Xiaojie Liu1, Xingyu Zheng2, Guanhua Du3, Zhenyu Li2, Xuemei Qin4. 1. Modern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, Shanxi, China; Shanxi Key Laboratory of Active Constituents Research and Utilization of TCM, Taiyuan 030006, Shanxi, China. Electronic address: liuxiaojie@sxu.edu.cn. 2. Modern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, Shanxi, China; Shanxi Key Laboratory of Active Constituents Research and Utilization of TCM, Taiyuan 030006, Shanxi, China. 3. Beijing Key Laboratory of Drug Target and Screening Research, Institute of Materia Medica, Chinese Academy of Medical Sciences, Beijing 100050, China. 4. Modern Research Center for Traditional Chinese Medicine of Shanxi University, Taiyuan 030006, Shanxi, China; Shanxi Key Laboratory of Active Constituents Research and Utilization of TCM, Taiyuan 030006, Shanxi, China. Electronic address: qinxm@sxu.edu.cn.
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE: Xiaoyaosan (XYS), a famous TCM prescription with a long history of clinical use for relieving a wide variety of depression symptoms, consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.). AIM OF THE STUDY: We aimed to characterize the diversity and variation of two kinds metabolites of brain, i.e. aqueous and lipophilic metabolites, gaining comprehensive insights into the metabolic processes of depression-like behavior, and to reveal the mechanisms of antidepressant-like effects of XYS. MATERIALS AND METHODS: We first established a CUMS (Chronic Unpredictable Mild Stress)-induced depression-like behavior model. We then extracted both aqueous and lipophilic metabolites of rat brains by a two-phase extraction method, which were subsequently characterized by two differential sequences of 1H nuclear magnetic resonance (NMR). Multivariate analysis including Principal Components Analysis (PCA) and Orthogonal Partial Least Squares-Discriminate Analysis (OPLS-DA) was applied. RESULTS: Metabolic profiling by PCA indicated that XYS significantly reversed the metabolic perturbation caused by CUMS. OPLS-DA showed a total of 15 metabolites including 6 lipophilic and 9 aqueous metabolites was screened as potential biomarkers involved in CUMS-induced depression-like behavior. On top of this, five pathways including (1)D-glutamine and D-glutamate metabolism, (2) valine, leucine and isoleucine biosynthesis, (3) alanine, aspartate and glutamate metabolism, (4) taurine and hypotaurine metabolism and (5) arginine and proline metabolism were recognized as the most influenced pathways associated with the process of CUMS-induced depression-like behavior. Notably, XYS significantly reversed abnormality of 5 aqueous and 4 lipophilic metabolites to normal, suggesting that XYS synergistically mediated abnormalities of multiple pathways (1), (3), (4) and (5). CONCLUSIONS: It is the first report to investigate the antidepressant-like effects and underlying mechanisms of XYS from the perspective of brain metabolites. In a broad sense, this study brings novel and valuable insights to evaluate the efficacy of traditional Chinese medicine (TCM), to interpret mechanisms, and to provide the theoretical basis for further research on therapeutic mechanisms in clinical practice.
ETHNOPHARMACOLOGICAL RELEVANCE: Xiaoyaosan (XYS), a famous TCM prescription with a long history of clinical use for relieving a wide variety of depression symptoms, consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.). AIM OF THE STUDY: We aimed to characterize the diversity and variation of two kinds metabolites of brain, i.e. aqueous and lipophilic metabolites, gaining comprehensive insights into the metabolic processes of depression-like behavior, and to reveal the mechanisms of antidepressant-like effects of XYS. MATERIALS AND METHODS: We first established a CUMS (Chronic Unpredictable Mild Stress)-induced depression-like behavior model. We then extracted both aqueous and lipophilic metabolites of rat brains by a two-phase extraction method, which were subsequently characterized by two differential sequences of 1H nuclear magnetic resonance (NMR). Multivariate analysis including Principal Components Analysis (PCA) and Orthogonal Partial Least Squares-Discriminate Analysis (OPLS-DA) was applied. RESULTS: Metabolic profiling by PCA indicated that XYS significantly reversed the metabolic perturbation caused by CUMS. OPLS-DA showed a total of 15 metabolites including 6 lipophilic and 9 aqueous metabolites was screened as potential biomarkers involved in CUMS-induced depression-like behavior. On top of this, five pathways including (1)D-glutamine and D-glutamate metabolism, (2) valine, leucine and isoleucine biosynthesis, (3) alanine, aspartate and glutamate metabolism, (4) taurine and hypotaurine metabolism and (5) arginine and proline metabolism were recognized as the most influenced pathways associated with the process of CUMS-induced depression-like behavior. Notably, XYS significantly reversed abnormality of 5 aqueous and 4 lipophilic metabolites to normal, suggesting that XYS synergistically mediated abnormalities of multiple pathways (1), (3), (4) and (5). CONCLUSIONS: It is the first report to investigate the antidepressant-like effects and underlying mechanisms of XYS from the perspective of brain metabolites. In a broad sense, this study brings novel and valuable insights to evaluate the efficacy of traditional Chinese medicine (TCM), to interpret mechanisms, and to provide the theoretical basis for further research on therapeutic mechanisms in clinical practice.
Authors: Tatiana J Carneiro; Martin Vojtek; Salomé Gonçalves-Monteiro; João R Neves; Ana L M Batista de Carvalho; Maria Paula M Marques; Carmen Diniz; Ana M Gil Journal: Pharmaceutics Date: 2022-01-22 Impact factor: 6.321