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基于气相色谱-质谱联用技术的血清代谢组学揭示了大鼠模型中鞣花酸的解热机制。

Serum Metabolomics Based on GC-MS Reveals the Antipyretic Mechanism of Ellagic Acid in a Rat Model.

作者信息

Xie Fengfeng, Xu Liba, Zhu Hua, Li Yinlan, Nong Lizhen, Chen Yaling, Zeng Yanfang, Cen Sijie

机构信息

School of Chemistry and Chemical Engineering, Guangxi MinZu University, Nanning 530006, China.

Guangxi Engineering Research Center of Ethnic Medicine Resources and Application, Guangxi Key Laboratory of Zhuang and Yao Ethnic Medicine, Collaborative Innovation Center of Zhuang and Yao Ethnic Medicine, Guangxi University of Chinese Medicine, Nanning 530200, China.

出版信息

Metabolites. 2022 May 25;12(6):479. doi: 10.3390/metabo12060479.

Abstract

Ellagic acid (EA) is a polyphenol dilactone that has been reported to have antipyretic, anti-inflammatory, anti-tumor, and antioxidant activities, but the mechanism of action has not been reported. In this study, serum metabolomics was used to explore the mechanism of EA on rat fever induced by beer yeast, and to screen out marker metabolites to provide a reference for the antipyretic effect of EA. The acute fever model of male Sprague Dawley rats involved subcutaneous injection with 20% aqueous suspension of yeast (15 mL/kg) in their back. At the same time of modeling, EA was given orally by 10 mL/kg intragastric administration for treatment. During the experiment, the temperature and its change values of rats were recorded, and Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), Prostaglandin E2 (PGE2), Cyclic Adenosine Monophosphate (cAMP), Superoxide Dismutase (SOD) and Malondialdehyde (MDA)—six physiological and biochemical indexes of rats—were detected after the experiment. In addition, the hypothalamus of each rat was analyzed by Western blot (WB), and the levels of Phospho Nuclear Factor kappa-B (P-NF-κB P65) and IkappaB-alpha (IKB-α) were detected. Then, the serum metabolites of rats in each group were detected and analyzed by gas chromatograph mass spectrometry and the multivariate statistical analysis method. Finally, when screening for differential metabolites, the potential target metabolic pathway of drug intervention was screened for through the enrichment analysis of differential metabolites. Pearson correlation analysis was used to systematically characterize the relationship between biomarkers and pharmacodynamic indicators. EA could reduce the temperature and its change value in yeast induced fever rats after 18 h (p < 0.05). The level of IL-6, TNF-α, PGE2, cAMP, SOD and MDA of the Model group (MG) increased significantly compared to the Normal group (NG) (p < 0.001) after EA treatment, while the levels of the six indexes in the serum and cerebrospinal fluid of yeast-induced rats decreased. The administration of yeast led to a significant increase in Hypothalamus P-NF-κB P65 and IKB-α levels. Treatment with EA led to a significant decrease in P-NF-κB P65 levels. Moreover, combined with VIP > 1 and p < 0.05 as screening criteria, the corresponding retention time and characteristic mass to charge ratio were compared with the NIST library, Match score > 80%, and a total of 15 differential metabolites were screened. EA administration significantly regulated 9 of 15 metabolites in rat serum. The 15 differential metabolites involved linoleic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, galactose metabolism, biosynthesis of unsaturated fatty acids and glycerolipid metabolism. Pharmacodynamic correlation analysis was conducted between 15 different metabolites and six detection indexes. There was a significant correlation between 13 metabolites and six detection indexes. D-(−)-lactic acid, glycerin, phosphoric acid, 5-oxo-L-proline were negatively correlated with TNF-α, and p values were statistically significant except for L-tyrosine. In addition, glycerin was negatively correlated with IL-6, PGE2 and MDA, while phosphoric acid was negatively correlated with IL-6. In conclusion, EA may play an antipyretic anti-inflammatory role through the inhibition of the IKB-α/NF-κB signaling pathway and five metabolic pathways, which may contribute to a further understanding of the therapeutic mechanisms of the fever of EA.

摘要

鞣花酸(EA)是一种多酚二内酯,据报道具有解热、抗炎、抗肿瘤和抗氧化活性,但其作用机制尚未见报道。本研究采用血清代谢组学方法探讨EA对啤酒酵母诱导的大鼠发热的作用机制,并筛选出标志物代谢物,为EA的解热作用提供参考。雄性Sprague Dawley大鼠的急性发热模型是在其背部皮下注射20%酵母水悬液(15 mL/kg)。在建模的同时,给予EA 10 mL/kg灌胃治疗。实验过程中记录大鼠体温及其变化值,实验结束后检测大鼠白细胞介素-6(IL-6)、肿瘤坏死因子-α(TNF-α)、前列腺素E2(PGE2)、环磷酸腺苷(cAMP)、超氧化物歧化酶(SOD)和丙二醛(MDA)六项生理生化指标。此外,通过蛋白质免疫印迹法(WB)分析每只大鼠的下丘脑,检测磷酸化核因子κB(P-NF-κB P65)和IκB-α的水平。然后,采用气相色谱-质谱联用仪和多元统计分析方法对各组大鼠的血清代谢物进行检测和分析。最后,在筛选差异代谢物时,通过差异代谢物的富集分析筛选药物干预的潜在靶代谢途径。采用Pearson相关分析系统地表征生物标志物与药效学指标之间的关系。EA可使酵母诱导发热大鼠在18 h后体温及其变化值降低(p<0.05)。EA治疗后,模型组(MG)大鼠的IL-6、TNF-α、PGE2、cAMP、SOD和MDA水平与正常组(NG)相比显著升高(p<0.001),而酵母诱导大鼠血清和脑脊液中六项指标水平降低。酵母给药导致下丘脑P-NF-κB P65和IκB-α水平显著升高。EA治疗导致P-NF-κB P65水平显著降低。此外,以VIP>1且p<0.05作为筛选标准,将相应的保留时间和特征质荷比与NIST库进行比较,匹配分数>80%,共筛选出15种差异代谢物。EA给药显著调节大鼠血清中15种代谢物中的9种。这15种差异代谢物涉及亚油酸代谢、苯丙氨酸、酪氨酸和色氨酸生物合成、半乳糖代谢、不饱和脂肪酸生物合成和甘油酯代谢。对15种不同代谢物与六项检测指标进行药效学相关性分析。13种代谢物与六项检测指标之间存在显著相关性。D-(-)-乳酸、甘油、磷酸、5-氧代-L-脯氨酸与TNF-α呈负相关,除L-酪氨酸外,p值具有统计学意义。此外,甘油与IL-6、PGE2和MDA呈负相关,而磷酸与IL-6呈负相关。综上所述,EA可能通过抑制IκB-α/NF-κB信号通路和五条代谢途径发挥解热抗炎作用,这可能有助于进一步了解EA治疗发热的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6476/9228490/20601667f7d2/metabolites-12-00479-g001.jpg

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