A Simple and Rapid UPLC-PDA Method for Quality Control of Nardostachys jatamansi

• Abstract
• Introduction
• Results and Discussion
• Materials and Methods
• Plant materials and reagents
• UPLC-photodiode array detection analysis
• UPLC-time-of-flight mass spectrometry analysis
• Sample preparation
• Reference compounds and standard solution preparation
• UPLC method validation
• Serotonin transporter assay
• Data analysis
• References

Abstract

Nardostachys jatamansi is a well-documented herbal agent used to treat digestive and neuropsychiatric disorders in oriental medicinal systems. However, few simple, rapid, and comprehensive methods were reported for quality assessment and control of N. jatamansi. Herein, a UPLC with photodiode array detection method was developed for both fingerprint investigation of N. jatamansi and simultaneous quantitative analysis of the six serotonin transporter modulatory constituents in N. jatamansi. For chromatographic fingerprinting, 24 common peaks were selected as characteristic peaks to assess the consistency of N. jatamansi samples from different retail sources. Six of the common peaks (5, 7, 12, and 16 – 18) were identified as desoxo-narchinol A, buddleoside, isonardosinone, nardosinone, kanshone H, and (−)-aristolone, respectively, by phytochemical investigation. Five of the six compounds significantly either enhanced or inhibited serotonin transporter activity, while (−)-aristolone (18) didnʼt show any serotonin transporter activity. In quantitative analysis, the six compounds showed good linearity (r > 0.999) within test ranges. The precision, expressed as relative standard deviation, was in the range of 0.25 – 2.77%, and the recovery of the method was in the range of 92 – 105%. The UPLC-photodiode array detection-based fingerprint analysis and quantitative methods reported here could be used for routine quality control of N. jatamansi.

Introduction

Roots and rhizomes of Nardostachys jatamansi DC. (Caprifoliaceae) have been used and are well documented in oriental medicinal systems, including traditional Chinese medicine (TCM), Ayurveda, and Unani medicine, for the treatment of digestive and neuropsychiatric disorders [1], [2], [3]. N. jatamansi (“Gansong” in Chinese) is well known for its sesquiterpenoids, including aristolane-type, nardosinane-type, and guaiane-type derivatives, possessing a variety of bioactivities such as sedative, tranquilizing, antiulcer, antidepressant, anticonvulsant, anti-arrhythmic, antiasthmatic, and anti-pancreatitis activities [1], [4], [5], [6]. Nowadays, N. jatamansi is included in many Chinese patent prescriptions, such as Wenxin Keli granules and Shensong Yangxin capsules, for the treatment of cardiac and cerebral diseases [7]. A number of constituents from N. jatamansi were found to show significant activity on the serotonin transporter (SERT) in our previous studies [8], [9]. Since SERT plays critical roles in the pathophysiology of both digestive and neuropsychiatric disorders, our continuing work is a contribution to the understanding of mechanisms underlying the traditional uses of N. jatamansi.

Until now, several analytical methods have been developed for quality control of Nardostachys species. GC-MS coupled with chemometric methods was proposed for analysis of the essential oil [10]. In addition, liquid chromatographic methods have been exploited for qualitative and quantitative analyses of the reported constituents nardosinone [11], [12], chlorogenic acid [11], valerenic acid, valeranone, and nardin [13] – [17]. Generally, these methods just focused on one or a few constituents among the abovementioned ones, and they have limitations for overall evaluation of the main constituents and their activities. Further, there is still a lack of comprehensive quality evaluation methods for future exploitation of N. jatamansi for the treatment of digestive and neuropsychiatric disorders.

Fingerprint analysis has become a routine strategy for quality control of traditional Chinese medicines and has even been introduced and accepted by the World Health Organization for the evaluation of herbal medicines [18], [19]. Thus, in the present work, a fingerprint analysis method based on UPLC with photodiode array detection (PDA) was developed for the quality assessment of N. jatamansi. In addition, five main sesquiterpenoids, including desoxo-narchinol A (5), isonardosinone (12), nardosinone (16), kanshone H (17), and (−)-aristolone (18) as well as buddleoside (7) ([Fig. 1]), were simultaneously quantified in N. chinensis and evaluated for their SERT modulating activities using a previous established protocol [8], [9].

Results and Discussion

Roots and rhizomes of N. jatamansi were extracted under sonication. To optimize the extraction conditions, the following parameters were tested: methanol-water mixtures with 0, 30, 50, 70, and 100% MeOH, plant material/solvent (m/v) ratios of 1 : 10, 1 : 20, 1 : 40, 1 : 100, and 1 : 200, and extraction times of 10, 30, 60, and 120 min. As a result, 100% MeOH was selected as the extraction solvent with a plant material/solvent ratio of 1 : 20 and an extraction time of 120 min.

In addition, mobile phase, column temperature, and wavelength detection were optimized using one of the N. jatamansi samples (sample S10) to improve resolution and sensitivity of UPLC analysis and also reduce the separation time. To avoid ionization of the acidic constituents, formic acid was added into the mobile phase. Methanol and acetonitrile were examined as organic mobile phase components, and then column temperatures of 25 and 40 °C were compared. Wavelength detection was determined by recording chromatograms with full wavelength scanning. The optimized conditions were a gradient of acetonitrile in aqueous formic acid as the mobile phase, column temperature of 40 °C, and detection wavelength at 280 nm over 31 min.

Eleven N. jatamansi samples were purchased from different retail stores all over China. They were all labeled as coming from Sichuan province in China. Among them, sample S1 was purchased from Gansu province, S2 from Guizhou province, S3 and S4 from Hebei province, S5 from Henan province, S6 from Inner Mongolia Autonomous Region, S7 from Sichuan province, S8 and S9 from Tianjin city, and S10 and S11 were purchased from Beijing city. All the samples were analyzed by UPLC-PDA under optimized chromatographic conditions. The chromatograms of the 11 batches of N. jatamansi samples are shown in [Fig. 2]. Peaks that were present in all 11 samples with good resolution were assigned as “characteristic peaks”. Thus, 24 characteristic peaks were selected in the fingerprint chromatograms, as shown in [Fig. 3 B]. The 11 chromatograms were then imported into the software Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine in which the similarities of the chromatograms for the 11 batches of samples were calculated by comparison to a reference fingerprint, which was based on the mean of all the chromatograms. The similarity values were all above 0.800, which indicated a good consistency between the 11 batches of samples (Table 4S, Supporting Information).

To identify the 24 characteristic peaks, UPLC-time-of-flight mass spectrometry (TOFMS) under both negative and positive ion modes was applied to analyze one randomly selected extract of N. jatamansi (sample 10). The MS fragmentation patterns observed in the UPLC-TOFMS analysis of nine reference compounds were used for comparison. As shown in [Table 1], 21 compounds among the 24 characteristic peaks, and 7 non-characteristic peaks were tentatively characterized. By comparing the retention times ([Fig. 3]) and MS data with those of standard compounds, seven characteristic peaks (peaks 5, 7, 9, 12, 16 – 18) were unequivocally identified as desoxo-narchinol A (5), buddleoside (7), nardosinonediol (9), isonardosinone (12), nardosinone (16), kanshone H (17), and (−)-aristolone (18), respectively. These compounds, except buddleoside, which was available as a commercial reference sample, were isolated in the course of our phytochemical study of N. jatamansi (see Experimental section, Supporting Information), and their structures were identified by comparing their NMR data with those previously reported [20], [21], [22], [23], [24]. Nardosinone (16) has been documented as the primary constituent for quality control of N. jatamansi in Chinese Phamacopoeia (Volume 1, 2015 Edition). Furthermore, this peak had a moderate retention time (t _R 14.64 min), stable peak area, and symmetric shape in the fingerprint chromatograms, so it was chosen as the reference peak for validation of the aforementioned UPLC-PDA fingerprinting method.

Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were applied to investigate the similarity of fingerprints [25]. HCA results are presented as a dendrogram in [Fig. 4 A]. The 11 Nardostachys samples could be grouped into 2 large clusters, A and B by HCA. Within cluster A, the samples S2-S4 obtained from Guizhou and Hebei, were grouped into one subcluster (I), while four samples (S1 S5, S8, and S9) from Gansu, Henan, and Tianjin fell into another subcluster (II) based on their similar chemotypes. For cluster B, samples (S6, S7, S10 and S11) from Inner Mongolia Autonomous Region, Sichuan, Beijing Tongrentang, and National Institutes for Drug and Food Control, Beijing were divided into two subgroups (III and IV). HCA can discriminate the available samples from different local retail pharmacies. The samples from Tongrentang and National Institutes for Drug and Food Control, two popular TCM suppliers with great authority in China, together with those from Sichuan and Inner Mongolia Autonomous Region, represent high value materials with a comparatively higher content of the main constituents, while samples from other suppliers have an average quality, with the content of nardosinone (peak 16) only slightly higher than the one required in the Chinese Pharmacopoeia. According to their labeling, all samples were from the Sichuan province, which is known as the main producer of commercial N. jatamansi herbal material. Thus, the observed differences suggest that other factors, such as growing altitude, collecting time, processing/drying method, and storage conditions, affect the quality of N. jatamansi herbal materials. This underlines the need for the development of process analytical technologies (PAT) for quality control of N. jatamansi.

PCA results are presented in [Fig. 4 B, C]. The score plot based on the first two principal components (2PCs, 94.5% of variance explained) is shown in [Fig. 4 B]. PC1 (75.0%) and PC2 (19.5%) were then used to reduce the original data matrix to a two-dimensional data set. Similar to HCA, PCA can divide all samples into two separated groups, demonstrating the qualitative discrimination power of this method. To select potential chemical markers for quality control from the 24 characteristic peaks in the fingerprint chromatograms, PCA loading values of these peaks were plotted ([Fig. 4 C]). In general, a peak with a higher loading value means that the peak area of the corresponding compound varies more significantly among the studied samples and can be recognized as a dominant variation for sample classification. Thus, five identified characteristic peaks ([Fig. 3 A]: peaks 5, 12, and 16 – 18) with high loading values, together with the quantified constituent buddleoside (peak 7) [26], were selected and recommended as potential markers for future quality control of N. jatamansi.

SERT is a classic target of drug discovery for neuropsychiatric and digestive disorders. Exploring SERT active constituents from N. jatamansi may help in understanding its traditional uses as a medicinal drug and functional food. SERT activity of the selected markers was assessed by a previous established protocol [8], [9]. Some of the data have been recently reported as part of a large study on the SERT regulatory activity of N. chinensis sesquiterpenoids [27]. Compounds 5, 7, 12, and 17 enhanced SERT activity, while 16 inhibited SERT activity, and 18 didnʼt show any activity on SERT. Interestingly, among the SERT active compounds, the nardosinane-type sesquiterpenoids desoxo-narchinol A (5) and nardosinone (16) exhibited activities opposite of SERT ([Table 2]). Desoxo-narchinol A has been proposed to be a norsesquiterpenoid derivative of nardosinone [28]. This suggests that intrinsic conversions exist between SERT enhancers and SERT inhibitors in the underground parts of N. jatamansi, which may affect the SERT-targeted applications of this plant.

Finally, the above developed UPLC-PDA method was validated and employed for the simultaneous quantitative analysis of six marker compounds (5, 7, 12, 16, 17, and 18) in N. jatamansi, (Tables 6S and 7S, Supporting Information). The six compounds showed good regressions (r > 0.999) within the test ranges. The intraday and inter-day precision expressed as relative standard deviation was in the range of 0.25 – 1.76% and 1.34 – 2.77%, respectively, and the recovery of the method was in the range of 92 – 105%. All data were within the limits specified in the Chinese Pharmacopoeia. As shown in [Fig. 5] and Table 8S, Supporting Information, the content ranges for desoxo-narchinol A (5), buddleoside (7), isonardosinone (12), nardosinone (16), kanshone H (17), and (−)-aristolone (18) were 0.15 – 0.55, 0.05 – 0.58, 0.06 – 0.47, 1.18 – 20.01, 1.73 – 8.59, and 2.23 – 8.07 mg/g, respectively. The nardosinane-type sesquiterpenoid nardosinone and the two aristolane-type sesquiterpenoids kanshone H and (−)-aristolone were the major constituents in all samples.

In conclusion, the chromatographic fingerprinting, SERT activity evaluation, and multicomponent quantitative analysis reported here can provide valuable information for quality evaluation and control of N. jatamansi traditionally used against neuropsychiatric and digestive disorders. They can also be used for classifying and discriminating samples from different retail sources, although a much larger number of samples will be needed to establish more robust distinction criteria.

Materials and Methods

Plant materials and reagents

Eleven batches of herbal material samples, S1 (Lanzhou, Gansu), S2 (Guiyang, Guizhou), S3 (Hebei 1), S4 (Hebei 2), S5 (Kaifeng, Henan), S6 (Hohhot, Inner Mongolia Autonomous Region), S7 (Aba County, Aba Prefecture, Sichuan), S8 (Tianjin 1), S9 (Tianjin 2), S10 (Tongrentang, Beijing), and S11 (National Institutes for Drug and Food Control, Beijing) were purchased from different retail pharmacies in ten provinces in November 2015 (Table 1S, Supporting Information). They were identified by Prof. Tian-Xiang Li as dried roots and rhizomes of N. jatamansi DC. Voucher specimens were deposited in Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China. HPLC grade acetonitrile was obtained from Sigma-Aldrich Chemical Co. Deionized water was prepared by a laboratory water purification system (Millipore Ltd.). Other reagents of HPLC or analytical grade were purchased from Tianjin Damao Reagent Co., Ltd.

UPLC-photodiode array detection analysis

A Waters Acquity UPLC system (Waters Co. Ltd.) consisting of a binary solvent manager with an online degasser, an autosampler, a photodiode array UV detector (PDA), and a column oven was used. The system was controlled by an Empower 2 workstation. All analyses were carried out on an UPLC column (2.1 × 100 mm, 1.7 µm) maintained at 40 °C during the whole analytical process. The mobile phase consisted of 0.05% formic acid aqueous solution (A) and acetonitrile (B) at a flow rate of 0.3 mL/min. The gradient elution program was optimized and the final conditions were as follows: initially, 10% B; 0 – 13 min, linearly changed to 40% B; 13 – 21 min, linearly changed to 50% B; 21 – 26 min, linearly changed to 95% B; 26 – 31 min, kept at 95% B. The sample injection volume was 3.0 µL. The detector was set at 280 nm for acquiring chromatograms and the UV spectra were recorded between 210 – 400 nm.

UPLC-time-of-flight mass spectrometry analysis

A Waters Xevo G2-S QTOF-MS system (Waters Acquity UPLC system tandem Waters Xevo G2-S MS, Software version: MassLynx V4.1) was used for the analysis. UPLC conditions were the same as those for UPLC-PDA analysis. For MS analysis, nitrogen was used as the desolvation gas at a flow rate of 600 L/h. The cone gas flow rate was set at 50 L/h. The source temperature was set at 100 °C and the desolvation temperature was fixed at 400 °C. The capillary voltage was 2500 V and the cone voltage was 30 V. The collision energy was set at 25 eV. The scan frequency was 10 s. The spectra were recorded from m/z 50 to m/z 1500 in full scan mode.

Sample preparation

The dried underground parts of N. jatamansi were powdered and passed through a 40-mesh sieve directly before extraction. Then, 0.5 g powder of each sample was extracted by sonication (300 W, 40 kHz) with 10 mL methanol for 2 h, and the solution was made up to its original weight with methanol. Each solution was centrifuged for 10 min at 14 000 rpm (13 217 × g) and filtered through a 0.22-µm filter membrane before analysis. Next, 3 µL of the sample solutions were injected into the UPLC-PDA system and separated under the optimized chromatographic conditions.

Reference compounds and standard solution preparation

Reference compounds including desoxo-narchinol A (5), isonardosinone (12), nardosinone (16), kanshone H (17), and (−)-aristolone (18) were isolated and purified by extensive chromatographic methods from the ethanol extract of N. jatamansi, and their structures were elucidated by analysis of the 1D and 2D NMR data and comparison of their NMR and TOFMS data (see Supporting Information for isolation and identification) with those reported. The purity of each compound was determined to be above 95% by ¹H-NMR analysis. Buddleoside (Lot No. AW366B, purity > 98%) was purchased from Tianjin Yifang Technology Co. Ltd. The positive controls fluoxetine (Lot No. F132, purity > 98%) and tianepine (Lot No. T1692, purity > 98%) were purchased from Sigma. Reference compounds were accurately weighed and dissolved in methanol, and then mixed and diluted to appropriate concentration ranges for the preparation of the calibration curves. A mixed standard solution containing 1.394 mg/mL of desoxo-narchinol A, 1.142 mg/mL of buddleoside, 1.097 mg/mL of isonardosinone, 7.820 mg/mL of nardosinone, 5.250 mg/mL of kanshone H, and 2.632 mg/mL of (−)-aristolone was prepared and diluted (2, 4, 8, 16, 32, and 64 times) to a series of working standard solutions, consecutively. The chromatogram of the mixed standard solution is shown in [Fig. 3 A]. All the solutions were stored at 4 °C before analysis.

UPLC method validation

The method was validated in terms of linearity, limits of detection and quantification (LODs and LOQs), precision, repeatability, stability, and recovery tests. The six compounds were identified by comparing their retention times and MS data with those of the reference compounds. Each concentration for the calibration curves was analyzed in triplicate. The LODs and LOQs were calculated as three times and ten times the signal-to-noise ratios, respectively. Intra- and inter-day precision tests were conducted using six replicated injections of the same sample on the same day and on three consecutive days, respectively. Six independently prepared samples were analyzed to check the repeatability. Stability of the method was investigated in triplicate with one sample solution (stored at 4 °C) injected into the UPLC system at 0, 2, 4, 8, 14, and 24 h, consecutively. A recovery test was carried out to evaluate the accuracy of this method by adding defined amounts [32.4 µg for desoxo-narchinol A, 19.6 µg for buddleoside, 17.6 µg for isonardosinone, 1964.4 µg for nardosinone, 1090.4 µg for kanshone H, and 1713.2 µg for (−)-aristolone] of the six standard solutions to two different amounts (0.25 g/0.1 g) of extracts in sextuplicate.

Serotonin transporter assay

To test SERT activity of the compounds, a validated stably transfected hSERT-HEK293 cell line was used in a high content assay. The fluorescent substrate APP⁺ was used to examine SERT activity and the fluorescent dye Hoechst 33 342 to stain cellular nuclei. The effects of the test compounds on SERT function were calculated by the following equation: Relative fluorescent intensity (RFI) = (Intracellular APP⁺ fluorescent intensity treatment/Intracellular APP⁺ fluorescent intensity control). The positive control drugs in testing SERT function included SSRI fluoxetine 2.0 µM and SSRE tianeptine 1.0 µM. All test compounds were run in triplicate and repeated three times (n = 9) [8], [9].

Data analysis

For chromatographic fingerprint assessment and multivariate analysis, the softwares Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (version 2004A, National Committee of Pharmacopoeia, China) and SPSS Statistics (version 21) were used. For SERT activity evaluation, data from the SERT functional assays were analyzed by using SPSS software (Version 11.5, IBM Company). The RFI values under different treatments were evaluated by one-way analysis of variance (ANOVA), followed by post hoc testing using Dunnettʼs multiple comparisons tests. P values < 0.05 were considered to be significant. The results are expressed as the mean ± S. E. M. of at least six independent experiments.

Conflict of Interest

The authors declare that no conflicts of interest exist.

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (grant No. 81603250), the International Science & Technology Cooperation Program of China (grant No. 2013DFA31620), and the New Drug Discovery Platform (grant No. 2012ZX09304007).

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Correspondence

• References

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  Search in Google Scholar
• 2 Shang XF, Tao CX, Miao XL, Wang DS, Dawa T, Wang Y, Yang YG, Pan H. Ethno-veterinary survey of medicinal plants in Ruoergai region, Sichuan province, China. J Ethnopharmacol 2012; 142: 390-400
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