The Impact of Diaphorina citri-Vectored ‘Candidatus Liberibacter asiaticus’ on Citrus Metabolism

Huanglongbing (HLB), also known as “citrus greening disease,” is a citrus disease associated with the phloem-limited bacterium ‘Candidatus Liberibacter asiaticus’ (CLas) that has devastated crop yield, fruit quality, and productivity among citrus groves globally (Wang 2019). The most frequent route of transmission occurs via the Asian citrus psyllid (ACP; Diaphorina citri Kuwayama; Hemiptera: Liviidae), but the bacterium may also be transmitted by grafting with infected plant material (Bové 2006; Liu and Tsai 2000). Although commercial citrus production in California presently remains largely unaffected by HLB, the spread of ACP and the confirmation of infected trees in residential neighborhoods has created great concern among growers (Garcia Figuera et al. 2021; Warnert 2012). HLB transmission is expedited by the short time period (<15 days) in which young flush become infectious after ACP feeding and, thus, entire groves can become infected within a year, largely asymptomatically (Lee et al. 2015). Indeed, since 2012 there has been an exponential increase in the number of trees positively identified with HLB in California (CDFA 2021), and this number is expected to rise rapidly without intervention.

Visual inspections are ineffective for disease management because of the lengthy incubation period of CLas, which causes some trees to remain asymptomatic for years (Gottwald 2010). Inevitably, these trees serve as a source of inoculum for ACP and exacerbate the spread of the disease (Coletta-Filho et al. 2014). This limitation has made the development of an early detection technology (EDT), a test capable of identifying diseased trees during the early stages of infection, a top priority among stakeholders seeking to protect the citrus industry (Keremane et al. 2015). Quantitative PCR (qPCR) is the regulatory standard for diagnosing HLB, in which a cycles-to-threshold (Ct) value <37 indicates whether a tree is infected with CLas (Lin et al. 2006). Methods relying on qPCR are considered the regulatory standard; however, this technique is associated with a high false-negative rate resulting from the uneven distribution of CLas in planta, which results in variable bacterial titers depending on from what parts of the tree tissue samples are collected (Coy et al. 2014; Morgan et al. 2012). Further, titers of CLas are also observed to vary seasonally in regions with hot climates (Lopes et al. 2016).

Several advances have been made in the development of EDTs for HLB, including improvements in the sensitivity of detecting pathogen genetic material in asymptomatic samples (Wheatley et al. 2021), DNA-based detection in the root system (Braswell et al. 2020) through the targeting of ACP feeding sites (Pandey and Wang 2019), and canine olfactory detection (Gottwald et al. 2020). Another EDT approach involves the use of metabolomics, which is a powerful tool that can provide a detailed snapshot of metabolism through the measurement of low-molecular-weight metabolites. Although the visual symptoms of HLB can take as long as 3 years to appear in mature field trees (Bové 2006; Folimonova and Achor 2010; Johnson et al. 2014), fruit drop is observed in the first few months after infection, which suggests host metabolism is altered in the early stages of HLB (Bassanezi et al. 2011). Previous metabolomics research demonstrated that CLas-tolerant varieties of citrus accumulate higher concentrations of amino acids involved in plant defense (Killiny and Hijaz 2016), and that CLas-induced metabolic signatures vary by host genotype (Hung and Wang 2018a). Metabolomics has also been used to identify potential biomarkers for early detection of HLB, including citrate and malate (Liu et al. 2020), and differences in metabolite profiles are shown to emerge earlier than detection by PCR (Hung and Wang 2018b). These studies demonstrate the utility of this technology for detecting and monitoring CLas infection in citrus, and support its use as an EDT. However, differences in disease pathogenesis according to vector transmission have not been explored.

Previously, our lab demonstrated that ¹H nuclear magnetic resonance (NMR)-based metabolomics distinguishes healthy and HLB-affected greenhouse citrus trees that were inoculated with CLas through grafting using the leaf metabolome (Chin et al. 2020; Ramsey et al. 2020) and root metabolome (Padhi et al. 2019). These studies found lower sugar concentrations in infected plants and that select metabolites, such as proline and trigonelline, were elevated with infection. The purpose of our investigation was to evaluate the reproducibility of this technique in greenhouse-grown citrus trees inoculated with CLas via ACP. Our primary hypothesis was that metabolic changes induced by CLas infection via ACP result in shifts in the leaf and root metabolome that are similar to infection induced by graft-inoculation.

MATERIALS AND METHODS

Plant materials.

Leaves were sampled from citrus trees (n = 16) generated by grafting scions of ‘Lisbon’ lemon (Citrus limon) 6-month-old ‘Carrizo’ rootstock (Citrus sinensis (L.) × Poncirus trifoliata) grown from certified seed. All scion plant material was obtained as certified-pathogen-tested from the University of California (UC) Citrus Clonal Protection Program. Trees grew an additional 6 months before experimental procedures. Trees were grown and maintained in an insect-free greenhouse in 2-gallon pots containing a 2:1 mixture of UC mix No. 2 and peat moss at the UC Davis Contained Research Facility (Davis, CA). The greenhouse was maintained at 27°C (± 1.5°C) with supplemental lighting (high-pressure sodium lights) and a photoperiod of 16 h-light, 8-h darkness. Humidity ranged from 30 to 50%. Plants were watered as needed and fertilized each time with complete fertilizer (5-12-26) containing magnesium (31 ppm), sulfate (SO₄ 125 ppm), iron (3 ppm), manganese (0.50 ppm), zinc (0.15 ppm), copper (0.15 ppm), boron (0.50 ppm), molybdenum (0.10 ppm), and calcium (116 ppm).

Experimental design.

Trees were randomly selected to be exposed to ACP that were infected with the ‘Hacienda Heights’ strain of CLas (exposed: n = 10) or CLas-free ACP (control: n = 6). Exposure to ACP was done using a caged-infestation procedure, as described in Hall and Moulton (2018). Given the inability of ACP to transmit CLas by feeding on mature leaves (Pandey et al. 2021), cages were placed on branches with flush or with young, tender leaves consistent with early flush shoot vegetative states (Cifuentes-Arenas et al. 2018). All trees were grown in the same soil and were maintained under the same conditions. The ACP colonies used for inoculation were raised on plants that were confirmed positive for CLas by qPCR. The proportion of experimental ACP that was confirmed to be infected with CLas and used for inoculation was calculated and is reported in Table 1. Experimental plants received ACP that fed on leaves sourced from ‘Lisbon’ lemon trees, and healthy (CLas-free) ACP were reared on ‘Lisbon’ lemon plants that were confirmed by qPCR to be free of CLas.

TABLE 1. Experimental quantitative PCR cycles-to-threshold (Ct) values^a of ‘Candidatus Liberibacter asiaticus’ (CLas) in ‘Lisbon’ lemon plants exposed to CLas+ Asian citrus psyllid (ACP)

	Weeks (postexposure)
Rep	0		8	12	16	20	52	Status		Infected ACP (%)b	Ct valuec
1	ND		ND	39.38	37.64	35.38	26.48	CLas+		80	24.3 ± 3.1
3	ND		ND	29.44	26.64	27.68	25.77	CLas+		12	28.4 ± 5.9
4	ND		39.26	25.68	32.74	38.01	30.76	CLas+		37	27.4 ± 2.3
6	ND		ND	36.91	ND	39.39	28.60	CLas+		20	23.7 ± 2.9
9	ND		ND	29.56	24.42	25.61	30.89	CLas+		84	25.8 ± 3.3
10	ND		37.41	34.02	24.64	25.48	30.35	CLas+		15	24.8 ± 2.5
2	ND		ND	ND	ND	ND	ND	CLas(−)		30	26.2 ± 3.7
5	ND		ND	ND	ND	ND	39.89	CLas(−)		20	25.5 ± 2.9
7	ND		ND	ND	ND	ND	ND	CLas(−)		25	29.4 ± 1.4
8	ND		ND	ND	ND	ND	ND	CLas(−)		55	26.5 ± 1.9

^aA plant was considered CLas+ if leaf material Ct values were <37 at any time point during the study. Values reported as “ND” indicate no gene product for CLas was detected; all other values are an average of two PCR runs. Control plants (i.e., exposed to ACP that were not infected with CLas) are not shown.

^bValues represent percent ACP with Ct values <32 at time of exposure (after being caged on infected source material).

^cValues are the average ± standard deviation of ACP with CLas Ct values <32, determined in duplicate.

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Two weeks before exposure, baseline plant samples were collected and all plants were pruned to encourage the growth of young tissue preferred by the psyllids for feeding. During exposure, ACP (n = ∼25 per plant) were placed in a sleeve cage (30.48 cm diameter × 71.12 cm length) that was secured onto each plant using a sponge and twist tie. ACP were allowed to feed on the plant for 14 days (December 2016), then anesthetized by CO_2, aspirated, and transferred to vials. The vials were placed on ice until collection was complete, and then were placed in a −80°C freezer until analysis. Plants were then treated with a combination of foliar and soil granular insecticides to remove any additional ACP life stages and were allowed to recover for 8 weeks in a greenhouse. Leaf sampling commenced 8 weeks postexposure (wpe) and was performed every 4 weeks until 52 wpe (February to December 2017). At 24 wpe, a miticide was applied to all plants because of a mite infestation. Data collected from this time point until the final (52 wpe) were excluded because of the potential confounding influence of the miticide on plant metabolism. Therefore, leaf samples were collected and analyzed for the following time points: baseline (2 weeks before ACP exposure), and 8, 12, 16, 20, and 52 wpe. Leaves that were collected for metabolomics (n = 4 per plant) were selected if they were free of any visual symptoms of HLB. Leaves were placed in sealable plastic bags and kept on dry ice until sampling was complete. Visual symptoms of HLB in the canopy were monitored throughout the study. Additionally, root samples were collected approximately 54 wpe by snipping feeder roots from each quadrant of the bulk root mass of each individual tree using stainless-steel surgical scissors, washed with de-ionized water to remove attached soil, blotted dry with paper towels, and pooled into a single sample. The scissors were sterilized (70% ethanol) between sample collections. All leaf and root samples were stored at −80°C until further processing.

Determination of plant infection status by qPCR.

The presence or absence of CLas in experimental plants was tested by performing qPCR on leaves randomly sampled monthly from the canopy; approximately four leaves were collected per tree, of which 200 mg (fresh weight) of midrib tissue was excised and used for qPCR as per the U.S. Department of Agriculture’s Animal and Plant Health Inspection Service, Plant Health and Quarantine (USDA-APHIS-PPQ 2012) protocol using the MagAttract Plant DNA Extraction Kit (Qiagen, Valencia, CA). A tree with a CLas Ct < 37 at least once during the study was considered to be infected with CLas (Floyd and Krass 2008).

Determination of exposed ACPs that were infected with CLas.

The percentage of exposed ACPs that were infected with CLas was determined by qPCR, where Ct < 32 was considered qPCR+ for CLas (Floyd and Krass 2008). A maximum of 20 individual ACPs per plant were extracted using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) as per its protocol for purification of total DNA from insects (Floyd and Krass 2008). Recovered DNA was used for qPCR following the U.S. Department of Agriculture protocols for detection of CLas DNA that targets the 16S ribosomal gene, and the wingless gene in D. citri using the Li primers (Li et al. 2006; USDA APHIS PPQ 2012). qPCR was performed in a CFX96 Touch Deep Well Real-Time PCR Detection System (Bio-Rad, Hercules, CA).

Leaf metabolite extraction.

Metabolites were extracted from leaf samples using procedures as described in Chin et al. (2020). Briefly, frozen leaves were hole-punched using a single hole chrome punch and lyophilized in a FreeZone Plus 4.5-liter Cascade Benchtop Freeze Dry System (Labconco, Kansas City, MO) for approximately 48 h. Approximately 65 mg of lyophilized leaf punches were ground in 2-ml screw-top microcentrifuge tubes containing one 3.5-mm diameter glass bead (BioSpec Products Inc., Bartlesville, OK) using a Mini-Beadbeater-16 cell disrupter (BioSpec Products Inc.). The plant material in each tube was then incubated with a 10-mM potassium phosphate buffer containing 10% 0.5 M EDTA (pH 6.8 ± 0.1, 1:20 wt/vol) in an Eppendorf Thermomixer (15 min, 90°C, 1,000 rpm) and centrifuged (15 min, 4°C, 14,000 relative centrifugal force [RCF]) using a Model 5415R microcentrifuge (Eppendorf North America, Hauppauge, NY). The supernatant was transferred to a second tube and centrifuged again (10 min, 4°C, 14,000 RCF), and 585 µl of supernatant was combined with 65 µl of internal standard containing 5 mM 3-(trimethylsilyl)-1-propanesulfonic acid-d6 (DSS-d₆), NaN₃, and D₂O (Chenomx Inc., Edmonton, Alberta, Canada). The final concentrations were 0.5 mM DSS-d₆, 0.02% NaN₃, and approximately 10% D₂O. A volume of 600 µl was transferred to 5-mm NMR tubes and stored at 4°C until NMR data were acquired (within 24 h of sample preparation).

Root metabolite extraction.

Frozen roots (∼1 g) were lyophilized in Falcon 15-ml conical centrifuge tubes (Thermo Fisher Scientific, Waltham, MA) for 48 h using a FreeZone Plus 4.5-liter Freeze Dry system (Labconco). Dried samples were stored at room temperature, protected from light, until use. Metabolite extraction in roots followed procedures, as described in Padhi et al. (2019). Briefly, approximately 75 mg of lyophilized root material was transferred to a 2-ml screw-cap microcentrifuge tube containing one 3.5-mm-diameter glass bead (BioSpec Products Inc.) and was ground for 2 min using a Mini-Beadbeater-16 cell disrupter; BioSpec Products Inc.). After grinding, samples were incubated with 10 mM of potassium phosphate buffer containing 10 mM of EDTA (pH 6.8 ± 0.1, 1:20 wt/vol) in a thermomixer (15 min, 90°C, 1,000 rpm; Eppendorf North America) and centrifuged (15 min, 4°C, 14,000 RCF) with a Model 5415R Micro Centrifuge (Eppendorf North America). The supernatant (1,000 µl) was combined with 100 mg of Chelex 100 resin in sodium form (Bio-Rad), and the mixture was allowed to stand for 15 min (4°C). Samples were centrifuged (15 min, 4°C, 14,000 RCF), and 400 µl of supernatant was transferred to a prewashed Amicon Ultra-0.5 ml Centrifugal Filter Unit with an Ultracel-3 membrane (EMD Millipore, Billerica, MA), and centrifuged again (30 min, 4°C, 14,000 RCF). After this, 207 µl of filtrate was combined with 23 µl of internal standard containing 5 mM of 3-(trimethylsilyl)-1-propanesulfonic acid-d6 (DSS-d₆), NaN₃, and D₂O (Chenomx Inc.). The final concentrations were 0.5 mM of DSS-d₆, 0.02% NaN₃, and approximately 10% D₂O. The pH of each sample was adjusted to 6.8 ± 0.1 using small amounts of 1 N HCl or NaOH and 180 µl was transferred to 3-mm NMR tubes and stored at 4°C until NMR data were acquired (within 24 h of sample preparation).

NMR data acquisition and metabolite quantification.

NMR spectra were acquired at 298 K using the “noesypr1d” pulse sequence on a Bruker Avance 600 MHz NMR Spectrometer equipped with a SampleJet (Bruker, Billerica, MA). The acquisition parameters were: 12-ppm sweep width, 2.5-s acquisition time, 2.5-s relaxation delay, and 100-ms mixing time. Water saturation was applied during the relaxation delay and mixing time. The resulting spectra were zero-filled to 128,000 data points and an exponential apodization function corresponding to a line-broadening of 0.5 Hz was applied before Fourier transformation using the program NMR Suite Processor v.8.2 (Chenomx Inc.). Metabolites were identified by comparing spectral features to a library of compounds using the program NMR Suite Profiler v.8.2 (Chenomx Inc.). Quantification was achieved through referencing to the added DSS-d₆ internal standard as described in Weljie et al. (2006).

Statistical analysis.

Metabolite concentrations were corrected for dilution and converted to nmol/g of dry weight. Leaf and root metabolite concentrations were evaluated for normality using histograms and the Shapiro-Wilk test. Differences in the concentration of metabolites from CLas+ exposed plants and control were compared at each time point using the Mann-Whitney U test and within-group differences over time were evaluated by the Friedman test. Results were considered significant if P < 0.05. Nonmetric multidimensional scaling (nMDS) was used to compare the leaf and root metabolome of control and CLas+ exposed plants. Shifts in the leaf and root metabolome were compared using permutational multivariate analysis of variance of cluster centers (termed “centroids”) on the Euclidean distance matrix created via nMDS using the ‘vegan’ package in the software R (https://www.r-project.org). Effect sizes were calculated in Microsoft Excel with Cliff’s delta (d) using the following calculation: (ABS[2*U]/n_an_b − 1), where U represents the calculated Mann-Whitney U statistic and n_an_b represents the product of the control and treatment group samples sizes (Goedhart 2016). Effect sizes were interpreted as follows: d < 0.147 “negligible”; d < 0.33 “small”; d < 0.474 “medium”; and d > 0.474 “large” (Romano et al. 2006). Absolute median log₂-fold-change values in metabolites between CLas+ exposed and control plant were calculated, with negative fold changes representing a reduction in metabolite concentration with exposure to CLas. Graphs were produced and statistical procedures were carried out in the software R v.4.0.2 (R Core Team 2012).

RESULTS

Infection status of experimental plants postexposure.

Postexposure, 6/10 ‘Lisbon’ lemon trees were confirmed by qPCR to be infected with CLas. The earliest time point at which CLas was detected in exposed plants was at 12 wpe (Table 1). In the ACP colonies used to inoculate experimental trees, on average, 38 ± 26% of ACP were confirmed to be infected with CLas (Table 1). All control plants tested by qPCR were negative for CLas throughout the experiment. Of the six plants that were exposed and became infected (CLas+ exposed), 41 ± 33% of the ACP caged on plants were infected with CLas compared with 32 ± 15% of ACP that were caged on plants that did not develop HLB (CLas− exposed). Visual symptoms of infection began to appear at approximately 8 to 10 wpe and included scorched tips, yellowing, prominent veins, leaf drop, curling and mottling of leaves, and chlorosis (Fig. 1).

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Time-course analysis of the leaf metabolome of ‘Lisbon’ lemon trees during infection.

A summary of metabolite concentrations is found in Supplementary Table S1A. At baseline, no differences between lemon plants assigned as controls (exposed to CLas− ACP) or CLas (exposed to CLas+ ACP) were observed, except for quinic acid, which was higher in exposed plants, and the amino acid threonine, which was higher in the plants assigned to control. Treatment was applied (exposure to either CLas+ or CLas−ACP for 2 weeks) and changes in metabolite concentration were tracked over a 52-week observation period. The time points 24 through 48 wpe were removed because of the application of miticide at 24 wpe, which is metabolically disruptive and therefore difficult to interpret in the context of this study (Fig. 2).

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Generally, metabolite concentrations in both control and CLas+ exposed lemons tended to follow a similar pattern consistent with a rapid growth phase during early development. However, within-group changes over time, as assessed by Friedman rank sum testing, revealed treatment-specific fluctuations in metabolites, and between-group differences. As assessed by Mann-Whitney U testing conducted at each time point, it was revealed how infection status influenced the leaf metabolic profile. For sugars, fructose concentrations significantly increased from baseline at early and midstudy (8, 16, and 20 wpe) in control plants, but only at 16 wpe in CLas+ plants, suggesting infection may have depressed fructose accumulation. Difference testing between groups showed that fructose, sucrose, and galactose concentrations were lower in CLas+ plants midstudy, while glucose was elevated.

For amino acids, the concentration of alanine, isoleucine, leucine, phenylalanine, and valine did not change over time in the control group, but were significantly lower in CLas+ plants at study cessation compared with midstudy (16 and 20 wpe), except for leucine, which was elevated in CLas+ plants. Other notable differences included a drop in asparagine concentrations at 20 wpe relative to baseline in controls only, and a significant and dramatic rise in arginine at 52 wpe compared with baseline, 8, and 12 wpe. Proline concentrations declined significantly in the control group at 20 wpe relative to 16 wpe, but remained elevated in CLas+ plants, and tyrosine was significantly lower at 52 wpe compared with 8, 12, and 16 wpe in CLas+ but not control plants. Between-group differences were observed in several amino acids midstudy, including elevations in arginine, isoleucine, leucine, asparagine, lysine, proline, threonine, and valine. At study cessation, the concentrations of isoleucine, phenylalanine, threonine, tyrosine, and valine were lower, whereas the concentration of arginine was dramatically higher, in CLas + plants.

For metabolites involved in defense, CLas+ plants exhibited lower concentrations of GABA, proline betaine, serine, and synephrine at study cessation relative to midstudy, while quinic acid concentrations were higher. Trigonelline concentrations dropped dramatically in controls at study cessation compared with early and midstudy time points, but remained consistently elevated in the infected group. Between-group differences in GABA concentrations were observed at midstudy (elevated in CLas+ lemons), and at study cessation (lower in CLas+ lemons), while trigonelline was higher in CLas+ plants at 12 and 52 wpe. Quinic acid concentrations were elevated in control compared with infected plants midstudy. Synephrine concentrations were not different between groups, except at 52 wpe (lower in CLas+ plants). No differences in serine concentrations were observed throughout the observation period.

For metabolites involved in energy metabolism, acetone concentrations increased from baseline to midstudy in control, but not CLas+, plants. Choline increased in controls midstudy relative to baseline (not observed in infected plants). Citrate concentrations sharply declined in CLas+ plants at study cessation relative to early and midstudy time points. Formate was lower in both groups at 52 wpe relative to 8 wpe, and was consistently higher in control compared with infected plants. Malate concentrations increased from baseline at 16 wpe and then declined at 52 wpe in control plants, whereas concentrations increased from baseline in infected plants at 8 and 12 wpe, but did not increase further. Methanol increased from baseline in both groups, but concentrations at 52 wpe were lower than 12 and 16 wpe. Myo-Inositol increased from baseline in both groups at 16 and 20 wpe, and was lower in control at 52 wpe relative to 16 wpe. Uridine concentrations remained consistent over time in controls, but was significantly lower in CLas+ plants at study cessation compared with midstudy. Several between-group differences were observed, including higher concentrations of acetone, formate, malate, and choline at mid- and end-study time points in controls. Additionally, myo-inositol was elevated in controls relative to CLas+ plants at 8 and 16 wpe, and uridine and citrate was elevated in controls at the final time point.

Plots created by nMDS visualized the leaf metabolome of infected and control plants over time, and permutational multivariate analysis of variance of centroids identified key time points at which the leaf metabolome differentiated infection status (Fig. 2). The leaf metabolomes of control and CLas+ plants were indistinguishable at baseline (before exposure), but separate clusters emerged, beginning at 8 wpe. Interestingly, this significant clustering disappeared at 12 wpe, reappeared dramatically at 16 wpe, and remained significant throughout the remainder of the observation period. Log₂-fold-changes in the concentration of metabolites in CLas+ leaves relative to control complement these findings by demonstrating the progression of metabolite changes over time, with few large fold-changes in metabolites before exposure and at 12 wpe, and larger differences at the mid- and end-study time points (Fig. 3). The greatest separation between controls and CLas+ leaves (denoted by the R² value) was observed at 16 and 20 wpe compared with study cessation, when visual symptoms of HLB were most apparent.

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Root metabolome at study cessation.

Principal component analysis and nMDS were used to visualize the root metabolome at study cessation (Supplementary Fig. S1) and the results are summarized in Supplementary Table S1B. Clear separation by infection status is visible, with the metabolites trigonelline and proline betaine, and to a lesser extent asparagine, glucose, proline, and synephrine driving separation between the groups. In total, the concentration of 17 metabolites in CLas+ roots were significantly different from control. Other significantly different metabolites included all other sugars (fructose, galactose, and sucrose), the amino acids aspartate, isoleucine, proline, threonine, tyrosine, and valine, and the metabolites myo-inositol, and succinate. The concentrations of these metabolites were significantly reduced with infection, with the exception of trigonelline, which increased. At study cessation, the leaf metabolome also presented with 17 significantly different metabolites, but with fewer differences in sugars observed, including a notable increase in the concentrations of glucose and the amino acid arginine, and more differences in metabolites involved in energy metabolism and defense (formate, citrate, malate, GABA, and choline) that were not observed in the root system (Table 2).

TABLE 2. Comparison of the ‘Lisbon’ lemon leaf and root metabolome^a at study cessation

Metabolite	Leaves (52 wpe)					Roots (54 wpe)
	Control	CLas+	P value	↑ ↓	Effect sizeb	Control	CLas+	P value	↑ ↓	Effect size
	(n = 6)	(n = 6)				(n = 6)	(n = 6)
Fructose	6,405 (1,145)	7,863 (4,025)	0.2298		Large	5,527 (2,824)	2,579 (1,181)	0.0306	↓	Large
Galactose	2,148 (743)	1,729 (191)	0.1087		Large	354 (34)	204 (57)	0.0082	↓	Large
Glucose	7,146 (3,364)	41,437 (25,086)	0.0051	↑	Large	3,531 (1483)	1,552 (451)	0.0051	↓	Large
Sucrose	36,927 (8,492)	57,362 (29,503)	0.1735		Large	63,069 (18,025)	30,210 (11,777)	0.0082	↓	Large
Alanine	1,030 (260)	903 (180)	0.3785		Medium	1,885 (677)	1,170 (491)	0.0131	↓	Large
Arginine	1,709 (332)	10,249 (9,217)	0.0050	↑	Large	1,105 (145)	808 (292)	0.1282		Negligible
Asparagine	3,989 (2,240)	3,397 (4,815)	1.0000		Negligible	40,758 (34,029)	7,919 (4,430)	0.0453	↓	Large
Aspartate	2,115 (228)	2,201 (690)	0.9362		Negligible	3,182 (879)	1,518 (129)	0.0082	↓	Large
Isoleucine	257 (74)	149 (47)	0.0131	↓	Large	100 (19)	63 (27)	0.0131	↓	Large
Leucine	504 (45)	476 (163)	0.5752		Small	129 (30)	108 (29)	0.1735		Large
Lysine	3,018 (625)	2,029 (617)	0.1282		Large	540 (151)	449 (135)	0.4712		Small
Phenylalanine	861 (585)	538 (177)	0.0306	↓	Large	514 (100)	506 (121)	0.4712		Small
Proline	52,910 (5,957)	45,217 (14,543)	0.3785		Medium	52,553 (18330)	14,620 (4,189)	0.0051	↓	Large
Threonine	1,452 (506)	919 (298)	0.0131	↓	Large	576 (261)	357 (98)	0.0131	↓	Large
Tyrosine	1,689 (593)	931 (242)	0.0051	↓	Large	316 (169)	190 (65)	0.0306	↓	Large
Valine	534 (125)	317 (113)	0.0131	↓	Large	297 (91)	172 (30)	0.0051	↓	Large
Formate	1,878 (435)	1,176 (416)	0.0051	↓	Large	4,352 (758)	3,943 (466)	0.4712		Small
Citrate	25,375 (10,039)	5,709 (7,295)	0.0131	↓	Large	14,109 (7,840)	21,033 (8,950)	0.1282		Large
Malate	50,467 (9,834)	30,356 (9,537)	0.0306	↓	Large	34,240 (6,114)	23,454 (12,558)	0.3785		Medium
Myo-inositol	6,979 (1,852)	5,621 (1,769)	0.3785		Medium	1,732 (1019)	749 (335)	0.0051	↓	Large
GABA	10,344 (3,959)	5,368 (1,439)	0.0202	↓	Large	5,704 (3,296)	3,944 (1,522)	0.0927		Large
Serine	8,923 (2,495)	8,341 (3,741)	1.0000		Negligible	1,571 (964)	654 (213)	0.0051	↓	Large
Proline betaine	25,873 (4,210)	19,675 (4,846)	0.0303	↓	Large	7,608 (6645)	16,021 (6,095)	0.0656		Large
Quinic acid	29,287 (14,356)	40,460 (54,118)	0.0656		Large	1,392 (475)	1,052 (133)	0.1282		Large
Choline	4,487 (1,317)	3,066 (789)	0.0131	↓	Large	2,636 (719)	2,526 (748)	0.5752		Small
Succinate	ND	ND	NA	NA	NA	669 (181)	415 (82)	0.0131	↓	Large
Uridine	438 (258)	204 (69)	0.0050	↓	Large	190 (41)	150 (53)	0.1282		Large
Synephrine	13 (3)	5 (4)	0.0073	↓	Large	91 (8)	46 (28)	0.0131	↓	Large
Trigonelline	426 (231)	1,239 (806)	0.0131	↑	Large	870 (396)	2,247 (674)	0.0051	↑	Large
Acetone	309 (70)	173 (35)	0.0051	↓	Large	245 (152)	134 (40)	0.1735		Large
Methanol	45,929 (6,743)	38,259 (13,126)	0.2980		Medium	5,193 (709)	6,015 (1002)	0.1282		Large

^aMetabolites were extracted from leaves and feeder roots of ‘Candidatus Liberibacter asiaticus’ (CLas)+ and control ‘Lisbon’ lemon grafted onto ‘Carrizo’ rootstock at 54 wpe. Values are median (interquartile range). Results that are significantly different are highlighted in bold; arrows show direction of change for significant results (down arrow, concentrations decreased with CLas infection; up arrow, concentrations increased with infection). wpe, weeks postexposure; ND, not determined; NA, not available.

^bEffect sizes reported as Cliff’s delta (d) and are interpreted as follows: Negligible, d < 0.11; Small, 0.11 < d < 0.28; Medium, 0.28 < d < 0.43; Large, d > 0.43.

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DISCUSSION

The aim of this study was to examine the metabolic effects of ACP-vectored CLas in greenhouse-grown ‘Lisbon’ lemon trees and to compare these results to previously published findings on graft-inoculated infection (Ramsey et al. 2020). This study confirms that ¹H NMR-based metabolomics distinguishes healthy plants from those infected with CLas , the putative disease-causing agent of HLB, when the plants are insect-inoculated compared with graft-inoculated.

The caged-infestation procedure used to inoculate experimental plants resulted in 6/10 lemon trees becoming infected. Discrimination by infection status was evident early during disease development (by 8 wpe). The early effects of infection were marked by lower concentrations of glucose, proline betaine, formate, pyruvate, and myo-inositol, alongside higher valine and citrate concentrations in CLas+ lemons compared with control. These results overlap somewhat to those observed in graft-inoculated ‘Lisbon’ lemon plants (Ramsey et al. 2020); however, several differences may be noted. Although clustering was evident at the earliest time point (2 weeks after grafts were applied) in our previous study (Ramsey et al. 2020), in this study, measurement at 2 wpe was not possible from the early application of insecticides, which posed a metabolic challenge that would confound measures made by metabolomics. However, both graft- and ACP-inoculated infections resulted in an early response, which disappeared at 12 wpe and then reemerged with strong clustering observed at 22 and 16 wpe, respectively. This suggests both modes of pathogen vectoring induce a similar response in the plant. Similar to grafting, plants that were infected with CLas via ACP exhibited increased glucose concentrations at the end of experimental measurement; however, while GABA concentrations increased in CLas+ plants infected by graft at the end of the experimental observation period, 46 wpe (Ramsey et al. 2020), we observed lower concentrations of this metabolite at 52 wpe. It is also possible that some of the differences in plant response were caused by the activation of immune pathways initiated by insect herbivory compared with mechanical damage induced by grafting. Low-, medium-, and high-density ACP populations are observed to influence the concentration of several amino acids in leaves after 7 days of feeding (Chin et al. 2017). However, it is unknown if these effects are sustained long-term. Furthermore, while this study observed higher asparagine concentrations at 20 wpe, Ramsey et al. (2020) found lower asparagine in infected plants at 22 weeks postgrafting. Other amino acids such as proline, isoleucine, and leucine, which are important organic osmolytes, were elevated in CLas+ plants 12 to 20 wpe. Elevated proline concentrations were also observed in graft-inoculated C. limon (Ramsey et al. 2020) and C. sinensis greenhouse trees (Chin et al. 2020), with similar postexposure timelines. Further, several amino acids including arginine, asparagine, and proline were observed as important for discriminating CLas+ citrus from control at 22 and 46 weeks postgrafting (Chin et al. 2021).

This study also examined the effect of CLas infection on the root system of ‘Lisbon’ lemons grafted onto ‘Carrizo’ rootstock. These findings are similar to those reported in graft-inoculated greenhouse-grown ‘Lisbon’ lemon plants, which were also grown on ‘Carrizo’ rootstock, and also reported lower concentrations of all sugars measured, several amino acids (alanine, aspartate, proline, threonine, and valine), and synephrine (Padhi et al. 2019). This study found significantly higher trigonelline concentrations in root samples from infected plants, but a similar observation was not made in the root system of graft-inoculated plants (Padhi et al. 2019). These findings suggest that metabolic changes occurring during advanced stages of HLB do not differ in the root system of the plant irrespective of method of inoculation.

Although ‘Carrizo’ usage has declined after the release of new rootstock developed for improved performance against HLB (Bowman and Faulkner 2016), it remains popular in the cultivation of commercial citrus, and has previously been identified as resistant to the disease (Tirado-Corbalá et al. 2018). Few studies have explored HLB pathogenesis in the root system in ‘Lisbon’ lemon/‘Carrizo’ rootstock, adding to the novelty of this study. However, Folimonova et al. (2009) observed that ‘Eureka’ lemon was highly tolerant to HLB when grafted onto either ‘Volkamer’ lemon or ‘Carrizo’ citrange rootstock relative to other citrus genotypes.

An earlier NMR study of leaves from symptomatic and asymptomatic Valencia sweet orange trees grown in a commercial orchard found reduced proline betaine and malate concentrations and higher sucrose concentrations in symptomatic trees (Freitas et al. 2015). Malate concentrations were also reduced in this study, alongside increases in citrate at multiple time points. Interestingly, citrate was identified as the preferred carbon source to sustain growth for Liberibacter crescens, a bacterium that is metabolically similar to CLas (Cruz-Munoz et al. 2018). This suggests that CLas is able to manipulate host metabolism to increase citrate production. A similar observation is made in ACP, in which the expression of enzymes involved in citrate production are upregulated among insects carrying CLas (Killiny et al. 2018), and Coates et al. (2020) demonstrated that CLas exposure induces changes in genes involved with energy metabolism in both male and female ACP. Cruz-Munoz et al. (2018) note that upregulated citrate concentrations may occur in response to a secondary phosphorous deficiency, and foliar phosphate fertilization appears to improve the symptom severity and yield of CLas-affected citrus. Interestingly, the effect of CLas on nutrient reabsorption in citrus is species-dependent where, for example, infection improves phosphorous reabsorption in C. limon but hinders it in Citrus reticulata (Cao et al. 2015). Phosphorus concentrations in soil and in planta were not measured in this study; however, it is theoretically possible that CLas may have exploited this phosphorous-mining mechanism by inducing a deficiency to upregulate citrate production, and thus secure a rich supply of citrate to feed on. Future studies on the impact of CLas on citrus plant metabolism could clarify this by including measures of phosphorus and citrate concentrations in their analyses.

A major limitation of this work was the age of the trees studied, which were 1 year old at the outset of the experimental period. This corresponds to the early phase of tree life and a rapid period of growth that may have created experimental noise. In addition, the visual symptoms of HLB appear much sooner in greenhouse-grown plants compared with mature field-grown trees, with the latter sometimes taking several years before symptoms manifest (Lee et al. 2015). However, a strength of this study is its longitudinal design, which evaluated the plant response to HLB over time. The pattern of changes observed, including a large early response followed by a muted response and strong resurgence, may provide clues as to how to manage HLB at the early stages of infection; this is the most important time to intervene. The application of insecticides after the 2-week exposure period in which ACP fed on the experimental plants precluded any investigation on possible metabolic effects that may have been induced by insect herbivory. Another limitation of this study was that root samples were collected at only one time point. We chose to perform root collection at study cessation because sampling throughout the study period was anticipated to create metabolic stress that would confound our analyses. To avoid stress-induced experimental noise, future studies seeking to examine longitudinal changes in the root metabolome could be performed in mature trees. Braswell et al. (2020) demonstrated that root-based HLB detection in young (4- to 5-year-old) sweet orange and grapefruit trees was a highly reliable tool for early detection, identifying 99% of infected trees compared with 42% with leaf sampling.

This study supports the use of NMR-based metabolomics in identifying CLas+ in ‘Lisbon’ lemon citrus using leaf tissue, and, similar to infections caused by grafting, can discriminate healthy plants from plants inoculated by ACP during the early stages of infection. The novel findings of this study describe, longitudinally, the metabolic effects of CLas during the early phases of infection. CLas appears to exploit host metabolism by feeding on metabolites involved in the citric acid cycle and induces the expression of several amino acids involved in defense early during infection. We also demonstrate that the root metabolome of ‘Lisbon’ lemons grafted onto ‘Carrizo’ rootstock is the same whether CLas is vectored by ACP or by grafting. Future studies that examine the longitudinal impact of CLas infection in mature field-grown trees and the short- and long-term impact of insect herbivory on citrus metabolism will clarify the role of NMR as an EDT for Huanglongbing.