Comprehensive Chemical Study on Different Organs of Cultivated And

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Chinese Journal of Natural Medicines 2021, 19(5): 391-400 doi: 10.1016/S1875-5364(21)60038-9

•Research article•

Comprehensive chemical study on different organs of cultivated and wild Sarcandra glabra using ultra-high performance liquid chromatography time-of-flight mass spectrometry (UHPLC-TOF-MS)

WANG Cai-Yun1Δ, LU Jing-Guang1Δ, CHEN Da-Xin2, WANG Jing-Rong1, CHE Kai-Si1, ZHONG Ming3, ZHANG Wei1*, JIANG Zhi-Hong1*

1 State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China; 2 Fujian Key Laboratory of Integrative Medicine on Geriatric, Academy of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; 3 Guangxi Key Laboratory of Traditional Chinese Medicine Quality Standards, Guangxi Institute of Chinese Medicine and Phar- maceutical Science, Nanning 530022, China Available online 20 May, 2021

[ABSTRACT] To illuminate the similarities and differences between wild and cultivated Sarcandra glabra (S. glabra), we performed a comprehensively study on 26 batches of cultivated S. glabra and 2 batches of wild S. glabra. Chemical constituents and distribution characteristics of roots, stems and leaves in both wild and cultivated S. glabra were investigated through UHPLC-TOF-MS method. The result revealed that there were significant differences between roots, stems and leaves in S. glabra. And the chemical contents in the root part were less or even absence than those in leaf and stem, which suggested the root organ could be excluded as medicine. Meanwhile, the chemical contents of stems and leaves in cultivated S. glabra was sightly higher than that of wild samples. Therefore, cultivated S. glabra may have a high potential for substitution of wild S. glabra without affecting its pharmaceutical properties. In summary, our study could provide important information to the molecular basis for quality control of S. glabra. [KEY WORDS] S. glabra; UHPLC-TOF-MS; Root; Stem; Leaf [CLC Number] R917 [Document code] A [Article ID] 2095-6975(2021)05-0391-10

ism, bone fractures and even bruises since ancient history [1, 2]. Introduction S. glabra mainly contains caffeoyl derivatives, flavonoids, [3-6] Sarcandra glabra (S. glabra) is an evergreen shrub nor- coumarins and sesquiterpenoids etc. . These types of com- mally found in south China, Japan and southeastern Asia, ponents have been reported as the main active constituents which belongs to the Chloranthaceae family. The whole plant which are associated with S. glabra’ biological effects such as anti-oxidant, anti-tumor, anti-infectious and anti-inflam- of S. glabra has been used in the traditional Chinese medicin- matory [7-12]. al preparations for treating various diseases including cancer, The natural resources of S. glabra have greatly de- pneumonia, appendicitis, gastritis enteritis, diarrhea, rheumat- creased in these recent years. For a better use of this valuable resource, a large number of S. glabra have been cultivated. In [Received on] 17-Apr.-2020 order to improve rational use of S. glabra in clinical studies, [Research funding] This work was supported by the Science and Technology Development Fund, Macau SAR (No. 0023/2019/ it is critical to understand the chemical difference between AKP) and Guangxi Science and Technology Department Fund (No. cultivated and wild S. glabra. At present, the quality control AD17195002). of S. glabra is mainly determined according to the Chinese [*Corresponding author] E-mail: [email protected] (ZHANG Pharmacopoeia, in which only isofraxidin and rosmarinic Wei); [email protected] (JIANG Zhi-Hong) ∆These authors contributed equally to this work. acid are determined by HPLC-UV detection, and this analyt-

These authors have no conflict of interest to declare. ical method is insufficient for a comprehensive quality con-

– 391 – WANG Cai-Yun, et al. / Chin J Nat Med, 2021, 19(5): 391-400 trol of S. glabra and its preparations [1]. Several high-perform- Quality control (QC) sample was prepared by mixing every

ance liquid chromatography and capillary electrophoresis batch of samples. methods have been developed for the analysis of S. glabra Preparation of standard and sample solutions and its medicinal preparations [13]. For example, LI et al. [6] Stock solutions of 5-CQA (4), 3-CQA (5), 4-CQA (6), developed a rapid analytical method based on a UHPLC sys- neoastilbin (27), astilbin (30), 3, 4-diCQA (32), isoastilbin tem coupled with a linear ion trap high-resolution mass spec- (33), 3, 5-diCQA (34), neoisoastilbin (38), 4, 5-diCQA (43) trometer for qualitative identification of the constituents of S. were prepared in 50% (V/V) methanol at the concentration of glabra and its related preparations. And then, a high-perform- 100 μg·mL−1. The stock solution was stored in a refrigerator ance liquid chromatography-electrospray ionization-tandem at 4 °C for analysis. mass spectrometry (HPLC-ESI-MS/MS) method was further The powdered sample of S. glabra (0.1g) was accurately established to quantify 17 main compounds isolated from S. weighed and placed into a 50 mL centrifugal tube. Then glabra and its preparations [14]. However, there is no compre- 25.00 mL of 50% methanol was accurately added. The total hensive research that evaluate the similarity and identify the weight of the tube with the solution was weighted. The mix- differences between cultivated and wild S. glabra, although a ture was sonicated for 30 min with occasional shakings at few reports of the analysis of chemical constituents of S. room temperature and was centrifuged at 1800 g for 5 min glabra have already been published. This becomes the major subsequently. The weight of the tube with the sample solu- obstacle in clinical usage of S. glabra. tion was weighted again to ensure the lossless of the solvent. In this study, a comprehensive and systematically analys- The supernatant was filtered through a 0.22 μm PTFE filter to is of the chemical constituents was studied in both wild and afford sample solution for analysis. Quality control (QC) cultivated S. glabra samples using UHPLC-TOF-MS. sample was prepared following the same procedure. Moreover, the distribution characteristics of chemical com- UHPLC-TOF-MS conditions ponents was also described for the roots, stems and leaves. The liquid chromatography was assembled by an Agi- The aim of this study was to illuminate the similarities and lent 1290 infinity system consisting of binary pumps with in- differences in complex fingerprints between wild and cultiv- tegrated vacuum degasser (G4220A), thermostat (G1330B), ated S. glabra samples. This is very important for authoriza- standard autosampler (Model G4226A) and thermo statted column compartment (Model G1316C). The mass spectro- tion and quality control of S. glabra. meter was an Agilent 6230 TOF mass spectrometer equipped Materials and Methods with Agilent Jet Stream (AJS) source. Data acquisition was

Chemicals carried out by Agilent Mass hunter® workstation B.05.00 software on a DELL computer (Agilent, Singapore). HPLC grade acetonitrile and methanol were purchased The chromatographic separations were achieved on an from Merck (Darmstadt, Germany). HPLC grade formic acid Agilent Extend C RRHD column (1.8 μm, 100 mm × 2.1 was purchased from Fluka (Buchs, Switzerland). Water used 18 mm I.D., Agilent). A gradient program was used with mobile in this study was deionized and further purified by Milli-Q phase consisting of solvent A (0.1% (V/V) formic acid in wa- Plus system (Millipore, Inc., MA, USA) at 18.2 MΩ cm. Oth- ter) and solvent B (0.1% (V/V) formic acid in acetonitrile) as er reagents used were of analytical grade. Marker com- follows: 0−12 min, 10%−20% B; 12−20 min, 20%−95% B; pounds of 5-O-caffeoylquinic acid (5-CQA), 3-O-caf- 20−23 min, 95% B; 23−26 min, 10% B. The flow rate was feoylquinic acid (3-CQA), 4-O-caffeoylquinic acid (4-CQA), 0.3 mL·min−1. The injection volume was 2 μL and the column 3, 4-O-dicaffeoylquinic acid (3,4-diCQA), 3, 5-O-dicaf- temperature was maintained at 30 °C. feoylquinic acid (3, 5-diCQA) and 4, 5-O-dicaffeoylquinic The mass spectrometer was operated in negative ion acid (4,5-diCQA) were purchased from Chengdu MUST Bio- mode with mass scanning range of m/z 100 to m/z 1700. The Technology Co., Ltd. (Chengdu, China). Neoastilbin, astilbin, optimized MS conditions were set as the followings: drying neoisoastilbin and isoastilbin were bought from Chengdu gas temperature, 325 °C; drying gas flow, 9.0 L·min−1; nebuli-

Alfa Biotechnology Co., Ltd. (Chengdu, China). zer, 35 psi; sheath gas temperature, 325 °C; sheath gas flow, Plant materials 11.0 L·min−1; fragmentor, 150 V; skimmer, 65 V; and octo-

Twenty-six batches of cultivated S. glabra (9 seeding pole RF, 500 V; VCap., 3500 V; nozzle, 1500 V. Agilent TOF samples and 17 sprouting samples) from different proven- reference solution was applied for calibration of mass drift by ance places of China were collected for the experiment. Two using the reference mass ions of m/z 112.9855 and m/z

batches of wild S. glabra were collected at Youxi country, 966.0007. Sanming city, Fujian Province. All the plant materials collec- Results and Discussion ted were taxonomically identified and provided by Prof. JI- ANG Zhi-Hong (Table 1). Each batch of sample was firstly Optimization of sample preparation separated into different parts, i.e., leaves, stems and roots. In order to achieve improved separations and higher ex- Then the samples of each part were cut into smaller pieces, traction efficiency, the extraction conditions (solvents and ex- grounded into powder and passed through a 50-mesh sieve. traction times) for sample solutions were optimized carefully.

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Table 1 Twenty-eight batches of S. glabra samples from China

Sample Code Origin of sample Collection date

S1 Minhou country, Fuzhou city, Fujian Province 03/2012 S2 Qingliu country, Sanming city, Fujian Province 03/2012 S3 Sanyuan district, Sanming city, Fujian Province 03/2012 S4 Sanming city, Fujian Province 03/2012 S5 Sanyuan district, Sanming city, Fujian Province 03/2012 S6 Mingxi country, Sanming city, Fujian Province 03/2012 S7 Liancheng country, Longyan city, Fujian Province 03/2012 S8 Wuyishan city, Fujian Province 03/2012

Sprouts a,b S9 Sanyuan district, Sanming city, Fujian Province 03/2012 S10 Sanyuan district, Sanming city, Fujian Province 03/2012 S11 Anxi country, Quanzhou city, Fujian Province 03/2012 S12 Yongchun country, Quanzhou city, Fujian Province 03/2012

S13 Yongtai country, Fuzhou city, Fujian Province 03/2012 S14 Sanyuan district, Sanming city, Fujian Province 03/2012 S15 Sanyuan district, Sanming city, Fujian Province 03/2012 S16 Huaan country, Zhangzhou city, Fujian Province 03/2012 S17 Pinghe country, Zhangzhou city, Fujian Province 03/2012

S18 Jinhua city, Zhejiang Province 03/2012 S19 Nanchang city, Jiangxi Province 03/2012 S20 Quzhou country, Zhejiang Province 03/2012 S21 Ganzhou city, Jiangxi Province 03/2012

Seeds a,b S22 Xinyu city, Jiangxi Province 03/2012 S23 Heyuan city, Guangdong Province 03/2012 S24 Donglan country, Hechi city, Guangxi Province 03/2012 S25 Meizhou city, Guangdong Province 03/2012 S26 Jiujiang city, Jiangxi Province 03/2012 S27 Youxi country, Sanming city, Fujian Province 09/2012 wild S28 Youxi country, Sanming city, Fujian Provincee 04/2012 a the growing period of all samples (seeds and sprouts) was three years b the growing region of all samples was Sanyuan, Sanming, Fujian Province

The methanol concentration of extraction solvents (30%, gorithm in Agilent Mass hunter software. To identify the 50%, 70% and 100%) were firstly examined by comparing compounds from S. glabra samples, a personal database was the number and abundance of peaks in total ion chromato- created based on the compounds recorded in Dictionary of grams (TIC) of each extraction solvent. As a result, 50% Natural Products (Chapman & Hall/CRC Press, Boca Raton, methanol was finally adapted because of its high extraction FL, USA) and literatures [13, 15-17]. efficiency. Moreover, the amount of the most abundant ten In this study, the negative mode was primarily employed, components extracted from each extraction showed that one- since most of the compounds showed higher response in neg-

time extraction was adequate for the extraction. ative mode as opposed to the positive mode. Compounds Identification of chemical constituents in S. glabra based on were identified by comparing their accurate mass (typically UHPLC-TOF-MS analysis [M − H]– and [M + HCOO]– under negative scan mode of This comprehensive chemical profiling of the com- UHPLC-TOF-MS with theoretical value obtained from per- pounds was achieved by employing “Find by Formula ” al- sonal database. Matching scores (100 is perfect) of the identi-

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Table 2 The identification results of S. glabra by UHPLC-TOF-MS Identified Theoretical Measured Diff No. tR/min Name Formula Score ion mass (m/z) mass (m/z) (ppm) − 1 0.850 [M − H] quinic acid C7H12O6 191.0561 191.0559 1.08 99.69

− 2 1.157 [M − H] fumaric acid C4H4O4 115.0037 115.0038 −0.82 87.66

− 3 2.168 [M − H] protocatechuic acid C7H6O4 153.0193 153.0196 −1.75 98.58

c − 4 2.210 [M − H] 5-CQA C16H18O9 353.0878 353.0888 −2.90 96.25

c − 5 3.271 [M − H] 3-CQA C16H18O9 353.0878 353.0892 −3.83 94.60

c − 6 3.652 [M − H] 4-CQA C16H18O9 353.0878 353.0894 −4.47 92.86

− 7 3.661 [M − H] caffeic acid C9H8O4 179.0350 179.0355 −2.81 97.84

− 8 4.025 [M + HCOO] isofraxidin-7-O-β−D-glucoside C17H20O10 429.1038 429.1049 −2.56 96.66

− 9 4.025 [M − H] fraxidin C11H10O5 221.0455 221.0463 −3.54 97.03

− 10 4.058 [M − H] fraxin C16H18O10 369.0827 369.0834 −1.80 98.22

− 11 4.216 [M − H] isomer of 7 C9H8O4 179.0350 179.0355 −3.07 97.59

− 12 4.233 [M − H] isoliquiritigenin 7-O-β−D-glucoside C21H24O10 435.1297 435.1301 −1.07 98.96

− 13 4.887 [M − H] drovomifoliol-O-β−D-glucopyranoside C20H32O10 431.1923 431.1926 −0.70 82.25

− 14 4.987 [M − H] 4-dHCQA C16H16O8 335.0772 335.0781 −2.53 82.65

− 15 5.045 [M − H] dihydrovomifoliol-O-β−D-glucopyranoside C20H34O10 433.2079 433.2083 −0.85 97.87 5,7,3′,4′-tetrahydroxy-dihyflavanones-3-rhamnosyl/ − 16 5.120 [M − H] 3,5,7,3′,5′-pentahydroxyflavanonol-3-O-α−L- C21H22O11 449.1089 449.1093 −0.30 96.95 rhamnopyranoside − 17 5.517 [M − H] 5-dHCQA C16H16O8 335.0772 335.0783 −3.20 96.56

− 18 5.750 [M − H] isomer of 16 C21H22O11 449.1089 449.1089 0.08 99.39

− 19 6.065 [M − H] methyl-5-O−caffeoylquinate C17H20O9 367.1035 367.1047 −3.48 78.71

− 20 6.545 [M − H] 6,7,8-trihydroxycoumarin-7-O-α-L−rhamnopyranoside C15H16O9 339.0722 339.0737 −4.48 75.93

− 21 7.366 [M − H] (2R/2S)-naringenin-6-C−β−D-glucopyranoside C21H22O10 433.1140 433.1146 −1.37 99.03

− 22 7.548 [M − H] sarcaglaboside H C21H32O9 427.1974 427.1972 0.38 47.56

− (2R/2S)-naringenin-6-C-β-D-glu-copyranosyl- 23 7.764 [M − H] C26H30O14 565.1563 565.1568 −0.98 99.00 (6→1)-apiose − 24 7.872 [M − H] isomer of 21 C21H22O10 433.1140 433.1146 −1.37 99.01

− 25 8.328 [M − H] isomer of 23 C26H30O14 565.1563 565.1568 −0.94 97.14

− 26 8.452 [M − H] isofraxidin C11H10O5 221.0455 221.0461 −2.40 97.10

c − 27 9.397 [M − H] neoastilbin C21H22O11 449.1089 449.1096 −1.41 98.60

− 28 9.579 [M + HCOO] sesquiterpene lactone C21H28O9 469.1715 469.1719 −0.77 86.63

− 29 9.770 [M−H] quercetin-3-O-β-D-glucuronide C21H18O13 477.0675 477.0682 −1.61 98.77

c − 30 10.052 [M − H] Astilbin C21H22O11 449.1089 449.1100 −2.44 97.24

− 31 10.947 [M − H] rosmarinic acid-4-O-β-D-glucoside C24H26O13 521.1301 521.1310 −1.76 98.31

c − 32 11.594 [M − H] 3,4-diCQA C25H24O12 515.1195 515.1201 −0.60 85.92

c − 33 11.710 [M − H] Isoastilbin C21H22O11 449.1089 449.1092 −0.65 93.26

c − 34 12.033 [M − H] 3,5-diCQA C25H24O12 515.1195 515.1191 0.85 47.24

− 35 12.041 [M − H] kaempferol 3-O-β-D-glucuronide C21H18O12 461.0725 461.0735 −2.05 97.49

− 36 12.050 [M − H] quercetin-3-O-β-D-rhamnoside C21H20O11 447.0933 447.0940 −1.54 79.73 − 37 12.075 [M − H] glabraoside A, B, C C30H30O13 597.1614 597.1617 −0.56 95.14 c − 38 12.083 [M − H] neoisoastilbin C21H22O11 449.1089 449.1095 −1.15 98.98

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Continued Identified Theoretical Measured Diff No. tR/min Name Formula Score ion mass (m/z) mass (m/z) (ppm) − 39 12.456 [M − H] isomer of 37 C30H30O13 597.1614 597.1610 0.55 95.17

− 40 12.555 [M + HCOO] ethyl rosmarinate C20H20O8 433.1140 433.1141 −0.15 80.64

− 41 12.729 [M − H] isomer of 37 C30H30O13 597.1614 597.1612 0.31 99.61

− 42 12.953 [M − H] rosmarinic acid C18H16O8 359.0772 359.0785 −3.62 94.63

c − 43 13.625 [M − H] 4,5-diCQA C25H24O12 515.1195 515.1191 0.71 98.97

− 44 13.666 [M − H] isomer of 42 C18H16O8 359.0772 359.0783 −3.04 96.23

− 8,9-Dihydroxy-4(15),7(11)-eudesmadien-12,8- 45 13.915 [M − H] C15H20O4 263.1289 263.1296 −2.54 97.22 olide;(8βOH,9α)-form/(-)-istanbulin A − 46 13.931 [M − H] (-)-epiafzelechin 7-O-β-D-glucopyranoside C21H24O10 435.1297 435.1305 −1.83 98.46

− 47 13.940 [M + HCOO] sarcaglaboside C/sarcaglaboside A C21H30O8 455.1923 455.1934 −2.44 85.80

− 48 14.139 [M − H] sesquiterpene lactone C21H28O9 423.1661 423.1662 −0.37 98.43

− 49 14.537 [M − H] N-trans-feruloyltyramine C18H19NO4 312.1241 312.1248 −2.08 93.96

− 50 14.636 [M + HCOO] 5-hydroxy-7,4′-dimethoxy-isoflavanones C17H14O5 343.0823 343.0837 −4.07 93.64

− 51 14.727 [M + HCOO] isomer of 47 C21H30O8 455.1923 455.1930 −1.66 94.11

− 52 14.736 [M − H] isomer of 45 C15H20O4 263.1289 263.1293 −1.62 96.11

− 53 14.785 [M − H] methyl rosmarinic acid C19H18O8 373.0929 373.0937 −2.13 94.98

− 54 15.448 [M − H] 4,4′-biisofraxidin C22H18O10 441.0827 441.0832 −1.12 92.27

− 55 15.681 [M − H] scoparone C11H10O4 205.0506 205.0508 −0.72 72.64

− 56 15.788 [M − H] 3,3′-biisofraxidin C22H18O10 441.0827 441.0841 −3.13 95.44

− 57 15.938 [M − H] isomer of 52 C15H20O4 263.1289 263.1293 −1.71 85.25

− 58 16.501 [M − H] sarcanolide B C36H40O10 631.2549 631.2549 −0.07 88.24 c Compared with the commercial reference standards. fied compounds were calculated based on ion mass error, iso- sample prepared in all root, stem and leaf parts of the samples tope space and isotope abundances. A summary of these iden- using the approach described above. The total ion chromato- tified compounds profile was presented in Table 2 which in- graphy (TIC) profile of the whole plant of Sarcandra glabra cluded the retention times, molecular formulas, theoretical was shown in Fig. 1. Among them, 19 phenolic acids (com- masses (m/z), measured masses (m/z) and matching scores of pounds 1−7, 11, 14, 17, 19, 31, 32, 34, 40−44, 53) [19], 21 each sample (with typical mass errors less than 5 ppm) [18]. flavonoids (compounds 12−13, 15−16, 18, 21, 23−25, 27, Ten compounds of 5-CQA (4), 3-CQA (5), 4-CQA (6), 29−30, 33, 35−39, 41, 46, 50), 6 coumarins (compounds neoastilbin (27), astilbin (30), 3, 4-diCQA (32), isoastilbin 8−10, 20, 26, 55), 11 terpenoids (compounds 22, 28, 45, (33), 3, 5-diCQA (34), neoisoastilbin (38), 4, 5-diCQA (43) 47−48, 51−52, 54, 56−58) and N-trans-feruloyltyramine (49) were used for further confirmation of the identification res- were identified in the QC sample. Most of them were charac-

ults. This was performed by comparing their retention time terized for the first time in cultivated Sarcandra glabra. and mass spectra data with those of reference compounds. Distribution characteristics of chemical constituents in roots, The results of this confirmation had shown that the feature of stems and leaves of S. glabra TOF data not only allowed the detection of known target According to the results (Supplementary Table S1-S3), compounds, but also allowed retrospective searching for compounds such as quinic acid (1), 5-caffeoylquinic acid (4), compounds that could be present in the samples. After identi- 3-caffeoylquinic acid (5), caffeic acid (7), (2R/2S)-naringenin- fication or classification of the unknown compounds, abso- 6-C-β-D-glucopyranoside (21), quercetin-3-O-β-D-glucuro- lute peak area of each characteristic peak was used to obtain a nide (29), astilbin (30), rosmarinic acid-4-O-β-D-glucoside data matrix consisting of 28 objects and 58 variables, which (31), neoisoastilbin (38) and the isomer of rosmarinic acid could semi-quantitatively express the chemical properties in (44) were found to have a good level of absolute peak areas the chromatographic profile of samples. in the leaf of S. glabra. These compounds were reported to be As shown in Table 2, total 58 compounds were unam- effective in cancer treatment, against virus infections and biguously identified or tentatively characterized from the QC even helped to improve patients’ immune systems [20-23].

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×106 −ESI TIC Scan Frag = 150.0 V ZJF-QC3-4-r002. d 2.2 43 + 44 1 5 2.0 1.8 1 1.6 1.4 31 2 30 1.2 1.0 6 + 7 0.8 34 + 35 + 36 + 45 + 46 + 47 8 + 9 + 10 54 0.6 14 + 1517 29 37 + 38 3 + 4 11 + 12 23 51 + 52 0.4 18 21 24 27 42 53 57 13 1920 26 32 39 48 58 0.2 33 0 16 22 25 28 40 41 4950 55 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 t/min Fig. 1 Total Ion Chromatogram (TIC) profile of S. glabra samples in negative ion modes

In the stem organ of S. glabra, a high absolute peak area of absolute peak areas and some samples were even found to was found in compounds 1, 4, 5, 7, 17, 21, 26, 30, 31, 44. have some compounds absence in the root organ. However, compounds such as 13, 20, 42, 47, 51, 54 were In order to evaluate the data of those three organs from found to have a low level of absolute peak areas. these samples, principal component analysis (PCA) was per- In the root organ of S. glabra, its chemical composition formed using the Multibase 2014 software applied within a was very similar to the leaf and stem organs. A high absolute Microsoft Excel 2010® environment (Numerical Dynamic, ht- peak area was found on compounds 1, 5, 8, 12, 17, 26, 28, 30, tp://www.numericaldynamics.com/index.html). The results of 31, 44. 17 compounds out of 58 were found to have low level principal component analysis were presented as plots (PC1

A stem 8.205

root leaf

−7.09 11.85 PC2 (19.4%) −3.90 PC1 (49.6%)

B 43 0.2708 34 32 14 52 5 41 39 10 −0.151 0.1810 16

PC2 (19.4%) −0.156 PC1 (49.6%) Fig. 2 (A) The PCA score plot. X-axis represents the first principal component which explains 49.6% of the total variance; Y-axis means the second principal component which explains 19.4% of the total variance. (B) The corresponding loading plot of the top 10 contributors of S. glabra samples

– 396 – WANG Cai-Yun, et al. / Chin J Nat Med, 2021, 19(5): 391-400 and PC2) with two axes described in Fig. 2A and Fig. 2B. By Similarity between samples from different origins applying multivariate statistical analysis with principle com- Fig. 4−Fig. 6 show the compositional differences in root, ponent analysis (PCA), the chromatographic fingerprints of stem and leaf from different origins of S. glabra. The ten three parts of 26 batches cultivated and 2 batches wild S. components with the highest abundance in various parts of S. glabra were further analyzed. As shown in Fig. 2, PCA was glabra were selected as indicators to compare samples from composed of two plots, score and loading plot, in which they different origins. The selected compounds except for com- were complementary and could be superimposed. The score ponents 8, 26 and 28 from each tissue consisted of phenolics plot was a summary of the relationships between the samples and flavonoids. The components 8 and 28 were detected only (Fig. 2A). The first two principle components (PCs) are ac- in very small amounts from the stem and leaf. counted for 69.0% of explained variance (PC1 = 49.6%, As shown in Fig. 4−Fig. 6, the cultivated S. glabra stems PC2 =19.4%). The score plot in Fig. 2A showed a clear sep- and leaves had higher abundance of the 10 contributors than aration of roots, stems and leaves of S. glabra. Visual exam- those of wild samples except for component 1 from S. glabra ination of the plot reveals that the chemical profile of indi- stems. The cultivated S. glabra roots only had higher abund- vidual samples of each part was quite similar as they gathered ance of components 5, 17 and 26 than wild roots. The 26 cul- to form large cluster. The loading plot of PCA represented an tivated batches of S. glabra were all prepared in two forms, overview relationship between the variables (58 chemical both sprouts and seeds. They were all cultivated under same components determined) used in the analysis, which was also conditions and growing period. And the results show that a mean to interpret the patterns seen in the score plot. Based there is no significant difference between sprouts and seeds. on the loading plot, chemical components that were influen- In addition, cosine similarity and Pearson product-mo- tial on the classification model can be determined by further ment correlation coefficient (P-coefficient) were used to cal- study. Totally 10 components were also identified to be con- culate the similarities between the 28 samples by comparing tributors for the classification of different parts according to the 58 compounds as variables (Table 3). In this study, these ® the criterion set by PCA software (Fig. 3). coefficients were determined using the Microsoft Excel 2010

8000000.0 Root 800000.0 Stem 6000000.0 600000.0 Leaf

400000.0 4000000.0

200000.0 Absolute peak area 2000000.0 0 10 14 16 32 34 39 41 43 52

0 5 10 14 16 32 34 39 41 43 52 Fig. 3 Comparison on the absolute peak area of 10 contributors among root, stem and leaf of S. glabra

3000000 Sprout

Seed

Wild 2000000

absolute peak area 1000000

0 1 5 8 12 17 26 28 30 31 44 Fig. 4 Comparison on the absolute peak area of the top 10 contributors in root among different sources

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1.0×1007 Sprout

Seed 8000000.0 Wild

6000000.0

4000000.0 Absolute peak area

2000000.0

0 1 4 5 7 17 21 26 30 31 44 Fig. 5 Comparison on the absolute peak area of the top 10 contributors in stem among different sources

1.5×1007 Sprout

Seed

Wild 1.0×1007

5000000.0 Absolute peak area

0 1 4 5 7 21 29 30 31 38 44 Fig. 6 Comparison on the absolute peak area of the top 10 contributors in leaf among different sources

software. With the calculated results, the similarities in the taken up less than 10% of the whole plant of S. glabra and

three organs of those identified compounds between all the will not affect the pharmaceutical effects of the herb itself. samples were determined. The values of the results between Substitutability of the cultivated S. glabra the wild and cultivated samples were slightly different. The With the results from the comprehensive study, the sub- similarity results of the wild samples were all above 0.8. And stitutability of the cultivated S. glabra was also studied and the similarity results of the cultivated samples were mostly discussed. The chemical contents in the samples were found above 0.9. to be very similar between the wild and cultivated samples With these data and the comprehensive analysis of those and among those cultivated samples themselves. The chemic- 28 batches, there were no significant differences found al quantities were also found similar between all the cultiv- between the samples cultivated from both seeds and sprouts ated samples and slightly different between wild and cultiv- and no significant differences found between the wild and ated samples. The chemical composition content was shown

cultivated samples. slightly higher in cultivated S. glabra than those of wild Aboveground organs as medicine samples in both stems and leaves. This is hard evidence for From the previous discussions, the main bioactive con- the substitutability of the cultivated S. glabra on the wild S.

stituents were generally located in the leaf and stem parts of glabra in the future clinical application. S. glabra. In the leaf and stem part of S. glabra, most of the Conclusions bioactive constituents with the most abundance were found. In the root part of the herb, the chemical quantities were a lot In summary, a comprehensive analytical study was per- less than those in leaf and stem part of the herb and some formed on 26 batches of cultivated S. glabra and 2 batches of chemicals were found even absences. This result suggested wild S. glabra. A total number of 58 compounds including that there was no significant influence if the root part was ex- phenolic acids, flavonoids, coumarins and terpenoids of three cluded from the usage as medicine. As the root part only tissues (root, stem and leaf) of S. glabra were profiled via a

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Table 3 Similarity among twenty-eight batches of S. glabra samples from China

Leaf organ Stem organ Root organ Sample Code P-coefficient Cosine similarity P-coefficient Cosine similarity P-coefficient Cosine similarity S1 0.945 0.955 0.970 0.975 0.906 0.926 S2 0.996 0.996 0.999 0.999 0.940 0.947 S3 0.972 0.976 0.998 0.998 0.981 0.986 S4 0.995 0.996 0.997 0.998 0.957 0.965 S5 0.973 0.978 0.997 0.997 0.936 0.952 S6 0.891 0.913 0.998 0.998 0.969 0.975 S7 0.965 0.972 0.988 0.990 0.959 0.968 S8 0.984 0.987 0.999 0.999 0.954 0.964

Sprouts S9 0.985 0.988 0.995 0.995 0.990 0.991 S10 0.955 0.963 0.994 0.995 0.910 0.932 S11 0.981 0.985 0.999 0.999 0.967 0.970

S12 0.931 0.939 0.991 0.993 0.947 0.959 S13 0.991 0.993 0.998 0.999 0.953 0.964 S14 0.992 0.993 0.998 0.999 0.962 0.971 S15 0.905 0.916 0.990 0.990 0.976 0.980 S16 0.994 0.995 0.999 0.999 0.973 0.980 S17 0.954 0.963 0.997 0.998 0.965 0.972 S18 0.991 0.993 0.994 0.995 0.983 0.987 S19 0.957 0.966 0.997 0.998 0.971 0.976 S20 0.988 0.990 0.993 0.993 0.964 0.972 S21 0.977 0.982 0.997 0.998 0.952 0.963 Seeds S22 0.998 0.998 0.994 0.995 0.946 0.959 S23 0.986 0.989 0.994 0.995 0.961 0.971 S24 0.993 0.994 0.998 0.998 0.995 0.996 S25 0.998 0.998 0.997 0.998 0.951 0.962 S26 0.991 0.992 0.994 0.994 0.951 0.956 S27 0.810 0.870 0.861 0.884 0.801 0.833 wild S28 0.827 0.889 0.921 0.933 0.847 0.886

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Cite this article as: WANG Cai-Yun, LU Jing-Guang, CHEN Da-Xin, WANG Jing-Rong, CHE Kai-Si, ZHONG Ming, ZHANG Wei, JIANG Zhi-Hong. Comprehensive chemical study on different organs of cultivated and wild Sarcandra glabra using ultra-high performance liquid chromatography time-of-flight mass spectrometry (UHPLC-TOF-MS) [J]. Chin J Nat Med, 2021, 19(5): 391-400.

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