Lizeng Zhang

Metabolomics study on the anti-depression effect of xiaoyaosan on rat model of chronic unpredictable mild stress.

ETHNOPHARMACOLOGY Xiaoyaosan, a famous Chinese prescription, composed of Poria (Poria cocos (Schw.) Wolf), Radix Paeoniae Alba (Paeonia lactiflora Pall.), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.), Herba Menthae (Mentha haplocalyx Briq.), and Rhizoma Zingiberis Recens (Zingiber officinale Rosc.), has been widely used in the clinic for treating mental disorders. Behavior and biochemical analyses indicate xiaoyaosan has obvious anti-depression activity. However, there is no report on the effects of xiaoyaosan using a metabolomics approach. AIM OF THE STUDY A urinary metabolomics method was applied to evaluate the efficacy of xiaoyaosan on rat model of chronic unpredictable mild stress. MATERIAL AND METHODS Rats were divided into 6 groups and drugs were administered during the 21-day model building period. Urine was measured using GC-MS, processed with XCMS and Microsoft Excel and analyzed by SIMCA-P and SPASS software. Variable importance in projection statistics and loading plot were used to find biomarker ions. RESULTS Clear separation between model and each drug group was achieved. High dose group of xiaoyaosan was much closer to control group than middle dose group and amitriptyline group. The time-dependent recovery tendency in high dose group was obtained. CONCLUSIONS In term of anti-depression effect, high dose xiaoyaosan was the most effective and amitriptyline equaled middle dose xiaoyaosan as shown by metabolomics strategy and behavior tests. Some common and characteristic metabolites on the anti-depression of xiaoyaosan and amitriptyline were obtained. The work showed metabolomics is a valuable tool in studying the efficacy and potential biomarkers of therapeutic effect of complex prescriptions.

Metabonomic study on chronic unpredictable mild stress and intervention effects of Xiaoyaosan in rats using gas chromatography coupled with mass spectrometry

ETHNOPHARMACOLOGY Xiaoyaosan (XYS), a famous Chinese prescription, composed of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix Paeoniae Alba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.) Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae (Mentha haplocalyx Briq.), and Rhizoma Zingiberis Recens (Zingiber officinale Rosc.), has been widely used in the clinic for treating mental disorders. Behavior and biochemical analyses indicate XYS has obvious anti-depression activity. However, there is no report on the effects of XYS using a metabolomics approach. AIM OF THE STUDY Depression is a prevalent complex psychiatric disorder and its pathophysiological mechanism is not yet well understood. This paper was designed to study metabonomic characters of the depression induced by chronic unpredictable mild stress (CUMS) and the therapeutic effects of XYS, classic traditional Chinese medicine (TCM) in treating the depression. MATERIAL AND METHODS A plasma metabonomics method based on gas chromatography/mass spectrometry (GC/MS) was developed. Principal component analysis (PCA) was utilized to classify and reveal the differences between the model group and control group. In turns, the concentration of these differences was analyzed with t-test to determine whether XYS was possible to influence the metabolic pattern induced by CUMS. RESULTS The significant difference in metabolic profiling was observed from model group compared with drug-dose group by using the PCA, indicating the recovery effect of XYS on CUMS rats. Some significantly changed metabolites like glycine, glucose and hexadecanoic acid have been identified. These biochemical changes are related to the disturbance in amino acid metabolism, energy metabolism and glycometabolism, which are helpful to further understand the CUMS and the therapeutic mechanism of XYS. CONCLUSIONS Metabonomic approach is helpful to further understanding the pathophysiology of depression and assisting in clinical diagnosis of depression and is also a valuable tool for studying the essence of Chinese medicines syndrome theory and therapeutic effect mechanism of TCM.

Antidepressant-like effects of the fractions of Xiaoyaosan on rat model of chronic unpredictable mild stress.

ETHNOPHARMACOLOGICAL RELEVANCE Xiaoyaosan (XYS), composed of Radix Bupleuri, Radix Angelicae Sinensis, Radix Paeoniae Alba, Rhizoma Atractylodis Macrocephalae, Poria, Herba Menthae, Rhizoma Zingiberis Recens and Radix Glycyrrhizae, is a valuable traditional Chinese medicine (TCM) which is used for the treatment of depression in China. In the formula, Radix Bupleuri usually serves as the principal drug, Radix Angelicae Sinensis and Radix Paeoniae Alba serve as the ministerial drugs, Rhizoma Atractylodis Macrocephalae, Poria, Herba Menthae and Rhizoma Zingiberis Recens serve as adjunctive drugs, Radix Glycyrrhizae serves as messenger drug, they coordinate with each other and enhance the effect of the formula. In our previous experiments, the antidepressant effect of XYS was revealed. However, the antidepressant part (or component) of this prescription was still obscure. We divided the XYS into five different polar fractions, and explored the antidepressant activity of five different polar fractions to identify the active fraction. MATERIALS AND METHODS Behavior research and metabonomics method based on (1)H NMR were used for efficacy study of different fractions in chronic unpredictable mild stress (CUMS) model of depression. Rats were divided into 8 groups and drugs were administered during the 21 days model building period. The urine samples of rats were collected overnight (12h) on 21 day and the metabolic profiling of the urine was measured using NMR. Multivariate analysis was also utilized to evaluate the active fraction of XYS. RESULTS In the behavior research, there were significant difference between the lipophilic fraction group (XY-A) and the model group. In addition, with pattern recognition analysis of urinary metabolites, the results showed a clear separation of the model group and control group, while XY-A group was much closer to the control group in the OSC-PLS score plot. Seven endogenous metabolites contributing to the separation of the model group and control group were detected, while XY-A group regulated the 5 perturbed metabolites showing a tendency of recovering to control group. CONCLUSIONS The present work suggested that petroleum ether fraction was the most effective fraction, implying that lipophilic components contribute to the antidepressant effect of XYS.

Metabolic Fingerprinting of Tussilago farfara L. Using 1H‐NMR Spectroscopy and Multivariate Data Analysis

INTRODUCTION The flower bud of Tussilago farfara L. is widely used for the treatment of coughs, bronchitis and asthmatic disorders in traditional Chinese medicine. In Europe, the plant has been used as herbal remedies for virtually the same applications, but the leaves are preferred over flowers. OBJECTIVE To systematically evaluate the chemical profiles of Tusssilago farfara leaves and flowers along with the identification of the polar and non-polar metabolites. METHODOLOGY Metabolic profiling carried out by means of ¹H-NMR spectroscopy and multivariate data analysis was applied to crude extracts from flowers and leaves. Metabolites were identified directly from the crude extracts through one-dimensional and two-dimensional NMR spectra. RESULTS A broad range of metabolites were detected without any chromatographic separation. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) of ¹H-NMR data provided a clear separation between the samples. The corresponding loadings plot indicated that higher levels of phenylpropanoids, amino acids, organic acids and fatty acids, as well as lower levels of sugars, terpenoids and sterols were present in the leaves, as compared with flowers. For the flowers, more phenylpropanoids were present in fully open flowers, while more sugars and fatty acids were present in flower buds. CONCLUSION NMR spectra (one- and two-dimensional) are useful for identifying metabolites, especially for the overlapped signals. The NMR-based metabolomics approach has great potential for chemical comparison study of the metabolome of herbal drugs.

A 1H-NMR plasma metabonomic study of acute and chronic stress models of depression in rats

To investigate and compare the metabonomic profiles of three stress-based models of depression, the effects of acute and chronic stress on the production of systemic endogenous metabolites were investigated. Such metabonomic analysis may provide researchers a new way of selecting appropriate animal models for the study of depression and antidepressants. Rats were subjected to one of three stress-based models: CUMS, FST-1d, or FST-14d. Endogenous metabolites excreted in plasma were analyzed using NMR in conjunction with multivariate and statistical techniques. The metabonomic study indicated that the concentration of different plasma metabolites could be used to differentiate among depression models: TMA, aspartic acid, glutamate, AcAc, NAc, alanine, lactate, Leu/Ile, lipids increased and proline, β-HB, valine decreased in the CUMS model; TMA decreased in the FST-1d model; α-glucose, β-glucose, β-HB, valine and lipids increased in the FST-14d model. The results suggested that metabonomics is a potentially appropriate method for evaluating depression models. According to the metabonomics study, CUMS model was more suitable and sensitive than the acute FST-1d model and predictable FST-14d model. The CUMS model was more appropriate for investigating both the efficacy of antidepressants and their mechanisms of action, while the FST-14d model should only be used for evaluating the efficacy of treatment.

Urinary metabonomic study using a CUMS rat model of depression.

Chronic unpredictable mild stress (CUMS) is a well‐validated model of depression. In this study, a urinary metabonomics method based on the NMR spectrometry was used to study the metabolic perturbation in CUMS‐induced rat depression model. With pattern recognition analysis, a clear separation of CUMS rats and healthy controls was achieved, and nine endogenous metabolites contributing to the separation were identified. CUMS‐treated rats were characterized by the increase of glycine, pyruvate, glutamine, and asparagines, as well as the decrease of 2‐oxoglutarate, dimethylglycine, citrate, succinate, and acetate. The urinary biochemical changes related to the metabolic disturbance in CUMS induced depression, and the possible correlations with live qi stagnation in traditional Chinese medicine are discussed. The work shows that CUMS is a reliable model for studying depression, and the noninvasive urinary metabolomic method is a valuable tool to investigate the biochemical pertubations in depression as an early diagnostic means. Copyright

Metabolomic profiling of the flower bud and rachis of Tussilago farfara with antitussive and expectorant effects on mice

ETHNOPHARMACOLOGICAL RELEVANCE Flower bud of Tussilago farfara L. is widely used for the treatment of cough, bronchitis and asthmatic disorders in the Traditional Chinese Medicine. However, due to the increasing demands, adulteration with rachis is frequently encountered in the marketplace. No report demonstrated the chemical and pharmacological differences between flower bud and rachis before. MATERIALS AND METHODS The water extracts were orally administrated to mice. Ammonia induced mice coughing model was used to evaluate the antitussive activity. The expectorant activity was evaluated by volume of phenol red in mices tracheas. Metabolites were identified directly from the crude extracts through 1D- and 2D-NMR spectra. A metabolic profiling carried out by (1)H NMR spectroscopy and multivariate data analysis was applied to crude extracts from flower bud and rachis. RESULTS Flower bud significantly lengthened the latent period of cough, decreased cough frequency caused by ammonia and enhanced tracheal phenol red output in expectorant evaluation. Principal component analysis (PCA) yielded good separation between flower bud and rachis, and corresponding loading plot showed that the phenolic compounds, organic acid, sugar, amino acid, terpene and sterol contributed to the discrimination. CONCLUSIONS These findings provide pharmacological and chemical evidence that only flower bud can be used as the antitussive and expectorant herbal drug. The high concentration of chlorogenic acid, 3,5-dicaffeoylquinic acid, rutin in flower buds may be related with the antitussive and expectorant effects of Flos Farfara. To guarantee the clinical effect, rachis should be picked out before use.

Metabolomic profiling of the antitussive and expectorant plant Tussilago farfara L. by nuclear magnetic resonance spectroscopy and multivariate data analysis.

This study aims to find metabolites responsible for antitussive and expectorant activities of Tussilago farfara L. by metabolomic approach. Different parts (roots, flower buds, and leaves) of the title plant were analyzed systematically. The in vivo study revealed that the leaves and flower buds had strong antitussive and expectorant effects. Then ¹H NMR spectrometry together with principal component analysis (PCA) and partial least squares discriminant (PLS-DA) analysis were used to investigate the compounds responsible for the bioactivities. PCA was used to find the differential metabolites, while PLS-DA confirmed a strong correlation between the observed effects and the metabolic profiles of the plant. The result revealed that chlorogenic acid, 3,5-dicaffeoylquinic acid, and rutin may be closely related with the antitussive and expectorant activities. The overall results of this study confirm the benefits of using metabolic profiling for screening active principles in medicinal plants.

Species Classification and Quality Assessment of Chaihu (Radix Bupleuri) Based on High-Performance Liquid Chromatographic Fingerprint and Combined Chemometrics Methods

A high-performance liquid chromatographic (HPLC) method was established to analyze 36 Chaihu (Radix Bupleuri) samples collected from three species (Bupleurum chinense DC., B. scorzonerifolium Willd. and B. smithii Wolff.). Addition of trifluoroacetic acid into the mobile phase resulted in fingerprint chromatograms with stable baselines. There were thirty-two characteristic peaks in the standard fingerprint of B. chinense DC. Different recognition pattern methods, including similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA) and partial least squares-discrimination analysis (PLS-DA) were utilized to analyze the 36 samples based on the contents of chemical constituents. Consistent results from SA, HCA and PCA analysis illustrated the rationalisation for why B. smithii Wolff. was not quoted in the Chinese Pharmacopoeia and classified samples were in agreement with their species. PLS-DA loading plots showed the chemical markers which had the most influences on the separation among different species. However, SA, HCA and PCA could not differentiate between wild and cultivated B. chinense DC. as well as between samples from different provinces. HPLC fingerprint in combination with chemometric techniques provided a very flexible and reliable method for homogeneity evaluation and quality assessment of traditional Chinese medicine.

Metabonomic Analysis of Urine from Chronic Unpredictable Mild Stress Rats Using Gas Chromatography–Mass Spectrometry

Depression is a prevalent complex psychiatric disorder and its pathophysiological mechanism is not yet well understood. In this study, we investigated the metabolic profiling of urine samples from chronic unpredictable mild stress (CUMS) rats to find potential disease biomarkers and research pathology of depression. Metabolome in urine was analyzed using gas chromatography/mass spectrometry (GC/MS) in conjunction with multivariate statistical techniques. The urine samples of male Sprague–Dawley rats were collected at different time points and then were derivatized by methoximation/silylation. Clear separation between the model and control group was achieved, and 15 metabolites were identified, which suggested that the depressed state may be related to neurotransmitter, energy metabolism and immunity. The time-dependent trajectory of metabolites pattern revealed that the maximum biochemical change happened on the 21st day, which was consistent with the results of behavior tests. The study suggested that the metabonomic approach could be used as a potentially powerful tool to investigate the biochemical change in certain physiopathological conditions, such as depression, as an early diagnostic means.