Quercetin Modulates Liver Metabolic Profile in the Chronic Unpredictable Mild Stress Rat Model Based on Metabolomics Technology

Statistical analysis software (SAS, version 9.4) was used for statistical analysis. Two-way ANOVA was used to evaluate the main and interaction effects of the CUMS and quercetin. The post hoc least significant difference (LSD) test was used to analyze the multiple comparisons. Data are presented as mean ± standard deviation (SD). If the P value is < 0.05, the difference in means is considered statistically significant. SPSS (27.0) was used for receiver operating characteristic (ROC) curve analysis. GraphPad Prism 5 was used to generate all charts. A heatmap of metabolite was performed by using the software R version 4.0.2.The UPLC BEH C18 column (100×2.1mm, 1.7μm) was used for chromatographic separation. The mobile phase consists of 0.1% formic acid (solvent A) and acetonitrile (solvent B). Liquid phase gradient setting was as follows: 0 to 0.5min, 98% A; 0.5 to 1.5min, 80% A; 1.5 to 6min, 30% A; 6 to 12min, 2% A; 12 to 14min, 30% A; 14 to 16min, 98% A. The flow rate was set to 0.45mL/min and the injection volume was 2μL. The temperature of the autosampler and the column were set to 4℃ and 35℃. The QC sample was injected after every 10 measurements to monitor the stability of the instrument and evaluate the reproducibility of the UPLC-MS systems.Date feature alignment, nontargeted signal detection, and signal integration were performed by Progenesis QI software. Subsequently, EZinfo software (version 2.0) was used for the statistical analysis of metabolite features. Principal component analysis (PCA) was used to assess the repeatability of technical and methodological. Then, partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) was performed to examine the best separation between the groups. Furthermore, the model was validated by a cross‐validation tool (SIMCA‐P software; version 14.0) to avoid the risk of overfitting. The S-plot and the value of variable importance in the projection (VIP) scores >1.0 were used to select differential metabolites. Finally, differential metabolites with fold change ≥ 2, and P＜0.05 were filtered as significantly changed metabolites.Preliminary identification of metabolites was performed using the Human Metabolome Database (HMDB). Finally, metabolites were identified based on m/z and MS/MS spectra compared with public databases. Metabolites pathway analysis was performed with Metaboanalyst (http://www.mataboanalyst.ca) using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (https://www.genome.jp/kegg/kegg2.html) and the Small Molecule Pathway Database (SMPDB, http://www.smpdb.ca).

本研究采用统计分析软件SAS（版本9.4）开展统计学分析。采用双因素方差分析（Two-way ANOVA）评估慢性不可预见性温和应激（Chronic Unpredictable Mild Stress, CUMS）与槲皮素（quercetin）的主效应及交互效应，并通过事后最小显著差异（Least Significant Difference, LSD）检验进行多重比较分析。数据以平均值±标准差（Standard Deviation, SD）表示，当P值小于0.05时，认为组间均值差异具有统计学意义。采用SPSS（27.0）进行受试者工作特征（Receiver Operating Characteristic, ROC）曲线分析；采用GraphPad Prism 5绘制所有实验图表。代谢物热图的绘制采用R软件（版本4.0.2）。色谱分离采用UPLC BEH C18色谱柱（100×2.1mm，1.7μm），流动相由0.1%甲酸（流动相A）与乙腈（流动相B）组成，液相色谱梯度洗脱程序设置如下：0~0.5min，98% A；0.5~1.5min，80% A；1.5~6min，30% A；6~12min，2% A；12~14min，30% A；14~16min，98% A。流速设定为0.45mL/min，进样体积为2μL，自动进样器与色谱柱温度分别设定为4℃与35℃。每连续检测10个样本后注入质控（Quality Control, QC）样本，以监测仪器稳定性并评估UPLC-MS系统的重现性。采用Progenesis QI软件完成数据特征对齐、非靶向信号检测与信号整合分析；随后采用EZinfo软件（版本2.0）进行代谢物特征的统计学分析。采用主成分分析（Principal Component Analysis, PCA）评估技术与方法学层面的重复性，继而采用偏最小二乘判别分析（Partial Least Squares Discriminant Analysis, PLS-DA）与正交偏最小二乘判别分析（Orthogonal Partial Least Squares Discriminant Analysis, OPLS-DA）考察组间最优分离效果。此外，采用交叉验证工具SIMCA-P软件（版本14.0）对模型进行验证，以避免过拟合风险。通过S图与投影变量重要性（Variable Importance in Projection, VIP）得分>1.0的指标筛选差异代谢物，最终筛选倍数变化≥2且P<0.05的差异代谢物作为显著性差异代谢物。采用人类代谢组数据库（Human Metabolome Database, HMDB）进行代谢物的初步鉴定，最终通过匹配公共数据库中的质荷比（m/z）与串联质谱（MS/MS）谱图完成代谢物鉴定。采用Metaboanalyst工具（http://www.metaboanalyst.ca），结合京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路数据库（https://www.genome.jp/kegg/kegg2.html）与小分子通路数据库（Small Molecule Pathway Database, SMPDB, http://www.smpdb.ca）进行代谢物通路富集分析。