基于UHPLC-QE-MS的CCI模型大鼠的血清代谢组学研究

采用超高效液相色谱-四级杆静电场轨道阱质谱（UHPLC-QE-MS）非靶向代谢组学方法，观察CCI模型大鼠血清内源性代谢物的变化，筛选出慢性坐骨神经痛大鼠血清差异性代谢物，分析慢性疼痛对差异性代谢物的影响。将12只SPF级SD雄性大鼠随机均分为正常组和坐骨神经慢性压迫损伤（CCI）组，每组6只。CCI组建立大鼠左侧坐骨神经慢性压迫损伤模型，正常组除不结扎坐骨神经，其余步骤一样。14天后腹主动脉采血, 分离血清，对大鼠血清中的代谢物进行代谢组学检测。利用UHPLC-QE-MS技术并结合PCA(主成分分析)筛选差异代谢物，利用MetabolicAnalyst5.0进行差异代谢物的富集分析。富集分析结果表明，与正常对照组相比,CCI模型大鼠血清有机酸、有机杂环化合物、脂肪酰基、碳水化合物、核酸、有机氮化合物、碳氢化合物等9类代谢物具有统计学差异。结果表明：基于UHPLC-QE-MS的血清代谢组学方法能够有效区分正常组和CCI组，筛选出的差异代谢物有助于慢性疼痛的机制及药物靶点研究。

Serum Metabolomics Study of CCI Model Rats Based on UHPLC-QE-MS

In this study, ultra-high performance liquid chromatography-quadrupole electrostatic field orbital trap mass spectrometry ( UHPLC-QE-MS ) non-targeted metabolomics method was used to observe the changes of endogenous metabolites in serum of CCI rats, screen out the serum differential metabolites of chronic sciatica rats, and analyze the effect of chronic pain on differential metabolites. Twelve SPF SD male rats were randomly divided into the normal control group and a chronic constriction injury ( CCI ) group, with 6 rats in each group. A chronic compression injury model of the left sciatic nerve was established in the CCI group. The normal control group had the same steps except no sciatic nerve ligation. After 14 days, abdominal aorta blood was collected, and serum was separated, and then the metabolites in rat serum were detected by metabolomics. The differential metabolites were screened by UHPLC-QE-MS combined with PCA ( principal component analysis ), and the enrichment analysis of differential metabolites was performed by Metabolic Analyst 5.0. The enrichment analysis results showed that compared with the normal control group, the serum organic acids, organic heterocyclic compounds, fatty acyl, carbohydrates, nucleic acids, organic nitrogen compounds, hydrocarbons and other nine metabolites of CCI model rats were statistically different. The serum metabolomics method based on UHPLC-QE-MS can effectively distinguish the normal group and the CCI group, and the screened differential metabolites are helpful in studying the mechanism of chronic pain and drug targets.