Objective: To investigate the effect of respiratory syncytial virus (RSV)-related pulmonary infection on endogenous metabolites in large intestinal mucosa in BALB/c mice using metabolomics technology based on gas chromatography-mass spectrometry (GC-MS).
Methods: Mice were randomly divided into a control group and a RSV pneumonia model group (n=16 each). The mouse model of RSV pneumonia was established using intranasal RSV infection (100×TCID50, 50 μL/mouse, once a day). After 7 days of intranasal RSV infection, the mice were sacrificed and GC-MS was used to identify endogenous metabolites and measure the changes in their relative content in colon tissue. SMCA-P12.0 software was used to perform principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) for endogenous metabolites in colon tissue. The differentially expressed metabolites in colon tissue were imported into the metabolic pathway platform Metaboanalyst to analyze related metabolic pathways.
Results: PCA and OPLS-DA showed significant differences between the control and RSV pneumonia model groups. A total of 32 metabolites were identified in the colon tissue of the mice with RSV pneumonia. The RSV pneumonia model group had significant increases in the content of leucine, isoleucine, glycine, alanine, arachidonic acid, and lactic acid, which were related to the valine, leucine, isoleucine, arachidonic acid, and pyruvic acid metabolic pathways.
Conclusions: RSV pneumonia might cause metabolic disorders in the large intestinal tissue in mice.
目的: 通过气相色谱-质谱联用（GC-MS）的代谢组学技术检测BALB/c小鼠合胞病毒（RSV）肺部感染对大肠黏膜组织内源性代谢物的影响。
方法: 将小鼠随机分为对照组和RSV肺炎模型组，每组16只。采用RSV（100×TCID50，50μL/只，每日1次）滴鼻感染法建立小鼠RSV肺炎模型。于滴鼻7d后处死各组小鼠，运用GC-MS检测大肠组织内源性代谢物及其相对含量的变化；使用SMCA-P12.0软件对大肠组织中内源性代谢物进行主成分分析（PCA）和正交偏最小二乘法-判别分析（OPLS-DA）；将大肠组织中的差异性代谢物导入代谢通路平台Metaboanalyst，以进一步分析相关代谢通路。
结果: PCA和OPLS-DA分析均显示对照组和RSV肺炎模型组可显著区分。RSV肺炎小鼠的大肠黏膜组织中共测得32种代谢产物，与对照组比较，其中亮氨酸、异亮氨酸、甘氨酸、丙氨酸、花生四烯酸、乳酸等含量均显著增高（P < 0.05），主要与缬氨酸、亮氨酸、异亮氨酸代谢、花生四烯酸代谢和丙酮酸代谢通路有关。
结论: RSV肺炎可能引起小鼠大肠黏膜组织的代谢紊乱。