3,3-d4-3-(trimethylsilyl)propionic acid sodium salt.

290 291

Funding

292

This research was supported by Coordenação de Aperfeiçoamento de Pessoal

293

de Nível Superior (CAPES), Fundação de Apoio ao Desenvolvimento do Ensino,

294

Ciência e Tecnologia do Estado de Mato Grosso do Sul (FUNDECT) and

295

Fundação Araucária.

296

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References (1) Texeira D. C.; Ayres A. J.; Kitajima E. W.; Tanaka F. A. O.; Danet J. L.; Jagoueix-Eveillard S.; Saillard C.; Bové J. M. First report of a Huanglongbing-like disease of citrus in Sao Paulo State, Brazil, and association of a new Liberibacter species, “Candidatus Liberibacter americanus”, with the disease. Plant Dis. 2005, 89, 107. (2) Coletta-Filho, H. D.; Takita, M. A.; Targon, M. L. P. N.; Machado, M. A. Analysis of the 16S rDNA sequences from citrus-huanglongbing bacteria reveal a different “Ca. Liberibacter” strain associated to the citrus disease in Sao Paulo, Brazil. Plant Dis. 2005, 89, 848–852. (3) Halbert, S. E. The discovery of huanglongbing in Florida. Proceedings of 2nd International

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http://freshfromflorida.s3.amazonaws.com/2nd_International_Canker_Huanglong bing_Research_Workshop_2005.pdf. Accessed 16 October 2014. (4) Garnier M.; Bové J. M. Structure trilamellaire des deux membranes qui entourent les organismes procaryotes associés à la maladie du “greening” des agrumes. Fruits 1977, 32, 749-752. (5) Bové, J. M. Huanglongbing: a destructive, newly-emerging, century-old disease of citrus. J. Plant Pathol. 2006, 88, 7-37. (6) da Graça, J. V. Citrus greening disease. Annu. Rev. Phytopathol. 1991, 29, 109-136. (7) Coletta-Filho, H. D.; Carlos, E. F.; Alves, K. C. S.; Pereira, M. A. R.; Boscariol-Camargo, R. L.; Souza, A. A.; Machado, M. A. In planta multiplication

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and graft transmission of Candidatus Liberibacter asiaticus revealed by RealTime PCR. Eur. J. Plant Pathol. 2010, 126, 53-60. (8) Fan, J.; Chen, C.; Achor, D. S.; Brlansky, R. H.; Li, Z.; Gmitter Jr.; F. G. Differential anatomical responses of tolerant and susceptible citrus species to the infection of ‘Candidatus Liberibacter asiaticus’. Physiol. Mol. Plant Pathol. 2013, 83, 69-74. (9) Folimonova, S. Y.; Robertson, C. J.; Garnsey, S. M.; Gowda, S.; Dawson, W. O. Examination of the responses of different genotypes of citrus to Huanglongbing (Citrus Greening) under different conditions. Phytopathology 2009, 99, 1346-1354. (10) Etxeberria, E.; Gonzalez, P.; Achor, D.; Albrigo, G. Anatomical distribution of abnormally high levels of starch in HLB-affected Valencia orange trees. Physiol. Mol. Plant Pathol. 2009, 74, 76-83. (11) Fan, J.; Chen, C.; Brlansky, R. H.; Gmitter Jr, F. G.; Li, Z. G. Changes in carbohydrate metabolism in Citrus sinensis infected with ‘Candidatus Liberibacter asiaticus’. Plant Pathol. 2010, 59, 1037-1043. (12) Cevallos-Cevallos, J. M.; Futch, D. B.; Shilts, T.; Folimonova, S. Y.; ReyesDe-Corcuera, J. I. GC-MS metabolomic differentiation of selected citrus varieties with different sensitivity to citrus Huanglongbing. Plant Physiol. Biochem. 2012, 53, 69-76. (13) 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.

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Figure Captions

Figure 1. Representative 1H NMR spectral profile of the extracts from the asymptomatic (1) and symptomatic (2) leaves (A) and roots (B).

Figure 2. PCA score (A) and loading (B) plots from 1H NMR spectra of the extracts from non-detected HLB (), asymptomatic () and symptomatic () leaves. Legend: Mal, malate; Pro, proline; Pro-bet, proline betaine; Suc, sucrose.

Figure 3. PCA score (A) and loading (B) plots from 1H NMR spectra of the extracts from non-detected HLB (), asymptomatic () and symptomatic () roots. Legend: Suc, sucrose.

Figure 4. A) Relative ratio (obtained by integration from signal of the compound in the 1H NMR spectra normalized by TMSP-D4 signal) of sucrose in the extracts from leaves (1) and roots (2); proline betaine (3), malate (4) and proline (5) in the extracts from leaves. Data are displayed as a mean of relative ratio ± standard deviation. Different letters on bars indicate significant differences (P