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Development of Ultra Performance Liquid Chromatography Tandem Mass Spectrometry Method for Simultaneous Identification and Quantitation of Potential Osteogenic Phytochemicals in Butea monosperma

Development of Ultra Performance Liquid Chromatography Tandem Mass Spectrometry Method for... Abstract An ultra performance liquid chromatography coupled with hybrid triple-quadrupole linear ion trap tandem mass spectrometry (UPLC-ESI-QqQLIT-MS-MS) method in multiple reaction monitoring mode was developed for identification and simultaneous determination of potential osteogenic compounds in ethanol extracts of different plant parts of Butea monosperma collected from different geographical regions. The chromatographic separation was carried out on an Acquity UPLC CSH C18 column (1.7 μm, 2.1 × 100 mm) with 0.1% (v/v) formic acid in water and methanol as mobile phase under gradient conditions in 8 min. The developed method was validated according to the guidelines of international conference on harmonization. The correlation coefficients of all the calibration curves were ≥0.9995 and recoveries ranged from 95.2 to 105.8% (RSD ≤ 1.95%). Relative standard deviations of intra-day, inter-day precisions and stability were ≤1.74, 1.84 and 2.8%, respectively. The quantitative results showed remarkable differences in the content of all potential osteogenic compounds in different parts of the plant as well as samples from different geographical regions. Quantitative variations studied from principal component analysis indicated tentative markers for B. monosperma cultivars which can discriminate sample of different geographical regions. Introduction Butea monosperma (Lam.) Taub (Syn. Butea frondosa) is commonly known as Flame of the Forest (1). It is mainly reported for the treatment of diarrhea, diabetes, sore throat (2) and has been known to exhibit a wide variety of biological activities like anti-fertility (3), anti-diabetic (4), anti-tumor and anti-asthmatic (5). The important bioactive metabolites of B. monosperma are butin, isobutrin, butrin, biochanin A, calycosin, ononin, lupeonone, lupeol, flemmichapparin C, buteaspermin A, buteaspermin B, buteaspermanol, cladrin and genistein (1, 6). Recent phytochemical investigation on the ethanol extract (EE) of bark of B. monosperma has resulted in the isolation and identification of compounds daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] (Figure 1) as the principle constituents using bioassay-guided fractionation (1). Medicarpin [7] has shown significant osteogenic activity in a dose-dependent manner (7). The actual quantity of these compounds in B. monosperma plant parts is important to evaluate the quality and bioactivity. Figure 1. View largeDownload slide Compounds isolated from B. monosperma bark. Figure 1. View largeDownload slide Compounds isolated from B. monosperma bark. Several analytical methods, such as high-performance thin-layer chromatography (8) high-performance liquid chromatography (9) and gas chromatography-mass spectrometry (10) have been developed for the determination of the secondary metabolites in plant extracts of B. monosperma. However, these methods lack high resolution, high sensitivity and selectivity or large consumption of solvents and longer analysis time (11, 12). UPLC-triple-quadrupole tandem MS (UPLC-ESI-QqQLIT-MS-MS) with multiple reactions monitoring (MRM) mode serve as the preferred technique for the detection of selected metabolites in plant extracts (13–17). Hence, an UPLC-ESI-QqQLIT-MS-MS method was developed and validated for simultaneous quantitation of potential osteogenic compounds in B. monosperma leaf, stem, twig, bark and samples from different geographical regions. Experimental Chemicals and materials Acetonitrile, methanol (LC-MS grade) and formic acid (analytical grade) were purchased from Fluka, Sigma-Aldrich (St. Louis, MO, USA). AR grade ethanol was purchased from Merck Millipore (Darmstadt, Germany). Milli-Q Ultra-pure water was obtained from Millipore water purification system (Millipore, Milford, MA, USA). The reference standards with purity ≥95% of daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] were isolated and collected from bark of B. monosperma by Maurya et al. (1). Leaf and bark of B. monosperma were collected from Jammu, (leaf; J1 BL, bark; J1 BB), Vijaypura, (leaf; J2 BL, bark; J2 BB), Uttarbehni, (leaf; J3 BL, bark; J3 BB), Uttar Pradesh (leaf; UP BL, bark; UP BB) and Mizoram (leaf; Mz BL, bark; Mz BB), from naturally growing population. Stem (Mz ST) and twig (Mz TW) of B. monosperma were also procured from Mizoram University campus. The voucher specimens of collected plant material are reported in Supplementary Table SI. Extraction and isolation The dry plant parts of B. monosperma were homogeneously powdered by a pulverizer. The dried powder of each part (~15 g) was weighed and sonicated with 150 mL of 100% ethanol for 30 min at 25°C temperature using ultrasonic water bath (53 KHz), and left for 24 h at room temperature (~26–28°C.). This extraction process was carried out in three repeats for each sample. The total filtrate from three repeats of each sample were combined and filtered through Whatman filter paper and evaporated to dryness under reduced pressure using rotatory evaporator (Buchi Rotavapor-R2, Flawil, Switzerland) at 40°C. In case of B. monosperma bark, EE was further, triturated with acetone (3 × 20 mL). Acetone soluble fraction (AF) was concentrated under reduced pressure and used for analysis. Sample preparation Dried residues (~1 mg) were weighed accurately and dissolved in 1 mL of 100% methanol using ultrasonicator (Bandelin SONOREX, Berlin). The solutions were filtered through 0.22- μm syringe filter (Millex-GV, PVDF, Merck Millipore, Darmstadt, Germany). The filtrates were further diluted with methanol to final working concentration. About 2 μL aliquot was injected into the UPLC–MS-MS system for analysis. Preparation of calibration standards solution Primary stock solutions of compounds daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] were individually prepared by dissolving the compounds in methanol to achieve desired concentration of 1 mg/mL. A mixed standard stock solution containing compounds [1–9] was also prepared in methanol. Then, the working standard solutions were prepared by diluting the mixed standard stock solution with methanol to a series of concentrations within the ranges 0.5–1,500 ng/mL for plotting calibration curves (Supplementary Table SII). The calibration curves were constructed by plotting the value of peak areas versus the value of concentrations of each compound. All stock solutions were stored at −20°C until use. Instrumentation and analytical conditions An acquity ultra performance liquid chromatography (UPLC) system consisting of an auto sampler and a binary pump (Waters, Milford, MA) equipped with a 10-μL loop was used. The compounds were separated on an Acquity UPLC CSH C18 column (1.7 μm, 2.1 × 100 mm, Waters, Milford, MA) analytical column at 30◦C. A gradient elution was achieved using two solvents: 0.1% (v/v) formic acid in water (A) and mehanol (B) at a flow rate of 0.35 mL/min. The gradient program consisted of an initial hold to 50% (B) till 2 min then increased from 50 to 53% (B) in 3 min, 53 to 56% (B) in 4.5 min, 56 to 60% (B) in 5.5 min, 60 to 65% (B) in 6 min, 65 to 98% (B) in 6.8 min, 98 to 90% (B) in 7.2 min, 90 to 50% (B) in 7.5 min, followed by initial condition of 50% B till 8.0 min, with a sample injection volume of 2 μL. The UPLC system was interfaced with hybrid linear ion trap triple-quadrupole mass spectrometer (API 4000 QTRAP™ MS-MS system from AB Sciex, Concord, ON, Canada) equipped with electrospray (Turbo V™) ion source. ESI in negative ion mode were used to optimize the parameters which were as follows: the ion spray voltage was −4,200 V, the turbo spray temperature, 550◦C; nebulizer gas, 20 psi; heater gas, 20 psi; collision gas, and curtain gas at 20 psi. Optimization of the mass spectrometric conditions were carried out by infusing 100 ng/mL solutions of the compounds dissolved in methanol at 10 μL/min flow rate using a Harvard syringe pump (Harvard Apparatus, South Natick, MA, USA). The full range scan from m/z 100 to 1,000 in-ESI-MS analysis was recorded. The precursor ion, product ion, corresponding declustering potential (DP), entrance potential (EP), collision energy (CE) and cell exit potential (CXP) were optimized and the most intense product ion from precursor ion of each compound was chosen for the MRM (Table I). Analyst 1.5.1 software (AB Sciex) was used for data acquisition and data processing. Table I. Compound Dependent Parameters (MRM) of Compounds 1–9 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 DP, declustering potential; EP, entrance potential; CE, collision energy; CXP, cell exit potential. Table I. Compound Dependent Parameters (MRM) of Compounds 1–9 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 DP, declustering potential; EP, entrance potential; CE, collision energy; CXP, cell exit potential. Analytical method validation The developed UPLC–MS method was validated according to the guidelines of international conference on harmonization (ICH, Q2R1) by specificity, selectivity, linearity, LODs and LOQs, precision, stability and recovery (18). Specificity and selectivity Stock solutions of the extracts and standard compounds were prepared in methanol. The chromatographic interferences were assessed by comparing chromatograms of blank methanol and the methanol samples spiked with compounds [1–9]. Linearity of calibration curves The linearity of the method was established by constructing calibration curves over a concentration range from 0.5 to 1,500 ng/mL. Six concentrations of calibration standard solution were used and analyzed in triplicate, to construct the calibration curves by plotting the ratios of the peak areas of each standard to the concentration of each compound (Table I). The slope, intercept, and correlation coefficient of each calibration curve were determined by linear regression analysis. Limits of detections and limits of quantitations The limits of detections (LODs) and limits of quantitations (LOQs) were defined as a signal-to-noise ratio (S/N) equal to 3.3 and 10, respectively. Precision, stability and recovery Intra- and inter-day variations were chosen to determine the precision of the developed method. For intra-day precision test, the standard solutions were analyzed for six replicates within one day, while for inter-day precision test, the solutions were examined in duplicate on three consecutive days. In order to again assess the intra- and inter-day precision and accuracy of the assay, samples at low, medium, and high concentrations were prepared as described above. Further, the intra-day and intra-day precision of the assay were assessed for the analysis of samples in six replicates within a day and three consecutive days, respectively. The accuracy was calculated on the basis of the difference in the mean calculated concentration. In order to investigate the solution stability of the samples, each sample solution was analyzed at 0, 2, 4, 8, 12 and 24 h and variations were expressed in relative standard deviation (RSD). Recovery assays were carried out for compounds 1–9 by spiking samples with known amount of compounds at three different concentration levels (120, 100 and 80%), respectively, in triplicate. Principal component analysis Principal component analysis (PCA) was carried out on the basis of contents of compounds 1–9 in five collections of leaf and bark, which are of B. monosperma from different geographical regions in India, using Minitab 17.0 software. Results Optimization of UPLC-QqQLIT-MS/MS conditions Different columns like Acquity BEH C18 column (2.1 mm × 50 mm, 1.7 μm) and Acquity UPLC CSH C18 column (2.1 mm × 100 mm, 1.7 μm), flow rates, mobile phases and column temperatures were tested resulting in the best combination, as described in experimental section for resolution and detection of the compound 1–9. ESI positive (+) and negative (−) ion modes were evaluated, observing that the best response for compounds [1–9] was achieved in the (−) ESI mode. All the compound dependent MS parameters (precursor ion, product ion, DP and CE) were carefully optimized in (−) ESI mode by flow injection analysis (FIA) using individual standard solution. The chemical structures of all nine compounds were characterized based on their retention behavior and MS information. In the full scan mass spectra, the parent ion of daidzein (m/z 252.9) [1], cajanin (m/z 299.3) [2], isoformononetin (m/z 266.7) [3], cladrin (m/z 297.2) [4], formononetin (m/z 267.0) [5], methylformononetin (m/z 280.9) [6], medicarpin (m/z 269.0) [7], prunetin (m/z 283.0) [8] and buteaspermanol (m/z 284.9) [9] were stable in high abundance. The most intensive product ions under the product ion scan mode were for daidzein [1] at m/z 252.9 → 223.0, cajanin [2] m/z 299.3 → 164.9, isoformononetin [3] m/z 266.7 → 251.9, cladrin [4] 297.2 → 267.0, formononetin [5] m/z 267.0 → 251.9, methylformononetin [6] m/z 280.9 → 265.9, medicarpin [7] m/z 269.0 → 254.0, prunetin [8] m/z 283.0 → 267.9 and for buteaspermanol [9] at m/z 284.9 → 269.9. The mass spectrometric parameters were optimized to obtain the higher signal of precursor ions and product ions as above mentioned. Figure 2 shows the MS/MS spectra and MRM transitions of compounds [1–9]. Figure 2. View largeDownload slide ESI-MS/MS spectra and MRM transitions for isolated compounds of B. monosperma bark. Figure 2. View largeDownload slide ESI-MS/MS spectra and MRM transitions for isolated compounds of B. monosperma bark. Selectivity and specificity No interfering peaks were observed at the retention time of each compound in blank methanol sample. All compounds were rapidly eluted with retention times of 1.5, 3.6, 3.4, 2.7, 4.3, 4.8, 4.5, 5.7 and 1.9 min for daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9], respectively (Figure 3). Figure 3. View largeDownload slide Extracted ion chromatograms (XIC) of compounds, [1--9] isolated from B. monosperma bark. Figure 3. View largeDownload slide Extracted ion chromatograms (XIC) of compounds, [1--9] isolated from B. monosperma bark. Linearity, limits of detection and quantitation The calibration curves of compounds 1–9 showed a linear relationship between peak area and concentration over the range of 1–100 for daidzein [1], 0.5–20 for cajanin [2], 0.5–200 for isoformononetin [3], 0.5–25 for cladrin [4], 0.5–25 for formononetin [5], 0.5–100 for methylformononetin [6], 0.5–250 for medicarpin [7], 1–125 for prunetin [8] and 0.5–25 for buteaspermanol [9], respectively. The correlation coefficient (R2) of the calibration curves for all compounds were found more than 0.9995 (Table II). Based on the standard deviation of the response and the slope, the LODs and LOQs for each compound varied from 0.03 to 0.30 ng/mL and 0.09 to 0.92 ng/mL, respectively, (Table II) which are much lower than those reported by earlier HPLC methods (9–12). Table II. Validation Parameters of the Developed Method S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 Table II. Validation Parameters of the Developed Method S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 Precision, stability and recovery Intra-day and inter-day precisions for each compound are given in Table II. The assay values on both the occasions (intra- and inter-day) were found to be within the accepted variable limits. Intra-day and inter-day precision were less than <1.74% and 1.84%, respectively. Stability of sample solutions stored at room temperature (~26–28 °C) was investigated by replicate injections of the sample solution at 0, 2, 4, 8, 12 and 24 h. The RSDs values of stability of the nine compounds were ≤2.80%. A recovery test was applied to evaluate the accuracy of this method. Three different concentration levels (high, middle and low) of the analytical standards were added into the samples in triplicate and mean recoveries were determined. The developed analytical method had shown good accuracy with overall recovery in the range from 95.2 to 105.8% (RSD ≤ 1.95%) (Table II). Method application to real samples The developed and validated UPLC-ESI-QqQLIT-MS-MS method was applied to quantitate the potential osteogenic compounds in EE solutions of different plant/parts of B. monosperma (Supplementary Figure S1) and the contents of all compounds are listed in Table III. Table III. Contents (in mg/kg) of Compounds 1–9 in Different B. monosperma Samples and Plant Parts (n = 3) S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 bdl, below detection level. Table III. Contents (in mg/kg) of Compounds 1–9 in Different B. monosperma Samples and Plant Parts (n = 3) S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 bdl, below detection level. Discussion The results indicated that there were remarkable differences in contents of these compounds in B. monosperma plant /parts samples of different geographical regions. All compounds were also analyzed in acetone fraction of barks EE and found in good yield except methylformononetin which was below detection level (Table III). Acetone fraction was reported as a rich source of these compounds, which was in accordance with reports (1). On comparative analysis of B. monosperma leaf, stem, bark and twig collected from Mizoram daidzein [1] (2,490 mg/kg) was found as the most abundant compound in stem while cajanin [2] (53.5 mg/kg), isoformononetin [3] (24,900 mg/kg), cladrin [4] (1,195 mg/kg) and prunetine (1,45,000 mg/kg) [8] were abundant in bark. The total content of all bioactive compounds was highest in the bark. All these bioactive compounds were firstly identified and quantitated in the leaf of B. monosperma which has the second highest total content. The content of all compounds was insignificant in twig. In all geographical collection of leaf daidzein [1] (1,800 mg/kg) was highest in UP region while the isoformononetin [3] (40,600 mg/kg) was most abundant in Jammu region. The contents of medicarpin [7] (6,950 mg/kg), prunetin [8] (49,000 mg/kg) and buteaspermanol [9] (6,750 mg/kg) were also high in Jammu region (Figure 4). The total content of compounds in leaf collected from Mizoram was higher than UP sample. The total content of osteogenic compounds (compounds 1–5 and 7) was highest in the leaf of Jammu region and lowest in UP region. Formononetin was below detection level in the bark from all geographical regions. Bark of all samples was the richest source of prunetin and also found in the highest amount from Mizoram region samples (Figure 5). Total content of all bioactive compounds was highest in bark of Mizoram region. Figure 4. View largeDownload slide Comparative content of compounds [1–9] in different geographical sample of B. monosperma. Figure 4. View largeDownload slide Comparative content of compounds [1–9] in different geographical sample of B. monosperma. Figure 5. View largeDownload slide PCA score plots for discrimination of the bark (A) and leaf (B). Figure 5. View largeDownload slide PCA score plots for discrimination of the bark (A) and leaf (B). PCA-based discrimination of B. monosperma leaf and bark samples from different geographical regions PCA was applied to explore contribution of compounds 1–9 for discrimination of B. monosperma leaf and bark collected from different geographical regions of India. The content of all nine compounds in five samples of each leaf and bark were determined simultaneously and three replicate of each sample were subjected to PCA analysis. Hence, the data matrix was composed of 15 × 9 for leaf and 15 × 9 for bark samples. The PCA was performed using a correlation matrix. To discriminate the bark samples of all selected geographical region, the content of compounds [1–9] were subjected to PCA analysis in which formononetin [5] (m/z 267.0) was not significant due to zero variance. The PCA score plot from the rest eight variables completely discriminated the bark samples of selected geographical regions (Figure 5A and Supplementary Figure S2A). In case of leaf out of nine variables (content of compounds), only five variables namely daidzein [1] (m/z 252.9), cajanin [2] (m/z 299.3), isoformononetin [3] (m/z 266.7), cladrin [4] (m/z 297.2) and formononetin [5] (m/z 267.0) were able to discriminate the cases of geographical regions (Figure 5B and Supplementary Figure S2B). It indicated that the content of bioactive molecules can discriminate the case of different geographical regions and could be used as bioactive marker compounds for the B. monosperma leaf and bark. Conclusion In this study, an accurate, rapid and validated UPLC-ESI-QqQLIT-MS-MS method was developed for potential osteogenic compounds [1–9]. This is the first report for simultaneous determination of these potential osteogenic compounds in leaf, bark, stem and twig by UPLC-ESI-QqQLIT-MS-MS. The method is reproducible and has provided good validation parameters in terms of linearity, regression coefficient, LOD, LOQ, precisions, stability and recovery. Moreover, method was successfully applied in the analysis of B. monosperma leaf and bark samples collected from different regions of India. The method would find wide use in quantitating these compounds in herbal extracts from other plants and dietary supplements. PCA effectively served the purpose of discriminating the cases of geographical variation on the basis of contents of these compounds which can serve as bioactive markers for the discrimination of B. monosperma leaf and bark of different geographical regions and for quality control purposes. Supplementary data Supplementary material is available at Journal of Chromatographic Science online. Acknowledgments Grateful acknowledgement is made to SAIF, CSIR-CDRI, Lucknow, where the mass spectrometric studies were carried out. V.B. is thankful to CSIR, New Delhi. CDRI communication no-9689. References 1 Maurya , R. , Yadav , D. K. , Singh , G. , Bhargavan , B. , Narayana , P. 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Google Scholar CrossRef Search ADS 18 International Conference on Harmonisation (ICH) Guidelines, Validation of Analytical Procedures: Text Methodology Q2 (R1); ( 2005 ): Accessed in February, 2014. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Chromatographic Science Oxford University Press

Development of Ultra Performance Liquid Chromatography Tandem Mass Spectrometry Method for Simultaneous Identification and Quantitation of Potential Osteogenic Phytochemicals in Butea monosperma

Journal of Chromatographic Science , Volume 56 (8) – Sep 1, 2018
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Oxford University Press
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0021-9665
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10.1093/chromsci/bmy050
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29800074
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Abstract

Abstract An ultra performance liquid chromatography coupled with hybrid triple-quadrupole linear ion trap tandem mass spectrometry (UPLC-ESI-QqQLIT-MS-MS) method in multiple reaction monitoring mode was developed for identification and simultaneous determination of potential osteogenic compounds in ethanol extracts of different plant parts of Butea monosperma collected from different geographical regions. The chromatographic separation was carried out on an Acquity UPLC CSH C18 column (1.7 μm, 2.1 × 100 mm) with 0.1% (v/v) formic acid in water and methanol as mobile phase under gradient conditions in 8 min. The developed method was validated according to the guidelines of international conference on harmonization. The correlation coefficients of all the calibration curves were ≥0.9995 and recoveries ranged from 95.2 to 105.8% (RSD ≤ 1.95%). Relative standard deviations of intra-day, inter-day precisions and stability were ≤1.74, 1.84 and 2.8%, respectively. The quantitative results showed remarkable differences in the content of all potential osteogenic compounds in different parts of the plant as well as samples from different geographical regions. Quantitative variations studied from principal component analysis indicated tentative markers for B. monosperma cultivars which can discriminate sample of different geographical regions. Introduction Butea monosperma (Lam.) Taub (Syn. Butea frondosa) is commonly known as Flame of the Forest (1). It is mainly reported for the treatment of diarrhea, diabetes, sore throat (2) and has been known to exhibit a wide variety of biological activities like anti-fertility (3), anti-diabetic (4), anti-tumor and anti-asthmatic (5). The important bioactive metabolites of B. monosperma are butin, isobutrin, butrin, biochanin A, calycosin, ononin, lupeonone, lupeol, flemmichapparin C, buteaspermin A, buteaspermin B, buteaspermanol, cladrin and genistein (1, 6). Recent phytochemical investigation on the ethanol extract (EE) of bark of B. monosperma has resulted in the isolation and identification of compounds daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] (Figure 1) as the principle constituents using bioassay-guided fractionation (1). Medicarpin [7] has shown significant osteogenic activity in a dose-dependent manner (7). The actual quantity of these compounds in B. monosperma plant parts is important to evaluate the quality and bioactivity. Figure 1. View largeDownload slide Compounds isolated from B. monosperma bark. Figure 1. View largeDownload slide Compounds isolated from B. monosperma bark. Several analytical methods, such as high-performance thin-layer chromatography (8) high-performance liquid chromatography (9) and gas chromatography-mass spectrometry (10) have been developed for the determination of the secondary metabolites in plant extracts of B. monosperma. However, these methods lack high resolution, high sensitivity and selectivity or large consumption of solvents and longer analysis time (11, 12). UPLC-triple-quadrupole tandem MS (UPLC-ESI-QqQLIT-MS-MS) with multiple reactions monitoring (MRM) mode serve as the preferred technique for the detection of selected metabolites in plant extracts (13–17). Hence, an UPLC-ESI-QqQLIT-MS-MS method was developed and validated for simultaneous quantitation of potential osteogenic compounds in B. monosperma leaf, stem, twig, bark and samples from different geographical regions. Experimental Chemicals and materials Acetonitrile, methanol (LC-MS grade) and formic acid (analytical grade) were purchased from Fluka, Sigma-Aldrich (St. Louis, MO, USA). AR grade ethanol was purchased from Merck Millipore (Darmstadt, Germany). Milli-Q Ultra-pure water was obtained from Millipore water purification system (Millipore, Milford, MA, USA). The reference standards with purity ≥95% of daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] were isolated and collected from bark of B. monosperma by Maurya et al. (1). Leaf and bark of B. monosperma were collected from Jammu, (leaf; J1 BL, bark; J1 BB), Vijaypura, (leaf; J2 BL, bark; J2 BB), Uttarbehni, (leaf; J3 BL, bark; J3 BB), Uttar Pradesh (leaf; UP BL, bark; UP BB) and Mizoram (leaf; Mz BL, bark; Mz BB), from naturally growing population. Stem (Mz ST) and twig (Mz TW) of B. monosperma were also procured from Mizoram University campus. The voucher specimens of collected plant material are reported in Supplementary Table SI. Extraction and isolation The dry plant parts of B. monosperma were homogeneously powdered by a pulverizer. The dried powder of each part (~15 g) was weighed and sonicated with 150 mL of 100% ethanol for 30 min at 25°C temperature using ultrasonic water bath (53 KHz), and left for 24 h at room temperature (~26–28°C.). This extraction process was carried out in three repeats for each sample. The total filtrate from three repeats of each sample were combined and filtered through Whatman filter paper and evaporated to dryness under reduced pressure using rotatory evaporator (Buchi Rotavapor-R2, Flawil, Switzerland) at 40°C. In case of B. monosperma bark, EE was further, triturated with acetone (3 × 20 mL). Acetone soluble fraction (AF) was concentrated under reduced pressure and used for analysis. Sample preparation Dried residues (~1 mg) were weighed accurately and dissolved in 1 mL of 100% methanol using ultrasonicator (Bandelin SONOREX, Berlin). The solutions were filtered through 0.22- μm syringe filter (Millex-GV, PVDF, Merck Millipore, Darmstadt, Germany). The filtrates were further diluted with methanol to final working concentration. About 2 μL aliquot was injected into the UPLC–MS-MS system for analysis. Preparation of calibration standards solution Primary stock solutions of compounds daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9] were individually prepared by dissolving the compounds in methanol to achieve desired concentration of 1 mg/mL. A mixed standard stock solution containing compounds [1–9] was also prepared in methanol. Then, the working standard solutions were prepared by diluting the mixed standard stock solution with methanol to a series of concentrations within the ranges 0.5–1,500 ng/mL for plotting calibration curves (Supplementary Table SII). The calibration curves were constructed by plotting the value of peak areas versus the value of concentrations of each compound. All stock solutions were stored at −20°C until use. Instrumentation and analytical conditions An acquity ultra performance liquid chromatography (UPLC) system consisting of an auto sampler and a binary pump (Waters, Milford, MA) equipped with a 10-μL loop was used. The compounds were separated on an Acquity UPLC CSH C18 column (1.7 μm, 2.1 × 100 mm, Waters, Milford, MA) analytical column at 30◦C. A gradient elution was achieved using two solvents: 0.1% (v/v) formic acid in water (A) and mehanol (B) at a flow rate of 0.35 mL/min. The gradient program consisted of an initial hold to 50% (B) till 2 min then increased from 50 to 53% (B) in 3 min, 53 to 56% (B) in 4.5 min, 56 to 60% (B) in 5.5 min, 60 to 65% (B) in 6 min, 65 to 98% (B) in 6.8 min, 98 to 90% (B) in 7.2 min, 90 to 50% (B) in 7.5 min, followed by initial condition of 50% B till 8.0 min, with a sample injection volume of 2 μL. The UPLC system was interfaced with hybrid linear ion trap triple-quadrupole mass spectrometer (API 4000 QTRAP™ MS-MS system from AB Sciex, Concord, ON, Canada) equipped with electrospray (Turbo V™) ion source. ESI in negative ion mode were used to optimize the parameters which were as follows: the ion spray voltage was −4,200 V, the turbo spray temperature, 550◦C; nebulizer gas, 20 psi; heater gas, 20 psi; collision gas, and curtain gas at 20 psi. Optimization of the mass spectrometric conditions were carried out by infusing 100 ng/mL solutions of the compounds dissolved in methanol at 10 μL/min flow rate using a Harvard syringe pump (Harvard Apparatus, South Natick, MA, USA). The full range scan from m/z 100 to 1,000 in-ESI-MS analysis was recorded. The precursor ion, product ion, corresponding declustering potential (DP), entrance potential (EP), collision energy (CE) and cell exit potential (CXP) were optimized and the most intense product ion from precursor ion of each compound was chosen for the MRM (Table I). Analyst 1.5.1 software (AB Sciex) was used for data acquisition and data processing. Table I. Compound Dependent Parameters (MRM) of Compounds 1–9 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 DP, declustering potential; EP, entrance potential; CE, collision energy; CXP, cell exit potential. Table I. Compound Dependent Parameters (MRM) of Compounds 1–9 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 Compound no. Compound Retention time (min) Precursor (Q1) mass (Da) Product (Q3) mass (Da) Dwell time (ms) Declustering potential (eV) Entrance potential (eV) Collision energy (eV) Cell exit potential (eV) [1] Daidzein 1.5 252.9 223.0 200 −110.2 −11.0 −45.0 −12.5 [2] Cajanin 3.6 299.3 164.9 200 −94.5 −8.2 −30.0 −13.1 [3] Isoformononetin 3.4 266.7 251.9 200 −92.2 −9.0 −29.0 −22.1 [4] Cladrin 2.7 297.2 267.0 200 −141.0 −8.8 −32.0 −18.1 [5] Formononetin 4.3 267.0 251.9 200 −108.1 −9.3 −29.0 −23.1 [6] Methylformononetin 4.8 280.9 265.9 200 −175.0 −9.0 −30.0 −26.0 [7] Medicarpin 4.5 269.0 254.0 200 −81.0 −9.7 −24.5 −21.3 [8] Prunetin 5.7 283.0 267.9 200 −131.3 −10.0 −31.0 −17.1 [9] Buteaspermanol 1.9 284.9 269.9 200 −86.0 −10.5 −26.0 −22.0 DP, declustering potential; EP, entrance potential; CE, collision energy; CXP, cell exit potential. Analytical method validation The developed UPLC–MS method was validated according to the guidelines of international conference on harmonization (ICH, Q2R1) by specificity, selectivity, linearity, LODs and LOQs, precision, stability and recovery (18). Specificity and selectivity Stock solutions of the extracts and standard compounds were prepared in methanol. The chromatographic interferences were assessed by comparing chromatograms of blank methanol and the methanol samples spiked with compounds [1–9]. Linearity of calibration curves The linearity of the method was established by constructing calibration curves over a concentration range from 0.5 to 1,500 ng/mL. Six concentrations of calibration standard solution were used and analyzed in triplicate, to construct the calibration curves by plotting the ratios of the peak areas of each standard to the concentration of each compound (Table I). The slope, intercept, and correlation coefficient of each calibration curve were determined by linear regression analysis. Limits of detections and limits of quantitations The limits of detections (LODs) and limits of quantitations (LOQs) were defined as a signal-to-noise ratio (S/N) equal to 3.3 and 10, respectively. Precision, stability and recovery Intra- and inter-day variations were chosen to determine the precision of the developed method. For intra-day precision test, the standard solutions were analyzed for six replicates within one day, while for inter-day precision test, the solutions were examined in duplicate on three consecutive days. In order to again assess the intra- and inter-day precision and accuracy of the assay, samples at low, medium, and high concentrations were prepared as described above. Further, the intra-day and intra-day precision of the assay were assessed for the analysis of samples in six replicates within a day and three consecutive days, respectively. The accuracy was calculated on the basis of the difference in the mean calculated concentration. In order to investigate the solution stability of the samples, each sample solution was analyzed at 0, 2, 4, 8, 12 and 24 h and variations were expressed in relative standard deviation (RSD). Recovery assays were carried out for compounds 1–9 by spiking samples with known amount of compounds at three different concentration levels (120, 100 and 80%), respectively, in triplicate. Principal component analysis Principal component analysis (PCA) was carried out on the basis of contents of compounds 1–9 in five collections of leaf and bark, which are of B. monosperma from different geographical regions in India, using Minitab 17.0 software. Results Optimization of UPLC-QqQLIT-MS/MS conditions Different columns like Acquity BEH C18 column (2.1 mm × 50 mm, 1.7 μm) and Acquity UPLC CSH C18 column (2.1 mm × 100 mm, 1.7 μm), flow rates, mobile phases and column temperatures were tested resulting in the best combination, as described in experimental section for resolution and detection of the compound 1–9. ESI positive (+) and negative (−) ion modes were evaluated, observing that the best response for compounds [1–9] was achieved in the (−) ESI mode. All the compound dependent MS parameters (precursor ion, product ion, DP and CE) were carefully optimized in (−) ESI mode by flow injection analysis (FIA) using individual standard solution. The chemical structures of all nine compounds were characterized based on their retention behavior and MS information. In the full scan mass spectra, the parent ion of daidzein (m/z 252.9) [1], cajanin (m/z 299.3) [2], isoformononetin (m/z 266.7) [3], cladrin (m/z 297.2) [4], formononetin (m/z 267.0) [5], methylformononetin (m/z 280.9) [6], medicarpin (m/z 269.0) [7], prunetin (m/z 283.0) [8] and buteaspermanol (m/z 284.9) [9] were stable in high abundance. The most intensive product ions under the product ion scan mode were for daidzein [1] at m/z 252.9 → 223.0, cajanin [2] m/z 299.3 → 164.9, isoformononetin [3] m/z 266.7 → 251.9, cladrin [4] 297.2 → 267.0, formononetin [5] m/z 267.0 → 251.9, methylformononetin [6] m/z 280.9 → 265.9, medicarpin [7] m/z 269.0 → 254.0, prunetin [8] m/z 283.0 → 267.9 and for buteaspermanol [9] at m/z 284.9 → 269.9. The mass spectrometric parameters were optimized to obtain the higher signal of precursor ions and product ions as above mentioned. Figure 2 shows the MS/MS spectra and MRM transitions of compounds [1–9]. Figure 2. View largeDownload slide ESI-MS/MS spectra and MRM transitions for isolated compounds of B. monosperma bark. Figure 2. View largeDownload slide ESI-MS/MS spectra and MRM transitions for isolated compounds of B. monosperma bark. Selectivity and specificity No interfering peaks were observed at the retention time of each compound in blank methanol sample. All compounds were rapidly eluted with retention times of 1.5, 3.6, 3.4, 2.7, 4.3, 4.8, 4.5, 5.7 and 1.9 min for daidzein [1], cajanin [2], isoformononetin [3], cladrin [4], formononetin [5], methylformononetin [6], medicarpin [7], prunetin [8] and buteaspermanol [9], respectively (Figure 3). Figure 3. View largeDownload slide Extracted ion chromatograms (XIC) of compounds, [1--9] isolated from B. monosperma bark. Figure 3. View largeDownload slide Extracted ion chromatograms (XIC) of compounds, [1--9] isolated from B. monosperma bark. Linearity, limits of detection and quantitation The calibration curves of compounds 1–9 showed a linear relationship between peak area and concentration over the range of 1–100 for daidzein [1], 0.5–20 for cajanin [2], 0.5–200 for isoformononetin [3], 0.5–25 for cladrin [4], 0.5–25 for formononetin [5], 0.5–100 for methylformononetin [6], 0.5–250 for medicarpin [7], 1–125 for prunetin [8] and 0.5–25 for buteaspermanol [9], respectively. The correlation coefficient (R2) of the calibration curves for all compounds were found more than 0.9995 (Table II). Based on the standard deviation of the response and the slope, the LODs and LOQs for each compound varied from 0.03 to 0.30 ng/mL and 0.09 to 0.92 ng/mL, respectively, (Table II) which are much lower than those reported by earlier HPLC methods (9–12). Table II. Validation Parameters of the Developed Method S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 Table II. Validation Parameters of the Developed Method S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 S. no. Reference standards Linearity Precision (%RSD) Stability %RSD (n = 5) Recovery (n = 3) Linear range (ng/mL) R2 Regression equation LOD (ng) LOQ (ng) Intra-day (n = 6) Inter-day (n = 6) Mean RSD (%) 1. Daidzein 1.0–100 1.0000 y = 4584 × x + 697.9 0.03 0.09 0.12 0.21 1.58 102.3 1.06 2. Cajanin 0.5–20 0.9999 y = 2622 × x − 53.94 0.12 0.36 1.32 0.95 0.78 95.2 1.41 3. Isoformononetin 0.5–200 0.9995 y = 138 × x − 7.64 0.04 0.11 1.74 1.07 2.21 102.7 1.85 4. Cladrin 0.5–25 1.0000 y = 12057 × x − 700.9 0.11 0.32 1.39 1.84 2.14 98.8 0.92 5. Formononetin 0.5–25 0.9999 y = 297 × x + 84.8 0.15 0.45 0.98 1.65 2.06 105.8 1.88 6. Methylformononetin 0.5–100 1.0000 y = 432.8 × x − 0.100 0.30 0.92 0.61 1.20 2.80 101.6 1.95 7. Medicarpin 0.5–250 0.9998 y = 187 × x + 8.15 0.13 0.39 0.51 0.98 1.51 97.1 1.65 8. Prunetin 1–125 1.0000 y = 300 × x + 48.6 0.06 0.18 1.23 0.98 2.40 100.9 1.45 9. Buteaspermanol 0.5–25 0.9999 y = 10300 × x − 1620 0.05 0.14 0.11 1.01 1.56 104.2 1.32 Precision, stability and recovery Intra-day and inter-day precisions for each compound are given in Table II. The assay values on both the occasions (intra- and inter-day) were found to be within the accepted variable limits. Intra-day and inter-day precision were less than <1.74% and 1.84%, respectively. Stability of sample solutions stored at room temperature (~26–28 °C) was investigated by replicate injections of the sample solution at 0, 2, 4, 8, 12 and 24 h. The RSDs values of stability of the nine compounds were ≤2.80%. A recovery test was applied to evaluate the accuracy of this method. Three different concentration levels (high, middle and low) of the analytical standards were added into the samples in triplicate and mean recoveries were determined. The developed analytical method had shown good accuracy with overall recovery in the range from 95.2 to 105.8% (RSD ≤ 1.95%) (Table II). Method application to real samples The developed and validated UPLC-ESI-QqQLIT-MS-MS method was applied to quantitate the potential osteogenic compounds in EE solutions of different plant/parts of B. monosperma (Supplementary Figure S1) and the contents of all compounds are listed in Table III. Table III. Contents (in mg/kg) of Compounds 1–9 in Different B. monosperma Samples and Plant Parts (n = 3) S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 bdl, below detection level. Table III. Contents (in mg/kg) of Compounds 1–9 in Different B. monosperma Samples and Plant Parts (n = 3) S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 S. no. Sample Daidzein (1) Cajanin (2) Isoformononetin (3) Cladrin (4) Formononetin (5) Methylformononetin (6) Medicarpin (7) Prunetin (8) Buteaspermanol (9) 1. EE 34.6 24.7 263.5 bdl 64.5 4.665 68 43.55 5.5 2. AF 164.5 135.5 259.5 1.44 276 bdl 244.5 161.5 16.85 3. Mz ST 2,490 bdl 255 bdl 4.15 bdl 8.1 179.5 5.6 4. Mz TW 100.5 bdl 253.5 bdl 0.28 1.2 5.9 3.705 3.57 5. J1 BL 295 bdl 10600 31.75 bdl 196 1,810 10,800 820 6. J2 BL 1,230 2.79 40,600 22.95 28.25 39.05 6,950 49,000 2,605 7. J3 BL 540 bdl 32,050 bdl bdl 9.3 98 33,150 6,750 8. UP BL 1,800 2.45 660 31.95 bdl 9.3 91 1,570 795 9. Mz BL 131 4.165 3,530 147 70 227.5 2,495 22,300 1,895 10. J1 BB 288 bdl 13,900 23.9 bdl 15.8 63.5 70,000 235 11. J2 BB 156.5 bdl 13,250 1.11 bdl 18.5 123 57,000 98 12. J3 BB 56 bdl 8,000 145 bdl 2.255 67.5 41,800 7.55 13. UP BB 2,715 181.5 1,480 163 bdl 46.65 233.5 49,250 117 14. Mz BB 411 53.5 24,900 1,195 bdl 7.65 200.5 1,45,000 48.15 bdl, below detection level. Discussion The results indicated that there were remarkable differences in contents of these compounds in B. monosperma plant /parts samples of different geographical regions. All compounds were also analyzed in acetone fraction of barks EE and found in good yield except methylformononetin which was below detection level (Table III). Acetone fraction was reported as a rich source of these compounds, which was in accordance with reports (1). On comparative analysis of B. monosperma leaf, stem, bark and twig collected from Mizoram daidzein [1] (2,490 mg/kg) was found as the most abundant compound in stem while cajanin [2] (53.5 mg/kg), isoformononetin [3] (24,900 mg/kg), cladrin [4] (1,195 mg/kg) and prunetine (1,45,000 mg/kg) [8] were abundant in bark. The total content of all bioactive compounds was highest in the bark. All these bioactive compounds were firstly identified and quantitated in the leaf of B. monosperma which has the second highest total content. The content of all compounds was insignificant in twig. In all geographical collection of leaf daidzein [1] (1,800 mg/kg) was highest in UP region while the isoformononetin [3] (40,600 mg/kg) was most abundant in Jammu region. The contents of medicarpin [7] (6,950 mg/kg), prunetin [8] (49,000 mg/kg) and buteaspermanol [9] (6,750 mg/kg) were also high in Jammu region (Figure 4). The total content of compounds in leaf collected from Mizoram was higher than UP sample. The total content of osteogenic compounds (compounds 1–5 and 7) was highest in the leaf of Jammu region and lowest in UP region. Formononetin was below detection level in the bark from all geographical regions. Bark of all samples was the richest source of prunetin and also found in the highest amount from Mizoram region samples (Figure 5). Total content of all bioactive compounds was highest in bark of Mizoram region. Figure 4. View largeDownload slide Comparative content of compounds [1–9] in different geographical sample of B. monosperma. Figure 4. View largeDownload slide Comparative content of compounds [1–9] in different geographical sample of B. monosperma. Figure 5. View largeDownload slide PCA score plots for discrimination of the bark (A) and leaf (B). Figure 5. View largeDownload slide PCA score plots for discrimination of the bark (A) and leaf (B). PCA-based discrimination of B. monosperma leaf and bark samples from different geographical regions PCA was applied to explore contribution of compounds 1–9 for discrimination of B. monosperma leaf and bark collected from different geographical regions of India. The content of all nine compounds in five samples of each leaf and bark were determined simultaneously and three replicate of each sample were subjected to PCA analysis. Hence, the data matrix was composed of 15 × 9 for leaf and 15 × 9 for bark samples. The PCA was performed using a correlation matrix. To discriminate the bark samples of all selected geographical region, the content of compounds [1–9] were subjected to PCA analysis in which formononetin [5] (m/z 267.0) was not significant due to zero variance. The PCA score plot from the rest eight variables completely discriminated the bark samples of selected geographical regions (Figure 5A and Supplementary Figure S2A). In case of leaf out of nine variables (content of compounds), only five variables namely daidzein [1] (m/z 252.9), cajanin [2] (m/z 299.3), isoformononetin [3] (m/z 266.7), cladrin [4] (m/z 297.2) and formononetin [5] (m/z 267.0) were able to discriminate the cases of geographical regions (Figure 5B and Supplementary Figure S2B). It indicated that the content of bioactive molecules can discriminate the case of different geographical regions and could be used as bioactive marker compounds for the B. monosperma leaf and bark. Conclusion In this study, an accurate, rapid and validated UPLC-ESI-QqQLIT-MS-MS method was developed for potential osteogenic compounds [1–9]. This is the first report for simultaneous determination of these potential osteogenic compounds in leaf, bark, stem and twig by UPLC-ESI-QqQLIT-MS-MS. The method is reproducible and has provided good validation parameters in terms of linearity, regression coefficient, LOD, LOQ, precisions, stability and recovery. Moreover, method was successfully applied in the analysis of B. monosperma leaf and bark samples collected from different regions of India. The method would find wide use in quantitating these compounds in herbal extracts from other plants and dietary supplements. PCA effectively served the purpose of discriminating the cases of geographical variation on the basis of contents of these compounds which can serve as bioactive markers for the discrimination of B. monosperma leaf and bark of different geographical regions and for quality control purposes. Supplementary data Supplementary material is available at Journal of Chromatographic Science online. Acknowledgments Grateful acknowledgement is made to SAIF, CSIR-CDRI, Lucknow, where the mass spectrometric studies were carried out. V.B. is thankful to CSIR, New Delhi. CDRI communication no-9689. References 1 Maurya , R. , Yadav , D. K. , Singh , G. , Bhargavan , B. , Narayana , P. 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Google Scholar CrossRef Search ADS 18 International Conference on Harmonisation (ICH) Guidelines, Validation of Analytical Procedures: Text Methodology Q2 (R1); ( 2005 ): Accessed in February, 2014. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Journal of Chromatographic Science – Oxford University Press

Published: Sep 1, 2018

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