Studies on the Changes of Pharmacokinetics Behaviors of Phytochemicals and the Influence on Endogenous Metabolites After the Combination of Radix Bupleuri and Radix Paeoniae Alba Based on Multi-Component Pharmacokinetics and Metabolomics.

Congcong Chen,Guanhua Du,Yuzhi Zhou,Qicai Yin,Xiaoxia Gao,Junshen Tian,Xuemei Qin

doi:10.3389/fphar.2021.630970

Abstract

Radix Bupleuri-Radix Paeoniae Alba (RB-RPA) is a classic herb pair, which is commonly used to treat depression by soothing “liver qi stagnation” in the clinic. However, little is yet known concerning the combination mechanism of Radix Bupleuri (RB) and Radix Paeoniae Alba (RPA), their bioactive forms in vivo and the regulatory effects on the organism. The present study aimed to elucidate the changes in multi-component pharmacokinetics (PK) behavior after the combination of RB and RPA by a high-resolution full-scan mode of UPLC-HRMS method (a total of 38 components PK profiles were obtained, of which 23 components come from RB and 15 components come from RPA). Moreover, the metabolomics approach was used to analyze the dynamic response of endogenous metabolites intervened by RB-RPA, and the correlation between concentration-time curves of 38 components from RB-RPA and the dynamic response profiles of endogenous metabolites was characterized by Pearson correlation analysis. The results demonstrated that the combination of RB and RPA could significantly improve the bioavailability of five components in RB, and six components in RPA. Besides, metabolomics results indicated that a total of 21 endogenous metabolites exhibited time-dependent changes in response to the RB-RPA administration, of which 12 endogenous metabolites were significantly increased, and nine endogenous metabolites were significantly decreased. Furthermore, correlation analysis results indicated that the components with significantly improved bioavailability after combination such as saikogenin F, saikogenin G, albiflorin, methyl gallate, paeonimetabolin II were significantly positively correlated with picolinic acid, a metabolite with neuroprotective effect; saikogenin F, saikogenin G were significantly positively correlated with itaconic acid, a endogenous metabolite with anti-inflammatory activity; and albiflorin, paeonimetabolin II were significantly positively correlated with α-linolenic acid, a metabolite with strong protective actions on brain functions. These results indicated that the combination of RB and RPA can enhance each other’s neuroprotective and anti-inflammatory activities. In this study, A novel and efficient strategy has been developed to analyze the influence of the combination of RB and RPA in vivo behaviors by combining multi-component pharmacokinetics with metabolomics, which was contributed to clarifying the scientific connotation of herb–herb compatibility.

Highlights

RB is the dried root of the umbelliferous plant Bupleurum chinense DC
Modern pharmacological studies have shown that the analgesic, antiinflammatory, and antidepressant effect was significantly improved after the combination of RB and RPA
To analyze the RB-RPA herb pair-induced endogenous metabolites variations, the acquired data at each time point from Compound Discoverer 3.0 (removal of 55 RB-RPA herb pair metabolites previously identified in rats plasma (Yin et al, 2019)) were imported into SIMCA-P software for multivariate statistical analysis, such as the principal components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial leastsquares discriminant analysis (OPLS-DA)

Summary

INTRODUCTION

RB is the dried root of the umbelliferous plant Bupleurum chinense DC It has been widely used in Asia for thousands of years due to its pharmaceutical effects on antipyretic, analgesic, anti-inflammatory and anti-depressant (Ashour and Wink, 2011). The saponins such as saikosaponin A, saikosaponin D were the main active components of antidepressant effect (Tian et al, 2016). Modern pharmacological studies have shown that the analgesic, antiinflammatory, and antidepressant effect was significantly improved after the combination of RB and RPA PK-PD correlation analysis was used to comprehensively analyze the effect of “plant metabolome” on “body metabolome” by integrating pharmacokinetics and metabonomics technology

MATERIALS AND METHODS

AND DISCUSSION

CONCLUSION

Findings

ETHICS STATEMENT