An integrating strategy for serum metabolomics and microarray analysis to expand the understanding of diet-induced obesity

Literature Information

Publication Date 2021-06-15
DOI 10.1039/D1AY00821H
Impact Factor 2.896
Authors

Wuping Liu, Jingjing Xu, Tao Dai, Guiping Shen, Jianghua Feng


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Abstract

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.

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Analytical Methods

Analytical Methods
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Analytical Methods welcomes early applications of new analytical and bioanalytical methods and technology demonstrating the potential for societal impact. We require that methods and technology reported in the journal are sufficiently innovative, robust, accurate, and compared to other available methods for the intended application. Developments with interdisciplinary approaches are particularly welcome. Systems should be proven with suitably complex and analytically challenging samples. We encourage developments within, but not limited to, the following technologies and applications: global health, point-of-care and molecular diagnostics biosensors and bioengineering drug development and pharmaceutical analysis applied microfluidics and nanotechnology omics studies, such as proteomics, metabolomics or glycomics environmental, agricultural and food science neuroscience biochemical and clinical analysis forensic analysis industrial process and method development

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