DOI: 10.1002/jssc.201700473 RESEARCH ARTICLE Comparative analysis of 15 chemical constituents in Scutellaria baicalensis stem-leaf from different regions in China by ultra-high performance liquid chromatography with triple quadrupole tandem mass spectrometry Baofei Yan Weijie Xu Shulan Su Shaoqing Zhu Zhenhua Zhu Huiting Zeng Ming Zhao Dawei Qian Jin-ao Duan Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, and Key Laboratory of Chinese Medicinal Resources Recycling Utilization, State Administration of Traditional Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, China Correspondence Professor Shulan Su, Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu Province, China. Email: sushulan1974@163.com Additional corresponding author Professor Jin-ao Duan Email: duanja@163.com Scutellaria baicalensis is a traditional Chinese herbal medicine containing multiple components, which has been extensively used in clinics to treat epidemic febrile disease and hyperactivity cough. To get a deeper understanding about Scutellaria baicalensis stem-leaf resources, we analyzed 15 chemical constituents in 35 batches of Scutellaria baicalensis stem-leaf from eight regions in China. A rapid, simple, and sensitive method using ultra-high performance liquid chromatography coupled with triple quadrupole electrospray tandem mass spectrometry has been developed for the first time to simultaneously determine 15 chemical constituents (including phenolic acids and flavonoids) in Scutellaria baicalensis stem-leaf. Sufficient separation of 15 target constituents was achieved on a Waters Acquity UPLC BEH C 18 (2.1 mm 100 mm, 1.7 μm) column within 14 min under the optimized chromatographic conditions. The established method was validated and showed good linearity, precision, repeatability, stability, and recovery and was successfully applied for the simultaneous determination of the 15 chemical constituents in these samples. Hierarchical clustering analysis and principal components analysis were performed to estimate and classify these samples based on the contents of the 15 chemical constituents. This study provided theoretical basis and scientific evidence for the development and utilization of Scutellaria baicalensis stem-leaf resources. KEYWORDS hierarchical clustering analysis, principal components analysis, regional differences, traditional Chinese medicine, ultra-high performance liquid chromatography 1 INTRODUCTION Abbreviations: HCA, hierarchical clustering analysis; PCA, principal components analysis; TCM, traditional Chinese medicine; TQ-MS/MS, triple quadrupole mass spectrometer Conflict of interest: The authors have declared no conflict of interest. Traditional Chinese medicines (TCMs) have been frequently used in China and some countries such as South Korea and Japan. They are always regarded as the typical or representatives of alternative and complementary therapies. TCMs have been gaining attractions throughout the world [1,2]. Scutellaria baicalensis is a kind of perennial herb plant that derived J Sep Sci. 2017;1 12. www.jss-journal.com 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim 1
2 YAN ET AL. from Labiatae family, its dry roots are officially listed in the Chinese Pharmacopoeia [3]. It is a highly valued and widely used TCM with the virtue of dissipate heat and drying the damp and purge fire to eliminate toxin, recorded in Shennong s Classic of Materia Medica (200 300 AD, Han Dynasty). Today, a number of studies have demonstrated that S. baicalensis has been widely used in clinics for the therapy of antibacterial, antiviral, anti-cancer, hepatoprotection, antioxidant, anticonvulsant, and neuroprotective effects [4 6]. Hundreds of chemical components of S. baicalensis build up its efficacious and reliable biological activities. S. baicalensis contains a variety of flavones, diterpenes, phenylethanoid glycosides, amino acids, essential oils, and phenolic acids. Its dried roots contain over 30 kinds of flavonoids, such as baicalin, baicalein, wogonin, wogonin 7-O-glucuronide, oroxylin A, oroxylin A 7-O-glucuronide, etc. [5,7,8]. Like the roots, its dried stems and leaves are also rich in flavones and some additional phenolic acids, such as scutellarin, baicalin, baicalein, chrysin, wogonoside, wogonin, p-coumaric acid, ferulic acid, p-hydroxybenzoic acid, caffeic acid, etc. [9 12]. Because of the important medicinal value, S. baicalensis and its relevant preparation are included in about 70% Chinese patent medicine products that are widely used, such as Huangqin capsule, Huangqin tablets, and Baicalin capsule [7,13]. It has estimated that the annual demand of S. baicalensis was more than 5000 tons. In recent decades, the natural resources of S. baicalensis was deficient, and gradually replaced by artificial cultivation, hence cause the expansion of planting area and increase of production [14,15]. In fact, the biomass of S. baicalensis stem-leaf is more than roots, which are permitted for clinical use. S. baicalensis stem-leaf was abandoned as waste during the roots harvest, which cause huge waste of resources and ecological environment pollution [16,17]. As we know, waste is a misplaced resource, Ginkgo biloba leaves containing a large number of active chemical components used to be regarded as waste, but now, it has been developed and utilized into raw medicines and have being widely used in clinical practice [18,19]. In the same way, S. baicalensis stem-leaf that is also rich in active chemical components and has been regarded as nontraditional medicinal parts could be sufficiently developed and utilized, and ultimately create health value, ecological value, and economic value. It is well known that the therapeutic effect of TCMs is attributed to the synergic effect of its multiple chemical bioactive compounds [20,21]. So the sensitive and fast UHPLC coupled with a triple quadrupole mass spectrometer (TQ- MS/MS) method was developed for simultaneous quantitation of 15 components (4 phenolic acids and 11 flavonoids) in S. baicalensis stem-leaf, which dramatically simplified the complicated chromatographic separation and identification for multiple components of this plant [22,23]. As a result, the study might provide a constructive approach to simultaneously and quickly quantify several active compounds in S. baicalensis stem-leaf. Another well-known truth is that herbs collected from various regions are discrepant in the types and quantities of chemical components that influence their therapeutic effects [24]. So 35 batches of S. baicalensis stem-leaf were collected from eight regions of China. In addition, hierarchical clustering analysis (HCA) and principal components analysis (PCA) were performed to estimate and classify the samples based on the contents of the 15 chemical components. Furthermore, it shows theoretical basis and scientific evidence for development and utilization of S. baicalensis stem-leaf resources, and ultimately contributes to human health, environment, and recycling economy. 2 MATERIALS AND METHODS 2.1 Chemicals and reagents Acetonitrile and formic acid (HPLC grade) were all purchased from Merck (Darmstadt, Germany); deionized water was obtained by a Milli-Q water purification system (Millipore, Billerica, MA, USA). Other chemicals and reagents were analytical grade. Chemical standards including p- hydroxybenzoic acid (1), caffeic acid (2), p-coumaric acid (3), ferulic acid (4), luteoloside (5), scutellarin (6), cosmosiin (7), baicalin (8), wogonoside (10), baicelein (12), wogonin (13), chrysin (14), oroxylin A (15) were purchased from Spring & Autumn Biological Engineering, Nanjing, China. Luteolin (9) and apigenin (11) were purchased from Pffeffer Biological Technology, Chengdu, China. The purity of each reference compound was over 98% determined by HPLC analysis. The chemical structures of 15 reference compounds are presented in Fig. 1. 2.2 Plant materials Thirty-five batches of samples (samples 1 35) of S. baicalensis stem-leaf were collected from Jiangsu, Heilongjiang, Shandong, Gansu, Shanxi, Hebei, Shaanxi, and Beijing provinces, PR China during 2016.06 to 2016.08. The botanical origin of materials was identified as Scutellaria baicalensis by the corresponding author, and the voucher specimens were deposited at the Herbarium in Nanjing University of Chinese Medicine, China. After collection, the samples were allowed to dry at 45 C for 6 days, then pulverized into homogeneous powders (40 mesh) and stored under dry conditions at room temperature before analysis. 2.3 Preparation of standard solutions A mixed standard stock solution containing the reference compounds 1-15 was prepared in 90% methanol, then the mixed standard stock solution was diluted with 90% methanol
YAN ET AL. 3 FIGURE 1 Chemical structures of 15 reference compounds in S. baicalensis stem-leaf to a series of appropriate concentrations. All the standard solutions above were stored at 4 C until use and filtered through a 0.22 μm cellulose membrane before injection. 2.4 Preparation of sample solutions The dried powder (0.5 g) of 35 samples, which was weighed accurately, was put into a 50 ml conical flask with stopper, and 40 ml 60% ethanol was added. After accurate weighing, ultrasonication (100 khz) was performed at 50 C for 40 min, afterwards the same solvent was added to compensate for the weight lost during extraction. After centrifugation (13 000 rpm, 10 min) and filtered through a 0.22 μm membrane filter, all the sample solutions were stored at 4 C before the injection into UHPLC TQ- MS/MS system for analysis. 2.5 Chromatographic conditions and instrumentation Analysis was performed on a Waters Acquity UHPLC system (Waters, Milford, MA), which consisting of a quaternary pump solvent management system, an online degasser, an autosampler, and a triple quadrupole mass detector. An Acquity UPLC BEH C 18 (2.1 mm 100 mm, 1.7 μm) column was applied for all analyses. The mobile phase was composed of A (water and 0.1% formic acid) and B (acetonitrile) using a gradient elution of 5 5% B at 0 1 min, 5 60% B at 1 11 min, 60 95% B at 11 12 min, 95 5% B at 12 12.2 min, and 5 5% B at 12.2 14 min. The flow rate of mobile phase was set at 0.40 ml/min. The column temperature was conditioned at 35 C, the autosampler was maintained at 4 C, and the injection volume was 2 μl. The TQ-MS/MS was operated in both positive and negative modes with a capillary voltage of 3 kv, a cone gas flow of 20 L/h, a collision gas flow of 0.15 ml/min, a desolvation gas flow of 1000 L/h, a desolvation temperature of 550 C, a source temperature of 150 C, and full-scan spectra from 100 to 1000 Da. The raw data were acquired and processed with MassLynx 4.1 software. The MS/MS detection parameters of 15 compounds and the typical chromatograms are presented in Table 1 and Fig. 2. 2.6 Validation of UHPLC TQ-MS/MS method 2.6.1 Calibration curves, LOD, and LOQ The linearity was obtained by preparing a series of concentrations of standard solution with at least five appropriate concentrations in duplicate. The lowest concentration of working solution for calibration use was diluted with corresponding solvent to a series of concentrations. LOD and LOQ for each analyte were acquired while the S/Ns was 3 and 10, respectively. The peak height divided by the background noise value was used for the calculation of the S/N. 2.6.2 Precision, repeatability, and stability To evaluate the precision, we analyzed the standard solutions with six replicates, the RSDs of the peak area for each standard compounds was calculated. To confirm the repeatability in this developed method, six different sample solutions were prepared from the same sample (sample 1, collected from Jiangsu). And then these samples were analyzed and variations were expressed by RSD, and the stability was evaluated
4 YAN ET AL. TABLE 1 MS/MS detection parameters of 15 compounds in S. baicalensis stem-leaf Cone Collision Compounds t R (min) MW MRM transitions/sim voltage (V) energy (ev) Ion mode 1. p-hydroxybenzoic acid 2.97 138.13 139.074>95.115 16 12 ES + 2. Caffeic acid 3.44 180.15 179.096>135.044 22 14 ES 3. p-coumaric acid 4.24 164.16 163.032>119.077 20 14 ES 4. Ferulic acid 4.60 194.19 193.074>134.066 20 14 ES 5. Luteoloside 4.66 448.38 449.202>287.143 20 18 ES + 6. Scutellarin 4.69 462.37 463.223>287.13 20 28 ES + 7. Cosmosiin 5.19 432.38 433.233>271.155 18 20 ES + 8. Baicalin 5.90 446.37 447.223>271.133 20 22 ES + 9. Luteolin 6.31 286.23 285.096>132.859 44 32 ES 10. Wogonside 6.79 460.41 461.223>270.167 20 44 ES + 11. Apigenin 7.05 270.24 269.16>116.897 40 34 ES 12. Baicelein 7.68 270.24 271.16>123.073 40 34 ES + 13. Wogonin 8.88 284.27 283.138>268.061 24 16 ES 14. Chrysin 9.00 256.24 257.138>69.01 42 40 ES + 15. Oroxylin A 9.23 284.26 285.16>168.034 24 32 ES + MRM, multiple reaction monitoring. FIGURE 2 UHPLC TQ-MS/MS chromatogram of 15 compounds in S. baicalensis stem-leaf by storing the sample solutions mentioned above (sample 1) at 4 C, then analyzed at 0, 2, 4, 8, 12, and 24 h, respectively. 2.6.3 Recovery Spike recovery test was chosen to evaluate the accuracy of this method. It was performed by adding the corresponding 15 target compounds at low (80% of known contents), medium (same as known contents), and high (120% of known contents) levels into the sample (sample 1) preparation, then measured in six duplicates. The spiked samples were then extracted, processed, and quantified in accordance with the methods mentioned above. The spike recoveries were calculated using the following equation: Recovery% = [ (measured amount original amount) amount added] 100% (1) 2.7 Sample determination All the samples were prepared according to Section 2.4, and thereafter determined according to the chromatographic conditions and instrumentation. Quantification of each compound
YAN ET AL. 5 was calculated based on linear calibration plots of the peak areas versus the corresponding concentration. The content of total phenolic acids was the sum of p-hydroxybenzoic acid, caffeic acid, p-coumaric acid, ferulic acid. The content of total flavonoids was the sum of luteoloside, scutellarin, cosmosiin, baicalin, luteolin, wogonoside, apigenin, baicelein, wogonin, chrysin, oroxylin A. 2.8 Method for hierarchical clustering analysis of samples The HCA was performed by SPSS 19.0 software. Ward s method was applied, and squared Euclidean distance was selected as a measurement. Dendrogram resulting from the 15 target compounds derived from UHPLC TQ-MS/MS profiles of the test samples. 2.9 Method for principal components analysis of samples The PCA was carried out by SPSS 19.0 software. In this paper, the 15 target compounds analyzed from the 35 samples composed a data matrix with 35 rows and 15 columns, which was used for PCA analysis after normalization. The first two principal components were extracted, and the scatter plot obtained by plotting the scores of PC 1 versus PC 2. 3 RESULTS AND DISCUSSION 3.1 Optimization of extraction procedure In this paper, several extraction methods, solvents, and times were established to obtain the best extraction efficiency. The results revealed that ultrasonic bath extraction was more effective than refluxing for the 15 target compounds analyzed, so the further experiments were carried out with ultrasonic bath extraction. Various solvents including water, different ratios of methanol, and ethanol were screened, and the best solvent was found to be 60% ethanol, which enabled less interfering peaks and provided the highest values in the contents of the 15 markers. The volume of 60% ethanol, times of ultrasonic bath extraction and duration of extraction were also investigated to confirm the best extraction procedure. The results demonstrated that the optimized extraction method is as follows: each sample was extracted one time in ultrasonic bath with 40 ml 60% ethanol for 40 min. 3.2 Optimization of the chromatographic conditions To obtain chromatograms with symmetric peak shape and optimum separation in a short analysis time, the chromatographic conditions were optimized. The resolutions of these compounds were tested and compared with different RP conditions using a variety of analytical columns such as Acquity UPLCHSST3(2.1mm 100 mm, 1.8 μm) column, Acquity UPLC BEH C 18 (2.1 mm 100 mm, 1.7 μm) column and Thermo Scientific Hypersil GOLD (3 mm 100 mm, 1.9 μm) column. The results showed that Acquity UHPLC BEH C 18 (2.1 mm 100 mm, 1.7 μm) column could achieve chromatograms with stronger retention as well as better resolution ability for the 15 target compounds analyzed than others under the same mobile phase. Different kinds of solvent systems were tested for the good separation in the multi-ingredients determination such as water/methanol, water/methanol with 0.1 or 0.5% formic acid, water/acetonitrile, water/acetonitrile with 0.1 or 0.5% formic acid. The results showed that acetonitrile/0.1% formic acid water solution was the most suitable mobile phase to simultaneously separate different kinds of target compounds in these samples. Flow rate ranging from 0.1 to 0.5 ml/min and column temperature range of 30 40 C were also tested. The results showed that the separation was maximized when column temperature was maintained at 35 C at a flow rate of 0.4 ml/min. 3.3 Optimization of MS/MS conditions Full-scan MS method was applied to examine the target compounds in both positive and negative ionization modes to optimize MS conditions. The results indicated that the sensitivity and intensity of caffeic acid, p-coumaric acid, ferulic acid, luteolin, apigenin, wogonin obtained from the negative ion mode was higher than that from the positive ion mode; while p-hydroxybenzoic acid, luteoloside, scutellarin, cosmosiin, baicalin, wogonoside, baicelein, chrysin, oroxylin A had better sensitivity and intensity at positive ion mode. Therefore, the marker compounds were determined under the ESI + or ESI mode based on the sensitivity and intensity of their signals. All of the analytes were detected in direct infusion mode respectively and equipped with a proper transition for the MS analysis to increase the sensitivity of them. As a result, the condition of multiple reaction monitoring determination was obtained on account of the highest sensitivity and specific ion pairs in the quantitative results, as well as cone voltage and collision energy subsequently optimized by the Intellistart program. 3.4 Method validation The developed UHPLC TQ-MS/MS method for quantitation of phenolic acids and flavonoids was validated by determining the linearity, LOD, LOQ, precision, repeatability, stability, and recovery. The results are shown in Table 2. All the marker substances showed good linearity with the determination coefficients (R 2 ) ranging from 0.9912 to 0.9997 in a
6 YAN ET AL. TABLE 2 Calibration curves, LOD, LOQ, precision, repeatability, stability, and recovery of the 15 references Compounds Calibration curves R 2 1.p-Hydroxybenzoic acid Linear range/ μg/ml LOD /ng/ml LOQ /ng/ml Precision (%, n = 6) Repeatablity (%, n = 6) Recovery (%, n = 3) Stability (%, n = 6) Mean RSD Y = 9.615 10 4 X+409.1 0.9946 0.13 133 20.86 69.53 2.91 3.04 3.26 100.07 2.03 2. Caffeic acid Y = 2.616 10 5 X+100.5 0.9997 0.126 129 33.13 110.43 3.17 3.38 2.37 98.75 2.23 3. p-coumaric acid Y = 1.900 10 5 X+573.2 0.9994 0.141 144 14.53 48.43 2.33 3.12 3.06 100.86 2.24 4. Ferulic acid Y = 6.048 10 4 X +16.6 0.9991 0.191 196 40.05 133.5 1.98 3.29 3.39 100.19 3.43 5. Luteoloside Y = 2.178 10 7 X+5271.6 0.9912 0.054 55.5 4.99 16.63 2.02 1.83 2.62 99.29 2.99 6. Scutellarin Y = 1.481 10 7 X+56479.0 0.9989 0.725 742 9.27 30.9 4.11 3.39 2.02 100.31 2.21 7. Cosmosiin Y = 2.989 10 7 X+132.8 0.9991 0.03 31 3.35 11.16 1.48 3.31 1.56 99.68 2.35 8. Baicalin Y = 3.223 10 7 X+4189.9 0.9996 0.058 59.5 1.98 6.6 3.11 2.10 3.24 99.71 2.23 9. Luteolin Y = 8.669 10 5 X+1777.3 0.9997 0.068 70 11.23 37.43 2.23 2.81 2.15 100.25 2.35 10. Wogonoside Y = 3.985 10 7 X 1934.9 0.9990 0.011 12.1 3.01 10.03 2.07 2.92 3.36 99.42 1.93 11. Apigenin Y = 3.370 10 5 X+448.5 0.9964 0.052 52.5 11.42 38.06 2.53 4.21 3.31 100.03 2.33 12. Baicelein Y = 7.549 10 7 X 1554.7 0.9969 0.014 15.2 2.8 9.33 1.86 2.53 4.13 99.32 3.45 13. Wogonin Y = 5.183 10 5 X+484..3 0.9998 0.013 11.7 2.1 7.04 3.15 2.93 3.78 102.15 3.51 14. Chrysin Y = 2.903 10 7 X +292.2 0.9997 0.007 7.17 1.7 5.67 1.36 1.95 2.19 101.08 2.33 15. Oroxylin A Y = 1.290 10 8 X +917.4 0.9991 0.006 6.14 1.53 5.1 2.05 2.41 1.67 98.62 2.39
YAN ET AL. 7 relatively wide concentration range. The results of precision test of the 15 analytes were less than 4.11%, repeatability and stability were less than 4.21 and 4.13%, and the overall recoveries were between 98.62 and 102.15% for the 15 target compounds, with RSDs less than 3.51%. As a result, it showed that the established method was accurate enough for the determination of 15 bioactive components in the samples. So the UHPLC TQ-MS/MS method is accurate, precise, and sensitive enough for quantitative evaluation of those bioactive components in the massive samples. 3.5 Sample analysis The established UHPLC TQ-MS/MS method was then subsequently applied to simultaneous determination of phenolic acids (p-hydroxybenzoic acid, caffeic acid, p-coumaric acid, ferulic acid) and flavonoids (luteoloside, scutellarin, cosmosiin, baicalin, luteolin, wogonoside, apigenin, baicelein, wogonin, chrysin, oroxylin A). The results (Table 3) showed that there were remarkable differences among the contents of the 15 target compounds in the massive samples. For example, scutellarin was the highest content constituent in all S. baicalensis stem-leaf samples, but its contents varied from 18.0247 to 46.0854 mg/g. The same variation could also be found in other constituents. Sample 2 from Heilongjiang had the highest contents of p-hydroxybenzoic acid, caffeic acid, p-coumaric, apigenin, wogonin, and total content of phenolic acids. Sample 5 from Gansu had the highest contents of luteoloside, cosmosiin, and oroxylin A. Samples 8 and 9 from Shanxi had the highest contents of luteolin, chrysin, and ferulic acid. Samples 11 and 21 from Hebei had the highest contents of baicelein, baicalin, and wogonoside. Sample 22 from Shaanxi had the highest content of scutellarin and total content of flavonoids. The total content of flavonoids was significantly higher than the total content of phenolic acids. It prompts that different regions with different geography (soil or minerals) and climate may attribute to the differences in the content of phenolic acids and flavonoids. Flavonoids with reliable biological activities could be the representative and abundant contents of S. baicalensis stem-leaf. 3.6 Hierarchical clustering analysis of the samples To evaluate the variation of S. baicalensis stem-leaf, HCA was performed based on the contents of 15 target compounds from UHPLC TQ-MS/MS profiles. The results (Fig. 3) showed that 35 tested samples of S. baicalensis stemleaf were divided into two main clusters (Ⅰ and Ⅱ) depending on their contents, which were divided into four subgroups (A, B, C, and D). The results showed that samples collected from same region were mostly classified into one cluster. For example, samples 13, 14, 15, and 16 (from Hebei province, China) together with samples 25, 26, and 29 (from Shaanxi province, China), 34 and 35 (from Beijing province, China) were classified in subgroup A. Samples 17, 18, 19, and 20 (from Hebei province, China) were classified in subgroup B. Samples 8 and 9 (from Shanxi province, China) were classified in subgroup C. Samples 7 and 10 (from Shanxi province, China) together with samples 11, 12, and 21 (from Hebei province, China), 22, 23, 24, 27, 28, and 30 (from Shaanxi province, China), 31, 32, and 33 (from Beijing, China) were classified in subgroup D. Almost all of the samples from Hebei, Shaanxi, and Beijing were classified in subgroup A and D, which prompts that it is very obvious that chemical compositions of samples from Heibei, Shaanxi, Beijing are similar to each other. Samples from Shandong and Gansu (with smaller S. baicalensis cultivation area and shorter S. baicalensis cultivation history than Hebei, Shaanxi, and Beijing) were classified in mutually separated subgroup, which implies that there is a clear difference between the samples from Shandong and Gansu. Cultivation area and history could affect the stability of the samples on the contents of the 15 target compounds. 3.7 Principal components analysis of the samples The determination results of 35 samples were further analyzed and classified by PCA. The first two principal components (PC 1 and PC 2) with more than 61% of the whole variances were extracted for analysis. PC 1 accounted for 37.80% variances and PC 2 accounted for 23.56%. The other principal components were abandoned due to their minor effects. The components loading matrix was shown in Table 4. According to their loadings, PC 1 had good correlation with compounds 4 8, 12, 14, and PC 2 had good correlation with compounds 1, 9, 11, 13, and 15, which indicated that almost all of the 15 compounds may contribute to the classification of the samples. The scatter plot was shown in Fig. 4, where each sample was represented as a marker. It was observable that the samples were clearly clustered into six domains. Sample 2 was in domain Ⅰ, sample 5 was in domain Ⅱ, samples 18 and 19 were in domain Ⅲ, samples 8 and 9 were in domain Ⅳ, samples 1, 3, 13, 14, 15, 16, 17, 20, 25, 26, 29, 34, and 35 were in domain Ⅴ and the rest were in domain Ⅵ. In fact, these results were consistent with their natural properties. For example, sample 2 was collected from Heilongjiang province, the easternmost and northernmost province of China with the lowest annual average temperature among the eight regions, it prompts that the unique geography and climate could promote the synthesis of phenolic acids. Samples from Shandong and Gansu were clustered into different domains, which indicates that samples from Shandong and Gansu have a clear difference in chemical compositions. Most of the samples were in domain Ⅴ and Ⅵ, which implies that samples from Hebei,
8 YAN ET AL. TABLE 3 The contents (mg/g) of 15 investigated compounds in samples of S. baicalensis stem-leaf Sample Analytes No. Region 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 TPA TF 1 Jiangsu 0.0331 0.1580 0.0598 0.0680 0.0551 26.7336 0.0103 1.2126 0.1107 0.0031 0.5492 0.0042 0.0205 0.0197 0.0107 0.3190 28.7298 2 0.0900 0.4405 0.4318 0.0381 0.0890 23.9268 0.0155 1.3900 0.3262 0.0241 4.5668 0.0184 0.6435 0.0598 0.1008 1.0005 31.1609 Heilongjiang 3 Shandong 0.0592 0.1330 0.1778 0.0582 0.0072 28.1993 0.0088 0.4716 0.0430 0.0153 0.2109 0.0026 0.0165 0.0012 0.0027 0.4283 28.9791 4 Shandong 0.0480 0.0527 0.0675 0.1070 0.2662 44.6383 0.0242 0.9709 0.0720 0.0476 0.4805 0.0466 0.0063 0.0604 0.0203 0.2753 46.6333 5 Gansu 0.0278 0.0302 0.0280 0.0732 0.5768 32.0684 0.1119 2.0046 0.3594 0.1073 2.4956 0.0693 0.0065 nd 0.2006 0.1592 38.0005 6 Gansu nd 0.0180 0.0244 0.0684 0.2231 29.9720 0.0354 1.2827 0.1786 0.0644 0.9933 0.0336 0.0091 0.1637 0.0906 0.1108 33.0463 7 Shanxi 0.0197 0.0636 0.0513 0.0850 0.1830 35.5961 0.0248 0.9096 0.1408 0.1778 0.9146 0.1406 0.0161 0.2430 0.0018 0.2194 38.3481 8 Shanxi 0.0301 0.0632 0.0518 0.0754 0.2373 29.9486 0.0332 0.5197 0.4207 0.0210 2.4591 0.1497 0.0232 0.6280 0.0118 0.2206 34.4524 9 Shanxi 0.0370 0.1957 0.0493 0.1228 0.3880 45.4258 0.0496 1.0864 0.1519 0.0062 0.9854 0.1155 0.0034 0.5562 0.1017 0.4047 48.8702 10 Shanxi 0.0379 0.1363 0.0455 0.0965 0.2399 31.8328 0.0408 0.8275 0.0818 0.0341 0.5378 0.0406 0.0015 0.1995 0.0830 0.3162 33.9196 11 Hebei 0.0260 0.0513 0.0435 0.0493 0.1733 21.4578 0.0260 2.3533 0.0959 0.8581 0.9807 0.2058 0.0690 0.2977 0.0238 0.1701 26.5415 12 Hebei 0.0385 0.0235 0.0333 0.0771 0.1044 27.9337 0.0305 1.9573 0.0459 0.2846 0.3515 0.0679 0.0200 0.3353 0.0014 0.1724 31.1327 13 Hebei 0.0270 0.1133 0.1251 0.0399 0.0258 18.6879 0.0077 0.1148 0.0331 0.0041 0.0743 0.0020 0.0059 nd 0.0207 0.3052 18.9762 14 Hebei 0.0322 0.1442 0.1465 0.0456 0.0078 20.2758 0.0098 0.1263 0.0521 0.0021 0.2067 0.0019 0.0048 0.0008 0.0006 0.3685 20.6887 15 Hebei 0.0306 0.1071 0.1582 0.0396 nd 18.0247 0.0074 0.1266 0.0435 0.0031 0.2208 0.0019 0.0067 0.0007 0.0006 0.3355 18.4361 16 Hebei 0.0408 0.2007 0.1755 0.0569 0.0225 30.3980 0.0127 0.3565 0.1349 0.0086 0.5149 0.0024 0.0169 0.0015 0.0008 0.4740 31.4697 17 Hebei 0.0431 0.1291 0.1875 0.0667 0.0175 27.5880 0.0130 1.3257 0.0750 0.0530 0.3536 0.0055 0.2685 0.0021 0.0103 0.4264 29.7121 18 Hebei 0.0637 0.2045 0.3502 0.0547 0.0107 27.4430 0.0080 1.3007 0.1411 0.0537 2.0898 0.0055 0.5026 0.0028 0.0002 0.6730 31.5582 19 Hebei 0.0787 0.2805 0.3426 0.0806 0.0731 32.5925 0.0115 1.7196 0.0937 0.3808 2.0663 0.0056 0.1867 0.0180 0.0027 0.7823 37.1505 20 Hebei 0.0344 0.1383 0.2568 0.0678 0.0181 22.8629 0.0057 1.3332 0.0877 0.0597 1.2898 0.0068 0.4878 0.0064 0.0031 0.4972 26.1612 21 Hebei 0.0165 0.0378 0.0645 0.0949 0.0921 36.7589 0.0222 2.6655 0.0367 1.2862 0.5191 0.1322 0.1054 0.0434 0.0166 0.2137 41.6782 22 Shaanxi 0.0224 0.0862 0.0556 0.1157 0.3061 46.0854 0.0418 1.6087 0.0604 0.3637 0.2399 0.0443 0.0193 0.0720 0.0042 0.2799 48.8459 23 Shaanxi 0.0141 0.0453 0.0480 0.0807 0.1265 25.4565 0.0220 0.6869 0.0313 0.1350 0.0525 0.0196 0.0117 0.0031 0.0018 0.1880 26.5469 24 Shaanxi 0.0361 0.0855 0.0490 0.1181 0.2901 44.6845 0.0390 2.1841 0.0616 0.6581 0.2751 0.0710 0.0393 0.1015 0.0080 0.2887 48.4123 25 Shaanxi 0.0413 0.2117 0.2281 0.0873 0.0412 27.4699 0.0088 0.9136 0.0694 0.0268 0.4053 0.0039 0.1927 0.0037 0.0107 0.5684 29.1460 (Continues)
YAN ET AL. 9 TABLE 3 (Continued) Sample Analytes No. Region 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 TPA TF 26 Shaanxi 0.0469 0.2476 0.2565 0.0830 0.0358 31.9231 0.0125 0.7010 0.1041 0.0139 0.7127 0.0030 0.0473 0.0065 0.0187 0.6341 33.5786 27 Shaanxi 0.0295 0.0709 0.0419 0.1101 0.2581 40.2755 0.0367 1.7111 0.0690 0.4495 0.2696 0.0923 0.0655 0.1017 0.0074 0.2523 43.3364 28 Shaanxi 0.0218 0.0641 0.0302 0.0945 0.2334 37.2550 0.0355 1.9050 0.0531 0.5753 0.1210 0.0515 0.0205 0.0535 0.1061 0.2106 40.4099 29 Shaanxi 0.0265 0.1601 0.1906 0.0460 0.0196 20.3081 0.0070 0.3201 0.0555 0.0066 0.2449 0.0024 0.0328 0.0033 0.0007 0.4232 21.0011 30 Shaanxi 0.0226 0.0614 0.0443 0.0842 0.1867 33.9931 0.0312 1.2145 0.0335 0.3025 0.1427 0.0344 0.0217 0.0395 0.0072 0.2125 36.0071 31 Beijing 0.0207 0.0640 0.0413 0.0800 0.1545 34.8970 0.0253 0.9020 0.0518 0.0593 0.2658 0.0270 0.0054 0.1031 0.0387 0.2060 36.5298 32 Beijing nd 0.0303 0.0348 0.0552 0.1233 22.5733 0.0214 1.5142 0.0382 0.5893 0.2858 0.1008 0.0437 0.0378 0.0111 0.1203 25.3388 33 Beijing 0.0203 0.0600 0.0412 0.0992 0.1890 43.0097 0.0286 1.1717 0.0637 0.1117 0.3702 0.0340 0.0064 0.1584 0.0011 0.2206 45.1444 34 Beijing 0.0210 0.1686 0.2613 0.0229 0.0390 20.2417 0.0079 0.1290 0.0472 0.0011 0.2195 0.0021 0.0026 0.0024 0.0007 0.4740 20.6932 35 Beijing 0.0314 0.2627 0.3276 0.0345 0.0343 25.5633 0.0081 0.0723 0.0773 0.0013 0.4667 0.0019 0.0052 0.0013 0.0013 0.6562 26.2329 nd = not detected; TPA = total phenolic acids; TF = total flavonoids Shaanxi, Beijing had a high degree of similarity in chemical compositions. 4 CONCLUDING REMARKS In the present study, four phenolic acids and eleven flavonoids were determined in S. baicalensis stem-leaf simultaneously by the developed UHPLC TQ-MS/MS method, which was simple and reliable analytical and successfully applied to 35 samples from eight regions. These 15 target compounds were analyzed simultaneously with acceptable performance of linearity, precision, repeatability, and accuracy in an analysis time of 14 min. From the results, 15 target components were identified and quantified, which clearly suggested that the S. baicalensis stem-leaf is rich in phenolic acids and flavonoids. In particular, flavonoids in the S. baicalensis stem-leaf were impressive, and S. baicalensis stem-leaf could be a good choice when scutellarin was utilized as major active constituents in TCMs. Phenolic acids and flavonoids in S. baicalensis stem-leaf can be extracted and enriched thereby using for preparation of natural antioxidants, medicines, or health products for treating or improving cardiovascular disease. HCA and PCA approaches applied on chromatographic data basing on UHPLC TQ-MS/MS method promote to cluster the samples of S. baicalensis stem-leaf from different regions. The results of HCA and PCA implied that samples of S. baicalensis stem-leaf from Shaanxi, Hebei, and Beijing shared the similar chemical composition. These areas have wide S. baicalensis cultivation area and long history of S. baicalensis cultivation, in where huge amounts of S. baicalensis stem-leaf are generated every year. The advantages of wide cultivation area, high yield, and similar chemical composition could make S. baicalensis stemleaf from Shaanxi, Hebei, and Beijing be widely, quickly, and easily developed and utilized compared with some famous region medicinal herbs that must be planted or collected in a specific area to guarantee clinical efficacy, and whose yield could not sometimes meet the clinical needs in time [25,26]. The presented UHPLC TQ- MS/MS method conjugated with HCA and PCA was certified very useful and helpful in developing and utilizing S. baicalensis stem-leaf resources better. Nowadays, S. baicalensis stem-leaf is usually regarded as waste that take up valuable land resources and cause environmental problems. So far, this is the first report about chemical constituents in S. baicalensis stem-leaf from different regions in China. It provided a deeper understanding about S. baicalensis stem-leaf resources and theoretical basis and scientific evidence for the development and utilization of S. baicalensis stem-leaf resources that could effectively alleviate the shortage of clinical medicines, reduce environmental pressure, and bring extra income to the vast number
10 YAN ET AL. FIGURE 3 Dendrograms of hierarchical cluster analysis for the 35 tested samples of S. baicalensis stem-leaf TABLE 4 Component loading matrix for PCA Analytes Compounds (PCs) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 0.517 0.722 0.864 0.709 0.855 0.662 0.789 0.585 0.137 0.502 0.145 0.724 0.489 0.524 0.408 2 0.606 0.494 0.369 0.035 0.363 0.117 0.388 0.278 0.831 0.135 0.946 0.140 0.592 0.265 0.608 of farmers in China [27,28]. Furthermore, the UHPLC TQ- MS/MS method established in this paper can be applied in future research of S. baicalensis stem-leaf and its preparation medicines. ACKNOWLEDGMENTS This work was supported by program for excellent talents in school of pharmacy of Nanjing university of Chinese Medicine (15ZYXET-2). This work was also supported by the Construction Project for Jiangsu Key Laboratory for High Technology Research of TCM Formulae (BM2010576; BK2010561), and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (ysxk-2014). This work also supported by the 2013 Program for New Century Excellent Talents by the Ministry of Education (Grant NCET-13-0873), 333 High-level Talents
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