Journal of Pharmaceutical and Biomedical Analysis 102 (2015) 110–118
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Simultaneous determination of 16 phenolic constituents in Spatholobi Caulis by high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry Yu Zhang 1 , Long Guo 1 , Li Duan, Xin Dong, Ping Zhou, E.-Hu Liu ∗ , Ping Li ∗ State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing 210009, China
a r t i c l e
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Article history: Received 1 August 2014 Received in revised form 1 September 2014 Accepted 6 September 2014 Available online 16 September 2014 Keywords: Spatholobi Caulis HPLC–MS/MS Phenolic compounds Principal component analysis Quantitative analysis
a b s t r a c t Spatholobi Caulis, the vine stem of Spatholobus suberectus Dunn, has been widely used in traditional Chinese and folk medicines for treatment of irregular menstruation, blood deficiency and rheumatalgia in clinic. In this study, an accurate and reliable high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry (HPLC–MS/MS) method was established for simultaneous determination of 16 phenolic bioactive constituents, including five flavanols, seven isoflavonoids, three flavanones and one chalcone in Spatholobi Caulis. The method validation results exhibited that the developed method had desirable specificity, linearity, precision and accuracy. The quantitative analysis results showed that flavanols were the abundant constituents in Spatholobi Caulis. Moreover, principal component analysis (PCA) was performed to assess the quality variation of samples collected from different regions in China. The PCA results indicated the quantitative analysis based on HPLC–MS/MS is a feasible method for quality assessment and control of Spatholobi Caulis. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Spatholobi Caulis, the vine stem of Spatholobus suberectus Dunn of the family Leguminosae, is specified in Chinese Pharmacopoeia (2010 version) with the name of Jixueteng. It has been widely used in traditional medicines for the treatment of blood stasis syndrome, rheumatism and menoxenia [1]. Pharmacological and clinical studies have demonstrated that Spatholobi Caulis possesses a variety of functions, including blood circulation improvement, antiplatelet, anti-inflammation, anti-bacterial, neuroprotection, and anti-cancer effects [2–7]. Phytochemical studies indicated that polyphenolic compounds, including flavanols, isoflavonoids, flavanones and chalcone, were the main bioactive components in Spatholobi Caulis [8,9]. Although there have been a few studies regarding the quantification of the active components in Spatholobi Caulis [10,11], rather limited investigations have been conducted for simultaneous determination of multicomponent in this herbal medicine. In Chinese
∗ Corresponding authors. Tel.: +86 25 83271379; fax: +86 25 83271379. E-mail addresses: [email protected] (E.-H. Liu), [email protected], [email protected] (P. Li). 1 The authors contributed equally to this work. http://dx.doi.org/10.1016/j.jpba.2014.09.006 0731-7085/© 2014 Elsevier B.V. All rights reserved.
Pharmacopoeia (2010 version), only thin layer chromatography (TLC) method was applied to authentication of Spatholobi Caulis using a single qualitative marker compound (formononetin), and no assay method has been developed, indicating the quality evaluation of this herbal medicine was insufficient. Moreover, there is an adulterant named Sargentodoxae Caulis (daxueteng) in the herbal medicine market. Spatholobi Caulis and Sargentodoxae Caulis are usually utilized under the same name “xueteng” in different areas, and are confusable for the morphological and macroscopic similarity [12]. The phenomena of homonym in prescription are confusing and unscientific or even dangerous in clinical therapy. In view of the current situation, it is necessary to develop a rapid and reliable method to evaluate the bioactive components for quality control of Spatholobi Caulis. It is well accepted that herbal medicines exert their curative effects through multiple components on multiple target sites [13]. Therefore, development of reliable methods to quantify multiple bioactive components for their comprehensive quality control has become a rational strategy [14,15]. Presently, several analytical techniques, such as thin layer chromatography (TLC), gas chromatography (GC), high performance liquid chromatography–ultraviolet detection (HPLC–UV), HPLC coupled with evaporative light scattering detection (HPLC–ELSD) and HPLC coupled to mass spectrometry (HPLC–MS), have already been
Y. Zhang et al. / Journal of Pharmaceutical and Biomedical Analysis 102 (2015) 110–118
widely used for the quality control of traditional Chinese medicines [16–19]. Among the analytical methods, the HPLC–MS technique has the advantages of abundant mass fragmentations and many scan modes afforded by tandem mass spectrometry can provide the required specificity and sensitivity, therefore, it is appropriate for simultaneous determination of multiple constituents of herbal medicines [20,21]. Since the constituents in Caulis Spatholobi are extremely complex and some are present in trace amounts, it is a tough and time-consuming task to simultaneously determine multiple constituents by HPLC–UV method. In this work, an accurate and reliable high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry (HPLC–MS/MS) method was established for determination of phenolic bioactive constituents in Spatholobi Caulis. A total of 16 phenolic constituents, including 5 flavanols, 7 isoflavonoids, 3 flavanones and 1 chalcone were selected as the marker compounds [10]. Multiple reaction monitoring (MRM), a tandem MS scan mode unique to triple quadrupole MS instrumentation, was employed for quantification in the present study. The validated method was applied to evaluate the quality of the samples from different geographical regions, and the results were further analyzed by principal component analysis (PCA) to provide more information about the chemical differences in each sample.
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2. Experimental 2.1. Chemicals, materials and reagents The reference compounds of gallocatechin (1), epigallocatechin (2), catechin (3), procyanidin B2 (4), epicatechin (5), taxifolin (6), ononin (7), liquiritigenin (8), daidzein (9), calycosin (10), naringenin (11), genistein (12), isoliquiritigenin (13), formononetin (14), prunetin (15), biochanin A (16) were purchased from Chengdu Must Bio-technology Co., Ltd. (Chengdu, China). The internal standard (I.S.) 5,7-dimethoxycoumarin was obtained from Aldrich chemical company, Inc. (Milwaukee, WI, USA). The structures of 16 reference compounds are shown in Fig. 1. The purities of these compounds were determined to be higher than 95% by high performance liquid chromatography–diode array detection analysis. 30 batches of Spatholobi Caulis collected in present study were the vine stem of S. suberectus Dunn from different provinces in China. 7 batches of the adulterants of Sargentodoxae Caulis were also collected for the experiment. The origins of the 37 batches of samples are shown in Table 3. The voucher specimens, identified by Prof. Ping Li from Department of Pharmacognosy in China Pharmaceutical University, have been deposited in the State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Fig. 1. Chemical structures of 16 reference substances.
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Methanol and formic acid of MS grade were purchased from Merck (Darmstadt, Germany). Ultrapure water was prepared using a Milli-Q water purification system (Millipore, Bedford, MA, USA). HPLC grade methanol (Nanjing Chemical Reagent Factory, China) was used for sample preparation. 2.2. Instrument and chromatographic conditions Chromatographic analysis was performed on an Agilent series 1290 HPLC system equipped with a quaternary pump, a degasser, an autosampler, a thermostated column compartment (Agilent Technologies, Palo Alto, CA, USA). Chromatographic separation was performed on an Agilent Eclipse plus C18 (4.6 mm × 50 mm, 1.8 m) column with an on-line filter in front of the column. The mobile phase was composed of 0.3% formic acid (A) and methanol (B), with a gradient elution as follows: 0 min, 15% (B); 5 min, 30% (B); 10 min, 40% (B); 14 min, 45% (B); 16 min, 45% (B); 20 min, 55% (B); 25 min, 100% (B). The flow rate was 0.5 ml/min, and the column temperature was set at 30 ◦ C. MS experiments were conducted on an Agilent 6460 triple quadrupole mass spectrometer equipped with electrospray ionization source (Agilent Technologies, Palo Alto, CA, USA). Quantification was performed in the positive ionization by MRM mode. The MS conditions were as follows: drying gas temperature, 300 ◦ C; drying gas flow, 10 L/min; sheath gas temperature, 250 ◦ C; sheath gas flow, 5 L/min; nebulizer pressure, 45 psi; capillary voltage, 4000 V. Data acquisition was performed with Agilent MassHunter Workstation. 2.3. Preparation of standard solutions Each standard solution was accurately weighed, and then dissolved in methanol–water (80:20, v/v) solvent to give the stock solutions. Working standard solutions containing 16 reference standards respectively detected in positive ion mode were prepared by diluting the stock solutions with methanol–water (80:20, v/v) solvent to a series of proper concentrations. To each standard solution, an aliquot of stock solution of 5,7-dimethoxycoumarin (I.S.) was added to make up a final concentration of 132 ng/ml. The solutions were stored at 4 ◦ C for further analysis. 2.4. Preparation of sample solutions 30 batches of Spatholobi Caulis and 7 batches of Sargentodoxae Caulis were collected from different provinces in China for the experiment. All the samples were cut into smaller pieces, further grounded into powder and passed through a 60-mesh sieve. Each sample powder (0.5 g) was weighed accurately soaked in 25 ml of 80% methanol. An appropriate amount of the internal standard solution was added, and the mixture was reflux for 2 h at 80 ◦ C. After that the extracted solution was cooled to room temperature and centrifuged at 13,000 rpm/min for 10 min. For quantification of the gallocatechin (1), epigallocatechin (2), catechin (3), procyanidin B2 (4), epicatechin (5) and ononin (7), the supernatant was firstly diluted 10 times with 80% methanol, and then an aliquot of 1 L of the sample was injected for HPLC analysis. For quantification of the other compounds, 1 L of each supernatant was directly injected into the HPLC instrument for analysis. 2.5. Method validation The calibration curves were established by injecting each working solution thrice. All calibration curves were constructed from the peak area ratio of the tested reference peak to that of the internal standard versus their concentrations. The limit of detection (LOD)
and limit of quantification (LOQ) for each analyte were defined by the concentrations that generated peaks with signal-to-noise values (S/N) of 3 and 10, respectively. The precision of the developed method was determined by the intra- and inter-day variations. For intra-day test, the samples were analyzed for six times within the same day, while for inter-day test, the samples were examined in duplicates for consecutive three days. The relative standard deviations (RSDs) were calculated as the measure of precision. To confirm the repeatability, six replicates of the same samples were extracted and analyzed. For the stability test, the same sample was stored at room temperature and analyzed by replicate injection at 0, 2, 4, 8, 16 and 24 h. The RSDs were used to evaluate the method repeatability and stability. Recovery was used to further evaluate the accuracy of the method. A known amount of the 16 standards were added into a 0.25 g powder of the same samples in sextuplicate, and then extracted and analyzed with the same procedures. 2.6. Data analysis Principal component analysis (PCA) was performed by SPSS 18.0. When the contents of investigated compounds were below the quantitation limit or not detected in the samples, the values of such elements were considered to be 0. 3. Results and discussion 3.1. Optimization of extraction conditions The extraction conditions were optimized in order to obtain satisfactory extraction efficiency. The extraction methods (ultrasonic and refluxing extraction), extraction solvents (60% methanol, 80% methanol, and 100% methanol) and extraction time (1, 2, and 3 h) were optimized by using univariate test. The results (Supplementary Table 1) showed that refluxing extraction was more effective than ultrasonic extraction, and 80% methanol was the most efficient extraction solvent among the tested different concentrations of methanol. In addition, it demonstrated that the target components could be extracted completely within 2 h. Refluxing extraction with 25 ml of 80% methanol for 2 h was finally selected for sample preparation. 3.2. Optimization of LC conditions In order to achieve rapid and efficient analysis, a short chromatographic column packed with 1.8 m porous particles was employed in HPLC system. Different mobile phase (including methanol–water, acetonitrile–water, methanol–formic acid solution, and acetonitrile–formic acid solution), flow rate (0.4, 0.5 and 0.6 ml/min) as well as column temperature (25, 30, and 35 ◦ C) were examined and compared. As a result, methanol–0.3% formic acid solution at a flow rate of 0.5 ml/min with the column temperature of 30 ◦ C resulted in satisfactory separation in a short analysis time. 3.3. Optimization of MS conditions In order to develop a sensitive and accurate quantitative method, the MS/MS fragmentation patterns for each compound were investigated. Firstly, MS spectra were studied in both positive and negative modes. All analytes showed maximum sensitivity operating in the positive ion mode. For the optimization of MRM conditions, the parameters of fragmentor voltage (FV) and collision energy (CE) were optimized to get the richest relativeabundance of
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Table 1 Retention time, related MS data of the target compounds. No.
Compound
RT (min)
[M + H]+ (m/z)
Precursor ion
Product ion
FV (V)
CE (V)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 I.S.
Gallocatechin Epigallocatechin Catechin Procyanidin B2 Epicatechin Taxifolin Ononin Liquiritigenin Daidzein Calycosin Naringenin Genistein Isoliquiritigenin Formononetin Prunetin Biochanin A 5,7-Dimethoxycoumarin
2.54 4.15 4.37 4.67 6.29 8.72 13.51 13.97 15.46 16.99 17.45 19.16 22.36 23.01 23.79 24.06 17.66
307.1 307.1 291.1 579.1 291.1 305.1 431.1 257.1 255.1 285.1 273.1 271.1 257.1 269.1 285.1 285.1 207.0
307.1 307.1 291.1 579.2 291.1 305.1 431.1 257.1 255.1 285.1 273.0 271.1 257.0 269.1 285.1 285.1 207.0
139.0 139.0 139.0 291.1 139.0 153.1 269.1 137.1 199.1 270.0 153.0 91.0 137.1 197.1 167.1 213.1 91.1
100 100 90 120 90 105 100 125 155 135 120 155 115 135 165 160 90
13 13 13 13 13 15 10 15 29 25 15 35 15 35 30 35 30
precursor and product ions. The MS/MS product ion spectra of the analytes are shown in Supplementary Fig. 1. The retention time (RT) and MS information for each analyte including [M + H]+ , precursor and product ions, FV and CE are shown in Table 1. 3.4. Method validation The calibration curves exhibited good linearity (r2 > 0.9957) within the test range. The LODs and LOQs were less than 2.0 ng/ml and 5.0 ng/ml, respectively. The intra- and inter-day variations (RSDs) for 16 analytes were less than 4.75 and 4.35%, respectively. The repeatability presented as RSDs was in the range from 1.73 to 4.88%, and the stability was less than 4.72%. The recoveries varied between 93.12 and 105.21% with RSDs less than 4.66%. The above data (Table 2) were considered to be satisfactory for subsequent analysis of all the samples. 3.5. Quantification of 16 phenolic compounds in Spatholobi Caulis 3.5.1. Quantitative analysis of samples The validated method was applied to analyze 37 samples, including 30 batches of Spatholobi Caulis (J1–J30) and 7 batches of Sargentodoxae Caulis (D1–D7). A total of 16 phenolic compounds, including 5 flavanols (gallocatechin, epigallocatechin, catechin, procyanidin B2 and epicatechin), 7 isoflavonoids (ononin, daidzein, calycosin, genistein, formononetin, prunetin and biochanin A), 3 flavanones (taxifolin, liquiritigenin and naringenin) and 1 chalcone (isoliquiritigenin) were quantified with the internal standard method based on respective calibration curves. The typical MRM chromatograms are shown in Fig. 2 and the quantitative results are presented in Table 3. As shown in the results, only 4 phenolic constituents were quantified in Sargentodoxae Caulis, other constituents were hardly detected. The results indicated that the bioactive constituents of Spatholobi Caulis and Sargentodoxae Caulis were quite different. The constituents which were not detected in Sargentodoxae Caulis could be considered as the characteristic components of Spatholobi Caulis. The total contents of each type of compounds were calculated, and it was clearly shown that flavanols (including gallocatechin, epigallocatechin, catechin, procyanidin B2 and epicatechin) with the total content range of 1647–7304 g/g were the most abundant constituents among the analytes. Among the flavanols, procyanidin B2 (4) and epicatechin (5) were present in higher concentrations with mean values of 1063 and 1794 g/g,
respectively. It should be noted that the contents of flavones were low in Spatholobi Caulis, even some active compounds could not be quantified or detected in several samples. Ononin (7) and formononetin (14), two bioactive isoflavonoids, were relatively abundant and their mean concentrations were 77.9 and 53.6 g/g, respectively. The results suggested that HPLC–MS/MS was a very powerful technique for quantitative analysis of multicomponent of herbal medicines in terms of time saving and sensitivity.
3.5.2. Quality assessment of Spatholobi Caulis In this study, principal component analysis (PCA) was further carried out to provide more information about the chemical differences of Spatholobi Caulis and Sargentodoxae Caulis and assess the quality variation of samples collected from different places in China. PCA is an unsupervised pattern recognition method used for analyzing, classifying and reducing the dimensionality of numerical datasets in a multivariate problem [22], and it has been widely used for the quality control of herbal medicines [23–25]. The contents of 16 analytes were set as variables, while 37 batches of samples were set as observations. The score scatter plot and the loading scatter plot are displayed in Fig. 3. The first, second and third principal components described 52.2%, 12.6% and 10.9% of the variability in the original observations, respectively, consequently the first three principal components accounted for 75.6% of the total variance. The PCA score scatter plot showed that all samples of Sargentodoxae Caulis (D1–D7) clustered in a small region, which could distinguish from the samples of Spatholobi Caulis. The samples of Spatholobi Caulis (J1–J30) were also clustered in one region but within a larger sphere, sample J7, J9, J19 and J25 were relatively discrete, which indicated the quality of the four samples were less stable compared with other samples. In the loading scatter plot, it could be observed that different variables have different contributions in samples differentiation, the points located near to each other indicated the contents of principal components were similar. Compound 4 (procyanidin B2 ) and 5 (epicatechin) had the highest scores from the three principal components absolute values, which demonstrated that these two compounds had significant relationship with sample variations. The PCA results indicated the chemical compositions of Spatholobi Caulis and Sargentodoxae Caulis were significantly different, and quantitative analysis based on HPLC–MS/MS was a feasible method for quality assessment and control of Spatholobi Caulis.
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No. Compounds
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Gallocatechin Epigallocatechin Catechin Procyanidin B2 Epicatechin Taxifolin Ononin Liquiritigenin Daidzein Calycosin Naringenin Genistein Isoliquiritigenin Formononetin Prunetin Biochanin A
Regression equation
r2
Linear range (ng/ml)
Y = 12.628X + 0.8537 0.9994 8.60–17200 Y = 11.345X + 0.2081 0.9998 10.20–20400 Y = 7.7564X + 0.5950 0.9995 8.20–16400 Y = 1.6432X − 0.2849 0.9978 8.64–21600 Y = 7.9748X + 0.7464 0.9995 10.00–20000 Y = 4.1171X − 0.0955 0.9991 1.92–4800 Y = 49.418X + 6.9135 0.9957 8.16–8160 Y = 9.8575X + 0.7478 0.9982 4.68–9360 Y = 7.4279X + 0.0204 0.9990 3.68–368 Y = 16.399X + 0.0196 1.0000 0.92–920 Y = 9.2816X − 0.0295 0.9999 4.08–20400 Y = 3.7792X − 0.0204 0.9997 5.00–500 Y = 10.945X + 0.3321 0.9990 8.08–4040 Y = 7.7583X + 0.0356 0.9999 8.32–832 Y = 2.2527X − 0.0514 0.9996 2.96–7400 Y = 2.1744X − 0.0118 0.9998 1.76–4400
LOQ (ng/ml)
0.86 1.02 0.82 0.86 1.00 1.92 0.10 0.94 0.74 0.92 4.08 5.00 0.40 0.83 1.48 1.76
LOD (ng/ml)
0.22 0.26 0.41 0.22 0.50 0.96 0.04 0.23 0.37 0.18 0.82 2.00 0.20 0.42 0.30 0.88
Precision RSD (%)
Intra-day (n = 6)
Inter-day (n = 9)
1.03 0.68 1.17 1.89 1.74 3.63 1.51 1.27 3.97 3.16 1.39 4.75 0.94 1.59 3.17 3.98
3.58 4.60 4.37 3.99 3.61 2.98 2.23 3.29 2.48 4.03 2.87 4.31 4.03 2.74 4.24 4.35
Repeatability RSD (%) (n = 6)
3.50 4.88 3.70 3.36 3.40 1.73 3.78 3.67 3.93 4.02 4.25 3.73 3.40 4.53 3.99 4.56
Stability RSD (%)
4.72 3.23 3.32 3.03 2.78 3.06 3.29 1.45 2.77 3.77 2.44 4.41 1.85 4.42 4.37 4.35
Recovery (n = 6)
Original (g)
Spiked (g)
Detected (g)
Recovery (%)
RSD (%)
45.47 110.26 202.15 145.50 347.89 0.87 12.35 1.11 0.85 0.27 1.43 1.48 2.02 5.82 0.85 0.43
48.96 120.65 210.90 148.00 335.00 0.88 12.35 1.14 1.01 0.28 1.45 1.50 2.70 4.80 0.80 0.40
95.52 237.20 424.15 299.59 671.45 1.70 24.82 2.24 1.90 0.54 2.89 3.00 4.78 10.29 1.61 0.84
102.23 105.21 105.26 104.11 96.59 94.32 100.97 99.12 103.96 96.43 100.69 101.33 102.22 93.12 95.00 102.50
3.53 1.86 4.66 2.91 2.72 2.54 1.12 4.61 3.64 3.58 2.89 4.34 4.10 1.65 2.55 3.46
Y. Zhang et al. / Journal of Pharmaceutical and Biomedical Analysis 102 (2015) 110–118
Table 2 Regression equation, LOD and LOQ, precision, repeatability, stability and recovery of 16 investigated compounds.
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Fig. 2. Total ion MRM chromatograms of the standard solution (A) and sample (B) obtained in positive mode for the investigated compounds. The peak numbers are in accordance with the compound numbers in Fig. 1.
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Table 3 The contents of 16 compounds in Spatholobi Caulis and Sargentodoxae Caulis (g/g, n = 3). Origin
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
J1 J2 J3 J4 J5 J6 J7 J8 J9 J10 J11 J12 J13 J14 J15 J16 J17 J18 J19 J20 J21 J22 J23 J24 J25 J26 J27 J28 J29 J30 D1 D2 D3 D4 D5 D6 D7
Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Guangdong Jiangxi Jiangxi Henan Fujian Hubei Xianggang Xianggang Xianggang Guangxi Guangdong Guangdong Miandian Yunnan Guangxi Zhejiang Sichuan Yunnan Guangxi Sichuan Guangdong
308.70 222.93 235.86 161.22 20.79 315.88 461.45 232.36 464.72 137.51 203.09 13.01 62.58 198.99 67.62 42.39 65.23 120.48 240.96 129.56 176.47 74.96 228.74 148.13 147.48 404.03 258.62 197.27 56.14 98.58 – – – – – tr tr
773.32 759.45 618.38 424.08 256.42 732.41 1057.85 585.99 1171.99 525.30 522.01 168.46 324.40 598.43 306.97 138.77 431.76 333.93 667.86 360.54 551.79 282.64 678.11 465.43 396.57 242.77 621.00 607.11 289.58 451.53 – – – – – tr tr
1149.13 955.35 926.91 649.18 666.84 784.02 1718.18 817.93 1635.86 614.38 661.56 498.45 1652.94 681.58 1039.43 414.81 962.91 536.28 1072.56 634.77 485.58 329.35 910.13 727.21 633.63 838.97 904.91 411.51 867.13 563.61 202.94 543.19 163.64 112.17 123.20 18.16 151.05
1449.09 1297.84 870.29 986.31 1185.42 822.14 1200.62 684.41 1368.83 1347.53 927.21 1031.44 1189.37 890.53 1868.67 515.57 2125.03 749.11 1498.22 559.08 1920.94 679.87 846.68 824.95 750.88 956.00 873.97 679.16 1093.68 692.47 3690.29 3827.41 3496.22 1845.56 3707.86 1127.36 2409.41
2954.09 2535.37 1564.03 1735.29 1528.91 1494.68 2155.44 1195.78 2391.57 2181.91 1499.45 1539.21 2275.93 1634.88 3518.99 535.56 3719.51 1324.24 2648.47 777.11 2267.54 807.30 1613.62 1384.31 1382.92 1594.82 1474.11 870.59 1941.32 1266.48 3304.41 2811.09 2822.19 921.10 2731.41 409.46 1213.23
4.97 4.56 3.24 5.18 2.58 3.77 2.44 4.60 9.20 3.21 4.58 3.38 2.25 2.68 3.44 3.05 3.51 5.23 10.46 4.01 3.96 3.08 4.24 3.66 6.53 3.48 3.20 4.07 3.23 4.34 1.97 3.06 2.06 3.26 1.94 2.17 2.58
93.48 46.90 27.44 168.51 47.47 118.86 11.91 78.31 156.62 45.54 65.58 61.67 7.15 139.06 53.40 36.94 18.30 66.97 133.95 44.37 519.05 49.80 32.96 44.64 60.31 58.55 29.54 43.76 50.56 25.00 – – – – – – –
22.06 14.89 5.99 11.85 3.45 9.41 3.06 22.81 45.63 18.07 9.75 4.08 tr 8.30 15.31 2.72 6.72 11.10 22.20 12.60 7.18 5.18 16.40 9.35 69.98 6.40 6.28 18.89 8.00 18.45 – – – – – – –
9.87 9.15 0.40 7.10 3.80 16.62 tra 7.79 15.58 15.01 8.49 5.20 0.68 13.73 16.43 0.56 7.01 11.49 22.97 4.84 9.23 1.56 7.80 1.97 38.66 3.63 3.11 9.72 2.78 11.82 – – – – – – –
2.61 3.69 0.08 4.79 0.10 2.70 tr 1.50 3.00 6.35 2.93 2.36 tr 3.08 6.23 –b 2.86 4.91 9.82 3.16 0.99 0.42 4.38 tr 7.02 1.53 0.76 2.10 0.95 6.77 – – – – – – –
18.86 10.95 8.77 12.66 2.55 7.18 2.61 18.00 36.01 15.05 9.51 3.44 0.53 4.49 13.07 3.49 6.63 10.41 20.82 13.73 5.86 7.71 9.57 6.52 29.34 7.01 6.91 14.39 10.29 31.73 – – – – – – –
29.01 16.92 5.14 20.95 5.10 23.98 1.31 27.25 54.51 36.03 22.40 7.90 2.43 9.86 42.36 1.35 13.71 16.90 33.81 14.93 15.34 7.71 13.15 4.34 48.63 13.90 7.72 24.88 7.66 32.20 – – – – – – –
27.57 30.51 10.54 28.01 4.07 13.26 3.33 29.23 58.47 142.62 14.32 4.04 tr 12.85 16.65 2.24 7.62 23.33 46.66 21.15 9.74 5.39 31.98 11.73 97.73 9.04 6.93 29.61 8.37 25.26 – – – – – – –
69.33 54.45 11.89 102.60 26.33 42.08 18.90 43.84 87.69 74.00 53.81 30.12 13.32 49.09 101.77 9.29 36.97 41.61 83.22 45.17 264.47 16.44 33.84 40.75 82.09 27.33 14.88 36.73 10.70 85.35 – – – – – – –
21.39 6.58 3.00 5.87 1.64 16.21 1.74 7.95 15.89 14.45 12.37 1.98 1.30 3.15 11.98 1.56 6.64 12.45 24.90 7.71 9.18 4.65 5.39 1.86 20.02 8.90 3.30 11.93 1.60 7.75 – – – – – – –
a b
Less than the quantifiable limit. Not detected.
16 5.44 4.25 2.38 8.77 0.77 3.04 0.81 3.26 6.53 6.96 4.70 2.60 0.49 2.94 17.96 0.88 5.11 4.13 8.26 3.96 7.14 2.43 4.23 1.08 11.47 3.67 1.83 3.75 1.01 4.96 – – – – – – –
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Sample
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Fig. 3. PCA score scatter plot (A) and loading scatter plot (B) of 37 samples. The sample codes in score scatter plot were the same as in Table 3. The dot numbers in loading scatter plot were in accordance with the compound numbers in Fig. 1.
4. Conclusion In this study, we established an efficient and accurate HPLC–MS/MS method for simultaneous quantification of 16 compounds in Spatholobi Caulis. Quantification was carried out on a triple quadrupole instrument using MRM mode. The established methodology displayed acceptable levels of linearity, precision, repeatability and accuracy. The results showed that flavanols were the relatively abundant constituents in Spatholobi Caulis. The PCA results based on the quantitative data indicated the chemical compositions of Spatholobi Caulis and Sargentodoxae Caulis were significantly different. The proposed method could be employed for quality control assay of Spatholobi Caulis and the results obtained from the study would be helpful in the establishment of a rational quality control standard for Spatholobi Caulis. Acknowledgments This study was supported by Project in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2012BAI29B07), National Natural Science Foundation of China (81202898) and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jpba.2014.09.006. References [1] The Pharmacopoeia Commission of PRC, The Pharmacopeia of the People’s Republic of China, Part I, China Medical Science Press, Beijing, 2010. [2] E.Y. Su, H.S. Chen, J. Chin, Clinical observation on aplastic anemia treated by Spatholobus suberectus composita, Chin. Integr. Tradit. West. Med. 17 (1997) 213–215. [3] B.J. Lee, I.Y. Jo, Y.M. Bu, J.W. Park, S. Maeng, H. Kang, W. Jang, D.S. Hwang, W. Lee, K. Min, J.I. Kim, H.H. Yoo, J.H. Lew, Antiplatelet effects of Spatholobus suberectus via inhibition of the glycoprotein IIb/IIIa receptor, J. Ethnopharmacol. 134 (2011) 460–467. [4] R.W. Li, G.D. Lin, S.P. Myers, D.N. Leach, Anti-inflammatory activity of Chinese medicinal vine plants, J. Ethnopharmacol. 85 (2003) 61–67.
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Journal of Pharmaceutical and Biomedical Analysis journal homepage: www.elsevier.com/locate/jpba
Simultaneous determination of 16 phenolic constituents in Spatholobi Caulis by high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry Yu Zhang 1 , Long Guo 1 , Li Duan, Xin Dong, Ping Zhou, E.-Hu Liu ∗ , Ping Li ∗ State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing 210009, China
a r t i c l e
i n f o
Article history: Received 1 August 2014 Received in revised form 1 September 2014 Accepted 6 September 2014 Available online 16 September 2014 Keywords: Spatholobi Caulis HPLC–MS/MS Phenolic compounds Principal component analysis Quantitative analysis
a b s t r a c t Spatholobi Caulis, the vine stem of Spatholobus suberectus Dunn, has been widely used in traditional Chinese and folk medicines for treatment of irregular menstruation, blood deficiency and rheumatalgia in clinic. In this study, an accurate and reliable high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry (HPLC–MS/MS) method was established for simultaneous determination of 16 phenolic bioactive constituents, including five flavanols, seven isoflavonoids, three flavanones and one chalcone in Spatholobi Caulis. The method validation results exhibited that the developed method had desirable specificity, linearity, precision and accuracy. The quantitative analysis results showed that flavanols were the abundant constituents in Spatholobi Caulis. Moreover, principal component analysis (PCA) was performed to assess the quality variation of samples collected from different regions in China. The PCA results indicated the quantitative analysis based on HPLC–MS/MS is a feasible method for quality assessment and control of Spatholobi Caulis. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Spatholobi Caulis, the vine stem of Spatholobus suberectus Dunn of the family Leguminosae, is specified in Chinese Pharmacopoeia (2010 version) with the name of Jixueteng. It has been widely used in traditional medicines for the treatment of blood stasis syndrome, rheumatism and menoxenia [1]. Pharmacological and clinical studies have demonstrated that Spatholobi Caulis possesses a variety of functions, including blood circulation improvement, antiplatelet, anti-inflammation, anti-bacterial, neuroprotection, and anti-cancer effects [2–7]. Phytochemical studies indicated that polyphenolic compounds, including flavanols, isoflavonoids, flavanones and chalcone, were the main bioactive components in Spatholobi Caulis [8,9]. Although there have been a few studies regarding the quantification of the active components in Spatholobi Caulis [10,11], rather limited investigations have been conducted for simultaneous determination of multicomponent in this herbal medicine. In Chinese
∗ Corresponding authors. Tel.: +86 25 83271379; fax: +86 25 83271379. E-mail addresses: [email protected] (E.-H. Liu), [email protected], [email protected] (P. Li). 1 The authors contributed equally to this work. http://dx.doi.org/10.1016/j.jpba.2014.09.006 0731-7085/© 2014 Elsevier B.V. All rights reserved.
Pharmacopoeia (2010 version), only thin layer chromatography (TLC) method was applied to authentication of Spatholobi Caulis using a single qualitative marker compound (formononetin), and no assay method has been developed, indicating the quality evaluation of this herbal medicine was insufficient. Moreover, there is an adulterant named Sargentodoxae Caulis (daxueteng) in the herbal medicine market. Spatholobi Caulis and Sargentodoxae Caulis are usually utilized under the same name “xueteng” in different areas, and are confusable for the morphological and macroscopic similarity [12]. The phenomena of homonym in prescription are confusing and unscientific or even dangerous in clinical therapy. In view of the current situation, it is necessary to develop a rapid and reliable method to evaluate the bioactive components for quality control of Spatholobi Caulis. It is well accepted that herbal medicines exert their curative effects through multiple components on multiple target sites [13]. Therefore, development of reliable methods to quantify multiple bioactive components for their comprehensive quality control has become a rational strategy [14,15]. Presently, several analytical techniques, such as thin layer chromatography (TLC), gas chromatography (GC), high performance liquid chromatography–ultraviolet detection (HPLC–UV), HPLC coupled with evaporative light scattering detection (HPLC–ELSD) and HPLC coupled to mass spectrometry (HPLC–MS), have already been
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widely used for the quality control of traditional Chinese medicines [16–19]. Among the analytical methods, the HPLC–MS technique has the advantages of abundant mass fragmentations and many scan modes afforded by tandem mass spectrometry can provide the required specificity and sensitivity, therefore, it is appropriate for simultaneous determination of multiple constituents of herbal medicines [20,21]. Since the constituents in Caulis Spatholobi are extremely complex and some are present in trace amounts, it is a tough and time-consuming task to simultaneously determine multiple constituents by HPLC–UV method. In this work, an accurate and reliable high performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry (HPLC–MS/MS) method was established for determination of phenolic bioactive constituents in Spatholobi Caulis. A total of 16 phenolic constituents, including 5 flavanols, 7 isoflavonoids, 3 flavanones and 1 chalcone were selected as the marker compounds [10]. Multiple reaction monitoring (MRM), a tandem MS scan mode unique to triple quadrupole MS instrumentation, was employed for quantification in the present study. The validated method was applied to evaluate the quality of the samples from different geographical regions, and the results were further analyzed by principal component analysis (PCA) to provide more information about the chemical differences in each sample.
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2. Experimental 2.1. Chemicals, materials and reagents The reference compounds of gallocatechin (1), epigallocatechin (2), catechin (3), procyanidin B2 (4), epicatechin (5), taxifolin (6), ononin (7), liquiritigenin (8), daidzein (9), calycosin (10), naringenin (11), genistein (12), isoliquiritigenin (13), formononetin (14), prunetin (15), biochanin A (16) were purchased from Chengdu Must Bio-technology Co., Ltd. (Chengdu, China). The internal standard (I.S.) 5,7-dimethoxycoumarin was obtained from Aldrich chemical company, Inc. (Milwaukee, WI, USA). The structures of 16 reference compounds are shown in Fig. 1. The purities of these compounds were determined to be higher than 95% by high performance liquid chromatography–diode array detection analysis. 30 batches of Spatholobi Caulis collected in present study were the vine stem of S. suberectus Dunn from different provinces in China. 7 batches of the adulterants of Sargentodoxae Caulis were also collected for the experiment. The origins of the 37 batches of samples are shown in Table 3. The voucher specimens, identified by Prof. Ping Li from Department of Pharmacognosy in China Pharmaceutical University, have been deposited in the State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Fig. 1. Chemical structures of 16 reference substances.
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Methanol and formic acid of MS grade were purchased from Merck (Darmstadt, Germany). Ultrapure water was prepared using a Milli-Q water purification system (Millipore, Bedford, MA, USA). HPLC grade methanol (Nanjing Chemical Reagent Factory, China) was used for sample preparation. 2.2. Instrument and chromatographic conditions Chromatographic analysis was performed on an Agilent series 1290 HPLC system equipped with a quaternary pump, a degasser, an autosampler, a thermostated column compartment (Agilent Technologies, Palo Alto, CA, USA). Chromatographic separation was performed on an Agilent Eclipse plus C18 (4.6 mm × 50 mm, 1.8 m) column with an on-line filter in front of the column. The mobile phase was composed of 0.3% formic acid (A) and methanol (B), with a gradient elution as follows: 0 min, 15% (B); 5 min, 30% (B); 10 min, 40% (B); 14 min, 45% (B); 16 min, 45% (B); 20 min, 55% (B); 25 min, 100% (B). The flow rate was 0.5 ml/min, and the column temperature was set at 30 ◦ C. MS experiments were conducted on an Agilent 6460 triple quadrupole mass spectrometer equipped with electrospray ionization source (Agilent Technologies, Palo Alto, CA, USA). Quantification was performed in the positive ionization by MRM mode. The MS conditions were as follows: drying gas temperature, 300 ◦ C; drying gas flow, 10 L/min; sheath gas temperature, 250 ◦ C; sheath gas flow, 5 L/min; nebulizer pressure, 45 psi; capillary voltage, 4000 V. Data acquisition was performed with Agilent MassHunter Workstation. 2.3. Preparation of standard solutions Each standard solution was accurately weighed, and then dissolved in methanol–water (80:20, v/v) solvent to give the stock solutions. Working standard solutions containing 16 reference standards respectively detected in positive ion mode were prepared by diluting the stock solutions with methanol–water (80:20, v/v) solvent to a series of proper concentrations. To each standard solution, an aliquot of stock solution of 5,7-dimethoxycoumarin (I.S.) was added to make up a final concentration of 132 ng/ml. The solutions were stored at 4 ◦ C for further analysis. 2.4. Preparation of sample solutions 30 batches of Spatholobi Caulis and 7 batches of Sargentodoxae Caulis were collected from different provinces in China for the experiment. All the samples were cut into smaller pieces, further grounded into powder and passed through a 60-mesh sieve. Each sample powder (0.5 g) was weighed accurately soaked in 25 ml of 80% methanol. An appropriate amount of the internal standard solution was added, and the mixture was reflux for 2 h at 80 ◦ C. After that the extracted solution was cooled to room temperature and centrifuged at 13,000 rpm/min for 10 min. For quantification of the gallocatechin (1), epigallocatechin (2), catechin (3), procyanidin B2 (4), epicatechin (5) and ononin (7), the supernatant was firstly diluted 10 times with 80% methanol, and then an aliquot of 1 L of the sample was injected for HPLC analysis. For quantification of the other compounds, 1 L of each supernatant was directly injected into the HPLC instrument for analysis. 2.5. Method validation The calibration curves were established by injecting each working solution thrice. All calibration curves were constructed from the peak area ratio of the tested reference peak to that of the internal standard versus their concentrations. The limit of detection (LOD)
and limit of quantification (LOQ) for each analyte were defined by the concentrations that generated peaks with signal-to-noise values (S/N) of 3 and 10, respectively. The precision of the developed method was determined by the intra- and inter-day variations. For intra-day test, the samples were analyzed for six times within the same day, while for inter-day test, the samples were examined in duplicates for consecutive three days. The relative standard deviations (RSDs) were calculated as the measure of precision. To confirm the repeatability, six replicates of the same samples were extracted and analyzed. For the stability test, the same sample was stored at room temperature and analyzed by replicate injection at 0, 2, 4, 8, 16 and 24 h. The RSDs were used to evaluate the method repeatability and stability. Recovery was used to further evaluate the accuracy of the method. A known amount of the 16 standards were added into a 0.25 g powder of the same samples in sextuplicate, and then extracted and analyzed with the same procedures. 2.6. Data analysis Principal component analysis (PCA) was performed by SPSS 18.0. When the contents of investigated compounds were below the quantitation limit or not detected in the samples, the values of such elements were considered to be 0. 3. Results and discussion 3.1. Optimization of extraction conditions The extraction conditions were optimized in order to obtain satisfactory extraction efficiency. The extraction methods (ultrasonic and refluxing extraction), extraction solvents (60% methanol, 80% methanol, and 100% methanol) and extraction time (1, 2, and 3 h) were optimized by using univariate test. The results (Supplementary Table 1) showed that refluxing extraction was more effective than ultrasonic extraction, and 80% methanol was the most efficient extraction solvent among the tested different concentrations of methanol. In addition, it demonstrated that the target components could be extracted completely within 2 h. Refluxing extraction with 25 ml of 80% methanol for 2 h was finally selected for sample preparation. 3.2. Optimization of LC conditions In order to achieve rapid and efficient analysis, a short chromatographic column packed with 1.8 m porous particles was employed in HPLC system. Different mobile phase (including methanol–water, acetonitrile–water, methanol–formic acid solution, and acetonitrile–formic acid solution), flow rate (0.4, 0.5 and 0.6 ml/min) as well as column temperature (25, 30, and 35 ◦ C) were examined and compared. As a result, methanol–0.3% formic acid solution at a flow rate of 0.5 ml/min with the column temperature of 30 ◦ C resulted in satisfactory separation in a short analysis time. 3.3. Optimization of MS conditions In order to develop a sensitive and accurate quantitative method, the MS/MS fragmentation patterns for each compound were investigated. Firstly, MS spectra were studied in both positive and negative modes. All analytes showed maximum sensitivity operating in the positive ion mode. For the optimization of MRM conditions, the parameters of fragmentor voltage (FV) and collision energy (CE) were optimized to get the richest relativeabundance of
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Table 1 Retention time, related MS data of the target compounds. No.
Compound
RT (min)
[M + H]+ (m/z)
Precursor ion
Product ion
FV (V)
CE (V)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 I.S.
Gallocatechin Epigallocatechin Catechin Procyanidin B2 Epicatechin Taxifolin Ononin Liquiritigenin Daidzein Calycosin Naringenin Genistein Isoliquiritigenin Formononetin Prunetin Biochanin A 5,7-Dimethoxycoumarin
2.54 4.15 4.37 4.67 6.29 8.72 13.51 13.97 15.46 16.99 17.45 19.16 22.36 23.01 23.79 24.06 17.66
307.1 307.1 291.1 579.1 291.1 305.1 431.1 257.1 255.1 285.1 273.1 271.1 257.1 269.1 285.1 285.1 207.0
307.1 307.1 291.1 579.2 291.1 305.1 431.1 257.1 255.1 285.1 273.0 271.1 257.0 269.1 285.1 285.1 207.0
139.0 139.0 139.0 291.1 139.0 153.1 269.1 137.1 199.1 270.0 153.0 91.0 137.1 197.1 167.1 213.1 91.1
100 100 90 120 90 105 100 125 155 135 120 155 115 135 165 160 90
13 13 13 13 13 15 10 15 29 25 15 35 15 35 30 35 30
precursor and product ions. The MS/MS product ion spectra of the analytes are shown in Supplementary Fig. 1. The retention time (RT) and MS information for each analyte including [M + H]+ , precursor and product ions, FV and CE are shown in Table 1. 3.4. Method validation The calibration curves exhibited good linearity (r2 > 0.9957) within the test range. The LODs and LOQs were less than 2.0 ng/ml and 5.0 ng/ml, respectively. The intra- and inter-day variations (RSDs) for 16 analytes were less than 4.75 and 4.35%, respectively. The repeatability presented as RSDs was in the range from 1.73 to 4.88%, and the stability was less than 4.72%. The recoveries varied between 93.12 and 105.21% with RSDs less than 4.66%. The above data (Table 2) were considered to be satisfactory for subsequent analysis of all the samples. 3.5. Quantification of 16 phenolic compounds in Spatholobi Caulis 3.5.1. Quantitative analysis of samples The validated method was applied to analyze 37 samples, including 30 batches of Spatholobi Caulis (J1–J30) and 7 batches of Sargentodoxae Caulis (D1–D7). A total of 16 phenolic compounds, including 5 flavanols (gallocatechin, epigallocatechin, catechin, procyanidin B2 and epicatechin), 7 isoflavonoids (ononin, daidzein, calycosin, genistein, formononetin, prunetin and biochanin A), 3 flavanones (taxifolin, liquiritigenin and naringenin) and 1 chalcone (isoliquiritigenin) were quantified with the internal standard method based on respective calibration curves. The typical MRM chromatograms are shown in Fig. 2 and the quantitative results are presented in Table 3. As shown in the results, only 4 phenolic constituents were quantified in Sargentodoxae Caulis, other constituents were hardly detected. The results indicated that the bioactive constituents of Spatholobi Caulis and Sargentodoxae Caulis were quite different. The constituents which were not detected in Sargentodoxae Caulis could be considered as the characteristic components of Spatholobi Caulis. The total contents of each type of compounds were calculated, and it was clearly shown that flavanols (including gallocatechin, epigallocatechin, catechin, procyanidin B2 and epicatechin) with the total content range of 1647–7304 g/g were the most abundant constituents among the analytes. Among the flavanols, procyanidin B2 (4) and epicatechin (5) were present in higher concentrations with mean values of 1063 and 1794 g/g,
respectively. It should be noted that the contents of flavones were low in Spatholobi Caulis, even some active compounds could not be quantified or detected in several samples. Ononin (7) and formononetin (14), two bioactive isoflavonoids, were relatively abundant and their mean concentrations were 77.9 and 53.6 g/g, respectively. The results suggested that HPLC–MS/MS was a very powerful technique for quantitative analysis of multicomponent of herbal medicines in terms of time saving and sensitivity.
3.5.2. Quality assessment of Spatholobi Caulis In this study, principal component analysis (PCA) was further carried out to provide more information about the chemical differences of Spatholobi Caulis and Sargentodoxae Caulis and assess the quality variation of samples collected from different places in China. PCA is an unsupervised pattern recognition method used for analyzing, classifying and reducing the dimensionality of numerical datasets in a multivariate problem [22], and it has been widely used for the quality control of herbal medicines [23–25]. The contents of 16 analytes were set as variables, while 37 batches of samples were set as observations. The score scatter plot and the loading scatter plot are displayed in Fig. 3. The first, second and third principal components described 52.2%, 12.6% and 10.9% of the variability in the original observations, respectively, consequently the first three principal components accounted for 75.6% of the total variance. The PCA score scatter plot showed that all samples of Sargentodoxae Caulis (D1–D7) clustered in a small region, which could distinguish from the samples of Spatholobi Caulis. The samples of Spatholobi Caulis (J1–J30) were also clustered in one region but within a larger sphere, sample J7, J9, J19 and J25 were relatively discrete, which indicated the quality of the four samples were less stable compared with other samples. In the loading scatter plot, it could be observed that different variables have different contributions in samples differentiation, the points located near to each other indicated the contents of principal components were similar. Compound 4 (procyanidin B2 ) and 5 (epicatechin) had the highest scores from the three principal components absolute values, which demonstrated that these two compounds had significant relationship with sample variations. The PCA results indicated the chemical compositions of Spatholobi Caulis and Sargentodoxae Caulis were significantly different, and quantitative analysis based on HPLC–MS/MS was a feasible method for quality assessment and control of Spatholobi Caulis.
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No. Compounds
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Gallocatechin Epigallocatechin Catechin Procyanidin B2 Epicatechin Taxifolin Ononin Liquiritigenin Daidzein Calycosin Naringenin Genistein Isoliquiritigenin Formononetin Prunetin Biochanin A
Regression equation
r2
Linear range (ng/ml)
Y = 12.628X + 0.8537 0.9994 8.60–17200 Y = 11.345X + 0.2081 0.9998 10.20–20400 Y = 7.7564X + 0.5950 0.9995 8.20–16400 Y = 1.6432X − 0.2849 0.9978 8.64–21600 Y = 7.9748X + 0.7464 0.9995 10.00–20000 Y = 4.1171X − 0.0955 0.9991 1.92–4800 Y = 49.418X + 6.9135 0.9957 8.16–8160 Y = 9.8575X + 0.7478 0.9982 4.68–9360 Y = 7.4279X + 0.0204 0.9990 3.68–368 Y = 16.399X + 0.0196 1.0000 0.92–920 Y = 9.2816X − 0.0295 0.9999 4.08–20400 Y = 3.7792X − 0.0204 0.9997 5.00–500 Y = 10.945X + 0.3321 0.9990 8.08–4040 Y = 7.7583X + 0.0356 0.9999 8.32–832 Y = 2.2527X − 0.0514 0.9996 2.96–7400 Y = 2.1744X − 0.0118 0.9998 1.76–4400
LOQ (ng/ml)
0.86 1.02 0.82 0.86 1.00 1.92 0.10 0.94 0.74 0.92 4.08 5.00 0.40 0.83 1.48 1.76
LOD (ng/ml)
0.22 0.26 0.41 0.22 0.50 0.96 0.04 0.23 0.37 0.18 0.82 2.00 0.20 0.42 0.30 0.88
Precision RSD (%)
Intra-day (n = 6)
Inter-day (n = 9)
1.03 0.68 1.17 1.89 1.74 3.63 1.51 1.27 3.97 3.16 1.39 4.75 0.94 1.59 3.17 3.98
3.58 4.60 4.37 3.99 3.61 2.98 2.23 3.29 2.48 4.03 2.87 4.31 4.03 2.74 4.24 4.35
Repeatability RSD (%) (n = 6)
3.50 4.88 3.70 3.36 3.40 1.73 3.78 3.67 3.93 4.02 4.25 3.73 3.40 4.53 3.99 4.56
Stability RSD (%)
4.72 3.23 3.32 3.03 2.78 3.06 3.29 1.45 2.77 3.77 2.44 4.41 1.85 4.42 4.37 4.35
Recovery (n = 6)
Original (g)
Spiked (g)
Detected (g)
Recovery (%)
RSD (%)
45.47 110.26 202.15 145.50 347.89 0.87 12.35 1.11 0.85 0.27 1.43 1.48 2.02 5.82 0.85 0.43
48.96 120.65 210.90 148.00 335.00 0.88 12.35 1.14 1.01 0.28 1.45 1.50 2.70 4.80 0.80 0.40
95.52 237.20 424.15 299.59 671.45 1.70 24.82 2.24 1.90 0.54 2.89 3.00 4.78 10.29 1.61 0.84
102.23 105.21 105.26 104.11 96.59 94.32 100.97 99.12 103.96 96.43 100.69 101.33 102.22 93.12 95.00 102.50
3.53 1.86 4.66 2.91 2.72 2.54 1.12 4.61 3.64 3.58 2.89 4.34 4.10 1.65 2.55 3.46
Y. Zhang et al. / Journal of Pharmaceutical and Biomedical Analysis 102 (2015) 110–118
Table 2 Regression equation, LOD and LOQ, precision, repeatability, stability and recovery of 16 investigated compounds.
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Fig. 2. Total ion MRM chromatograms of the standard solution (A) and sample (B) obtained in positive mode for the investigated compounds. The peak numbers are in accordance with the compound numbers in Fig. 1.
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Table 3 The contents of 16 compounds in Spatholobi Caulis and Sargentodoxae Caulis (g/g, n = 3). Origin
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
J1 J2 J3 J4 J5 J6 J7 J8 J9 J10 J11 J12 J13 J14 J15 J16 J17 J18 J19 J20 J21 J22 J23 J24 J25 J26 J27 J28 J29 J30 D1 D2 D3 D4 D5 D6 D7
Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Guangxi Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Yunnan Guangdong Jiangxi Jiangxi Henan Fujian Hubei Xianggang Xianggang Xianggang Guangxi Guangdong Guangdong Miandian Yunnan Guangxi Zhejiang Sichuan Yunnan Guangxi Sichuan Guangdong
308.70 222.93 235.86 161.22 20.79 315.88 461.45 232.36 464.72 137.51 203.09 13.01 62.58 198.99 67.62 42.39 65.23 120.48 240.96 129.56 176.47 74.96 228.74 148.13 147.48 404.03 258.62 197.27 56.14 98.58 – – – – – tr tr
773.32 759.45 618.38 424.08 256.42 732.41 1057.85 585.99 1171.99 525.30 522.01 168.46 324.40 598.43 306.97 138.77 431.76 333.93 667.86 360.54 551.79 282.64 678.11 465.43 396.57 242.77 621.00 607.11 289.58 451.53 – – – – – tr tr
1149.13 955.35 926.91 649.18 666.84 784.02 1718.18 817.93 1635.86 614.38 661.56 498.45 1652.94 681.58 1039.43 414.81 962.91 536.28 1072.56 634.77 485.58 329.35 910.13 727.21 633.63 838.97 904.91 411.51 867.13 563.61 202.94 543.19 163.64 112.17 123.20 18.16 151.05
1449.09 1297.84 870.29 986.31 1185.42 822.14 1200.62 684.41 1368.83 1347.53 927.21 1031.44 1189.37 890.53 1868.67 515.57 2125.03 749.11 1498.22 559.08 1920.94 679.87 846.68 824.95 750.88 956.00 873.97 679.16 1093.68 692.47 3690.29 3827.41 3496.22 1845.56 3707.86 1127.36 2409.41
2954.09 2535.37 1564.03 1735.29 1528.91 1494.68 2155.44 1195.78 2391.57 2181.91 1499.45 1539.21 2275.93 1634.88 3518.99 535.56 3719.51 1324.24 2648.47 777.11 2267.54 807.30 1613.62 1384.31 1382.92 1594.82 1474.11 870.59 1941.32 1266.48 3304.41 2811.09 2822.19 921.10 2731.41 409.46 1213.23
4.97 4.56 3.24 5.18 2.58 3.77 2.44 4.60 9.20 3.21 4.58 3.38 2.25 2.68 3.44 3.05 3.51 5.23 10.46 4.01 3.96 3.08 4.24 3.66 6.53 3.48 3.20 4.07 3.23 4.34 1.97 3.06 2.06 3.26 1.94 2.17 2.58
93.48 46.90 27.44 168.51 47.47 118.86 11.91 78.31 156.62 45.54 65.58 61.67 7.15 139.06 53.40 36.94 18.30 66.97 133.95 44.37 519.05 49.80 32.96 44.64 60.31 58.55 29.54 43.76 50.56 25.00 – – – – – – –
22.06 14.89 5.99 11.85 3.45 9.41 3.06 22.81 45.63 18.07 9.75 4.08 tr 8.30 15.31 2.72 6.72 11.10 22.20 12.60 7.18 5.18 16.40 9.35 69.98 6.40 6.28 18.89 8.00 18.45 – – – – – – –
9.87 9.15 0.40 7.10 3.80 16.62 tra 7.79 15.58 15.01 8.49 5.20 0.68 13.73 16.43 0.56 7.01 11.49 22.97 4.84 9.23 1.56 7.80 1.97 38.66 3.63 3.11 9.72 2.78 11.82 – – – – – – –
2.61 3.69 0.08 4.79 0.10 2.70 tr 1.50 3.00 6.35 2.93 2.36 tr 3.08 6.23 –b 2.86 4.91 9.82 3.16 0.99 0.42 4.38 tr 7.02 1.53 0.76 2.10 0.95 6.77 – – – – – – –
18.86 10.95 8.77 12.66 2.55 7.18 2.61 18.00 36.01 15.05 9.51 3.44 0.53 4.49 13.07 3.49 6.63 10.41 20.82 13.73 5.86 7.71 9.57 6.52 29.34 7.01 6.91 14.39 10.29 31.73 – – – – – – –
29.01 16.92 5.14 20.95 5.10 23.98 1.31 27.25 54.51 36.03 22.40 7.90 2.43 9.86 42.36 1.35 13.71 16.90 33.81 14.93 15.34 7.71 13.15 4.34 48.63 13.90 7.72 24.88 7.66 32.20 – – – – – – –
27.57 30.51 10.54 28.01 4.07 13.26 3.33 29.23 58.47 142.62 14.32 4.04 tr 12.85 16.65 2.24 7.62 23.33 46.66 21.15 9.74 5.39 31.98 11.73 97.73 9.04 6.93 29.61 8.37 25.26 – – – – – – –
69.33 54.45 11.89 102.60 26.33 42.08 18.90 43.84 87.69 74.00 53.81 30.12 13.32 49.09 101.77 9.29 36.97 41.61 83.22 45.17 264.47 16.44 33.84 40.75 82.09 27.33 14.88 36.73 10.70 85.35 – – – – – – –
21.39 6.58 3.00 5.87 1.64 16.21 1.74 7.95 15.89 14.45 12.37 1.98 1.30 3.15 11.98 1.56 6.64 12.45 24.90 7.71 9.18 4.65 5.39 1.86 20.02 8.90 3.30 11.93 1.60 7.75 – – – – – – –
a b
Less than the quantifiable limit. Not detected.
16 5.44 4.25 2.38 8.77 0.77 3.04 0.81 3.26 6.53 6.96 4.70 2.60 0.49 2.94 17.96 0.88 5.11 4.13 8.26 3.96 7.14 2.43 4.23 1.08 11.47 3.67 1.83 3.75 1.01 4.96 – – – – – – –
Y. Zhang et al. / Journal of Pharmaceutical and Biomedical Analysis 102 (2015) 110–118
Sample
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Fig. 3. PCA score scatter plot (A) and loading scatter plot (B) of 37 samples. The sample codes in score scatter plot were the same as in Table 3. The dot numbers in loading scatter plot were in accordance with the compound numbers in Fig. 1.
4. Conclusion In this study, we established an efficient and accurate HPLC–MS/MS method for simultaneous quantification of 16 compounds in Spatholobi Caulis. Quantification was carried out on a triple quadrupole instrument using MRM mode. The established methodology displayed acceptable levels of linearity, precision, repeatability and accuracy. The results showed that flavanols were the relatively abundant constituents in Spatholobi Caulis. The PCA results based on the quantitative data indicated the chemical compositions of Spatholobi Caulis and Sargentodoxae Caulis were significantly different. The proposed method could be employed for quality control assay of Spatholobi Caulis and the results obtained from the study would be helpful in the establishment of a rational quality control standard for Spatholobi Caulis. Acknowledgments This study was supported by Project in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2012BAI29B07), National Natural Science Foundation of China (81202898) and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jpba.2014.09.006. References [1] The Pharmacopoeia Commission of PRC, The Pharmacopeia of the People’s Republic of China, Part I, China Medical Science Press, Beijing, 2010. [2] E.Y. Su, H.S. Chen, J. Chin, Clinical observation on aplastic anemia treated by Spatholobus suberectus composita, Chin. Integr. Tradit. West. Med. 17 (1997) 213–215. [3] B.J. Lee, I.Y. Jo, Y.M. Bu, J.W. Park, S. Maeng, H. Kang, W. Jang, D.S. Hwang, W. Lee, K. Min, J.I. Kim, H.H. Yoo, J.H. Lew, Antiplatelet effects of Spatholobus suberectus via inhibition of the glycoprotein IIb/IIIa receptor, J. Ethnopharmacol. 134 (2011) 460–467. [4] R.W. Li, G.D. Lin, S.P. Myers, D.N. Leach, Anti-inflammatory activity of Chinese medicinal vine plants, J. Ethnopharmacol. 85 (2003) 61–67.
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