Wu Dong-Ning, Guan Le, Jiang Yi-Xin, Ma Su-Hua, Sun Ya-Nan, Lei Hong-Tao, Yang Wei-Feng, Wang Qing-Feng
Key Laboratory of Ministry of Education for TCM Viscera-State Theory and Applications, Liaoning University of Traditional Chinese Medicine, Shenyang 110847, China.
Clinical Evaluation Center, Institute of Clinical Basic Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Cardiovasc Diagn Ther. 2019 Dec;9(6):545-560. doi: 10.21037/cdt.2019.12.04.
The molecular mechanism of quercetin in the prevention and treatment of AS has been widely reported. However, the microbial and metabolic characteristics of quercetin in AS treatment are still poorly understood. In this study, we aimed to explore the gut microbial and metabolic signatures of quercetin in AS treatment and conduct an integrative analysis on its biomechanism.
An atherosclerosis mouse model was induced by a high cholesterol diet (HCD). The duration of the quercetin treatment was 12 weeks. We measured TC, TG, HDL and LDL for plasma biochemical analysis and TNF-α and IL-6 for plasma inflammatory analysis. Haematoxylin-eosin (HE) staining was conducted to evaluate the aortic structure and atherosclerosis. Bacterial DNA, which was extracted from mouse faeces, was identified by the V3-V4 regions of the 16S rRNA for microbiological analysis. The HeatMap package of BTtools was applied to visualize the data of the microbial difference matrix according to the OTU results. Fecal metabolites were assessed through LC-MS. Multivariate data analysis was conducted on the normalized data with SIMCA-P+. Significantly different metabolites were extracted based on the Pearson correlation coefficients at the level of P<0.05. Key significantly changed metabolites were screened from the intersection between metabolic signatures of the normal-model and model-quercetin groups. To investigate the biological function of quercetin on AS, we identified the differential metabolic signatures of the model vs. quercetin groups and performed KEGG analyses via MBROLE, MetaboAnalyst database.
Quercetin treatment for 12 weeks significantly reduced the levels of TC (P<0.001), TG (P<0.05), HDL (P<0.001), LDL (P<0.001), TNF-α (P<0.001) and IL-6 (P<0.001) compared with the model group. HE staining indicated that quercetin could protect damaged vessels caused by HFD. Bacteroidetes, Firmicutes and Proteobacteria were dominant microbial groups in the samples. There was no significant difference between the three groups (P>0.05) at the phylum level, and the genera Phascolarctobacterium and Anaerovibrio can be regarded as the key microbiota signatures of quercetin treatment. PLS-DA results further showed that these 18 faecal metabolites (clustered in 3 groups) had significant differences between the control, model and quercetin groups throughout the 12-day treatment. According to the quantitative analysis results, 32 key metabolic signatures were screened for quercetin treatment. The main pathway in quercetin treatment is primary bile acid biosynthesis, as 3α,7α,12α,26-tetrahydroxy-5β-cholestane (C27H48O4) was defined as the most important key metabolic signature.
We explored the gut microbial and metabolic involvement of quercetin in AS treatment and suggest the association between AS and gut metabolic regulation.
槲皮素在动脉粥样硬化(AS)防治中的分子机制已有广泛报道。然而,槲皮素在AS治疗中的微生物及代谢特征仍知之甚少。本研究旨在探究槲皮素在AS治疗中的肠道微生物及代谢特征,并对其生物力学机制进行综合分析。
采用高胆固醇饮食(HCD)诱导建立动脉粥样硬化小鼠模型。槲皮素治疗持续12周。检测血浆总胆固醇(TC)、甘油三酯(TG)、高密度脂蛋白(HDL)和低密度脂蛋白(LDL)用于血浆生化分析,检测血浆肿瘤坏死因子-α(TNF-α)和白细胞介素-6(IL-6)用于血浆炎症分析。采用苏木精-伊红(HE)染色评估主动脉结构及动脉粥样硬化情况。从小鼠粪便中提取细菌DNA,通过16S rRNA的V3-V4区域进行鉴定用于微生物分析。应用BTtools的HeatMap软件包根据操作分类单元(OTU)结果可视化微生物差异矩阵数据。通过液相色谱-质谱联用(LC-MS)评估粪便代谢产物。使用SIMCA-P+软件对标准化数据进行多变量数据分析。基于P<0.05的Pearson相关系数提取显著差异代谢产物。从正常模型组和模型-槲皮素组的代谢特征交叉点筛选关键的显著变化代谢产物。为研究槲皮素对AS的生物学功能,鉴定模型组与槲皮素组的差异代谢特征,并通过MBROLE、MetaboAnalyst数据库进行京都基因与基因组百科全书(KEGG)分析。
与模型组相比,槲皮素治疗12周显著降低了TC(P<0.001)、TG(P<0.05)、HDL(P<0.001)、LDL(P<0.001)、TNF-α(P<0.001)和IL-6(P<0.001)水平。HE染色表明槲皮素可保护高脂饮食(HFD)所致的血管损伤。拟杆菌门、厚壁菌门和变形菌门是样本中的主要微生物类群。在门水平上,三组之间无显著差异(P>0.05),而考拉杆菌属和厌氧弧菌属可被视为槲皮素治疗的关键微生物特征。偏最小二乘判别分析(PLS-DA)结果进一步显示,在整个12天的治疗过程中,这18种粪便代谢产物(聚为3组)在对照组、模型组和槲皮素组之间存在显著差异。根据定量分析结果,筛选出32个槲皮素治疗的关键代谢特征。槲皮素治疗的主要途径是初级胆汁酸生物合成,因为3α,7α,12α,26-四羟基-5β-胆甾烷(C27H48O4)被定义为最重要的关键代谢特征。
我们探究了槲皮素在AS治疗中的肠道微生物及代谢参与情况,并提示AS与肠道代谢调节之间的关联。