Multicompartmental LC-Q-TOF-Based Metabonomics as an Exploratory Tool to Identify Novel Pathways Affected by Polyphenol-Rich Diets in Mice

Metabonomics has recently been used to study the physiological response to a given nutritional intervention, but such studies have usually been restricted to changes in either plasma or urine. In the present study, we demonstrate that the use of LC-Q-TOF-based metabolome analyses (foodstuff, plasma, urine, and caecal content metabolomes) in mice offer higher order information, including intra- and intercompartment relationships. To illustrate this, we performed an intervention study with three different phenolic-rich extracts in mice over 3 weeks. Both unsupervised (PCA) and supervised (PLS-DA) multivariate analyses used for pattern recognition revealed marked effects of diet in each compartment (plasma, urine, and caecal contents). Specifically, dietary intake of phenolic-rich extract affects pathways such as bile acid and taurine metabolism. Q-TOF-based metabonomics demonstrated that the number of correlations is higher in caecal contents and urine than in plasma. Moreover, intercompartment correlations showed that caecal contents–plasma correlations are the most frequent in mice, followed by plasma–urine ones. The number of inter- and intracompartment correlations is significantly affected by diet. These analyses reveal the complexity of interorgan metabolic relationships and their sensitivity to dietary changes.

代谢组学（Metabonomics）近年来被用于探究特定营养干预下的机体生理响应，但此类研究通常仅聚焦于血浆或尿液中的代谢物变化。在本研究中，我们证实，对小鼠采用基于LC-Q-TOF的代谢组分析（涵盖食物样本、血浆、尿液及盲肠内容物的代谢组），可获得高阶信息，包括代谢区间内与区间间的关联特征。为验证这一结论，我们针对小鼠开展了为期3周的干预实验，为其饲喂三种不同的富酚提取物。用于模式识别的无监督主成分分析（PCA，Principal Component Analysis）与有监督偏最小二乘判别分析（PLS-DA，Partial Least Squares Discriminant Analysis）结果均显示，膳食干预对各代谢区间（血浆、尿液及盲肠内容物）均存在显著影响。具体而言，摄入富酚提取物会调控胆汁酸与牛磺酸代谢等代谢通路。基于Q-TOF的代谢组学分析显示，盲肠内容物与尿液中的代谢物关联数量高于血浆。此外，跨区间关联分析结果表明，小鼠体内盲肠内容物与血浆的关联最为频繁，其次为血浆与尿液间的关联。代谢区间内及跨区间的关联数量均会受到膳食干预的显著影响。上述分析揭示了器官间代谢关联的复杂性，以及其对膳食变化的响应敏感性。