药学学报, 2022, 57(5): 1420-1428
引用本文:
黄德华, 王力文, 宫文霞, 田俊生, 高晓霞, 秦雪梅, 杜冠华, 周玉枝. 基于血浆代谢组学和网络分析研究柴归颗粒的抗抑郁作用机制[J]. 药学学报, 2022, 57(5): 1420-1428.
HUANG De-hua, WANG Li-wen, GONG Wen-xia, TIAN Jun-sheng, GAO Xiao-xia, QIN Xue-mei, DU Guan-hua, ZHOU Yu-zhi. Based on plasma metabonomics and network analysis to research the mechanisms of Chaigui granules for treating depression[J]. Acta Pharmaceutica Sinica, 2022, 57(5): 1420-1428.

基于血浆代谢组学和网络分析研究柴归颗粒的抗抑郁作用机制
黄德华1,2,3, 王力文1,2,3, 宫文霞1,2,3, 田俊生1,2,3, 高晓霞1,2,3, 秦雪梅1,2,3, 杜冠华1,4, 周玉枝1,2,3*
1. 山西大学中医药现代研究中心, 山西 太原 030006;
2. 山西大学化学生物学与分子工程教育部重点实验室, 山西 太原 030006;
3. 地产中药功效物质研究与利用山西省重点实验室, 山西 太原 030006;
4. 中国医学科学院、北京协和医学院药物研究所, 北京 100050
摘要:
本研究整合代谢组学和生物网络分析工具从生物代谢网络角度系统分析柴归颗粒的抗抑郁作用机制。建立慢性不可预见性轻度应激(chronic unpredictable mild stress,CUMS)抑郁大鼠模型,采用基于LC-MS的血浆代谢组学发现柴归颗粒抗抑郁作用的关键代谢物和代谢途径。整合生物网络分析工具对柴归颗粒调节的关键代谢物进行网络分析,聚焦关键代谢通路,挖掘柴归颗粒抗抑郁作用的潜在靶点。结果显示与对照组相比,模型组大鼠血浆中20个代谢物含量有显著差异(P<0.05),柴归颗粒能显著回调二十二碳三烯酸、3-羟基丁酸、4-羟基苯甲醛、鹅去氧胆酸、胆酸、L-谷氨酰胺、乙醇酸、亚油基肉碱、L-酪氨酸、N-乙酰缬氨酸、棕榈酰肉碱和花生四烯酸等12种代谢物。对柴归颗粒调控的关键代谢物进一步网络分析表明花生四烯酸代谢可能是柴归颗粒发挥抗抑郁作用的重要通路,花生四烯酸代谢途径上的CYP2B6、CYP2E1、CYP2C9、CYP2C8、PLA2G6、PTGS2、ALOX15B、PTGS1、ALOX12和ALOX5等10个蛋白为柴归颗粒发挥抗抑郁作用的潜在靶点。本文涉及的动物实验操作均遵循山西大学动物伦理委员会的规定并通过动物实验伦理审查(批号:SXULL2020028)。
关键词:    柴归颗粒      慢性不可预见性轻度应激抑郁      血浆代谢组学      生物网络分析      花生四烯酸代谢     
Based on plasma metabonomics and network analysis to research the mechanisms of Chaigui granules for treating depression
HUANG De-hua1,2,3, WANG Li-wen1,2,3, GONG Wen-xia1,2,3, TIAN Jun-sheng1,2,3, GAO Xiao-xia1,2,3, QIN Xue-mei1,2,3, DU Guan-hua1,4, ZHOU Yu-zhi1,2,3*
1. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China;
2. The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China;
3. The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan 030006, China;
4. Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
Abstract:
The purpose of this study was to systematically analyze the antidepressant mechanism of Chaigui granules from the perspective of biological metabolic network by using integrated metabolomics and biological network analysis tools. The model of chronic unpredictable mild stress (CUMS) depression rat was established, and LC-MS-based plasma metabolomics was used to identify the key metabolites and analyze metabolic pathways underlying the antidepressant effects of Chaigui Granules. The key metabolites regulated by Chaigui granules was integrated with biological network analysis tools to further focus on the key metabolic pathways and explore the potential targets of the antidepressant effect of Chaigui granules. The results showed that there were significant differences in the plasma levels of 20 metabolites in the model group compared with the control group (P < 0.05), Chaigui granules significantly regulated 12 metabolites including docosatrienoic acid, 3-hydroxybutyric acid, 4-hydroxybenzaldehyde, chenodeoxycholic acid, cholic acid, L-glutamine, glycocholic acid, linoleyl carnitine, L-tyrosine,N-acetylvaline, palmitoylcarnitine, arachidonic acid. Further network analysis of the key metabolites regulated by Chaigui granules indicated that plasma arachidonic acid metabolism might be the core pathway for the antidepressant effect of Chaigui granules, with 10 proteins were potential targets for the antidepressant effect of Chaigui granules, including CYP2B6, CYP2E1, CYP2C9, CYP2C8, PLA2G6, PTGS2, ALOX15B, PTGS1, ALOX12 and ALOX5. The animal experimental operations involved in this paper was followed the regulations of the Animal Ethics Committee of Shanxi University and passed the animal experimental ethical review (Approval No. SXULL2020028).
Key words:    Chaigui granule    chronic unpredictable mild stress depression    plasma metabolomics    biological network analysis    arachidonic acid metabolism   
收稿日期: 2021-12-01
DOI: 10.16438/j.0513-4870.2021-1723
基金项目: 国家自然科学基金资助项目(82074323,81673572);国家“重大新药创制”科技重大专项(2017ZX09301047);山西省留学回国人员科技活动择优资助项目(201991);山西省回国留学人员科研资助项目(2020019).
通讯作者: 周玉枝,E-mail:zhouyuzhi@sxu.edu.cn
Email: zhouyuzhi@sxu.edu.cn
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参考文献:
[1] Bridges L, Sharma M. The efficacy of yoga as a form of treatment for depression[J]. J Evid Based Complement Altern Med, 2017, 22:1017-1028.
[2] Mitina M, Young S, Zhavoronkov A. Psychological aging, depression, and well-being[J]. Aging (Albany NY), 2020, 12:18765-18777.
[3] Chen JJ, Qin XM, Du GH, et al. Advances in the pathogenesis of depression based on purinergic system and purine metabolism[J]. Acta Pharm Sin (药学学报), 2021, 56:2464-2471.
[4] Smith K. Mental health:a world of depression[J]. Nature, 2014, 515:181.
[5] Jiao H, Yan Z, Ma Q, et al. Influence of Xiaoyaosan on depressive-like behaviors in chronic stress-depressed rats through regulating tryptophan metabolism in hippocampus[J]. Neuropsychiatr Dis Treat, 2019, 15:21-31.
[6] Oh DR, Yoo JS, Kim Y, et al. Vaccinium bracteatum leaf extract reverses chronic restraint stress-induced depression-like behavior in mice:regulation of hypothalamic-pituitary-adrenal axis, serotonin turnover systems, and ERK/Akt phosphorylation[J]. Front Pharmacol, 2018, 9:604.
[7] Opoku AK, Terhorst Y, Vega J, et al. Predicting depression from smartphone behavioral markers using machine learning methods, hyperparameter optimization, and feature importance analysis:exploratory study[J]. JMIR Mhealth Uhealth, 2021, 9:e26540.
[8] Ma WN, Zhou MM, Gou XJ, et al. Urinary metabolomic study of chlorogenic acid in a rat model of chronic sleep deprivation using gas chromatography-mass spectrometry[J]. Int J Genomics, 2018, 2018:1361402.
[9] Chu HB, Tan YD, Li YJ, et al. Anxiolytic and anti-depressant effects of hydroalcoholic extract from Erythrina variegata and its possible mechanism of action[J]. Afr Health Sci, 2019, 19:2526-2536.
[10] Wang FR, Qiao MQ, Xue L, et al. Possible involvement of μ opioid receptor in the antidepressant-like effect of shuyu formula in restraint stress-induced depression-like rats[J]. Evid Based Complement Alternat Med, 2015, 2015:452412.
[11] Shi ZP, Wu XY, Dong Q, et al. Mechanism and research progress of anti-depression Chinese medicine compound prescription[J]. Asia-Pac Tradit Med (亚太传统医药), 2017, 13:68-70.
[12] Chen L, Zheng XF, Gao XX, et al. Anti-depressant effect and mechanism of supercritical CO2 extract from compound Chaigui Fang[J]. China J Chin Mater Med (中国中药杂志), 2014, 39:2744-2750.
[13] Gao X, Li Y, Meng M, et al. Exploration of chemical composition and absorption characteristics of Chaigui granules based on UHPLC-Q-orbitrap-MS/MS[J]. J Pharm Biomed Anal, 2020, 187:113293.
[14] Zhao YX, Xu T, Tian JS, et al. Effect of Chaigui granule on gut microbiota in chronic unpredicted mild stress induced depression rats model[J]. Chin Tradit Herb Drugs (中草药), 2021, 52:736-743.
[15] Wang Z, Chen YY, Zhang YY, et al. Problems and solutions in study of multi-component and multi-target mechanism of action of Ttraditional Chinese Medicine[J]. Chin J Exp Tradit Med Form (中国实验方剂学杂志), 2018, 24:1-6.
[16] Hu H, Fang Z, Mu T, et al. Application of metabolomics in diagnosis of cow mastitis:a review[J]. Front Vet Sci, 2021, 8:747519.
[17] Su G, Wang H, Gao Y, et al. 1H-NMR-based metabonomics of the protective effect of Coptis chinensis and berberine on cinnabar-induced hepatotoxicity and nephrotoxicity in rats[J]. Molecules, 2017, 22:1855.
[18] Fiehn O. Metabolomics-the link between genotypes and phenotypes[J]. Plant Mol Biol, 2002, 48:155-171.
[19] Yao C, Tang N, Xie G, et al. Management of hepatic encephalopathy by traditional Chinese medicine[J]. Evid Based Complement Alternat Med, 2012, 2012:835686.
[20] Xu J, Zhang P, Huang Y, et al. Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease[J]. Genome Res, 2021, 31:1900-1912.
[21] Lee MY, Hu T. Computational methods for the discovery of metabolic markers of complex traits[J]. Metabolites, 2019, 9:66.
[22] Guo L, Li L, Xu Z, et al. Metabolic network-based identification of plasma markers for non-small cell lung cancer[J]. Anal Bioanal Chem, 2021, 413:7421-7430.
[23] Tian G, Hu YZ, Li C, et al. The mechanism of action of Pudilan Xiaoyan oral liquid against LPS-induced acute respiratory infection in mice based on biological network analysis and metabolomics[J]. Acta Pharm Sin (药学学报), 2021, 56:816-822.
[24] Liu X, Wei F, Liu H, et al. Integrating hippocampal metabolomics and network pharmacology deciphers the antidepressant mechanisms of Xiaoyaosan[J]. J Ethnopharmacol, 2021, 268:113549.
[25] Gong W, Zhu S, Chen C, et al. The anti-depression effect of Angelicae Sinensis Radix is related to the pharmacological activity of modulating the hematological anomalies[J]. Front Pharmacol, 2019, 10:192.
[26] Chen CC, Yin QC, Tian JS, et al. The mechanism of the anti-depression effect of the Radix Bupleuri-Radix Paeoniae Alba herb pair determined by liver metabolomics[J]. Acta Pharm Sin (药学学报), 2020, 55:941-949.
[27] Zhang H, Lu D, Li X, et al. Heavy ion mutagenesis combined with triclosan screening provides a new strategy for improving the arachidonic acid yield in Mortierella alpina[J]. BMC Biotechnol, 2018, 18:23.
[28] Larrieu T, Laye S. Food for mood:relevance of nutritional omega-3 fatty acids for depression and anxiety[J]. Front Physiol, 2018, 9:1047.
[29] Green P, Gispan-Herman I, Yadid G. Increased arachidonic acid concentration in the brain of flinders sensitive line rats, an animal model of depression[J]. J Lipid Res, 2005, 46:1093-1096.
[30] Bazinet RP, Laye S. Polyunsaturated fatty acids and their metabolites in brain function and disease[J]. Nat Rev Neurosci, 2014, 15:771-785.
[31] Le HD, Meisel JA, de Meijer VE, et al. The essentiality of arachidonic acid and docosahexaenoic acid[J]. Prostaglandins Leukot Essent Fatty Acids, 2009, 81:165-170.
[32] Li X, Qin XM, Tian JS, et al. Integrated network pharmacology and metabolomics to dissect the combination mechanisms of Bupleurum chinense DC-Paeonia lactiflora Pall herb pair for treating depression[J]. J Ethnopharmacol, 2021, 264:113281.
[33] Leonard BE. Inflammation and depression:a causal or coincidental link to the pathophysiology?[J]. Acta Neuropsychiatr, 2018, 30:1-16.
[34] Yan L, Xu X, He Z, et al. Antidepressant-like effects and cognitive enhancement of coadministration of Chaihu Shugan San and fluoxetine:dependent on the BDNF-ERK-CREB signaling pathway in the hippocampus and frontal cortex[J]. Biomed Res Int, 2020, 2020:2794263.
[35] Xie H, Jin D, Kang Y, et al. The effect of Piper laetispicum extract (EAE-P) during chronic unpredictable mild stress based on interrelationship of inflammatory cytokines, apoptosis cytokines and neurotrophin in the hippocampus[J]. BMC Complement Altern Med, 2015, 15:240.
[36] Zhao J, Niu C, Wang J, et al. The depressive-like behaviors of chronic unpredictable mild stress-treated mice, ameliorated by Tibetan medicine Zuotai:involvement in the hypothalamic-pituitary-adrenal (HPA) axis pathway[J]. Neuropsychiatr Dis Treat, 2018, 14:129-141.