Metabolomics is as an innovative technique for discriminating plant species. The objective of this study was to investigate the secondary metabolites of three different Aloe species, A. vera, A. arborescens, and A. saponaria profiled by 1H-NMR analysis. Principal component analysis (PCA) derived from the 1H-NMR spectra indicated a clear discrimination among the Aloe species, providing high predictability and good fitness of the PCA model (R2 = 0.928 and Q2 = 865). As observed in the PLS-DA score plot, discrimination was observed in the Aloe species with respect to primary metabolites including sugar and organic acid and secondary metabolites such as phenylpropanoids and carotenoids. A. vera was characterized by high levels of malate. On the other hand, as compared to the other Aloe species, A. arborescens was characterized by higher levels of Aloe nin and sugar metabolites such as sucrose and glucose. Furthermore, the secondary metabolites were quantitatively analyzed by HPLC, and the amounts of carotenoids including zeaxanthin, α- and β-carotene, and phenylpropanoids in A. arborescens were found to be significantly higher than those in the other Aloe species. In conclusion, we demonstrated that 1H-NMR-based metabolomics with chemometric analysis can be used for the facile discrimination of Aloe species.
Keywords: Aloe vera; Aloe Arborescens; Aloe Saponaria; 1H-NMR; Phenylpropanoid; Carotenoid
Aloe is a very common Liliaceae family, native to Africa,
containing approximately 400 species of tropical plants. Throughout
history, it has long been used for medical purposes. Meanwhile,
from the 400 species of Aloe, only a few have been traditionally used
as herbal medicine. In this regard, A. vera is the commonly used
form of Aloe for medical purposes. Aloe contains several classes
of secondary metabolites such as phenolic compounds, saponins,
sterols, and several anthraquinones. Aloin and emodin are the
most important anthraquinones, and they exhibit anti-bacterial,
anticancer, anti-viral, and analgesic activities [1-3]. Metabolomics
has been demonstrated to be an appropriate tool for the
composition analysis of plants and foods . Thus far, some studies
have reported the use of gas chromatography mass spectrometry
(GC–MS) and High Performance Liquid Chromatography (HPLC) for
the analysis of Aloe species [5,6]. On the other hand, the metabolite
profiles of Aloe species based on 1H-nuclear magnetic resonance
(NMR) spectroscopy have not been reported. Metabolomic analysis
techniques are preferable for obtaining metabolite profiles as they
are rapid and reproducible; moreover, the preparation procedures
of samples are simple [7,8]. A technique based on NMR can satisfy
those requirements, considering that NMR has been broadly
employed as a fingerprinting tool for the quality control analysis of
natural and synthetic products.
The use of 1H-NMR spectroscopy for metabolite profiling and fingerprint analyses has been reported for the characterization and analysis of comparative amounts of specific herbal extracts. Recently, several metabolic profiling techniques have been reported in general, and new methods have also been reported for metabonomic [9-11] and metabolomic studies [12,13]. Metabolite fingerprinting using 1H-NMR has been extensively used for various plant-derived products such as green tea [14,15], ginseng [16,17] wine [18-20], olive oil , Angelica gigas  , and others [23-25].Carotenoids, mainly found in photosynthetic organism including plant, bacteria, and fungi, are d a diverse group of organic compounds derived from the 2-C-methyl-D-erythritol 4-phosphate pathway (Figure 1). The group contains more than approximately 600 naturally occurring pigments responsible for yellow, orange, and red colors  being part of various physiological processes in plants. Meanwhile, in human, several carotenoids are considered essential nutrients, and the others exhibit protective effects against some diseases. For instance, α- and β-carotene are precursors of vitamin A, which are essential for the prevention of xerophthalmia, and blindness, and premature death [27,28]. In addition, the consumption of other carotenoids has been reported to significantly decrease the risk of lung and prostate cancer [29,30], photosensitivity disease, cataract, and cardiovascular diseases [31,32]. Meanwhile, phenylpropanoids are organic compounds that are synthesized from phenylalanine in plants (Figure 1).
It is also widely distributed in nature and is one of the highest secondary metabolites in the plant kingdom. The biosynthesis of various secondary metabolites such as antioxidants, light protectants, coumarins, hydroxyl-cinnamic amides, salicylic acid, lignins, flavonoids and pigments has been reported to follow the phenylpropanoid pathway [33,34]. However, while previous metabolic studies for Aloe species have mainly focused on biosynthesis of anthraquinones, which is represent one class of secondary metabolites in Aloe , the biosynthesis of carotenoid and phenylpropanoid remains neglected.In this study, 1H-NMR-based metabolite profiles of Aloe species such as A. vera, A. arborescens, and A. saponaria were investigated. Their secondary metabolites such as carotenoids and phenylpropanoids were also separated and quantified by HPLC. The present study is to give insight into metabolite profiling using 1H-NMR as a reliable approach for obtaining complementary description on primary and secondary metabolites among three different species of Aloe.
Materials and Methods
For chemical analysis, three species of one-year-old Aloe was supported by Jeju Aloe farm of Kim Jeong Moon Aloe (Jeju, Korea). First, the leaves of the three species of Aloe were harvested, respectively. Next, fresh samples were dipped into liquid nitrogen and stored at −80 °C in DF8510 deep-freezer (Ilshin Lab Co., Ltd., Daejeon, Korea) until further use. Finally, all the samples were freeze-dried at −80 °C for 72 h, and lyophilized samples were ground into a fine powder.
Sample Preparation for NMR Analyses
The sample preparation and NMR analysis were performed using a method reported in a previous study (Jung et al., 2013). First, Aloe powders were weighed into 100 mg. Second, 500 μL of methanol (d4) (99.8%), 400 μL of a 0.2 M phosphate buffer solution (0.2 M Na2HPO4, 0.2 M NaH2PO4 in deuterium oxide (D2O), pH 7.0), and 100 μL of 5 mM 2,2-dimethyl-2-silapentane-5-sulfonic acid (DSS, 97%) as extraction solvents were transferred to the sample powders. Third, DSS was used for the internal standard with a chemical shift (δ) of 0.0 ppm, and D2O was employed for the internal lock signal. Next, the extracts were adjusted to pH 7.0 using 1 mM HCl and NaOH solutions after sonication for 20 min and were centrifuged at room temperature at 13,000 rpm for 10 min. Finally, 600 μL of the extract was transferred to 5 mm NMR tubes (Norell, Landisville, NJ, USA) for NMR analysis.
1H-NMR spectra were recorded on a VNMRS 600 MHz NMR spectrometer (Agilent Technology, Santa Clara, CA, USA) using a triple-resonance 5 mm HCN salt-tolerant cold probe (Agilent Technology). A NOESY PRESAT pulse sequence, suppressing signals of the residual water, was used to obtain the spectra. 64 K data points were acquired from 32 scans using following parameters: spectral width, 8445.9 Hz; a relaxation delay, 2.0 s; and an acquisition time, 4.0 s; and a mixing time, 100 ms. All the spectra were Fouriertransformed with a line-broadening value of 0.5 Hz line, followed by phase-adjusting and baseline correction using Chenomx NMR suite 6.0 software (Chenomx Inc., Edmonton, Canada). The signal assignments of samples were facilitated with Chenomx NMR suite 6.0, a 600 MHz (pH 6.0−8.0) NMR database and comparison with literature values [35,36].
1H-NMR Data Analysis
1H-NMR data analysis was performed using a method reported in a previous study . Each NMR spectrum was bucketed by integrating regions containing an equal bin size of 0.01 ppm over a δ range of 0.8–7.70. All shifts associated with the solvent (i.e., between 3.25–3.33 and 4.73–4.92 ppm) and DSS were removed. The normalization of spectra was achieved with the standard (DSS) peak area, and the spectra was converted to the ASCII format. ASCII files were imported into MATLAB (R2006a; Mathworks, Inc., Natick, MA, USA), and all spectra were aligned using the correlation optimized warping (COW) method. For multivariate data analysis, SIMCA-P+ version 12.0 (Umetrics, Umea, Sweden) was used, and then the files were Pareto-scaled to minimize the effect of baseline noise and deviations. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were carried out to investigate the intrinsic variation in the data set and acquired an overview of variation among the groups. Variables with variable importance in projection (VIP) values > 1 in the PLS-DA model were sorted and heat map was generated from VIP values > 1 using MultiExperiment Viewer Ver. 4.9.0 (Mev, http://www.tm4.org/ mev/). The metabolites of Aloe extracts with VIP values > 1 were quantitated with the Chenomx NMR suite 6.0 software, comparing the integral of the DSS signal with the equivalent from a library of compounds including peak multiplicities and chemical shifts for all the compound resonances.
Extraction and HPLC Analysis of Carotenoids
The extraction and analysis method used for carotenoid analysis was similar to the previous studies [38, 39]. Briefly, 300 mg of powders from samples of the three species was transferred to 3 mL of 0.1% ascorbic acid/ethanol (w/v) and then vortexed for 30 s. The mixture was incubated in a water bath set at 85 °C for 5 min. Next, 120 μL of 80% potassium hydroxide (w/v) was loaded to saponify any potentially interfering oils and incubated set at 85 °C for 10 min. Subsequently, each sample was placed on ice to stop the reaction for 5 min, and then 50 μL of β-Apo-8’-carotenal (25 ppm), as an internal standard was added, Next, the sample was extracted with 1.5 mL cold distilled water and 1.5 mL of hexane (SAMCHUN Chemical, Pyeongtaek, Korea), and then centrifuged at 1,200 rpm at 4 °C to obtain supernatants. The above-mentioned procedure was performed twice more. Then, the collected extract was dried under nitrogen gas and re-suspended in 300 μL of dichloromethane/ methanol (50:50 v/v). An Agilent Technologies 1100 series (Palo Alto, CA, USA), HPLC system combined with a C30 YMC column (250 × 4.6 mm, 3 m; Waters Corporation, Milford, MA) and with a photodiode array (PDA) detector was used to separate carotenoid contents. HPLC condition was set as follows: detection wavelength, 450 nm; flow rate, 1.0 mL/min; injection volume, 20 μL. The gradient program was established: Solvent (A), methanol/water (92:8 v/v) with 10 mM ammonium acetate; Solvent (B); 0 min, 83% A; 23 min, 70% A; 29 min, 59%; 35 min, 30% A; 40 min, 30% A; 44 min, 83% A; and 55 min, 83% A. Each compound was identified and quantitated primarily compared with UV-visible spectrum data and retention times with that of standards.
Extraction and HPLC Analysis of Phenylpropanoid
Phenylpropanoid analysis was performed using a method reported in a previous study . External standards, hydrochloric acid, acetic acid and methanol were purchased from Extrasynthese (Genay, France), SAMCHUN Chemical (Pyeongtaek, Korea), Sigma- Aldrich Co., Ltd. (St. Louis, MO, USA) and J.T Baker® Chemicals (Phillipsburg, NJ, USA), respectively. Firstly, 6 mL of 62.5% aqueous methanol (v/v) composed of 2 g/L tert-butylhydroquinone was injected to a total of 100 mg of sample of the three species. After the addition of 1.5 mL 6 N hydrochloric acid, each sample was incubated at 90 °C for 2 h for hydrolysis and centrifuged at 3,000 rpm for 10 min. The supernatant was diluted 2 x was filtered through a 0.22 μm PTFE syringe filters into brown vials prior to HPLC-UV anaylsis. Each phenylpropanoid was identified and quantitated on a C18 column (250 × 4.6 mm, 5 μm; RStech; Daejeon, Korea) in a HPLC system (NS-4000, Futecs Daejeon, Korea) combined with an UV−Vis detector. HPLC condition was set as follows: detection wavelength, 280 nm; oven temperature, 40 °C; flow rate, 1.0 mL/min; injection volume, 20 μL. The gradient program was established: Solvent (A), Acetic acid/methanol/water (2.5:5.0:92.5 v/v/v); Solvent (B), Acetic acid/methanol/water (2.5:95:2.5 v/v/v); 0-48 min, 0-80% B; and 0% 48-58 min (total 58 min). Each compound was quantified according to peak areas and calculated as the equivalents of representative standard compounds.
GraphPad PRISM (ver. 5.0; GraphPad Software, Inc.) for Kruskal- Wallis test was used to test the significant differences in levels of metabolite among the three species of Aloe. Mann-Whitney tests were performed to reveal pairwise differences with the critical p value set at 0.05.
1H-NMR and Chemometric Data Analysis
Figure 2 indicated 1-dimensional 1H-NMR spectra of the aqueous extracts from A. arborescens, A. saponaria, and A. vera. Predominance of several metabolites such as fructose, glucose, isocitrate, malate, and sucrosewas observed. In particular, predominant signals of sugar compounds and organic acids were observed. A visual comparison revealed that signals of Aloe nin were observed along with predominant signals of sugars such as glucose and sucrose in the spectrum of A. arborescens.
First, PCA score plot was employed to determine if the metabolic fingerprint of Aloe samples was unique enough to discern the difference among the three species and identify the biomarkers for each species. Each point in the score plot describes an individual sample, and the samples indicating that similar variances are clustered together. The PCA score plot exhibited a clear separation among the three species (R2 = 0.928 and Q2 = 0.865). The model parameters for the explained variation, R2, and predictive capability, Q2, were significantly high (R2, Q2 > 0.5), indicating excellent model fitting. To identify the underlying variables contributing to the differentiation, we sorted VIP values from the PLS-DA model (Figure 3A, R2X= 0.882, R2X= 0.986, and Q2 = 0.973). In particular, A. arborescens was separated from two other species along the principal component 1, indicating that A. arborescens has the most different character, such as signals of Aloe nin, in its aqueous extract.
Variables with VIP values > 1 were represented using heat map (Figure 3B). Heat map showed different patterns among three Aloe species and each variable with VIP values > 1 were identified as malate, isocitrate, sucrose, glucose, Aloe nin, and fructose.
Quantitative Analysis of Metabolites
Concentrations of identified malate, isocitrate, sucrose, glucose, and fructose were determined using the 600 MHz library from Chenomx NMR Suite 6.0 and exhibited significant differences among three Aloe species (Figure 4). On the other hands, Aloe nin couldn’t be quantified because Aloe nin weren’t included in Chenomx library. A. vera was characterized by the highest levels of organic acid metabolites such as malate which are related to raw materials for cosmetics, health foods, and medicine, whereas A. arborescens was characterized by the lowest levels of organic acid metabolites such as isocitrate and malate. However, it was characterized by the highest levels of sugar metabolites such as sucrose and glucose. The isocitrate, malate, glucose and sucrose levels significantly differed between A. arborescens and A. saponaria. In addition, A. arborescens and A. vera showed differences in malate, glucose, and sucrose levels. A. saponaria and A. vera exhibited differing levels of isocitrate, malate, fructose, glucose, and sucrose.
Carotenoids from A. vera, A. arboresens, and A. saponaria were analyzed. As shown in Table 1, different patterns were observed depending on the amount of carotenoid in the three species. A total of five carotenoids (α-carotene, lutein, zeaxanthin, antheraxanthin, and β-carotene) were detected. Among the detected carotenoids in all species, the amount of lutein was the highest, while that of antheraxanthin was the lowest. Although, all Aloe species contained almost similar amounts of carotenoid compounds, the amount of zeaxanthin in A. arborescens was 2 times higher as compared with that in the other two species. Furthermore, this species contained more α-carotene (3.55 ± 0.10 μg/g) and β-carotene (55.57 ± 1.36 μg/g) compounds than in the other species: The amount of β-carotene was 1.6 times higher in A. arborescens than that in the others. The amounts of the different carotenoids in the three species were observed in the order of lutein > β-carotene > α-carotene > zeaxanthin > antheraxanthin.
*Each values represent mean ± SD.
Table 2 lists the differences in the amounts of the accumulated phenylpropanoid observed in the three Aloe species. After HPLC analysis, seven phenylpropanoids (p-coumaric acid, chlorogenic acid, benzoic acid, caffeic acid, quercetin, ferulic acid, and kaempferol) were detected. A. saponaria contained the highest amount of the total phenylpropanoid compounds (461.55 ± 16.13 μg/g), while as compared to A. saponaria, A. arborescens contained more phenylpropanoids (A. arborescens - 6, A. saponaria - 5, A. vera - 4). All Aloe species contained p-coumaric acid, ferulic acid, and benzoic acid. A. vera contained marginal amounts of the total phenylpropanoid compounds (180.83 ± 5.18 μg/g) compared to the other species. The highest amount of benzoic acid was observed in A. saponaria (372.79 ± 9.91 μg/g). Meanwhile, A. vera contained higher amounts of benzoic acid (83.78 ± 2.88 μg/g) as compared to other phenylpropanoid compounds. The amount of chlorogenic acid was higher in A. vera (72.05 ± 1.00 μg/g) as compared with that in A. arborescens (42.01 ± 0.34 μg/g), while no chlorogenic acid was detected in A. saponaria. The highest amount of caffeic acid (129.25 ± 20.78 μg/g) was observed in A. arborescens, with marginal amounts observed in A. saponaria (36.95 ± 0.48 μg/g); caffeic acid was not observed in A. vera. Quercetin and kaempferol were detected only in A. arborescens and A. saponaria, respectively.
*Each values represent mean ± SD.
Aloe is one of the most useful and widely used plants for various
purposes. Typically, A. vera is the most used commercial form of
Aloe in pharmaceuticals because it has been studied extensively, and
several researchers have reported that it exhibits more chemical
properties than the others. However, now, the other forms, A.
arborescens and A. saponaria, are also attracting attention caused
by their different chemical characteristics and medicinal uses. In
particular, A. saponaria and A. arborescens not only have similar,
but also a higher content of, metabolites as compared with A. vera.
HPLC was conducted to analyze secondary metabolite in the three
Unfortunately, studies with respect to carotenoids in Aloe are very limited . have reported that the accumulation of rhodoxanthin (red keto-carotenoid) in A. arborescens was induced under strong sunlight and its combination with drought environment. As shown in Figure 4, five carotenoids were present in the Aloe species, with lutein being present in the highest amount, which is a well-known carotenoid used as maintenance of eye health and eye-related diseases. Several studies have also described that the reduction in the risk for eye diseases was attributed to an increase in macular pigmentation [44,43]. Meanwhile, α, β-Carotene, being the most common precursors for vitamin A carotenoid, was abundant in A. arborescens (Table 2).
Phenylalanine is a precursor of phenylpropanoid, which is an extensively used compound. Based on the observed results, phenylalanine was not detected in A. arborescens. In this study, only seven compounds were analyzed. However, it may contain many other phenylpropanoids besides these seven compounds. Nicolson  has reported that phenylalanine is not detected from the nectar of A. arborescens, which is supported by the results of this study. All Aloe species have similar secondary metabolites, albeit differing in various amounts and patterns. In our results, the three species of Aloe had different phenylpropanoids. In particular, quercetin and kaempferol were specifically observed in A. arborescens and A. saponaria, respectively. A. greatheadii var. davyana extracts  A. ferox  contained pyrimidine, ketone, aldehyde, alkane, dicarboxylic acid, organic acid, alcohol, fatty acid, phenolic acid, indole, phytosterol, alkaloid, and phytosterol by GC–MS analysis. Because of its phytochemical composition, it shows promise in alleviating symptoms related to the prevention of cancer, diabetes, neurodegeneration, and cardiovascular diseases.
By LC–MS analysis, chlorogenic acid, caffeic acid, 5-p-coumaroylquinic acid, caffeoylshikimic acid, 5-p-cis coumaroylquinic acid, p-coumaric acid, and ferulic acid as well as apigenin, quercetin, luteolin, isovitexin, kaempferol, saponarin, isoorientin, and lutonarin have been identified in the flowers of A. vera . Further investigation of metabolic analysis and profiling could reveal the chemical properties of the Aloe species, and clinical trials would be necessary regarding the claims before accurate conclusions can be made.
In this study, the metabolic differences of three different Aloe species, A. vera, A. arborescens, and A. saponaria, were investigated by 1H-NMR-based metabolite profiling. The PCA derived from the 1H-NMR spectra indicated a clear discrimination among the Aloe species, providing high predictability and good fitness of the PCA model (R2 = 0.928 and Q2 = 865). As observed in the PLS-DA score plot, discrimination was observed in the Aloe species with respect to primary metabolites including sugar and organic acid and secondary metabolites such as phenylpropanoids and carotenoids. A. vera was characterized by high levels of malate, whereas A. arborescens was characterized by higher levels of Aloe nin and sugar metabolites such as sucrose and glucose. Furthermore, the secondary metabolites were quantitatively analyzed by HPLC, and the amounts of carotenoids including zeaxanthin, α- and β-carotene, and phenylpropanoids in A. arborescens were found to be significantly higher than those in the other Aloe species. It is demonstrated that 1H-NMR-based metabolomics with chemometric analysis can be used for the facile discrimination of Aloe species.
This work was supported by the Technology Development Program [grant number S3049433] funded by the Ministry of SMEs and Startups (MSS, Korea).
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