Inter-species developmental differences in metabonomic phenotypes

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Inter-species developmental differences in metabonomic phenotypes of Lycium ruthenicum and L. barbarum fruits Qi Wang, Shaohua Zeng, Xiangyu Wu, Hehua Lei, Ying Wang, and Huiru Tang J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00349 • Publication Date (Web): 07 Aug 2018 Downloaded from http://pubs.acs.org on August 11, 2018

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Journal of Proteome Research

Inter-species developmental differences in metabonomic phenotypes of Lycium ruthenicum and L. barbarum fruits Qi Wang1,2#,Shaohua Zeng3#, Xiangyu Wu2, Hehua Lei2, Ying Wang3 and Huiru Tang1,2*

1

State Key Laboratory of Genetic Engineering, Zhongshan Hospital and School of Life Sciences,

Human Phenome Institute, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Fudan University, Shanghai, 200438, China 2

CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of

Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, University of Chinese Academy of Sciences, Wuhan Hubei 430071, China 3

Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic

Improvement, Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou Guangdong 510650, China

*

To whom all correspondence should be addressed:

Huiru Tang: Tel, +86-21-51630725; fax, +86-21-51630381; Email, [email protected] #

These authors contributed equally to this work.

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ABSTRACT Fruits of Lycium ruthenicum (LR) and L. barbarum (LB) in Solanaceae family contain abundant bioactive metabolites used widely as functional food and natural medicine. To characterize the fruit developmental molecular phenotypes, we comprehensively analyzed metabolite composition of both Lycium fruits at three developmental stages using the combined NMR, LC-MS/MS and GC-FID/MS methods. The metabonomes of these fruits were dominated by over 90 metabolites including sugars, amino acids, TCA cycle intermediates, fatty acids, choline metabolites and shikimate-mediated plant secondary metabolites. Metabolic phenotypes of two species differed significantly at all three developmental stages; LB fruits contain significantly more sugars and amino acids but less TCA cycle intermediates, fatty acids and secondary metabolites than LR. Interspecies differences for fatty acid levels were much greater after color-breaking than pre-color-breaking. Furthermore, LR fruits contained more osmolytes than LB fruits indicating different osmoregulation requirements for these fruits during development. Significant differences were also present in biosynthesis of shikimate-mediated plant secondary metabolites in LR and LB. These findings provided essential metabolic information for plant physiology of these Lycium species and their utilizations demonstrating the usefulness of this metabonomic phenotyping approach for studying fundamental biochemistry of the plant development. Key words: Lycium ruthenicum Murr., Lycium barbarum L., fruit development, metabonomics, NMR, LC-MS/MS, GC-FID/MS


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Introduction Lycium barbarum L. (LB) and L. ruthenicum Murr. (LR) are two plants in Solanaceae family with well-known medicinal and nutritional functions. They are two species in the same Lycium genus but their fruits have fairly different macroscopic phenotypes in terms of shape and color. The former has red mature fruits with common names of wolfberry or goji berry whereas the latter has dark-purple or blackish mature fruits with a common name of black wolfberry.1 However, two Lycium fruits are both green until color-breaking stage at which drastic interspecies phenotypic differentiation occurs in fruit color. Therefore, color-breaking stage represents an important sampling time-point for studying the development-related changes in phenotypes for these two fruits. By using NMR, GC-FID/MS and UHPLC-MS methods in this study, we detected and identified more than 100 metabolites from these two Lycium fruits at three developmental stages pre- and post-color-breaking, By 2004, LB plantation alone reached about 82,000 hectares in China yielding nearly a million tons of wolfberries with a market value of hundred millions dollars.2 The LB fruits have been widely used in China for many years for their various positive effects on eyesight, cardiovascular disease, hypertension, diabetes, menoxenia and climacteric syndrome.3-5 L. ruthenicum is normally growing in central Asia, southern Russia, Qinghai-Tibet Plateau in northwestern China, Pakistan and Australia, whose fruits are also employed as a traditional remedy and functional food.6-8 The perceived bioactive components in these Lycium fruits include polysaccharides and the shikimate-mediated plant secondary metabolites (e.g., polyphenols) which are believed to be responsible for immunoenhancement and antioxidative activities, respectively.9, 10 Dynamic biochemical changes occur in both primary and secondary metabolisms such as the shikimate-mediated metabolites during the process of fruit development and maturation;11, 12



the contents of bioactive components are thus expected to be developmental dependent. Studies of such developmental dependence of fruit metabolisms is critically important for understanding basic plant physiology and potential applications. Therefore, a number of studies has been published for fruit development for grapes, tomatoes and peaches.11-14 Because of the medicinal and nutritional values, Lycium fruits have already been investigated in some of their carotenoids, polyphenols and polysaccharides with most of work focused on L. barbarum L. For instance, LB polysaccharide (LBP) was found to be one of most important classes of bioactive components with about 30 different LBP isolated and identified, which possessed antioxidant, visual function-improving, neuroprotective, immunomodulatory and antitumor bioactivities.15 In contrast, much less studies were reported for L. ruthenicum Murr though a polysaccharide, LRP4-A, was isolated and structurally characterized to some degree with MS and NMR.16 LB fruits contained significant amount of carotenoids whereas LR ones contained little even though activities of the carotenoid biosynthetic enzymes were similar in both species17; high transcription levels of carotenoid biosynthetic genes (PSY1, PDS, ZDS, CYC-B and CRTR-B2) in LB were accountable for the accumulation of carotenoids whereas significant CCD4 upregulation in LR reduced biosynthesis of carotenoids.17 More recently, all genes involving anthocyanin biosynthesis pathway were isolated and characterized in LR. In contrast, expression of these genes were almost undetectable in LB.1 All these studies collectively indicated that interspecies differences in macroscopic phenotypes for LB and LR fruits were associated with the differences in their metabolism. However, literature search has shown no published reports on the metabonomic phenotypes of these two Lycium fruits, their developmental dependence and interspecies differences.


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Metabonomics is a well-established powerful tool for tackling the above problems since this approach can simultaneously detect a large number of metabolites and their quantitative changes during a given biological process.18-20 In fact, a number of studies has successfully revealed the fruit metabonomic phenotypes under various conditions for tomatoes, grapes, peaches and apples.21-23 All these studies further demonstrated fruits as a metabolite-rich plant organ thus an excellent model for metabonomics studies of developmental biochemistry. For the time being, however, no such studies have been reported for both LR and LB fruits. In this work, therefore, we systematically analyzed the metabolite composition of two Lycium fruits (with close taxonomic relationship but distinctively different macroscopic phenotypes) at three different developmental stages using the combined NMR and LC-MS/MS approaches; fatty acid composition of these fruits were also quantitatively analyzed using GCFID/MS method at the same developmental stages. Our aims are (1) to define the fruit metabonomic phenotypes for two Lycium species at three different developmental stages and (2) to reveal their interspecies differences in this developmental dependences.



Materials and methods 1. Chemicals Methanol, n-hexane, potassium carbonate, K2HPO4.3H2O and NaH2PO4.2H2O (all analytical grade) were purchased from Sinopharm Chemical Reagent Co. Ltd. (Shanghai, China). D2O (99.9% D) and sodium 3-trimethylsilyl [2, 2, 3, 3-D4] propionate (TSP) were from Cambridge Isotope Laboratory (Miami, FL) whilst a mixture of 37 standard methyl esters of fatty acids were from Supelco (Bellefonte, PA). Acetonitrile (HPLC grade, ≥99.9%) and formic acid (99%) were purchased from Sigma-Aldrich (Shanghai, China) and J&K Scientific (Shanghai, China), respectively, whereas chlorogenic acid, caffeic acid, sinapic acid and vanillic acid were purchased from Aladdin (Shanghai, China). 2. Plant Materials Fruits of LB and LR were collected at three different developmental stages (S1, S2, and S3) respectively from two adjacent locations, Zhongning and Pingluo counties, both of which are in the Ningxia Hui Autonomous Region and have similar latitude, altitude and climate. The fruits at S1 stage (green and unripening) were collected 3 days prior to color breaking (representing the pre-color-breaking stage). The fruits at S2 stage were collected on the day of color-breaking (representing the color-breaking stage), at which L. ruthenicum fruits were light purple whereas L. barbarum fruits were light yellow (Figure 1). The fruits for S3 stage were collected 3 days after color-breaking (representing the post color-breaking stage). All these fruits were collected then snap-frozen in liquid nitrogen and then kept at -80 °C for further analysis. 3. Water content measurements


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Water content was measured using a standard gravimetric methods for plant tissues.24 Samples were weighed before and after each dehydration step and the dry weights were finally determined after drying in a 130°C oven until constant weight. Water content for each sample was worked out as a percentage of the fresh fruit weight. 4. Metabolite extraction for Lycium fruits Each sample of Lycium fruits was individually ground into powder in liquid nitrogen with a mortar and pestle. The powders were weighed as two portions for each sample. One portion (about 60 mg) was added with 1mL aqueous methanol (50%, v/v) followed with vortex-mixing, homogenization using a TissueLyser (Qiagen, Germany) (20 Hz, 90 s twice with a 90 s break) and then sonication (45 KHz, 200W) in an ice bath (15 sonication-break cycles, 1 min each).24 The supernatant was collected after 10 min centrifugation (16000g, 4 °C) and this procedure was repeated twice to obtain pooled supernatants. After removal of methanol under vacuum, dried extracts from lyophilization were re-dissolved in 600 μL phosphate buffer (0.1 M K2HPO4– NaH2PO4 in 100% D2O with 0.165mM TSP, pD 7.4). Following 10 min centrifugation (16000g, 4 °C), 550 μL supernatant from each sample was transferred into a 5-mm NMR tube, respectively, for NMR analysis. The other portion (about 20 mg) was homogenized in 1 mL HPLC-grade methanol with the same procedure described above using a TissueLyser. This solvent was chosen after comparing with three other different solvents, namely, aqueous methanol (80%, v/v), aqueous methanol (80%, v/v) added with 2% formic acid, and aqueous methanol (80%, v/v) added with hydrochloric acid (to pH about 2.5) in order to ensure the highest LC-MS signals for most concerned metabolites plus simplicity of extraction procedures. The last solvents is not recommended since metabolite extracts from the last solvent showed obviously lower LC-MS 7 / 38 ACS Paragon Plus Environment


signal intensities (data not shown) than those from the rest solvents (which had similar extraction performance). Homogenates were equally divided into two portions for each sample with one directly used for fatty acid composition analysis using GC-FID/MS as reported previously.25 The other portion was repeatedly extracted with 400 μL aqueous methanol (80%, v/v) thrice to obtain the pooled supernatant followed with removal of solvents in vacuo and lyophilization. The dried extracts were re-dissolved in 200 μL aqueous methanol (80%, v/v) and analyzed with UHPLCMS. 5. NMR spectroscopic analysis All NMR spectra were recorded at 298 K on a Bruker AVIII 600 spectrometer (600.13 MHz for 1H and 150.92 MHz for 13C) equipped with an inverse detection cryogenic probe (TXI, Bruker BioSpin, Germany). One dimensional 1H NMR spectra were acquired using NOESYPR1D pulse sequence with parameters as reported previously.26, 27 64 scans and 64k data-points were acquired with a 90° pulse length adjusted to about 10μs and a spectral width of 20 ppm in all 1H NMR experiments. T1 values of metabolites were measured using an inversionrecovery pulse sequence (with water-presaturation) with 24 relaxation delays of 0.02-41 seconds and were calculated from the signal integrals as a function of relaxation delays using TopSpin software (v3.2, Bruker BioSpin) as reported previously.24, 28 To obtain absolute quantities of metabolites, one dimensional 1H NMR spectra with full T1 relaxation were also acquired using NOESYGPPR1D pulse sequence with a total relaxation delay of 25.25 s, including a recycle delay of 22.5 s and acquisition time 2.75 s. Notably, both sets of spectra yielded the same statistical results as reported previously24 as long as the same parameters were employed for the control and treated groups. For NMR signal assignments (i.e., metabolite identification), a series of 2D NMR spectra were recorded for selected samples including 1H-1H COSY and TOCSY, 1H J-Resolved, 1H-13C HSQC and HMBC as previously reported.27, 28 6. Hyphenated chromatography-MS analyses


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UHPLC-MS analyses were conducted on a 1290 UHPLC system coupled with a 6530B Accurate-Mass Quadrupole Time-of-Flight mass spectrometer (Agilent Technologies, USA) with a Jet steam ESI ion source. Each sample (0.5L) was analyzed using an Agilent poroshell 120 EC-C18 column (2.1×100 mm, 2.7 μm) at 35℃ with mobile phases A (0.1% formic acid solution in water), B (0.1% formic acid solution in acetonitrile) and a flow rate of 0.6 mL/min. An optimized chromatographic method was established with elution gradients as: 2% B at 0 min, 10% B (15 min), 25% B (17 min), 40% B (20 min), 90% B (22 min) and 90% B (26 min). Mass spectra were acquired in the positive ion mode with parameters set as follows: capillary voltage, 4000 V; fragmentor, 175 V; nozzle Voltage 500 V; skimmer 65 V; octopole RF Peak 750 V; pressure of nebulizer, 50 psi; drying gas temperature, 350 ℃; sheath gas temperature, 350 ℃. Nitrogen was used as sheath and drying gas at a flow rate of 12.0 L/min and 10.0 L/min, respectively. Data were collected in centroid mode and the mass range was set at m/z 110–2000. Spectra for a pooled QC sample (from all LR and LB fruit extracts) were also acquired in the all ion MS/MS mode with collision energy of 0, 10, 20 and 40V to assist signal assignments. Masshunter workstation softwares were used for data analysis. Fatty acids in Lycium fruits were quantitatively measured using a GC-FID/MS method reported previously25 with some minor modifications. In brief, 20 L mixed standards (1mg/mL methyl heptadecanoate, 0.5 mg/mL methyl tricosanoate and 2mg/mL 3,5-di-tert-butyl-4hydroxytoluene) in n-hexane were added into a Pyrex tube followed by 500L fruit homogenate (equivalent to about 10mg fresh Lycium fruits) and 1 mL methanol-hexane mixture (4:l v/v). Methylation and GC-FID/MS detection were conducted as described previously 25, 29, 30 with results expressed as μmol per gram fresh fruits (Table 3, Figure S1). 7. Data analysis 9 / 38 ACS Paragon Plus Environment


After phase- and baseline-correction, all 1H spectra were referenced to TSP (δ 0.00). The spectral region δ0.60-9.90 of each spectrum was divided into segments of 0.002 ppm (1.2 Hz) using AMIX (v3.9.2, Bruker BioSpin) with water region at δ4.749–4.901 and methanol region at 3.339-3.381 discarded. The areas of all remaining segments were normalized to the fresh weight of Lycium fruits powder as peak area per mg fresh fruits.24, 28 Both PCA and OPLS-DA were conducted using SIMCA-P+ software (v12.0, Umetrics, Sweden) with the mean-centred data in the former whereas univariance-scaling in the latter. The quality of OPLS-DA models was evaluated with CV-ANOVA approach with p-values less than 0.05 as significant.31 The results were shown as scores plots and back-transformed loadings plots color-coded with the absolute values of Pearson correlation coefficients (|r|).32 In the loadings plots, variables (i.e. metabolites) with warm color (e.g. red) showed more significant contributions to intergroup differences than those with cold color (e.g. blue). In this study, 15 biological replicates were employed (n=15) hence the cut-off value of 0.497 for (|r|) (i.e., r > 0.497 or r < -0.497) were used to obtain metabolites exhibiting statistically significant inter-group differences (with p < 0.05). The quantitative levels for metabolites in Lycium fruits were calculated from integrals of the (clean and/or less overlapped) NMR signals of given metabolites using TSP as an internal reference28 using the completely relaxed NMR spectra directly. In the case of UHPLC-MS analysis, identification of metabolites was achieved by matching precursor and product ions together with isotope pattern with the publically accessible databases (metlin, https://metlin.scripps.edu/; HMDB, http://www.hmdb.ca/) and literatures.10, 3337

The quantitative results were shown as peak area of a given metabolite per milligram fresh

Lycium fruits as discussed previously28 and subjected to the Student’s t-test or nonparametric statistical analysis where appropriate using an in-house developed MATLAB script.38


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Identification of fatty acid were achieved by comparing with data from the mixed standards of 37 methylated fatty acids and further confirmed with their mass spectral features in the publically available databases. Fatty acids were quantified using two internal references with known concentration as previously described.29, 30 Results 1. Phenotypic features for Lycium fruits L. ruthenicum (LR) and L. barbarum (LB) fruits showed distinct phenotypic differences at all three developmental stages, namely, pre-color-breaking (S1), color-breaking (S2) and post-colorbreaking (S3) stages (Figure 1). At all three developmental stages, LR fruits were almost globose whereas LB fruits were elliptical in shapes (Figure 1). At S1, both fruits were green and stiff indicating their unripening nature. At the color-breaking stage, S2, LR fruits became light purple whereas LB ones turned light yellow. At post-color-breaking stage, S3, LR fruits turned purple whereas LB fruits became orange in color (Figure 1). Water contents in LB fruits were significantly higher than in LR ones at all three stages. On the other hand, LR fruits only showed significant increases in water contents from S2 to S3 whereas LB fruits showed significant increases in water contents during all three developmental stages (Figure 1). 2. Metabolites detected in the Lycium fruits Metabolites in Lycium fruits detected here consist of hydrophilic metabolites and fatty acids. The spectral resonances at different developmental stages (Figure 2) were assigned to specific metabolites based on the literature data24, 26, 39, 40, publicly accessible and the in-house developed databases. 71 metabolites were detected with NMR methods from various metabolic pathways with most of them unambiguously identified with a set of 2D NMR spectra (Figure 2



and Table S1) including 1H J-resolved, 1H−1H COSY, 1H−1H TOCSY, 1H−13C HSQC and HMBC. These include 19 amino acids, 17 organic acids (TCA cycle intermediates and phenolic acids), 11 carbohydrates, 1 flavonoids, 3 lipids, 3 choline metabolites, 2 nucleotides and 15 others including unknown metabolites. Fourteen fatty acids were also detected and confidently identified using GC-FID/MS methods using known standards. Using UHPLC-QTOFMS methods, furthermore, about 30 plant secondary metabolites were detected, relatively quantified and identified based on the literature data33, 34, 36, 37, 41, 42 including polyphenolic acids, anthocyanins, flavonols and phenolamides (Table S2). Amongst these, flavonols and anthocyanins were only tentatively assigned since they had the same ion in the positive mode mass spectra, including cyanidin and kaempferol (m/z, 287.2556), petunidin and (iso) rhamnetin (m/z, 303.0505), delphinidin and quercetin (m/z, 317.0661). Polyphenol glycosides were also assigned only tentatively due to lack of standards. For example, the precursor ion at m/z 933.2651 in LR was assigned only as petunidin-hexose-coumaroyl-disaccharide based on its product ions (m/z=771.2140, 479.1213, 317.0667) and absorbance at 520nm.33, 34, 43-45 Although unambiguous identification of them is ideal, such tentative assignments are actually sufficient for the purposes of this study since they all represent secondary metabolites from the shikimate pathway. Visual inspection of the NMR spectra of LB and LR fruits (Figure 2) showed clear development-dependence for both species and inter-species differences at three different development stages. For instance, during the fruit development, glucose (Glc) and fructose (Fru) levels increased clearly whilst sucrose (Suc) level declined in both fruits; LR fruits contained more citrate, chlorogenate (Chl) and betaine but less Glc, Fru and Suc than LB fruits at each given development stage.


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The quantitative results for abundant metabolites (Table 1), which was not reported previously to the best of our knowledge, gave detailed information about the aforementioned development-dependence and inter-species differences. Among all metabolites, sugars (Glc, Fru, Suc), betaine, citrate and malate (Mal) were the most abundant (about 10-170 mol per gram fresh Lycium fruits); Gln and Asn were the most abundant amino acids (about 2-17 mol/g fresh fruits); shikimate-pathway related metabolites including quinate, cinnamate and chlorogenate were in the range of 0.5-9 mol/g (Table 1). Amongst other shikimate-mediated secondary metabolites in these fruits, the agmatinebased phenolamides were most abundant followed with spermidine- and putrescine-based phenolamides (Figure S2, Table S3) judged relatively from LC-MS signal intensities. Coumaroyl-agmatine was the most abundant phenolamide in LR, followed by feruloyl-agmatine and N, N-dicaffeoyl-spermidine; N, N-caffeoyl, dihydrocaffeoyl-spermidine dihexose was the most abundant phenolamide in LB, followed by N, N-dicaffeoyl-spermidine dihexose and N, Nbisdihydrocaffeoyl-spermidine dihexose (Figure S2). However, absolute quantification of these potentially important phenolamides was not possible right now with unavailability of their standards. Fatty acids of Lycium fruits (Table 3, Figure S1) were dominated by palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1n9), linoleic acid (C18:2n6), γ-linolenic acid (C18:3n6) and α-linolenic acid (C18:3n3) accounting for over 97% of total fatty acids. 3. Developmental dependence for Lycium fruit metabonomes Principal component analysis (PCA) of NMR data for LR and LB fruits at different developmental stages was conducted to reveal potential group-clustering and possible outliers,



which were discarded in the subsequently analysis. The corresponding orthogonal partial-least squares discriminant analysis (OPLS-DA) was conducted to obtain the metabolites contributing significantly to inter-group differentiations. The results showed that all inter-species and interstage comparative models were good quality for LR and LB fruits at different development stages with Q2 values of 0.54–0.78 and p-values from CV-ANOVA results much smaller than 0.05 (Figure 3). These results clearly indicated the development dependence of the Lycium fruit metabonomes for both species and inter-species metabonomic differences at all three development stages. Loadings plots from the OPLS-DA revealed that about 50 fruit metabolites had significant level differences during their development for both Lycium species (Figure 3, Table 2). The levels of Arg, Asp, Asn, Cys, Fru, Glc, 6-phosphogluconic acid, isocitric acid and cinnamic acid were increased continuously during the development of Lycium fruits. In contrast, Val, GABA, succinate, quininic acid, folate, glycerophosphocholine (GPC), HX and uridine showed level decreases continuously during development. Inter-species differences were further observed for the development dependence of LR and LB fruits. Whilst LR fruits showed significant increases in the levels of mannose, raffinose, malate, para-aminobenzoate (PABA), choline and narigenin but decreases in Gln during the fruit mature process (from S2 to S3), LB fruits showed opposite changes. Furthermore, levels of formate, UDPG, 2VG, Tyr, Trp, Phe, Chl and gallic acid had significant changes only in LR fruits whereas Ile, citrate, betaine, NMNA and meta-hydroxybenzoic acid (MHBA) only showed level changes in LB fruits. Moreover, significant developmental dependences were observed for fatty acid composition of Lycium fruits (Table 3, Figure S1). LR fruits showed most of detected fatty acids were increased significantly from S1 to S2 and remained unchanged from S2 to S3 whereas


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tetracosanoic acid (C24:0) were not changed significantly from S1 to S3 and C18:3n3 decreased from S1 to S3. In LB fruits, the level of 8 fatty acids (C14:0, C16:0, C18:0, C20:0, C22:0, C24:0, C16:1n7, C18:2n6) remained unchanged from S1 to S2 and decreased significantly from S2 to S3 whilst C18:3n3 was decreased significantly from S1 to S3. In contrast, the content of 2 fatty acids (C8:0, C15:1) were significantly decreased from S1 to S2 with no changes from S2 to S3. Polyphenolic metabolites in these fruits had clear development dependence including phenolic acids, flavonols/anthocyanins and phenolamides (Table S3). Vanillic acid isomer and sinapic acid isomer showed level decreases in both LR and LB fruits during the fruit development whereas caffeic acid isomer had a level elevation from S1 to S2 but decline from S2 to S3. The levels of flavonols/anthocyanins were elevated from S1 to S2 in LR fruits whereas no significant changes for LB fruits. Both LR and LB fruits showed level increases for spermidine-based phenolamides from S1 to S2 and no changes till S3 stage (Figure S3). In contrast, LB fruits had significant declines in the levels of agmatine-based phenolamides during development whereas LR fruits had slight increases; Levels of putrescine-based phenolamides decreased slightly in LR but decreased significantly in LB during fruit development. 4. Interspecies metabonomic differences for Lycium ruthenicum and L. barbarum fruits OPLS-DA results of NMR data (Figure 4, Table 2) showed significant differences in metabonomic phenotypes for L. ruthenicum and L. barbarum fruits in terms of both primary and secondary metabolisms. At S1 stage, the levels of 23 metabolites (Raf, mannose, PGA, citrate, malate, succinate, choline, betaine, uridine, Ile, Val, Ala, IVG, GABA, Tyr, Trp, Phe, Chl, cinnamate, gallate, PABA and naringenin) were higher in LR than LB fruits whereas 7 metabolites (Fru, Suc, UDPG, Thr, Arg, Gln, Asn, formate) were more abundant in LB than LR. At S2 stage, 21 out of 23 metabolites showing inter-species differences in S1 (except mannose 15 / 38 ACS Paragon Plus Environment


and PGA) plus QA and NMNA were higher in LR than LB fruits whereas 10 metabolites (7 metabolites showing inter-species differences in S1 plus Glu, Arg and lipid) were higher in LB than LR fruits. At S3 stage, 19 out of 23 metabolites showing inter-species variations in S2 (with exception for Ala, succinate, uridine and QA) plus 2 steroids and MHBA were higher in LR than LB fruits whereas 11 metabolites (including all 10 metabolites showing inter-species differences in S2 except Suc together with Ala and Cys) were higher in LB than LR fruits (Table 2, Figure 4). Interspecies differences were also observed for the composition of fatty acids in two Lycium fruits (Table 3, Figure S1). At S1, LR fruits had more C20:0 and C20:1 but less C16:1n7 and C24:0 with no interspecies level differences for the rest fatty acids. At both S2 and S3 stages, LR fruits had significantly higher levels in all fatty acids than LB fruits with exception for C16:1n7 and C24:0. The levels of these two fatty acids were much lower in LR fruits than LB fruits at S2 stage but had no significant interspecies differences at S3 stage (Table 3, Figure S1). UHPLC-MS results further showed significant differences between two Lycium fruits in terms of the plant secondary metabolites at all three developmental stages (Table S3). LR fruits contained much more polyphenolic acids (caffeic acid, sinapic acid and chlorogenic acid) than LB fruits at all three development stages, confirming the NMR results described above (Table 2). Interestingly, LR fruits had much higher levels for a number of phenolamides (i.e., adducts between polyamines such as agmatine, putrescine and polyphenolic acids such as ferulic, coumaroyl and cinnamic acids) at all three development stages than LB fruits. Nevertheless, LR fruits contained more feruloyated putrescine and glycosylated spermidine-polyphenolic acid adducts than LB fruits only at S2 and S3 stages. In contrast, LR fruits contained much less


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glycosylated spermidine-polyphenolic acid adducts than LB fruits throughout the development stages (Figure S2). Petunidin-hexose-coumaroyl-disaccharide was found only in LR fruits.



Discussions A number of studies has indicated that fruit metabonomic phenotypes are developmental dependent for tomatoes, strawberries, grapes and peaches.11, 21-23 For Lycium ruthenicum and L. barbarum fruits, the most marked interspecies phenotypic differentiation occurred in terms of fruit color around color-breaking stage thus representing an important sampling stage for studying the development-related changes in phenotypes. By using NMR, GC-FID/MS and UHPLC-MS methods in this study, we detected and identified more than 100 metabolites from these two Lycium fruits at three developmental stages pre- and post-color-breaking, most of which were reported from these fruits for the first time. These included primary metabolites (e.g., amino acids, carbohydrates, fatty acids, TCA cycle intermediates, choline, and nucleotide metabolites) and shikimate-mediated secondary metabolites (flavonoids, cyanidins, polyphenolic acids and their polyamine adducts). These metabolites form the inter-pathway metabolic network and hence metabonomic phenotypes for the fruits of these two Lycium species (Figure 5). By measuring the metabolite composition at three different development stage, dynamic development-dependence and interspecies differences emerge for these species. Both Lycium fruits species showed clear developmental dependence in their metabonomic phenotypes which further showed inter-species differences involving multiple metabolic pathways (Figure 5). Such inter-species metabonomic differences were closely associated with the fruit macroscopic phenotypic differences especially color-breaking process and probably associated with their color (Figure 1a), tastes and nutritional or therapeutic properties. 1. Metabolism of sugars and TCA cycle during Lycium fruit development Glucose (Glc), fructose (Fru) and sucrose (Suc) are main sugars of fruits derived from photosynthesis and transported into the fruit cells through apoplast to be stored mainly in the 18 / 38 ACS Paragon Plus Environment

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vacuole.46 Sugar levels normally undergo remarkable changes during fruit development. For instance, sharp elevation of sugars has been observed during maturation or ripening of tomatoes, apples, grapes, kiwifruits, blueberries and peaches.13, 14, 23, 47, 48 However, significant inter-species differences are present in terms of sugar accumulations. For example, Suc was the dominant sugar in peaches whereas Glc and Fru were the major soluble sugars in most of other studied fruits.13, 14, 23, 47, 48 Here, we observed clear interspecies differences for these three major sugars between two Lycium fruits and their dynamic changes around color-breaking hence development dependence. Suc was the most abundant sugar in both Lycium fruits followed with Glc and Fru before colorbreaking. During post color-breaking period (S2 to S3 stages), both L. ruthenicum and L. barbarum fruits had significant elevation of Glc and Fru (over 3 times) with concurrent decline of Suc (about 50%) (Table 1) indicating that they had common development-associated changes of sugar metabolisms. Taking the sugar levels and their changes into consideration, the above changes indicated that the Glc and Fru elevations in both Lycium fruits were probably from other photosynthetic organs to larger extent than from Suc degradation. Although this broadly agrees with what has reported for the ripening process of tomatoes, apples, grapes, kiwifruits, blueberries and peaches 13, 14, 23, 47, 48, it is worth-noting that our observations has been made at the pre-ripening stages (i.e., prior to fruit ripening) of two different species, which has not been reported previously. Lycium fruit are photosynthetic and autotrophic organs that can both produce and consume sugars.49 Whilst these fruits act as carbon heterotrophs before the color breaking stage (S1-S2), photosynthesis in Lycium fruits become less efficient after the color breaker stage (S2). Interspecies differences were present for these Lycium fruits with the levels of Suc, Glc and Fru higher in LB fruits than LR fruits at all three development stages. Whilst Suc



level in LB fruits was about 25-30% higher than in LR at all three stages, Glc and Fru levels in LB fruits were 5-10 times higher than in LR at S2 and S3 stages indicating that LB fruits accumulated more soluble sugars in the maturing process. This is consistent with the fact that LB fruits are sweeter than LR fruits. Other sugars were also detected in the fruit of Lycium including raffinose (Raf), UDPglucose, ethyl-glucose and mannose although these sugars were much less abundant. Raf often acts as a carbon storage, osmolyte and antioxidant with an outstanding species-dependence in its levels.50 We found here that Raf level was not significantly different between LR and LB fruits before color-breaking. However, Raf level had a significant increase during color-breaking process (S1 to S3) in LR fruits whilst such changes were much in LB fruits. Consequently, Raf level was much higher in LR than in LB fruits after coloring breaking. Such development dependence and interspecies differences probably showed that LR fruits have a more pronounced osmoregulation and antioxidation requirements during the color-breaking, which will be discussed further with plant secondary metabolites. Mannose and galactose are essential components for plant cell walls, especially in hemicellulose which are not readily soluble in aqueous methanol though being able to absorb substantial amount of water to maintain cell wall flexibility.51, 52 Ethyl glucoside derived from glucose found in plant seeds such as rice 53had fairly low levels in both Lycium fruits here and its function in plant seed development remains to be clarified. TCA cycle intermediates (organic acids) contribute to plant cell energy metabolism, sour flavor and partially defense of fruits54 by deterring predators with such sourness prior to full development of seeds. Generally, glucose from photosynthesis and stored in vacuoles22 can contribute up to 50% of all these acids accumulated in green berries. Citrate and malate were the


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most abundant TCA cycle intermediates (Table 1) in both Lycium fruits whilst isocitrate, succinate and fumarate were also detectable (Figure 2, Table S1) though with much lower levels. Obvious interspecies differences were observable for the developmental dependence. LR fruits had significantly more citrate, malate and succinate than LB fruits at all three stages of development (Table 2) although such difference for malate was to much less extent at S1. Furthermore, LR fruits contained more citrate than malate at all three stages around colorbreaking and citrate level in LR fruits elevated significantly (over 30%) whereas malate level had a moderate decline from S1 to S3 (Table 1). In contrast, LB fruits contained less citrate than malate at S1 (pre-color-breaking) stage though were similar to LR after color-breaking; LB fruits only had moderate level changes for citrate but significant (over 40%) decline of malate level (Table 1). After color-breaking stage (S2 to S3), succinate level was significantly lower for both Lycium though citrate, fumarate and malate levels were not changed significantly, indicating some differences in TCA cycle at three different stages. It is also interesting to note the inverse changes of TCA intermediates against glucose indicating that some glucose contributes to TCA cycle via glycolysis, which, in theory, can be traced with the metabolic flux techniques 55 by using the 13C-labeled glucose or carbon dioxide. 2. Metabolism of amino acids during Lycium fruit development 20 amino acids and their close derivatives were detectable with NMR in both Lycium fruits during three developmental stages, which has not been reported previously. These include 17 proteogenic amino acids (Leu, Ile, Val, Ala, Thr, Glu, Gln, Pro, Asp, Asn, Lys, Arg, Cys, Phe, Tyr, Trp and His) and 3 non-proteogenic amino acids such as γ-aminobutyrate (GABA), paminobenzoic acid (PABA) and isovaleryl-glycine (IVG); ten of them were accurately quantified (Ile, Val, Thr, Ala, Gln, Asp, Asn, GABA, Trp, His) amongst which Gln, Asn, Asp, Ala and Thr



were the most abundant. Asn and Gln accounted for about 55% and 76% of all proteogenic amino acids, respectively, in both LR and LB fruits. These two amino acids were synthesized by asparagine synthase from Asp and Glu56 contributing collectively to the “umami and sour tastes”. The higher levels of sugars together with lower levels of organic acids in LB fruits probably afford much sweeter flavor of LB fruits than LR fruits. For both Lycium species, Asp, Asn and Cys showed consistent level elevation from S1 to S3 (Table 1) with some level declines observable for Ile, Val, Thr and GABA whereas after color-breaking, Arg level significantly elevated in both fruits (Table 1). LR fruits contained significantly more Thr, Gln and Asn at all three stages than LB fruits and more Arg only after color-breaking stage (Figure 5). In contrast, LR fruits contained much less other amino acids than LB ones. Although such amino acid changes has not been reported for these two species so far, it is conceivable that most of these changes are related to protein biosynthesis though Glu/Gln and Asp/Asn are also closely linked to TCA cycle the transamination of -ketoglutarate and oxaloacetate, respectively. Asp elevation has also been observed during fruit ripening in tomatoes12, 21, 57, peach11 and strawberry.58 Moreover, LR fruits contained significantly more Phe, Tyr and Trp than LB fruits, all of which were derived from the shikimate pathway as precursors of many plant secondary metabolites apart from their roles in protein biosynthesis. 3. Shikimate pathway mediated plant secondary metabolism The shikimate pathway mediated secondary metabolism varies significantly with species in higher plants but, in all cases, plays important roles in plant cell structural strengthening, defense against biotic and abiotic stressors and ultimately plant cell survival. 59, 60 In fact, shikimate pathway mediates several plant metabolic processes via chorismic acid, including biosyntheses of folate and Trp with para-aminobenzoic acid (PABA) and ortho-aminobenzoic 22 / 38 ACS Paragon Plus Environment

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acid as precursors, respectively. This pathway also facilitates biosynthesis of several classes of plant polyphenols including polyphenolic acids (such as caffeate, vanillate, sinapate, chlorogenate, gallate, cinnamate and coumourate), anthocyanidins (cyanidin, delphinidin and petunidin) and flavonols. All these polyphenols were generated from Phe via PAL-converted trans-cinnamic acid followed with hydroxylation by trans-cinnamate 4-monooxygenase to 4hydroxycinnamate (i.e., coumarate) which is then converted into coumaroyl-coenzyme A (coumaroyl-CoA) by 4-coumarate-CoA ligase. Coumaroyl-CoA acts as a central intermediate in the biosynthesis of many essential plant metabolites including lignols (precursors to lignin and lignocellulose), polyphenolic acids, anthocyanidins, flavonoids, proanthocyanidins, coumarins, stilbenes and other phenylpropanoids. Here, we detected dozens of the shikimate-mediated secondary metabolites including phenolic acids, anthocyanins, flavonoids and phenolamides in the fruits of two Lycium species using the combined NMR and LC-MS methods (Table S1, Table S2, and Figure 5). Six phenolic acids were quantified using NMR including quinate, chlorogenate, cinnamate, caffeate, vanillate and sinapate whereas anthocyanins, flavonols and phenolamides were only tentatively identified and relatively quantified due to lack of standards. Amongst them, chlorogenate, quinate and cinnamate were by far the most abundant secondary metabolites in both species with some interspecies differences at three development stages. Significantly higher levels of chlorogenate, quinate, cinamate, gallate and PABA in LR fruits than in LB at all three developmental stages indicates much more active shikimate-mediated secondary metabolism in the former. Caffeate, sinapate, vanillate and Chl were decreased significantly during the development of LB whereas the first two phenolic acids were decreased significantly from S2 to S3 in LR (Figure 5). PABA and chlorogenic acid are precursors in biosynthesis of folate and flavonols/anthocyanins,



respectively, whereas caffeate is a precursor in biosynthesis of phenolamides. The level declines for these phenolic acids indicated promoted biosynthesis of folate, flavonols/anthocyanins and phenolamides as antioxidants and self-defense. This further suggests that LR fruits probably have potentially greater medicinal value since all these phenolic acid mediated polyphenols are potent antioxidants and free radical scavengers.27, 28, 61-64 Phenolamides are amide-adducts formed with phenolic acids (e.g., caffeic acid, coumaric acid and dihydrocaffeic acid) and polyamines (e.g., agmatine, putrescine and spermidine). These adducts are ubiquitously found in plants with their structural and quantity varying with species and tissues in terms of chain length of amines and the types of phenolic acid substitution.36 It is known that phenolamides play many important roles in defense against abiotic and biotic stressors and linkage between carbon and nitrogen metabolism.65 Phenolamides also participate in signaling pathway by interacting with biomacromolecules such as DNA, RNA and proteins electrostatically so as to (1) modulate plant development via transglutaminase-mediated crosslinking, (2)regulate homeostasis of ions (e.g., Ca2+, Na+ and K+) by interacting with ion channels or receptors and (3) regulate cell-wall strengthening and lignification. Spermidine is required for post-translational modification of the eukaryotic translational initiation factor eIF5A to form deoxyhypusine.66 Furthermore, spermidine and ethylene shared a same precursor, S-adenosylmethionine67 in plant metabolism. In both Lycium fruits studied here, the main spermidine-based phenolamides containing N, N-dicaffeoyl and /or dihydrocaffeoyled dihexose were present at all three development stages. Most phenolamides (derivatives of agmatine, putrescine and spermidine) displayed an increase in their contents during the development of LR and LB fruits being consistent with the phenolamide accumulation reported in other cases at the early stage of


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development.36 The significance of the accumulations of these phenolamides in fruit development and plant physiology clearly warrants further detailed investigations. 4. Fatty acid and choline metabolism Fatty acids are important carbon and energy storage and essential components of phospholipids for cell membranes essentially required during plant growth when cell number and/or cell volumes increase rapidly. For this purpose, choline is also concurrently required since it is an important precursor for biosynthesis of phosphatidylcholine which is a major class of phospholipids for plant cell membrane.68 In plants, most of fatty acids are from de novo biosynthesis via acetyl-CoA generated from glycolysis. C18:2n6 is the most abundant fatty acid followed by C18:1n9 in both Lycium fruits at all three development stages (Table 3, Figure S1), both of which are synthesized from C16:0 and C18:0 by a number of desaturases including 12, 15 and 6 desaturases.69 Accumulation of C18:2n6 and C18:1n9 during the Lycium fruit development indicates promoted expression of these desaturases in these two fruits (with only small amount of their downstream metabolites such as ALA and GLA detected). The levels of fatty acids in LR fruits were higher at all three stages than LB ones probably due to much higher water content of LB fruits since LR fruits were generally smaller than LB fruits and the fatty acid levels were calculated from fresh fruit weights. It is interesting to note that the level of unsaturated fatty acids (UFA) was much higher (about 9 times) than saturated fatty acids (SFA) at all three development stages for both Lycium fruits though the significance remains unknown. With both Lycium fruits here showing obvious size growth from S1 to S3, the fruit growth associated steady decreases for fatty acids and choline in both species probably resulted from the increased phosphatidylcholines biosynthesis required for cell membrane biosynthesis. Choline is also an important precursor for biosynthesis of betaine, which is a small and highly soluble



zwitterionic metabolite, acting as an efficient osmolyte70 for cell development and stressprotectant against both biotic and abiotic stressors.71-73 The level homeostasis of betaine in both cases probably indicated that both fruits were not under any obvious stress. This further supported the notion that the level declines for choline from S1 to S3 were due to the enhanced biosynthesis of phosphatidylcholines. Although it is interesting to know the details in such biosynthesis of phospholipids (and whole lipidome) during fruit development using lipidomics techniques, such is beyond the scope of this study and will be covered in the future. To sum up, we discussed about metabolite composition of fruits from L. ruthenicum and L. barbarum at three development stages, namely, pre-color-breaking, color-breaking and post color breaking stages. Significant differences were present in the fruit metabonomics phenotypes of between these two Lycium species and such differences were dynamically dependent on fruit development. These differences were apparently involving metabolism of sugars and amino acids, TCA cycle, biosynthesis of fatty acids and cell membrane together with the shikimate pathway mediated plant secondary metabolism (Figure 5). In terms of shikimate-mediated secondary metabolites, both fruits contained large quantity of quinic acid and chlorogenic acids together with various phenolamides, the amide-adducts of phenolic acids (caffeic, ferulic and coumaric acids) and polyamines (spermidine, agmatine and putrescine). These secondary metabolites are expected to have important developmental functions worth-exploring in the future. Quantitative data for fatty acids and large number of other metabolites were obtained from these two fruits (at three development stages) providing useful information for future studies of wolfberries from these two species in the field of fruit biology or physiology in general and functional food or therapeutics. It would also be interesting to further explore the


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developmental dependence of these two fruits in their transcriptomes, proteomes, lipidome and multi-ome integrations. SUPPORTING INFORMATION: The following supporting information is available free of charge at ACS website http://pubs.acs.org Figure S1 Fatty acid contents in fresh Lycium fruit detected by GC-FID/MS. Figure S2 Percentage of each phenolamide in total phenolamides in fruit of LR (left) and LB (right). Figure S3 Peak areas of phenolamides and flavonols/anthocyanins (per milligram fruit）in two Lycium species at differential developmental stages. Table S1 Metabolites detected and identified from two Lycium fruits using NMR spectroscopy. Table S2 Identified metabolites in fresh Lycium fruits with UHPLC-MS/MS. Table S3. Quantitative results for plant secondary metabolites in fresh Lycium fruits measured with HPLC-MS/MS (means ±SD, n=10). Acknowledgements We acknowledge financial supports from the National Natural Science Foundation of China (31470391 and 31770334), Youth Innovation Promotion Association, CAS (2015286) and the Scientific Project of Ningxia Agriculture Comprehensive Development (znnfkj2015). The authors have no conflicts of interest. References (1)Zeng, S.; Wu, M.; Zou, C.; Liu, X.; Shen, X.; Hayward, A.; Liu, C.; Wang, Y. Comparative analysis of anthocyanin biosynthesis during fruit development in two Lycium species. Physiol. Plant. 2014, 150 (4), 505-516.



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Table 1. Quantitative data for metabolites in fresh Lycium fruits calculated from the completely relaxed 1H NMR spectra. Metabolites

δ1H

T1 (s)

Sugar Glucoseb 5.24 3.129 Fructosec 4.12 2.943 Ethyl-glucose 1.24 1.156 Sucrose 5.41 1.114 Raffinose 5.43 1.02 TCA intermediates Citrate 2.54 0.285 Malate 4.29 2.486 Amino acids Isoleucine 1.01 0.916 Valine 0.99 0.968 Threonine 1.33 0.842 Alanine 1.48 1.295 Glutamine 2.44 1.069 Aspartic acid 2.8 1.048 Asparagine 2.85 1.313 γ-aminobutyrate 2.3 NDd Tryptophan 7.5 3.572 Histidine 7.91 1.76 Choline metabolites Choline 3.21 2.253 Betaine 3.27 2.018 Nucleotide and others Uridine 5.90/5.92 NDd Hypoxanthine 8.2 3.764 N-MNA 9.13 NDd Formate 8.46 12.649 Secondary metabolites Quinate 1.86 0.682 trans-Cinnamate 6.46 1.647 U10d 6.54 1.247 Chlorogenate 5.31 1.639

a

LRS1 9.63±4.19 9.66±2.89 0.17±0.08 29.66±4.6 0.46±0.48

LRS2

Mean±SDa (μmol/g) LRS3 LBS1

11.46±6.39 36.56±18.00# 9.96±3.59 13.93±4.98# 0.19±0.1 0.23±0.19 29.96±5.61 18.67±8.04# 1±0.54* 1.97±0.83#

LBS2

LBS3

13.95±15.04 60.91±24.79*f 165.95±39.01#g 13.81±9.4 50.37±20.36*f 148.8±36.94#g 0.08±0.03e 0.04±0.01*f 0.03±0.02g e f 37.36±5.38 36.3±9.37 24.18±7.46# 0.57±0.39 0.87±0.48 0.78±0.35g

27.1±4.41 35.58±5.34* 37.71±4.57 19.72±4.09e 21.77±6.74f 24.03±4.42 26.4±5.21 22.63±3.95# 22.3±3.59 17.2±4*f 0.12±0.03e 0.18±0.05e 1.33±0.33e 1.24±0.52 8.39±2.93e 3.12±1.17e 14.73±4.96e 0.32±0.09 0.48±0.13 0.44±0.25

19.62±5.31g 13.02±3.41#g

0.44±0.23 0.52±0.15 0.95±0.22 1.61±0.5 2.71±1.78 1.97±0.61 4.02±4 0.31±0.14 0.58±0.19 0.4±0.22

0.33±0.1 0.33±0.08* 0.77±0.3 0.97±0.37* 2.83±1.73 2.65±1.69 6.57±4.04* 0.22±0.08* 0.57±0.22 0.63±0.38

0.27±0.13 0.19±0.07# 0.54±0.2# 0.51±0.11# 1.78±1.2# 3.18±1.98 6.38±4.49 0.13±0.05# 0.51±0.25 0.64±0.28

0.07±0.02*f 0.09±0.03*f 1.22±0.36f 0.69±0.27*f 8.8±4.41f 4.22±1.31*f 17.3±6.31f 0.2±0.05* 0.49±0.21 0.64±0.3*

0.08±0.02#g 0.1±0.03#g 1.28±0.32g 1.95±0.89#g 9.69±3.93g 5.48±1.05#g 16.33±4.56g 0.12±0.02# 0.43±0.22 0.72±0.26

4.74±0.64 45.46±11.5

5.47±0.9* 47.9±12.88

4.76±1.13 3.76±0.49e 2.91±0.37*f 39.99±9.67 21.92±4.12e 22.7±4.09f

2.23±0.33#g 18.71±3.98#g

0.41±0.13 0.21±0.03 0.43±0.15 0.15±0.07

0.32±0.1* 0.2±0.02 0.45±0.18 0.14±0.06

0.18±0.04# 0.17±0.02# 0.41±0.18 0.1±0.02#

0.3±0.13e 0.21±0.03 0.27±0.04e 0.15±0.02e

0.18±0.06*f 0.18±0.03*f 0.23±0.05*f 0.15±0.03f

0.16±0.08g 0.16±0.03 0.17±0.04#g 0.14±0.03g

2.49±1.5 0.83±0.44 0.37±0.33 7.45±1.79

2.12±1.45 0.9±0.37 0.37±0.26 9.02±3.26

1.22±1.08 0.86±0.67 0.23±0.14# 6.96±2.58

1.39±0.47e 0.53±0.47e 0.31±0.3 1.12±0.87e

1.13±0.2f 0.66±0.36 1.51±0.81*f 0.98±0.8f

1.02±0.18 0.74±0.28 2.09±0.56#g 0.62±0.44g

mean±SD (μmol/g fresh fruits) from 15 independent samples; bcalculated with-glucose assuming that -glucose accounts for 36% in its equilibrium solution; c calculated by -fructofuranose assuming that fructofuranose accounts for 25% in its equilibrium solution39; d not determined with its signals too small; * p

Inter-species developmental differences in metabonomic phenotypes

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