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Article
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:
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Abstract
2
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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1 Introduction
18 19
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.
41
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
48
the HLB-affected Valencia orange trees. The development of HLB in plants
49
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
51
sink tissues, such as roots. Starch is a natural product of carbon fixation in
52
plants; however, Ca. Liberibacter spp. induces significant modifications in the
53
phloem transport of photo-assimilates, which results in the excessive
54
accumulation of starch granules,10 beyond the sucrose accumulation due to the
55
carbohydrate imbalance.11
56
Gas Chromatography - Mass Spectrometry applied to the study of citrus cultivars
57
showed varying metabolic profiles in response to HLB.12 A metabolomic analysis
58
of the juice from HLB-affected fruits revealed significant changes in several
59
compounds,13 which may be associated with the effect of the pathogen on the
60
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-
63
pathogen interactions. This knowledge may prove fundamental for finding new
64
methods to control the disease. Nuclear Magnetic Resonance (NMR) has been
65
widely used in metabolomic analyses via different applications because this
66
robust technique enables the identification and quantification of metabolites.15 In
67
most cases, the samples are easily prepared, and the analysis is rapid and
68
reproducible. The combination of NMR and chemometrics can help to identify
69
metabolic patterns in plants under stress conditions such as those caused by
70
diseases.
71
In this context, the present work aimed to apply NMR and chemometrics to the
72
metabolomic evaluation of HLB-affected leaves and roots in the asymptomatic
73
and symptomatic stages of the disease.
74 75
2 Materials and methods
76 77
2.1 Plant material
78 79
The leaf and secondary root samples of symptomatic (SYM) and asymptomatic
80
(ASY) HLB-affected trees were collected in August 2012 from a 6-year-old grove
81
with Valencia sweet orange (Citrus sinensis L. Osbeck) on Rangpur Lime
82
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
84
grove management, pest control and fertilization.
85
The SYM plants showed the typical yellowish asymmetrical chlorosis of the
86
leaves, as well as small and lopsided fruits, whereas the ASY plants showed
87
normal shoots, leaves, and fruits. Samples from roots were collected of the same
88
side of the canopy where leaf samples were taken. All samples (the SYM and
89
ASY groups) were subjected to a titer estimation of Ca. Liberibacter asiaticus
90
using quantitative real-time PCR (qPCR).
91
A total of ten neighboring orange trees in the same planting row were collected:
92
five SYM and five ASY biological samples. About forty leaves and a piece of
93
secondary roots per tree were sampled. Among five ASY biological samples, one
94
plant did not show a detectable level of bacterium in the leaves by qPCR
95
analysis, but it showed a detectable level of bacterium in roots (in this study) and
96
fruits (data not shown). The same case occurred for one root. As reported by
97
Chin and coworkers (2014),13 the bacteria are not evenly distributed throughout
98
the tree, thus false negatives can occur in qPCR. Therefore, the negative
99
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
101
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 ±
108
2.3 for the ASY leaves, whereas the Ct values for roots were 31.6 ± 3.9 for the
109
SYM and 38.8 ± 0.7 for the ASY samples. Samples with Ct value ≥ 40 were
110
negative for Ca. Liberibacter asiaticus.
111 112
2.3 Sample preparation and NMR analysis
113
Each biological sample was independently analyzed, with three technical
114
replicates. For each replicate, 80 mg of leaves or roots were manually macerated
115
for 2 min. Extractions were performed with 1 mL of TMSP-D4/D2O 0.05% solution
116
in phosphate buffer (KH2PO4/Na2HPO4) at pH 5.4 and sonicated for 20 min. The
117
extracts were centrifuged, filtered and maintained at approximately 1 ºC until the
118
NMR analyses were performed. The extracts were directly inserted into 5 mm
119
NMR tubes.
120
The 1H NMR measurements were obtained using a Bruker DPX 300 (7.05 T)
121
spectrometer, which operated at 300.13 MHz for 1H. The 1H NMR spectra were
122
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
124
3.64 s, a relaxation delay of 2 s and a spectral window of 30 ppm. The spectra
125
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
128
at the default parameters to further support compound identification.
129 130
2.4 Principal Component Analysis (PCA) and statistical analysis
131 132
The 1H NMR spectra were introduced into the AMIX program (3.8 Bruker) and
133
subjected to exploratory analyses using PCA. The 0.75-8.26 ppm proton region
134
of the leaf extracts and the 0.70-8.10 ppm proton region of root extracts were
135
evaluated; the region between 4.60-5.20 ppm was excluded, which corresponds
136
to the deuterated water signal. Buckets were constructed through a simple
137
rectangular format with 0.04 ppm of width and integrated normalizing by the sum
138
of the absolute intensities. The samples were mean-centered and Pareto scaling
139
pre-processing was applied for leaves and roots.
140
Statistical analyses were performed using the integration values from the signals
141
with high loadings in PCA relative to the TMSP-D4 signal in the 1H NMR spectra.
142
The Student's t test was applied to assess the differences between the means of
143
the ASY and SYM groups. PCA and statistical analyses were performed with a
144
95% confidence level. A P-value below 0.05 was used to indicate statistical
145
significance.
146 147
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
152
signal intensities (Fig. 1). The
153
dimensional experiments and the literature16-19 supported the identification of
154
carbohydrates, amino acids, organic acids and other compounds. The identified
155
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
158 159
The changes caused by HLB in the leaves and roots of the citrus plants were
160
evaluated using PCA, which enabled the observation of the natural clustering of
161
the samples and unsupervised pattern recognition. The ASY and SYM leaves
162
were distinguished on the score plot (Fig. 2-A). The characteristic spectral region
163
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).
165
The loadings that corresponded to malate and proline betaine were important for
166
allocating the ASY samples to the more positive values of PC2. The ASY-ND
167
scores are close to those of the ASY leaves, although they were allocated to the
168
positive PC2 axis because of the greater contribution of proline, proline betaine
169
and malate, and the smaller contribution of sucrose.
170
In Fig. 3-A, the roots of the asymptomatic plants were indistinguishable from
171
those of symptomatic ones. However, there was a tendency of separation
172
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
174
responsible for allocating the ASY-ND roots to the more negative values of PC1
175
(Fig. 3-B).
176
Fig. 4 illustrates the relative proportion of highlighted metabolites in the loading
177
plots (sucrose, proline betaine, malate and proline), which are responsible for the
178
separation of the ASY and SYM samples. The SYM leaves had a higher sucrose
179
content than the ASY ones (Fig. 4-A1; P=4.77e-5), although the ASY and SYM
180
roots were not significantly different in terms of sucrose content (Fig. 4-A2;
181
P=0.086). The SYM leaves showed a significant decrease in the proline betaine
182
and malate content (Figs. 4-A3 and 4-A4; P=3.71e-9 and P=2.18e-6,
183
respectively), whereas the proline content was not significantly different between
184
the ASY and SYM leaves (Fig. 4-A5; P=0.65).
185 186
3.3 Role of sucrose, proline betaine, proline, and malate in HLB-affected citrus
187 188
Our results indicate that sucrose is an important metabolite for evaluating HLB-
189
affected leaves. Sucrose is the principal source of energy that is transported by
190
the phloem in plants, whereas starch is a stable source of energy that can be
191
stored in the plants. Several reports have indicated the accumulation of starch in
192
HLB-affected trees.8,10,20,21 However, starch accumulation is detrimental to the
193
plants because of the large volume that it occupies, which disintegrates the
194
thylakoid membrane and causes chlorosis of the leaves.9
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The starch and sucrose formations occur simultaneously, so an increase in
196
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transcriptome data from young HLB-infected leaves also show that the genes
198
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
200
asymptomatic and symptomatic leaves; however, both types of leaves were
201
sampled from infected plants with HLB symptoms.11 In our case, the
202
asymptomatic leaves were collected from asymptomatic plants; thus, we
203
observed a sucrose accumulation in the SYM leaves (Fig. 4-A1). The high
204
concentration of sucrose in the SYM leaves suggests that this metabolite cannot
205
be normally transported to other parts of the plant. For the roots, this
206
accumulation was not observed (Fig. 4-A2) because the phloem vessel was
207
blocked by the Ca. Liberibacter spp. bacteria, which alters the transport of
208
sucrose to all parts of the plant.
209
Proline betaine is commonly found in the Rutaceae species and can be formed
210
by consecutive methylations of proline.23 Proline and proline betaine are
211
traditionally considered non-toxic compatible osmolytes24 and are generally
212
associated with the osmotic adjustment and protection of subcellular structures
213
during abiotic 23,25-28 and biotic stresses.29
214
We detected a decrease in proline betaine content in the SYM leaves (Fig. 4-A3),
215
whereas no significant variation was observed for proline (Fig. 4-A5). Proline
216
betaine has not been reported in HLB-affected citrus leaves,30 but it has been
217
observed in juices of HLB-affected oranges with negligible variation.12,13 As noted
218
by Seifi et al. (2013),31 the redox-regulating potential of proline may be important
219
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
221
juices from asymptomatic and symptomatic fruits.13 These results are different
222
from the findings of Cevallos-Cevallos et al. (2011),30 who reported significantly
223
higher concentrations of this amino acid in HLB-affected leaves.
224
Despite the observed accumulation of proline in response to the abiotic and biotic
225
stresses in many plant species, the metabolic alterations in proline and proline
226
betaine content in the HLB-symptomatic leaves remain unclear and may indicate
227
a specific plant-pathogen relationship that specifically modifies this metabolic
228
pathway. Therefore, further studies on the precursors, co-factors, expression and
229
activities of the key enzymes in the metabolism and catabolism of proline and
230
proline betaine are necessary to understand and characterize the role of these
231
amino acids in the citrus response to HLB infection in different tissues and stages
232
of disease development.
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Malate is reported to be a substrate that performs various functions in the cells,32
234
which include supplying carbon skeletons for the biosynthesis of amino acids.33 It
235
is an important intermediary component in the citric acid cycle,34 and variations in
236
malate content have been associated with the plant response to stress
237
conditions.35 Malate can be formed from phosphoenolpyruvate, which is a
238
product of glycolysis. Phosphoenolpyruvate is carboxylated by the action of the
239
PEP carboxylase enzyme to produce oxaloacetate, which is reduced to malate
240
by the action of malate dehydrogenase.36 An important functionality in plants is
241
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
243
citric acid cycle and in the production of some amino acids.37
244
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
256
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-
258
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
262
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,
265
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
268
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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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