Anal Bioanal Chem DOI 10.1007/s00216-014-8432-1
RESEARCH PAPER
Integrated comparative metabolite profiling via MS and NMR techniques for Senna drug quality control analysis Mohamed A. Farag & Andrea Porzel & Engy A. Mahrous & Mo’men M. El-Massry & Ludger A. Wessjohann
Received: 24 September 2014 / Revised: 12 December 2014 / Accepted: 18 December 2014 # Springer-Verlag Berlin Heidelberg 2015
Abstract Senna alexandrina Mill (Cassia acutifolia and Cassia angustifolia) are used for the laxative medicine Senna. Leaves and pods from two geographically different sources were distinguished from each other via proton nuclear magnetic resonance (1H-NMR) and ultra performance liquid chromatography-mass spectrometry (UPLC-MS) analysis. Under optimized conditions, we were able to simultaneously quantify and identify 107 metabolites including 21 anthraquinones, 24 bianthrones (including sennosides), 5 acetophenones, 25 C/Oflavonoid conjugates, 5 xanthones, 3 naphthalenes, 2 further phenolics, and 9 fatty acids. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used to define both similarities and differences among samples. For sample classification based on tissue type (leaf and pod), both UPLC-MS and NMR were found to be more effective in separation than on geographical origin. Results reveal that the amounts of the major classes of bioactives in Senna, i.e., flavonoids and sennosides, varied significantly among organs. Leaves contained more flavonoids and ω-3 fatty acids but Electronic supplementary material The online version of this article (doi:10.1007/s00216-014-8432-1) contains supplementary material, which is available to authorized users. M. A. Farag (*) : E. A. Mahrous Pharmacognosy Department, College of Pharmacy, Cairo University, Kasr el Aini st., P.B. 11562, Cairo, Egypt e-mail:
[email protected]
fewer benzophenone derivatives than pods. In contrast, pods were more enriched in bianthrones (sennosides). PCA analysis was found to be equally effective in predicting the origin of the commercial Senna preparation using NMR and/or UPLC-MS datasets. Furthermore, a selection of six so far uninvestigated Senna species were analyzed by UPLC-MS. Results revealed that the Senna alata leaf in terms of secondary metabolite composition is the most closely related species to S. alexandrina Mill, showing the highest levels of the anthraquinone “rhein” and flavonoid conjugates. To the best of our knowledge, this study provides the first approach utilizing both UPLC-MS and NMR to reveal secondary metabolite compositional differences among Senna species. Keywords Senna alexandrina . S. bicapsularis . S. corymbosa . S. didymobotrya . S. alata . S. sophera . NMR . UPLC-MS . Sennosides . Principal component analysis . Laxative Abbreviations SLE Senna alexandrina leaf Egyptian SLI Senna alexandrina leaf Indian SPE Senna alexandrina pod Egyptian SPI Senna alexandrina pod Indian
M. A. Farag e-mail:
[email protected] A. Porzel : L. A. Wessjohann (*) Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120, Halle (Saale), Germany e-mail:
[email protected] M. M. El-Massry National Organization for Drug Control and Research (NODCAR), Dokki, P.B. 12553, Cairo, Egypt
Introduction Plant-based medicines become increasingly popular all over the world. The authentication of herbal raw materials is important to ensure their safety and efficacy. Some herbal drugs belonging to closely related species that differ in medicinal properties are difficult to identify owing to their close
M.A. Farag et al.
morphological and microscopic characteristics. Senna leaf and pod are one of the most common herbal drugs used interchangeably for constipation, as well as the preparations thereof [1], and numerous studies have been made to determine their principal constituents: anthracene derivatives (anthrone, bianthrone, and anthraquinone forms) and flavonoid derivatives [2, 3] (Fig. 1). Sennosides A and B (bianthrone glucosides) have proved to be the most active Senna constituents [4, 5]. Most of the anthranoids are present as pharmacologically inactive glycosides in Senna extracts but are thought to be activated by glycosidic cleavage in vivo by microorganisms in the intestinal flora [6]. Despite its wide clinical use, quality control has been relatively poor but is of high relevance considering its long-term use if, e.g., acute liver failure has occurred [7]. A major reason is that Senna has multiple botanical sources. The two most widely used Senna drugs are Cassia acutifolia Delile (known as Alexandrian Senna) and Cassia angustifolia Vahl (known as Indian Senna). Recent botanical classification identifies both as one species, and they are given the synonym Senna alexandrina Mill [8]. Commercial herbal teas, which have a laxative effect, mostly contain either the leaf or pod of S. alexandrina. However, variations due to geographical source or organ type are likely to affect the chemical composition and clinical efficacy of Senna preparations. Chemical investigation in the genus Senna has also mostly focused on
S. alexandrina with little information on other species’ secondary metabolite composition. A safer consumption of Senna laxative preparations requires a better knowledge of the qualitative and quantitative chemical composition in order to ensure that specific batches of ground powder or its extract are of the quality desired for a botanical dietary supplement [9]. As the anthraquinone content is an important quality criterion for Senna-derived laxatives [10], a number of analytical methods have been established for the different anthraquinone derivatives, mostly using HPLC as the technique of choice [11]. A method for the identification and quantification of phenolic compounds from Senna pods by HPLC and mass spectrometric detection (HPLC-MS) was developed by [9]. Finally, capillary zone electrophoresis and micellar electrokinetic capillary chromatography have been used for detection and, in some cases, for anthraquinone quantification [12, 13]. The determination of the quality control criteria for herbal drugs based on their entire chemical profile rather than a few markers only, i.e., sennosides in the case of Senna, is of importance for ensuring safety and efficacy. Metabolite profiling and fingerprinting analyses using spectroscopic techniques, such as proton nuclear magnetic resonance (1H-NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS), have been used to determine the identity and relative amounts of components in several herbal extracts.
Fig. 1 Structure of the major secondary metabolites detected in Senna extract discussed in the manuscript. Note that the carbon numbering system for each compound is used throughout the manuscript for NMR assignment and thus is based on analogy rather than IUPAC rules
OH
O
OH
8
9
1
5
10
4
4'
10'
5'
1'
9'
8'
OH
O
OH
R3
R1
R3
Sennoside A Sennoside B
R2
10 S, 10’S or 10 R, 10’R 10 S, 10’R or 10 R, 10’S
R1=R2=COOH, R3=H Sennidin A/B R1=COOH, R2=CH2OH, R3=H Sennidin C/D R1=R2=CH3, R3=OH Emodindianthrone OCH3
OH
12
7
1
R=COOH R= CH2OH
CH3
4
5 HO
Rhein Aloe-emodin
O
13 CH3
Tinnevellin glucoside R OH
3'
OH
COOH COOH
5 3
2
HO
O
5' 1
1'
8
3'
6
4 OH
O-Glu
O
OH
Cassiaphenone B-2-glucoside
1'
5'
1
OH
O
R=H Kaempferol R=OCH3 Isorhamentin R=OH Quercetin
Senna drug integrated metabolite profiling via MS and NMR
Metabolite fingerprinting by NMR is widely used for various plant-derived products, including hop [14], licorice [15], ginseng [16], green tea [17], and others [18, 19]. 1H-NMR is well suited for metabolite profiling as it allows the simultaneous detection of a diverse group of secondary metabolites in addition to abundant primary metabolites. In an NMR spectrum, signal intensity is proportional to molar concentration, enabling direct comparison among the relative concentrations of all compounds without the need for calibration curves. Moreover, UPLC-MS using electrospray ionization (UPLCESI-MS) is regarded as a particularly well-accepted platform for untargeted metabolite profiling in plant extracts. In comparison with conventional LC, UPLC achieves rapid metabolite analysis and can provide better peak separation than usually possible with standard LC methods. UPLC coupled with high-resolution quadrupole time-of-flight mass spectrometry qTOF-MS is a relatively new technology that can detect chemical compounds with high sensitivity. The use of UPLC-qTOF-MS for quality control assessment of phytomedicines and commercial plant drug preparations has been reported for analyses of green tea, ginseng, ephedra, and hypericum [20–22]. Because of these complementary analytical features of NMR and UPLC-MS, opportunities for leveraging both methods are being considered ideal to create more comprehensive metabolic profiling. While only few studies to date have combined both analytical techniques with multivariate analysis [14, 23], this approach has exciting potential for the field of plant metabolomics. The combined application of 1HNMR and UPLC-MS techniques is recommended for quality control and authentication of complex herbal medicines and products [24]. The present study aims to investigate Senna global bioactive secondary metabolism in the context of organ type and genetic diversity represented by six different Senna species so as to set a reliable framework for its quality control, authentication, and metabolite-based taxonomy.
Experiments Plant material The fresh plant specimens of S. alexandrina Mill. (Egypt), Senna alata (L.) Roxb, Senna bicapsularis (L.) Roxb, Senna corymbosa (Lam.), Senna didymobotrya (Fresen.), and Senna sophera (L.) Roxb were collected during the fruiting stage in May 2012 from Orman Botanical Garden, Cairo, Egypt, and the traded parts of S. alexandrina Mill. (Indian) were procured from Haraz Herbal Company, Cairo, Egypt. All plant specimens were authenticated by a plant taxonomist, Dr. Teresa Labib, Orman Botanical Garden, Cairo, Egypt. Plant names have been checked according to The Plant List http://www.
theplantlist.org/ [8] accessed on Sept. 9, 2014. Voucher specimens were deposited at the Herbarium of the Faculty of Pharmacy, Cairo University, Egypt. Senna slimming preparation was purchased from Sekem Pharmaceutical Company (Cairo, Egypt) as a crushed powder. The collected material was kept at −20 °C until further analyzed.
Chemicals and reagents Methanol-d4 (99.80 % D), acetone-d6 (99.80 % D), and hexamethyldisiloxane (HMDS) were provided from Deutero GmbH (Kastellaun, Germany). For NMR quantification and calibration of chemical shift, HMDS was added to a final concentration of 0.94 mM. Acetonitrile and formic acid (LC-MS grade) were obtained from J. T.Baker (The Netherlands); Milli-Q water was used for LC analysis. Chromoband C18 (500 mg, 3 ml) cartridge was purchased from MACHEREY-NAGEL (Düren, Germany). Sennoside A was purchased from Chromadex (Wesel, Germany). All other chemicals and standards were provided by Sigma-Aldrich (St. Louis, MO, USA).
Extraction procedure and sample preparation for NMR and MS analyses Dried and deep-frozen Senna pod and leaf were ground with a pestle in a mortar using liquid nitrogen. The powder (120 mg) was homogenized with 5 ml 100 % MeOH containing 10 μg ml−1 umbelliferone (an internal standard for relative quantification using LC-MS) using a Turrax mixer (11,000 RPM) for five 20-s periods. To prevent heating, a period of 1 min separated each mixing period. Extracts were then vortexed vigorously and centrifuged at 3000g for 30 min to remove plant debris. For NMR analysis, 3 ml was aliquoted using a syringe and the solvent was evaporated under a stream of nitrogen to dryness. Dried extracts were resuspended with 800 μl 100 % methanol-d4 containing HMDS. After centrifugation (13,000g for 1 min), the supernatant was transferred to a 5-mm NMR tube. All 1H-NMR spectra for multivariate data analysis were acquired consecutively within a 48-h time interval with samples prepared immediately before data acquisition. Repeated control experiments after 48 h showed no additional variation. For UPLC-MS analyses, 500 μl was aliquoted and placed on a (500 mg) C18 cartridge preconditioned with methanol and water. Samples were then eluted using 6 ml methanol, the eluent was evaporated under a nitrogen stream, and the obtained dry residue was resuspended in 1 ml methanol. Three microliters was used for UPLC-MS analysis. For each specimen, three biological replicates were provided and extracted in parallel under the same conditions.
M.A. Farag et al.
High-resolution UPLC-PDA-MS analysis
MS data processing for multivariate analysis (PCA and HCA)
Chromatographic separations were performed on an Acquity UPLC System (Waters) equipped with a HSS T3 column (100×1.0 mm, particle size 1.8 μm; Waters) applying the following elution binary gradient at a flow rate of 150 μl min−1: 0 to 1 min, isocratic 95 % A (water/formic acid, 99.9/0.1 [v/v]), 5 % B (acetonitrile/formic acid, 99.9/0.1 [v/v]); 1 to 16 min, linear from 5 to 95 % B; 16 to 18 min, isocratic 95 % B; and 18 to 20 min, isocratic 5 % B. The injection volume was 3.1 μl (full loop injection). The C18 bonded phase used for the HSS T3 sorbents is compatible with 100 % aqueous mobile phase and provides ultra-low MS bleed, while promoting superior polar compound retention which has been successfully used for the profiling of similar plant extracts [21]. Eluted compounds were detected from m/z 100 to 1000 using a MicroTOF-Q hybrid quadrupole time-offlight mass spectrometer (Bruker Daltonics) equipped with an Apollo-II electrospray ion source in negative ion modes using the following instrument settings: nebulizer gas, nitrogen, 1.6 bar; dry gas, nitrogen, 6 l min−1, 190 °C; capillary, −5500 V (+4000 V); end plate offset, −500 V; funnel 1 RF, 200 Vpp; funnel 2 RF, 200 Vpp; in-source CID energy, 0 V; hexapole RF, 100 Vpp; quadrupole ion energy, 5 eV; collision gas, argon; collision energy, 10 eV; collision RF, 200/400 Vpp (timing 50/50); transfer time, 70 μs; prepulse storage, 5 μs; pulser frequency, 10 kHz; and spectra rate, 3 Hz.
Relative quantification and comparison of Senna metabolic profiles after UPLC-MS was performed using XCMS data analysis software under R 2.9.2 environment, which can be downloaded for free as an R package from the Metlin Metabolite Database (http://137.131.20.83/download/) [25]. This software approach employs peak alignment, matching, and comparison, as described [21] to produce a peak list. The resulting peak list was processed using the Microsoft Excel software (Microsoft, Redmond, WA), where the ion features were normalized to the total integrated area (1000) per sample and imported into the R 2.9.2 software package for principal component analysis (PCA) and hierarchical clustering analysis (HCA). Absolute peak area values were autoscaled (the mean area value of each feature throughout all samples was subtracted from each individual feature area and the result divided by the standard deviation) prior to principal component analysis. This provides similar weights for all the variables. PCA was then performed on the MS-scaled data to visualize general clustering, trends, and outliers among the samples on the scores plot.
UPLC-ESI-MSn analysis ESI-MSn mass spectra were obtained from a LCQ Deca XP MAX system (ThermoElectron, San Jose, USA) equipped with an ESI source (electrospray voltage, 4.0 kV; sheath gas, nitrogen; capillary temperature, 275 °C) in negative ionization modes. The ion trap MS system is coupled with the exact Waters UPLC setup and using the same elution gradient. The MSn spectra were recorded during the UPLC run by using the following conditions: MS/MS analysis with a starting collision-induced dissociation energy of 20 eV and an isolation width of +2 amu in a data-dependent, negative ionization mode.
NMR analysis All spectra were recorded on an Agilent VNMRS 600 NMR spectrometer operating at a proton NMR frequency of 599.83 MHz using a 5-mm inverse detection cryoprobe. 1HNMR spectra were recorded with the following parameters: digital resolution, 0.367 Hz/point (32K complex data points); pulse width (pw), 3 μs (45°); relaxation delay, 23.7 s; acquisition time, 2.7 s; and number of transients, 160. Zero filling up to 128K and an exponential window function with lb=0.4 was used prior to Fourier transformation. 2D NMR spectra were recorded using standard CHEMPACK 4.1 pulse sequences (gDQCOSY, gHSQCAD, gHMBCAD) implemented in Varian VNMRJ 2.2C spectrometer software. The HSQC experiment was optimized for 1JCH =146 Hz with DEPT-like editing and 13C-decoupling during acquisition time. The HMBC experiment was optimized for a long-range coupling of 8 Hz; a two-step 1JCH filter was used (130–165 Hz). NMR data processing and PCA analysis
Identification of metabolites via UPLC-MS UPLC-MS files were converted to .netcdf file format using the File Converter tool in Bruker Daltonics software and further processed using AMDIS software to assist in adjacent peak deconvolution and background subtraction. Metabolites were characterized by their UV-vis spectra (220–600 nm), retention times relative to external standards, mass spectra and comparison to our in-house database, phytochemical dictionary of natural products database, and reference literature.
The 1H-NMR spectra were automatically Fourier transformed to ESP files using ACD/NMR Manager lab version 10.0 software (Toronto, Canada). The spectra were referenced to internal hexamethyl disiloxane (HMDS) at 0.062 ppm for 1HNMR and to internal CD3OD signals at 49 ppm for 13C-NMR, respectively. Spectral intensities were reduced to integrated regions, referred to as buckets, of equal width (0.04 ppm) within the region of δ 11.4 to −0.4 ppm. The regions between δ 5.0–4.7 and δ 3.4–3.25 corresponding to residual water and
Senna drug integrated metabolite profiling via MS and NMR
methanol signals, respectively, were removed prior to multivariate analyses. PCA was performed with R package (2.9.2) using custom-written procedures after scaling to HMDS signal and exclusion of solvent regions. NMR quantification For the quantification of metabolites listed in the Electronic Supplementary Material (ESM) Table S1 using NMR spectroscopy, the peak area of selected proton signals belonging to the target compounds and the peak area of the IS (HMDS) were integrated manually for all the samples. The following equation was applied for the calculations. mT =mass of the target compound in the solution used for 1H-NMR measurement [μg] mT ¼ M T MT IT ISt xSt xT cSt vSt PSt
I T xSt PST cSt vSt I St xT 100
Molecular weight of the target compound [g mol−1] Relative integral value of the 1H-NMR signal of the target compound Relative integral value of the 1H-NMR signal of the standard compound Number of protons belonging to the 1H-NMR signal of the standard compound Number of protons belonging to the 1H-NMR signal of the target compound Concentration of the standard compound in the solution used for 1H-NMR measurement [mmol L−1] Volume of the solution used for 1H-NMR measurement [ml] Certified value of the purity of the standard compound [%]
Results and discussion The major goal of this study was to investigate Senna secondary metabolites in an untargeted, holistic manner in the context of its genetic diversity and organ type so as to set a framework for quality control analysis and to help identify alternatives to this important botanical. Although officially approved Senna and unofficial Senna show significant differences in laxative effects, they are similar in physical appearance and are difficult to distinguish by conventional means. Consequently, a simple, rapid, and accurate method for the analysis of active constituents in Senna is deemed necessary. To accomplish this goal, chemical constituents of the commercial Senna drugs, S. alexandrina Mill represented by both leaf and pod samples and from different geographical origins Egypt and India, were subjected to metabolite fingerprinting
using NMR techniques without any preliminary separation step, and in parallel to chromatographic hyphenated UPLCMS techniques. Furthermore, metabolite profiles of leaves from five less-investigated Senna species, S. bicapsularis, S. corymbosa, S. didymobotrya, S. alata, and S. sophera, were determined by UPLC-MS to assist in the identification of alternative species and to have reference profiles for Senna drug authentication, i.e., adulteration detection. To allow for a comparative analysis of the metabolite data derived from these different technology platforms that is found compatible with both NMR and MS metabolomics [14, 15], a one-pot extraction method using 100 % methanol was developed. Owing to the complexity of acquired data, as reflected in the complexity of spectral data, multivariate analyses, i.e., hierarchical cluster analysis (HCA) and principal component analysis (PCA), were utilized to ensure good analytical rigorousness and define both similarities and differences among samples. Analysis of 1H-NMR spectra The 1H-NMR spectra of S. alexandrina Mill leaf and pod samples displayed two main regions. The first is an up-field region spanning from δ 1H=0.0 to 6.0 ppm that shows signals of high intensity, most of which could be assigned to primary metabolites, i.e., fatty acids and sugars. In the down-field region (δ 1H=6.0 to 9.0), 1H-NMR signals were observed at much lower intensities, mostly ascribed to phenolic secondary metabolites characteristic of Senna including naphthalene glycosides, benzophenone glycosides, anthraquinone derivatives, and flavonoids (ESM Fig. S1). Only few peaks in the 1HNMR spectra of Senna extract were readily assigned without 2D NMR, i.e., two signals at δ 1H=1.26–1.30 and δ 1H= 0.89 ppm belonging to the repeated methylenes and the terminal methyl of fatty acids, respectively. The assignment of unique 1H-NMR signals for most other metabolites required the examination of 2D spectra including 1H-1H-COSY, 1 H-13C HSQC, and HMBC. Using these NMR spectra, several characteristic signals for primary and secondary metabolites were assigned and are listed in Table 1 and Fig. 2. Among peaks identified in the up-field region, few signals exhibit a characteristic value to discriminate between different Senna samples including the two triplets at δ 1H=2.80 (J= 6.1 Hz) and δ 1H=0.97 ppm (J=7.5 Hz). Using 1H-13C correlations observed in the HMBC spectra, these two triplets were unequivocally assigned to the allylic methylene and the terminal methyl of ω-3 fatty acids (i.e., linolenic acid), respectively (ESM Fig. S2). Similarly, two other triplets at δ 1 H=2.77 (J=6.5 Hz) and δ 1H=0.89 ppm (J=6.8 Hz) were assigned to the allylic methylene and terminal methyl of other unsaturated fatty acids (n>2), i.e., linoleic acid and ω-6 fatty acid. These assignments were later confirmed by comparison with the 1H-NMR spectra of standard solutions of both linoleic and linolenic acids (ESM Fig. S3). Accordingly, the
M.A. Farag et al. Table 1 Resonance assignments with chemical shifts of constituents identified in 600 MHz 1H-NMR, 1H-13C-NMR, and HMBC NMR spectra of S. alexandrina Mill (Egypt) leaf extracts (methanol-d4) δ 13C in ppm
δ 1H in ppm
Metabolite
Assignment
Fatty acids (a)
t-CH3 –(CH2)n– C-2 C-11
0.88–0.91, br. m 1.26–1.32, br. m 2.30 2.77 t (J=6.5 Hz)
C-18 C-11/14 C-2 C-1, C-3 C-1 C-5′ C-1 C-5 C-2′/6′ C-3′/5′ C-8 C-6 C-2′ C-8 C-6 –OCH3
0.96 t (J=7.5 Hz) 2.81 t (J=7.5 Hz) 5.25 m 4.12, 4.44 5.39 d (J=3.7 Hz) 3.88 4.46 d (J=7.9 Hz) 4.20 8.08 d (J=8.8 Hz) 6.89 d (J=8.8 Hz) 6.4 d (J=1.9 Hz) 6.19 d (J=1.9 Hz) 8.01 d (J=1.8 Hz) 6.37 d (J=1.6 Hz) 6.17 d (J=1.6 Hz)
ω-6 fatty acids (b) ω-3 fatty acids (d) Triglycerides Sucrose (e) Glucuronic acid (g) Kaempferol (k)
Isorhamentin (i)
Sennidin (s)
Sennidina (s) Rhein (r) Rhein glycosidea (rg) Aloe-emodina Emodin Cassiaphenone Ba (c)
Tinnevellina (t)
a
C-10 C-10′
3.93 s 4.77 4.73
C-2 C-2′ C-10 C-2 C-2 C-4 C-4 C-11 C-11 C-3′ C-4 C-5 C-3 C-13 C-12 C-7 C-5 C-4
7.38 br. s 7.40 br. s 4.82 7.38 s 7.71 br. s 8.22 br. s 8.27 4.61 s 2.38 s 7.50 br. s 7.34 t (J=8.3 Hz) 6.59 d (J=8.5 Hz) 6.57 d (J=8.3 Hz) 2.28 s 2.57 s 6.75 s 6.96 s 7.05 s
12.4, 14.5 30.2 35.6 26.5 14.6 26.6 72.1 64.2 94.1 84.9 98.7 74.6 132.7 116.4 95.4 100.4 114.9 94.7 99.5
HMBC correlations δ 13C in ppm 32.6, 23.7 14.9,26.6, 28.3, 30.2,35.6 25.8, 30.6 129.2, 131.2 21.6, 132.9 129.2, 131.2, 132.9 175.3 74.1, 105 84.9, 72.1 76.5, 78.2 68.7, 71.9, 175.6 132.5, 159, 161.9 116.4, 123.9, 160.8 100.4, 105.2, 158.7, 166 95.4, 105.2, 162.7, 165.9 123.9, 148.4, 151.1 99.5, 104.6, 158, 165.9 94.7, 104.6, 162.7, 165.9
56.7 57.3 57.5
148.4, 171 117.8, 119.8, 121.8 118.1, 119.4, 121.4, 142.7
118.5 118.5 57.1 118.5 125.6 121.7 120.8 64.9 22.1 119.6 136.0 112.5 105.6 20.5 32.6 98.9 105.6 120.5
120.1, 121.9, 163.2, 171.6 120.1, 121.9, 163.2, 171.9 57.3, 121.7, 124.3, 158.9 121.7, 124.7 117.8, 121.6, 148.8, 171.6 118, 125.2, 171.6, 183.2 119.2, 125.6, 171.8, 183.7 119.7, 116.6, 144.7 113.1, 119, 144 122.6, 136.9, 171.9 120.7, 160.3, 164.5 105.6, 115.3, 164.5 112.7, 115, 160.3 120.4, 124.6, 135.9 124.4, 207.8 105.6, 11.3, 158.8 98.9, 110.6, 158.8 105.6, 110.6, 124.2
Values are observed in the NMR spectra of S. alexandrina Mill pod extract in methanol-d4
ratio of ω-3 to ω-6 fatty acids could be calculated from the integration values of their allylic methylenes, with the largest one measured in S. alexandrina leaf from Egypt (3:1) and the lowest one found in S. alexandrina pod from Egypt (1:4) as shown in ESM Fig. S4. Moreover, the percentile of ω-3 fatty
acids in the total fatty acid pool was calculated from the integration values of the corresponding terminal methyls (δ 1 H=0.96 for ω-3 fatty acids and δ 1H=0.87–0.92 ppm for all other fatty acids). These results point to a divergent fatty acid metabolism in Senna organs, with ω-3 fatty acids being
Senna drug integrated metabolite profiling via MS and NMR Fig. 2 Partial 1H-NMR spectra of the methanol extract of S. alexandrina leaf (Egypt), I; S. alexandrina leaf (India), II; S. alexandrina pod (Egypt), III; and S. alexandrina pod (India), IV, showing characteristic signals for secondary metabolites in the most relevant shift range (δ=6.0– 8.35 ppm). Peaks assigned in the spectra are labeled as follows: cassiaphenone-B, c; isorhamentin, i; kaempferol, k; kaempferol glycosides, kg; quercetin, q; rhein, r; sennidin, s; and tinnevellin (torachrysone), t. The identities of NMR peaks are listed in Table 1
k r
kg
r
i
q
s
i+q
r+s
k,i,q
kg
i
r
I) S. alexandrina leaf (Egypt) k, i, q i+q k i k q s+r
s+r
c
r+s
i+q c
s
c
t t
II) S. alexandrina leaf (India) k k c t III) S. alexandrina pod (Egypt)
c r
kg
c
s
r+s
t
t
k
t
c K
IV) S. alexandrina pod (India)
r
kg
c i
generally more enriched in leaf versus pod. However, it should be noted that the fatty acid content and distribution are not of (direct) relevance for medicinal applications. In Senna, flavonoids occur mostly as conjugates of flavonols, namely kaempferol, quercetin, and isorhamentin [3]. Several flavonoids including kaempferol, quercetin, isorhamentin, and their glycosides were identified in the down-field region of the 1H-NMR spectrum through the presence of their characteristic meta coupled protons (H-6 and H-8 of ring A, ESM Fig. S5 and S6). These flavonoids were differentiated from each other through the splitting pattern and coupling constants of protons in ring B (Table 1, Fig. 1). Different anthraquinones derivatives were also identified including several biologically active bianthrones, i.e., sennosides (glycoside) or sennidins (aglycone). These metabolites are characterized by the presence of HC–CH bond at 10–10′ positions and HMBC correlations arising from these protons used as an anchor to identify NMR peaks unique in sennidins (ESM Fig. S7 and S8). Several 1H-13C cross peaks were observed in the HSQC spectra of different Senna extracts representing H-10/H-10′ at δ 1H/13C values of 4.77/57.3, 4.73/ 57.5, 4.82/57.1, and 4.86/57.3 ppm. The abovementioned cross peaks had a different distribution in Senna samples, with the last two signals identified only in S. alexandrina pods, albeit not in leaves. Some of these protons show clear HMBC correlations to several carbons, and by following the 1H-13C cross correlation of these carbons, two 1H-NMR peaks unique for sennosides were assigned: H-2 at δ 1H between 7.37 and 7.41 ppm and H-4 at δ 1H=7.70–7.78 ppm depending on the type of sennoside (ESM Fig. S7 and S8). Accordingly, the well-resolved 1H-NMR peak for H-2 can be considered a possible marker for sennosides. The dimeric structure in sennidins was proved from key HMBC cross correlation between H-10/C10′ or H-10′/C10 appearing at δ 1H/13C
r+s
c
s
c
t
t k
t
c
ki
K
values of 4.82/57.3 ppm in S. alexandrina pod extracts. It is worth mentioning that signals for sennidins were detected in all examined samples, but the 1H and 13C chemical shifts observed for the characteristic proton signals were not identical. If unlikely matrix and association effects are not responsible, this suggests that the major sennidins in the pod extracts (i.e., meso form, 10R, 10′S or 10S, 10′R) are slightly different in structure from those found in the leaf extract (i.e., chiral form 10R, 10′R or 10S, 10′S). Similarly, different rhein (anthraquinone) derivatives were recognized in different Senna extracts; the two most abundant show their signal for the H-4 proton at δ 1H =8.22 and 8.27 ppm and with HMBC correlations to both the carboxylic group (C-11) at 172 ppm and the C-10 carbonyl at 183 ppm (ESM Fig. S9). Aloe-emodin signals could also be identified by following HMBC correlations to the hydroxyl methylene group at δ 1H/13C=4.6/64.9 ppm (ESM Fig. S10), whereas the most unique signal of emodin is that of CH3-11 appearing at 2.38 ppm (ESM Fig. S11). Other phenolic metabolites identified include the acetophenones “cassiaphenone B 2-glycoside” which show well-resolved signals at δ 1H=7.34 (t, J= 8.3 Hz), 6.59 (d, J=8.3 Hz), and 6.57 ppm (d, J=8.3 Hz) (ESM Fig. S12). In addition, the presence of the naphthalene glycoside “tinnevellin” in S. alexandrina was confirmed through the detection of a methyl group at δ 1H=2.57 ppm and its HMBC correlation to the keto group at δ 13C=210 ppm (ESM Fig. S13). Tinnevellin (torachrysone) glycoside was often considered as a chemical marker characteristic of Indian Senna (formerly C. angustifolia); nevertheless, our results show its presence in all four Senna drugs, confirming recent taxonomic classification [8] (The Plant List, 2013) for both Indian and Alexandrian senna as S. alexandrina. The ability of 1H-NMR to identify one unique well-resolved peak for each of the aforementioned secondary metabolites further
M.A. Farag et al.
allowed for their unbiased relative quantification in samples. The concentration of some of these bioactive metabolites using NMR quantification in different samples is shown in ESM Table S1, expressed as microgram per milligram dry ground plant powder. Unsupervised multivariate PCA analysis of 1H-NMR data PCA and OPLS-DA are often used to analyze large complex data sets. PCA is the most widely used multivariate data analyses method for chemometrics. NMR spectra from all samples derived from the four examined official Senna drugs studied along with the commercial sample were initially subjected to PCA analysis (ESM Fig. S14) to detect compositional differences among them. PCA analysis revealed that extracts of Senna leaves were enriched in signals for flavonoids whereas pod extracts were more enriched in naphthalene glycosides and benzophenones. PCA was initially performed within the 1H-NMR region of δ 11.4 to −0.4 ppm. The PC1/ PC2 scores plot (ESM Fig. S14A) shows that three major distinct clusters are formed from the five different samples studied, mostly along PC1 and PC2. On the left side of the plot, samples for S. alexandrina leaf from Egypt and India were positioned with negative PC1 values, whereas Egyptian S. alexandrina pod was located on the far right side with positive PC1 values. Interestingly, 1H-NMR-derived data show the clustering of the commercial Senna sample from Egypt closely with pod botanical samples grown in the same region with positive score values along PC1, suggesting that PCA can be used to predict samples of unknown origin, at least for the regional samples studied herein. We do admit that our selection of biological replicates is rather limited (n=3), but considering the large size of examined samples and the small variance within each type, our model is feasible to be challenged for analyzing more samples. Examination of the 1H-NMR loadings plot shows that this variability was mainly attributed to differences in two main regions: firstly, the fatty acid region where signals assigned to saturated fatty acids contributed to positive PC1 values, while signals of unsaturated ω-3 fatty acids contributed to negative PC2 values (ESM Fig. S14B). Considering our interest in the distribution of the more relevant secondary bioactive metabolites, i.e., flavonoids and anthraquinones, PCA was performed for all samples in a second step, with the fatty acids and sugar region of 1H-NMR spectra excluded from analysis (ESM Fig. S15A). PCA score plots derived from this reduced NMR dataset were in general agreement with the general dataset, except for the distinct separation of Egyptian and Indian S. alexandrina leaf samples along PC1, and with close clustering of pod-derived accessions from different origins. The loading plot for PC1 (ESM Fig. S15B) exposed the signals that had the greatest effect on this component. Two main groups were found to contribute negatively to PC1,
those assigned to kaempferol glycosides at δ 1H=8.04, 6.88, 6.36, and 6.16 ppm and the other group of signals at δ 1H= 8.22, 7.64, and 7.2 ppm assigned for rhein (Table 1). Meanwhile, 1H-NMR signals for sennosides observed at δ 1 H=7.71, 7.38, and 6.59 ppm show a positive contribution to PC1 (Table 1, ESM Fig. S7 and S8). Similarly, variance along the PC2 component could be explained by three groups of signals, one contributing negatively to PC2 values at δ 1H= 7.04 and 6.9 ppm assigned to tinnevellin glycoside (Table 1, ESM Fig. S13), while the two other groups exhibit a positive influence on PC2, namely through cassiaphenone signals at δ 1 H=7.34 and 6.56 ppm and isorhamentin glycoside signals at δ 1H=8.00, 7.76, 6.85, and 6.16 ppm. Although PCA analysis of the relevant NMR shift range data resulted in a tighter clustering of the individual Senna samples, this biased clustering appears to provide a better reflection of the pharmacological activity of Senna samples as it is mainly influenced by the concentration of its biologically active secondary metabolites. UPLC-ESI-MS peak identification LC-MS has been used for the qualitative and quantitative analyses of Tinnevelli Senna pod extract from Cassia senna var. angustifolia [9]. Senna anthraquinones and flavonoids are relatively polar compounds with carboxyl or phenol groups in the molecules and thus can be readily ionized in the electrospray ionization (ESI) source, especially in negative mode. Chemical constituents of Senna leaf and pod were analyzed by reversed-phase UPLC/PDA/(−)ESI-qTOF-MS, using a gradient mobile phase consisting of acetonitrile and aqueous formic acid that allowed for a comprehensive elution of all analytes within 13 min (ca. 800 s) compared to the 60min analysis time previously reported [9]. Simultaneously acquired UPLC-MS base peak intensity chromatograms of Indian and Egyptian S. alexandrina leaf and pod are presented in Fig. 3, and a comparison of the leaf extracts of S. bicapsularis, S. corymbosa, S. didymobotrya, S. alata, and S. sophera is presented in ESM Fig. S16. The identities, retention times, UV characteristics, and observed molecular and fragment ions for individual components are presented in ESM Table S2. Metabolite assignments were made by comparing retention time, UV/vis spectra, and MS data (accurate mass, isotopic distribution, and fragmentation pattern in negative ion mode) of the compounds detected with Senna species reported in the literature and searching the phytochemical dictionary of the natural products database (Wiley, CRC). Identifications were confirmed with standard compounds whenever available in-house. About 107 compounds, including 21 anthraquinones, 24 bianthrones (including sennosides), 5 acetophenones, 25 C/O-flavonoid conjugates, 5 xanthones, 3 naphthalenes, 2 phenolics, and 9 fatty acids, were resolved of which 94 were tentatively identified, with anthraquinones
Senna drug integrated metabolite profiling via MS and NMR 71
8
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21 26 49
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II) S. alexandrina leaf (India)
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III) S. alexandrina pod (Egypt) 6
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IV) S. alexandrina pod (India) 71
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77
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77 87
84 60 58 61
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99
89 80
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Rt (sec) Fig. 3 UPLC-qTOF-MS base peak chromatograms of the methanol extracts of S. alexandrina leaf (Egypt), I; S. alexandrina leaf (India), II; S. alexandrina pod (Egypt), III; and S. alexandrina pod (India), IV.
Chromatographic conditions are described under “Experiments.” The identities, Rt values, and basic UV and MS data of all peaks are listed in ESM Table S2
and sennosides accounting for the highest abundance among examined species (ESM Table S2).
Similar to sennoside A isomers, the ion chromatograms for m/ z 847 corresponding to sennoside C (54) and D (34) show similar fragmentation patterns. Aside from these sennosides, a number of less-abundant sennosides were identified as deglucosylated derivatives (79, 88, 89, 92, 93, 95, 96, 100, and 101) or sennosides exhibiting an extra double bond, likely at the C10–C10 linkage of sennosides (67). Among the four examined official Senna drugs, samples with the highest sennoside content were those from pods, while leaves showed lower amounts and in agreement with NMR results. In contrast, bianthrone aglycones, i.e., sennidin peaks 83, 88, 89, 93, 95, 96, and 100, were most prevalent in Egyptian leaf samples. Whether the enrichment of bianthrone aglycones in Egyptian Senna leaf is due to limited glucosyl transferase (GT) activity or degradation of sennosides (primary glycosides) due to the high moisture content in leaf and the simultaneous existence of active glucosidases has yet to be clarified. This is the first report on the difference in anthraquinone glycoside patterns among official Senna drugs. In addition to sennoside and bianthrone aglycones, several mono- and di-glycosides of anthraquinones were identified as derivatives of emodin, aloe-emodin, and rhein, based on their UV spectra. Rhein conjugates were most common and accounted for at least 59 % of all the anthraquinones, followed by emodin and aloe-emodin isomers in this order, readily differentiated by their MS/MS spectra. The fragmentation of
Identification of sennosides/anthraquinones The active principles of Senna extract are the anthraquinones, together with the Senna-specific bianthrones (sennosides). Sennosides (bianthrones) and anthraquinone glycosides are considered as the main purgative components, while free anthraquinones are reported to possess anti-inflammatory effects [26]. The characteristic C10–C10’ dimerization link cleavage was used for rapid identification of sennosides in Senna extracts, in addition to neutral losses of 28 and 44 mass units due to the elimination of carbonyl and carboxylic groups, respectively. A total of 24 sennosides were identified in this study, with sennoside A/B and C/D as major forms. In detail, sennoside A (37) gives a [M-H]− ion at m/z 861, which upon tandem MS yields m/z 699 and 537, resulting from the consecutive loss of two glucose moieties (162 amu, ESM Fig. S17). Another sennoside peak (32) shows a very similar molecular ion and tandem MS spectrum, albeit with an abundant ion at m/z 386 (30 % rel. int.) which was identified as coming from sennoside B. It has been reported that, in sennoside B (meso form), the C10–C10 bond is easier to be cleaved in contrast to the chiral form, sennoside A (10S, 10′S or 10R, 10′R), where the C10–C10 bond is more stable [27].
M.A. Farag et al.
emodin shows the elimination of CO to produce m/z 241, followed by the loss of one hydroxyl group to give m/z 225. The [M-H]− ion of aloe-emodin, however, only produces one fragment at m/z 240 ([M-H-CHO]) in agreement with previous reports [27]. The predominant rhein components were found to be rhein-O-glucoside (23) and rhein-O-diglucoside (10). It should be noted that in Senna drugs, free anthraquinones were detected at lower levels than their glycosides and sennosides, except for Indian leaf samples which showed slightly higher anthraquinone aglycone levels. The low aglycone levels suggest that sennosides (primary glycosides) and sennidins (secondary glycosides) are not subject to major chemical degradation. Rhein-8-O-glucoside (23) is recognized as a potential chemical marker for assessing degradation or storage condition effects on sennosides within the crude plant material [1]. Identification of flavonoids Flavonoids have been reported from different species of Senna [28] usually substituted with one or several sugars. Photodiode array detection provided an overview of the main flavonoid constituents in Cassia extract. UV spectra (200– 600 nm) were recorded for different flavonoid sub-classes including 11 flavones (nos. 5, 8, 22, 31, 39, 40, 46, 52, 57, 59, and 72) and 14 flavonols (nos. 3, 14, 15, 17, 21, 26, 28, 29, 35, 42, 60, 69, 71, and 75). Each sub-class has a characteristic UV spectrum. In the MS/MS analysis, the nature of sugars could be revealed from the elimination of the sugar residue, that is 162 amu (hexose; glucose or galactose) or 146 amu (rhamnose). Mono- and di-O-glycosides identified were all flavonol derivatives of quercetin, kaempferol, and isorhamnetin, with isorhamnetin conjugates as the most abundant. Isorhamnetin is a methylated derivative of quercetin and was found as an aglycon moiety in peaks 12, 22, 27, 30, 40, and 52. Similarly, MS spectra interpretation allowed for the detection of quercetin (m/z 301.0352, C15H9O7) in peaks 14, 15, 28, 60, and 48 and kaempferol (m/z 285.0329, 16 amu less than quercetin, C15H9O6) in peaks 3, 17, 29, and 71. In addition to the neutral loss of sugars which is normally seen for O-type flavonoid glycosides, several glycosides exhibited fragmentation patterns evident for C-type glycosides as evident from intense molecular ion peaks with M-90 and M-120 fragments in MSn spectra. In previous reports, it was demonstrated that luteolin and apigenin glycosides present in Senna occidentalis were of the C-glycoside type [28]. In detail, peak 8 was characterized by a [M-H]− at m/z 593 with fragment ions at m/z 503 ([M-H-90]−) and m/z 473 ([M-H-120]−) in accordance with the presence of apigenin-6,8-C-diglucoside (vicenin-2). Peak 31 had a [M-H]− at m/z 609, and its MSn spectrum showed ions at m/z 489 ([M-H-120]−) and m/z 519 ([M-H-90]−), corresponding to the fragmentation of a flavone C-diglycoside, tentatively identified as luteolin-6,8-C-
diglucoside (i.e., lucenin-2) [29]. Other C-glycosides identified include three luteolin conjugates, cassiaoccidentalin A (p ea k 52 ), c ass iao cc iden tali n B (pe ak 40) , an d cassiaoccidentalin C (peak 57), previously reported in S. occidentalis [30] and found almost exclusively in the S. sophera sample. It should be noted that both O- and Cflavonoid-type glycosides were generally more enriched in leaf versus pod, particularly in the Indian S. alexandrina leaf sample. Identification of fatty acids In the second half of the chromatographic run (350–900 s), particularly in the Egyptian S. alexandrina leaf extracts, MS spectra of several unsaturated fatty acids, that is, oleic (107), linoleic (102), and linolenic acid (103), were identified, as evident from high-resolution mass at 281.2484, 279.2328, and 277.217 with predicted molecular formulae of C18H33O2−, C18H31O2−, and C18H29O2−, respectively. Linolenic acid, an ω-3 fatty acid, predominated leaf samples’ fatty acid pool in agreement with NMR results (ESM Fig. S4). MS signals were also assigned for saturated fatty acids, that is, lignoceric acid (104) and palmitic acid (106), as evident from high-resolution masses m/z 367.3568 and 255.2323 with predicted molecular formulae of C 24 H 47 O 2 − and C 16 H 31 O 2 − , respectively. Negative ionization MS also revealed several unexpected hydroxylated fatty acids, major peaks 97, 98, and 99. In detail, peaks 97 and 99 show a mass weight of 293.212 and 295.227 amu, with predicted molecular formulae of C18H29O3− and C18H31O3−, respectively, and a loss of a water molecule (18 amu) suggestive of an extra hydroxyl group. Whether fatty acids contribute to the Senna purgative effect has yet to be examined. Identification of benzophenones/acetophenones In this study, several benzophenones were detected including cassiaphenone A-2′-glucoside, peak 1; cassiaphenone B-2′glucoside, peak 6; and cassiaphenone A, peak 82, as evident from their characteristic UVmax at 272 nm in addition to losses of 28 and 44 mass units, ascribed to carbonyl and carboxylic groups, respectively; a loss of 162 amu, hexose, in peaks 1 and 6 was also evident. Benzophenones serve as precursors for the biosynthesis of xanthones in a mixed shikimate/acetate biosynthetic pathway [31]. The presence of the acetophenones, torachrysone (C 14 H 14 O 4 , MW 246) and its glucoside (C20H24O9, MW 408) known as “tinnevellin-O-glucoside,” was confirmed in Senna. They were most abundant in the Indian S. alexandrina leaf sample found in peaks 77 and 49, respectively. Torachrysone “tinevellin” is regarded as a chemical marker for Indian S. alexandrina samples, but in our study, it was also identified in Egyptian samples, in agreement
Senna drug integrated metabolite profiling via MS and NMR
with their recent taxonomic classification as one drug and concurring with NMR results. Unsupervised multivariate PCA analysis of UPLC-MS data
Unsupervised multivariate HCA analysis of UPLC-MS data The other major goal of the current study was to investigate Senna global bioactive secondary metabolism in the context of its genetic diversity aside from organ type and geographical origin by examining five additional Senna species including S. didymobotrya, S. bicapsularis, S. corymbosa, S. sophera,
Pod(India)
leaf (Egypt)
0 -40000 -30000 -20000 -10000
PC(2 32%)
10000 20000
We compared the performance of PCA from UPLC-MS and 1 H-NMR spectra of extracts to better evaluate the classification potential of both technologies. When compared to the PC plot obtained from cut (selected shift range) NMR data (ESM Fig. S15A), it is apparent that the UPLC-MS results (Fig. 4a) were in general agreement except for the closer clustering of Indian and Alexandria pod samples along with the commercial Senna product in one group (positive score values). In both score plots, leaf samples were plotted on the left side (negative score values). Therefore, the prediction of samples of unknown origin should be possible, though with slightly better discrimination when using NMR. The separation observed in PCA can be explained in terms of the identified
compounds, using the loading plots for the PC1 signals. Two major groups stand out in this plot (Fig. 4b). The first one corresponds to the MS signals that contribute negatively to PC1 for flavonols (quercetin, m/z 301; kaempferol, m/z 285; and isorhamnetin, m/z 315) and fatty acids (linolenic acid, m/z 277). The second group of discriminating MS signals is assigned to cassiaphenones A/B glucosides and 6hydroxymusizin glucoside, which contribute positively along PC1 and suggest enrichments of acetophenones in pod versus leaf samples in Senna drugs.
leaf (India) Pod(Egypt) & commercial product
A
_ -50000
0
50000
0.3
PC1(57%) 301/374
0.2
285/422
Quercetin
0.1
Kaempferol
0.0 -0.1
Linolenic acid
-0.3
-0.2
PC2
Isorhamnetin 277.2/832
279.2/883 537.1/564 283/500 571.1/422 603.1/374 537.1/599 479.1/209 487.4/896 383.4/919 286/422 523.1/590 487.4/876 480.1/219 407.1/335 699.1/399 299.1/427 315/432 581.5/883 538.1/564 285/374 699.1/388 289.1/249 523.1/561 302/374 699.1/408 572.1/422 280.2/883 604.1/374 477.1/310 299/219 325.1/194 538.1/599 589/500 559.1/564 369/374 700.1/399 501.1/219 463.1/282 523.1/622 569.1/219 161/264 547.1/219 289.1/466 524.1/590 284/500 611.2/199 387.2/213 523.1/647 239/500 582.5/883 707.1/280 700.1/388 347.2/883 311.2/826 593.1/422 278.2/832559.3/667 559.3/653 447.1/323 959.2/219 685.2/468 559.1/599 433.2/827 509.1/581 677.1/273 861.2/276 325.1/184 548.1/219 113/778 524.1/561 559.5/883 419.1/291 461.1/320 545.1/590 587.1/374 631.1/432 555.4/832 457.1/181 381.2/260 113/828 113/933 539.1/564 293.1/181 415/374 564.3/661 393.1/194 391.2/924 475.1/337 300.1/427 351/500 883.7/883 113/368 113/290 481.1/219 685.2/502 257/500 287/422 573.1/422 415.2/883 560.1/564 567.1/500 960.2/219 627.1/564 393.1/321 300/219 316.1/432 353/422 509.1/558 113/582 113/507 476.3/734 463.1/326 590/500 685.2/412 862.2/276 591.4/868 259.1/452 286/374 299/375 283/564 284/564 631/218 566.3/712 459.2/924 113/792 303/374 305.1/225 323.2/832 323.2/924 649.4/883 113/687 113/912 521.1/334 545.1/561 539.1/599 478.1/310 501.6/219 745.1/273 269/562 295.2/756 571.1/374 569.1/511 560.3/667 560.5/883 560.1/599 613.1/590 627/599 461.1/193 459.1/181 705/218 464.1/282 333.1/306 547.1/229 367/427 708.1/279 884.7/883 113/843 113/452 510.1/581 113/667 531.1/282 113/921 113/858 113/242 483.2/884 481.2/832 775.1/279 285/500 594.1/422 556.4/832 561.3/712 435.2/233 391/374 981.2/219 370/374 883.2/277 113/323 211.1/884 476.3/654 299/526 325.2/883 326.1/194 678.1/273 686.2/503 686.2/415 546.1/590 551.2/885 525.1/591 113/257 529.1/320 113/337 113/188 113/631 113/440 113/315 513.1/281 545.1/310 546/219 543.1/335 502.1/219 588.1/374 583.5/883 655.1/272 299/483 268/563 595.3/719 281.2/883 577/219 570.1/219 415.2/255 413/500 627.3/667 628.1/564 632.3/661 565.3/661 564/219 563/219 399/422 434.2/826 462.1/320 437/374 443.2/183 441/501 452.3/681 401.1/221 615.1/422 611.2/266 613.1/561 615/218 625.1/205 555.2/253 395.2/190 459/374 383/432 371.1/194 379.2/826 113/462 113/398 580/219 305.2/832 301/423 348.2/883 349.2/940 353/374 650.4/883 609/219 695/564 693.1/253 709.2/465 813.1/273 525.1/561 529.1/194 113/805 113/479 113/224 512.1/219 113/411 113/766 523.1/213 250.1/222 243/500 240/500 245/424 546.1/561 543/219 480.1/229 485.3/690 482.1/219 493.2/367 501.1/210 585.1/426 585.1/482 589.1/335 685.2/387 737.4/925 746.1/273 789.1/399 535.6/219 268/590 670.4/925 669.4/925 293.2/537 275.1/363 271.2/823 279.2/832 279.1/310 595.2/925 599.1/427 601.1/485 601.4/924 577/501 572.1/374 570.1/511 569.2/329 417.2/313 414.2/832 417.2/940 415/422 419/501 627.5/883 628.1/599 631.5/831 639.4/883 556.2/253 568.1/500 561.1/306 561/219 562.3/712 461.1/285 399.3/818 461.2/252 399.3/831 435/427 447.1/284 436.2/233 433.2/253 441.1/194 447.2/667 456.2/213 453/374 611.1/335 614.1/590 615.4/882 617.2/835 621.2/940 613.1/310 621/564 626.1/205 429.2/287 394.1/321 431/374 388.2/213 375/422 702.1/399 707.1/387 700.3/661 879.7/925 171.1/884 163/194 181/336 162/264 205/263 207/218 221.1/477 227/500 473.2/287 473.3/884 470.2/281 476.1/335 471.4/926 465.1/282 581.1/281 299/501 301/277 299.3/915 301/219 300/209 307.2/883 315/392 317.1/432 324.2/832 324.2/924 349.2/883 349.1/270 354/422 354/374 352/500 337.2/883 339.2/823 679.1/273 681.1/590 681.1/310 688.1/273 685.1/834 687.2/884 686.2/387 689/564 651.1/304 651/500 609.1/374 895.1/500 546.1/310 546.5/219 549.3/667 549.2/834 553.2/940 431.1/333 431.1/233 695/599 364.2/884 368/427 709.1/280 714.4/832 723.1/399 721.5/940 725/500 863.2/276 885.7/883 843.1/279 807.1/273 814.1/273 791.1/272 761.1/273 761.1/253 113/890 509/501 509/219 531.1/355 531.1/321 527.2/925 530.1/320 532.1/282 527/374 113/268 511.2/183 113/608 512.6/218 113/213 113/433 113/178 113/548 113/470 113/621 113/878 113/732 113/558 113/202 513.3/667 513.4/883 520.3/681 520.9/918 521/374 514.1/281 231.1/321 233.1/884 229/264 523.3/859 245.1/276 539.2/301 541.2/287 543.1/831 544.3/655 544.1/335 479.1/310 481/500 487.3/667 484.2/884 485.2/940 477.3/654 481.1/209 498.1/219 493.1/306 502.9/501 505/374 501.2/825 591.1/214 588.9/374 589.1/374 591/500 585/220 585.5/940 579/219 253.2/867 255/500 255/219 661.1/422 659.4/868 655/422 658/500 657/500 739.1/273 747.1/273 753.1/411 781.4/832 535.1/219 537/219 522.1/335 258/500 593.1/374 597.1/320 663.2/929 669.6/883 671/281 287.1/323 289.1/478 288/422 287/374 295.2/835 275.1/452 283/424 277.1/652 284/427 600.1/427 602.4/924 593.3/649 573.4/832 573.2/596 573.1/374 577.1/304 577.1/266 573/374 573/422 571.1/269 570.1/752 569.1/752 570.2/329 570.9/501 569.1/375 570.2/297 571/219 569.2/294 415.2/312 419.1/284 419.2/296 417.1/318 416.2/883 416.2/256 418.2/940 416/422 414/500 407.1/238 407.2/310 407.2/666 407.2/832 407.2/823 936.2/273 952.7/883 951.7/883 937.2/273 955.2/310 929.2/276 640.9/422 640.4/883 641.1/191 629.1/294 628.3/654 632.5/831 635.4/832 637.4/832 639.1/374 631.1/273 631.1/392 636.3/777 637.2/329 638.9/501 639.2/254 637.2/297 635/500 632/217 557/374 567.1/273 565.4/836 562.3/607 562.3/667 565.2/276 563.5/940 399.2/283 434.2/241 435.1/246 435.1/233 399/374 443.2/268 439.1/195 444.2/183 442.1/194 437/422 443/422 442/501 405.1/349 453.1/226 404.2/275 403.1/301 453.3/681 457.1/270 456.1/335 449.1/311 449.1/228 449.1/284 455.4/859 403.2/275 448.1/284 455.1/335 925.3/595 963/500 611.1/221 620.3/936 619.3/935 613.2/273 619.2/885 623.2/253 614.1/310 615.2/328 623.4/832 624.4/832 624.1/253 626.2/300 555.2/286 391.2/832 392.2/924 393.2/260 457.2/232 395.1/321 460.2/925 395/500 397/501 387.2/239 389.1/246 375.1/285 373.2/832 375.2/883 377.2/259 373.1/301 374.1/301 371.1/241 377/179 383/393 373/500 880.7/924 883.2/303 113/654 137/341 171.1/832 163/264 205.2/741 194.1/583 212.1/832 221.2/685 212.1/884 215/500 467.2/279 469.2/278 471.3/832 474.3/614 469.1/335 471.2/282 475.1/277 475.2/832 470.1/335 475.4/885 465.1/304 463.3/331 465/500 464.6/303 464.1/303 580.1/283 580.4/832 581.2/232 299.1/440 305.2/910 306.9/264 313.2/924 323.1/228 323.1/264 321.2/867 316.1/392 321.1/244 325/280 361.2/332 327.1/349 347.2/832 355.1/497 357.1/426 325.2/624 327.3/940 351.2/924 353.1/553 350.2/940 327/404 356/500 353/500 337.2/832 339.1/349 339.2/883 341/500 680.1/273 691.1/252 689.2/940 687.2/387 687.2/411 649.3/595 650.3/595 651.1/294 643.4/883 647.1/273 651.4/884 644.9/501 645/304 652/500 653/219 649/281 609.3/595 609.3/688 897.1/500 896.1/500 895.2/304 609.1/368 608.3/688 547.2/263 549.3/654 550.2/834 553.1/509 547.1/310 552.2/884 549/501 550/678 549.1/219 549/678 362.2/832 361.2/736 691.4/832 694.1/273 695.3/654 693.1/273 692.3/359 693.1/205 425.2/201 425.1/275 694.1/253 421/422 420/500 429/427 421/374 699/217 367.1/232 707.4/832 707.3/341 709.1/273 709.3/316 711.3/595 708.1/387 713.4/832 713.2/359 717.4/884 719/500 725.2/303 723.1/273 722.5/940 729/422 726/500 723.4/595 723.4/634 724.1/273 724.4/595 724.4/634 853.4/884 853.2/335 871.6/832 857.3/595 858.3/595 864.2/303 873.2/277 890.7/940 889.7/940 885.2/277 889/500 833.5/932 823.1/253 829.3/335 828.6/824 789.4/595 790.4/595 796.4/757 797.1/295 808.1/273 807.5/652 791.4/634 791.4/595 805.4/925 812.7/924 811.7/924 813.7/924 790.4/940 524.2/316 529.3/703 531.1/334 528.2/925 533.1/321 532.1/304 529/281 113/744 511.1/430 511.1/380 113/640 113/537 113/819 113/382 511/422 510/500 113/715 519.1/316 516.1/304 519.1/328 516.1/284 515.1/284 233.1/832 227.2/835 231/263 523.2/294 252.2/832 242.2/436 243.2/508 249.1/756 245.1/335 242/500 241/500 253/348 246/424 543.1/255 541.1/281 542.3/688 480.3/766 480.3/688 481.1/229 486.2/939 487/501 482.2/834 483/422 483/374 500.1/275 498.1/303 497.2/317 488.3/667 494.1/486 489.1/321 491.3/621 489/422 489/374 497/427 501.2/241 587.1/317 591.1/320 588.3/681 584.1/304 586.5/940 583.1/304 581.3/249 583.1/284 582.1/281 255.1/454 311.1/265 311.2/612 309.2/880 311.1/276 313/433 313/374 673.2/398 675.4/595 655.2/241 655.1/374 676.4/595 676.3/688 654.5/940 653.5/940 677/374 740.1/273 730.1/294 737.1/252 731.1/923 738.4/924 744.3/688 755.1/885 755.1/253 747/500 782.4/832 786.4/884 785.4/884 787/500 775.1/386 775.1/411 535.5/924 534.5/924 536.2/360 521.3/681 499.2/227 269/314 592/500 257.2/924 259.1/335 267.2/735 263.2/759 595.3/211 596.1/261 597/281 595.1/261 594.3/649 661.3/649 663.1/294 667.1/273 666.4/883 663.2/923 665.1/320 756.1/253 291/264 286/500 287.1/497 287.1/364 285.2/779 295.2/788 297.2/760 271.1/378 271.1/506 272.2/823 275/264 283.1/536 283.3/940 283/374 283/281 278.1/645 277.2/667 277.2/817 282.3/940 281.2/941 607.1/273 597.2/281 603.4/924 598.1/320 599.1/282 601.2/253 605/500 599/219 603/281 573.3/751 569.2/609 569.4/777 415.3/639 405.2/316 926.2/273 946.6/832 945.6/832 622.2/325 612.2/266 613.2/405 640.4/832 639.4/832 639.2/227 563.3/619 565.2/301 397.3/779 462.1/287 399/415 446.1/303 446.1/280 433.2/218 390.1/314 390.1/271 389.2/233 432.2/227 436.1/269 443.3/845 455.2/213 451.2/316 457.1/313 450.2/281 449.1/304 405/415 691.3/358 925.3/609 610.3/609 614.2/924 615.2/609 617/179 623.3/838 555.1/421 395.2/758 430.2/317 395.2/211 430.6/303 430.1/303 381.2/222 383/415 707.1/228 727.2/307 727.2/272 878.6/832 879.6/832 891.5/924 211.1/832 506.3/751 463.1/320 579.4/832 579.3/692 581.2/260 313.1/483 322.2/893 329.1/343 329.1/451 325.2/778 355.1/214 355.3/932 346.2/832 338/415 681.4/758 687.2/325 642.2/279 643.2/258 650.3/609 653.1/356 643.2/400 646.1/273 647.4/832 892.5/924 608.1/249 551.4/832 549.1/180 431.2/227 431.2/290 431.1/303 361.2/708 427.2/292 693.3/338 695.3/609 692.3/316 729.1/295 855.2/319 851.2/335 863.2/303 862.2/303 847.2/346 821.3/319 795.4/758 801.2/268 801.2/319 805.3/343 811.2/254 809.2/255 793.2/272 525.2/893 527.4/834 533.5/924 511.3/832 511.5/924 512.5/924 515.1/304 521.2/277 513.2/305 228.1/341 233.1/301 523.2/262 243.1/296 245/402 541.1/415 541.3/688 500.1/311 497.2/229 491.1/335 493.1/486 503.1/269 505/422 501.1/337 585.2/376 579.1/283 583.2/371 583.2/411 675.1/280 672.1/273 675.1/249 655.2/398 655.3/609 743.2/255 755.2/222 537.2/245 538.3/745 269/365 271.1/593 595.2/282 596.2/294 593.2/893 662.1/295 665.2/325 670.2/250 759.1/300 756.2/276 297/399 293.2/736 272.1/410 273.1/832 601.1/179 633.2/255 637/218 567.1/311 567.2/689 403.2/231 447.2/236 448.1/304 925.7/273 612.3/255 613.2/255 625.2/300 457.2/893 397.1/201 397.2/448 389.2/893 389.1/314 389.1/271 432.2/750 433.1/381 701.4/674 467.1/179 307.2/619 335.2/832 337/484 691.3/315 649.3/609 645.1/273 609.3/609 609.1/240 925.2/273 430.2/651 385.1/226 385.1/201 692.2/300 423.2/234 711.3/609 707.3/336 718.4/884 728.4/758 724.4/609 877.6/832 870.5/924 858.3/609 873.2/347 835.4/675 839.2/208 791.4/609 791.3/315 521.1/380 251.2/832 485.2/197 477.1/326 579.3/781 581.2/290 313.1/341 677.1/288 677.1/221 551.2/294 729.2/273 745.3/342 847.5/924 775.3/349 773.2/208 768.4/674 499.1/273 263.1/362 669.2/250 671.2/378 755.2/276 537.3/745 271.1/415 595.2/406 419.1/326 640.2/242 568.4/776 565.2/651 435.1/269 405.2/293 961.6/935 613.2/924 612.2/273 621.2/325 623.1/179 397.1/188 432.1/275 707.1/273 580.2/306 359/484 555.1/179 369.3/891 726.2/272 724.4/648 869.5/924 891.2/280 828.6/919 828.6/889 825.6/883 540.1/415 540.3/688 505.3/751 578.4/832 309.2/580 309.2/553 653.4/675 534.1/179 521.2/295 499.2/688 256.2/924 671.2/396 742.2/255 595.2/366 595.2/295 597.2/257 562.3/619 433.2/241 433.1/311 337/415 610.1/289 728.2/273 463.1/292 641.2/279 646.4/832 429.2/317 429.2/346 364.2/689 722.4/595 725.4/696 771.2/261 499.1/311 493.1/293 591.4/882 661.1/295 676.4/609 270/484 597.2/201 607.1/249 593.3/924 401.2/278 449.2/281 610.1/221 395.2/423 227.1/341 857.3/609 861.2/303 831.2/317 816.3/335 767.4/675 270/593 595.2/321 295.2/651 605.2/840 431.1/276 727.4/758 309.2/571 321.2/893 329.2/448 345.2/832 691.1/300 431.2/689 729.1/229 772.2/209 497.2/651 293.1/244 293.2/718 593.3/679 413.2/832 627.1/253 556.3/838 449.1/406 432.1/311 375.2/506 362.2/651 723.4/648 790.4/609 499.1/380 741.2/255 271.1/409 662.1/229 293.2/709 443.1/247 447.1/304 611.3/255 187.1/315 609.1/222 431.2/750 497.2/643 577.4/832 253.2/893 539.1/415 661.1/322 291.2/675 283.1/331 445.1/281 700.4/675 466.1/179 328.2/422 645.4/832 725.2/272 227.1/380 579.2/306 291.2/667 561.1/484 723.4/609 721.4/595 533.1/179 675.4/609 285/179 567.1/560 465.1/170 429.2/651 848.2/297 826.6/933 815.3/335 270/415 594.2/295 593.1/243 640.2/280 624.2/300 595.2/229 432.1/381 609.1/289 771.2/208 255.2/924 592.3/924 225.1/244 577.3/704 611.2/273 429.2/643 648.3/641 607.3/903 363.2/689 789.4/609 594.2/322 296.2/689 661.1/229 555.3/837 699.4/674 269/484 275.2/644 626.1/253 847.2/296 625.3/712 227.1/438 431.1/311 361.2/651 465.1/179 591.3/924 294.2/651 722.4/609 269/593 593.1/295 623.2/300 327.2/423 639.2/279 647.3/641 594.2/229 593.1/322 431.1/381 610.1/273 578.3/720 269/415 625.1/253 295.2/689 721.4/609
479.1/219
6-Hydroxymusizin glucoside
Isorhamnetin dihexoside
rutin
B
Cassiaphenone glucoside
293.2/651 593.1/229 609.1/273 577.3/720
-0.4
-0.2
0.0
0.2
0.4
PC1 Fig. 4 UPLC-qTOF-MS (m/z 100–1000) principal component analyses of different Senna samples and commercial Senna product (n=3). The metabolome clusters are located at the distinct positions described by two vectors of principal component 1 (PC1=57 %) and principal component 2 (PC2=32 %). A Score plot of PC1 vs PC2 scores. B Loading plot for PC1
and PC2 with contributing mass peaks and their assignments, with each metabolite denoted by its mass/Rt (sec) pair. It should be noted that ellipses do not denote statistical significance but are rather for better visibility of clusters as discussed
M.A. Farag et al.
and S. alata. This can assist in Senna identification from its closely allied species and help to identify other Senna species with similar potential. All species (see “Plant material”) were analyzed under the same conditions using UPLC-MS. The data were subjected to HCA analysis to assess the heterogeneity between different genotypes. As compared to PCA, HCA allows interpretation of the results in a fairly intuitive graphical way. Cluster analysis of the different Senna samples, according to their UPLC-MS metabolite profile, showed two clear clusters of two and four genotypes (Supp. Fig. 18) referred to as groups 1a and 1b, respectively. Inspection of group 1a shows that the pod samples were clustered together in agreement with PCA results and apart from all leaf samples due to MS signals for benzophenones (cassiaphenone Bglucoside) and tinnevellin glucoside (Fig. 4a). Within group 1a, differences in organ composition are apparently dominant over species composition. S. alata leaf was found to be the most closely related to Indian and Egyptian S. alexandrina, showing the highest levels of rhein, emodin, and aloe-emodin (anthraquinones) and kaempferol 3-O-gentiobioside as revealed from the density of corresponding MS signals in the cluster heat map (data not shown) and suggesting that the latter species might be used as an alternative to S. alexandrina in the treatment of constipation. Kaempferol 3-O-gentiobioside was previously identified as the antidiabetic component in S. alata leaves functioning as an αglucosidase inhibitor [32]. It should be noted that the distant placement of samples for S. didymobotrya, S. bicapsularis, S. corymbosa, and S. sophera leaves in group 1b is due to their low amounts of anthraquinones. S. sophera was the most distant in comparison to all other species, grouped separately due to its enrichment in C-flavonoid glycosides, i.e., occidentalin A, B, and C.
experimental results, and interesting and meaningful differences between the various plant organs, species, and detection methods were identified. While the NMR approach allows for an easy quantification of flavonoids and anthraquinones contained in Senna extracts as major component, the high sensitivity of MS was more suitable for metabolites with low abundance. PCA consistently grouped and separated samples, independent of whether NMR chemical shifts or rt/mass signal pairs (UPLC-MS) were used as data basis, suggesting the validity of both methods for the classification of Senna official drugs and allied species. UPLC-MS or 1H-NMR analyses of crude Senna methanol extract were found useful in predicting the botanical origin of unknown extract. Analysis of data derived from both techniques provide scientific justification for the use of Egyptian and Indian S. alexandrina plants interchangeably and suggest that pod extracts are more enriched in the purgative active ingredient “sennosides” than leaves. Both techniques offered insight into the possible use of chemical criteria such as the ratio of ω-3 and ω-6 fatty acids to other fatty acids or the ratio of flavonoids to cassiaphenones, to differentiate between samples of different origins. One noteworthy species of this study is S. alata that showed a very similar chemical profile to that of S. alexandrina, posing it as a substitute candidate for more extensive biological studies to evaluate its laxative effect. Acknowledgments Dr. Mohamed A. Farag thanks the Alexander von Humboldt-Foundation, Germany, for financial support. We are grateful to Dr. Teresa Labib, Orman Herbarium, Cairo University, Cairo, Egypt, for providing Senna samples. We also thank Dr. Christoph Böttcher for assistance with the UPLC-MS, and we are grateful to Dr. Steffen Neumann and Dr. Tilo Lübken for providing R scripts for NMR and MS data analysis.
References Conclusions In this study, we present a novel comparative metabolite profiling and fingerprinting approach via UPLC-MS and 1D, 2D-NMR techniques for Senna drug authentication, quality control analysis, and chemotaxonomy. Both techniques offered insight into the possible use of chemical criteria such as the ratio of ω-3 and ω-6 fatty acids to other fatty acids or the ratio of flavonoids to cassiaphenones, to differentiate between samples of different origins and/or different organ types. To the best of our knowledge, this study provides the first comparative metabolomic approach to reveal compositional differences among official Senna drugs and its closely allied species and to confirm the close relation of C. acutifolia and C. angustifolia, both currently recognized as S. alexandrina. NMR and MS techniques coupled with multivariate data analyses were used and compared to obtain the
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