Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, 422 Siming South Road, Siming District, Xiamen, Fujian 361005, China.
Anal Methods. 2021 Jul 28;13(28):3127-3135. doi: 10.1039/d1ay00821h. Epub 2021 Jun 28.
Obesity is a key component of metabolic syndrome and is precipitated by complex interactions between multiple environmental and genetic factors. The integration of multi-level bioinformation is needed to understand the altered endogenous molecule and metabolic mechanisms. In this study, an integrated analytical strategy was proposed by combining microarray data from a gene expression omnibus database and in vitro serum metabolomic data to unearth bioinformation associated with cafeteria diet induced obesity. In the diet induced obese rats, 23 genes and 9 metabolites showed significant changes, in which the increased levels of alanine, lactate and lactate dehydrogenase B (Ldhb) and the decreased levels of citrate and pyruvate indicated an enhanced glycolysis and a disordered Krebs cycle. Furthermore, the closeness centrality of Slc27a2, Apobr, alanine and histidine in the correlations network of pathways, genes and metabolites was 0.5036, 0.5111, 0.5702, and 0.5352, respectively. These close links between metabolites and genes would be highly useful to assess the degree of obesity and to understand the developmental mechanism of obesity. The pathway enrichment analysis of genes and metabolites proved that a disturbed glucose metabolism and biosynthesis of amino acids are typical metabolic features of cafeteria-induced obesity. The metabolomics combined with microarray data not only could identify the biomarkers, but also would be beneficial to the follow-up research of obesity treatment, especially providing a methodological basis for the study of other diseases.
肥胖是代谢综合征的一个关键组成部分,是由多种环境和遗传因素之间的复杂相互作用引发的。为了了解内源性分子和代谢机制的改变,需要整合多层次的生物信息。在这项研究中,我们提出了一种综合分析策略,将基因表达组学数据库中的微阵列数据与体外血清代谢组学数据相结合,以挖掘与 cafeteria 饮食诱导肥胖相关的生物信息。在 cafeteria 饮食诱导肥胖的大鼠中,有 23 个基因和 9 种代谢物发生了显著变化,其中丙氨酸、乳酸和乳酸脱氢酶 B(Ldhb)水平升高,柠檬酸和丙酮酸水平降低,表明糖酵解增强和三羧酸循环紊乱。此外,在途径、基因和代谢物相关网络的接近中心性分析中,Slc27a2、Apobr、丙氨酸和组氨酸的接近中心性分别为 0.5036、0.5111、0.5702 和 0.5352。这些代谢物与基因之间的紧密联系对于评估肥胖程度和理解肥胖的发展机制非常有用。基因和代谢物的通路富集分析证明,葡萄糖代谢和氨基酸生物合成的紊乱是 cafeteria 诱导肥胖的典型代谢特征。代谢组学与微阵列数据相结合不仅可以识别生物标志物,还有助于肥胖治疗的后续研究,特别是为其他疾病的研究提供了方法学基础。