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American Chemical Society, Journal of Proteome Research, 8(12), p. 3755-3768, 2013

DOI: 10.1021/pr400398b

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High-Fat Diet Induces Dynamic Metabolic Alterations in Multiple Biological Matrices of Rats

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Obesity is a condition resulting from the interactions of individual biology and environmental factors causing multiple complications. To understand the systems metabolic changes associated with the obesity development and progression, we systematically analyzed the dynamic metabonomic changes induced by high-fat-diet (HFD) in multiple biological matrices of rats using NMR and GC-FID-MS techniques. Clinical chemistry and histopathological data were obtained as complementary information. We found that HFD intakes caused systematic metabolic changes in blood plasma, liver and urine samples involving multiple metabolic pathways including glycolysis, TCA cycle and gut microbiota functions together with the metabolisms of fatty acids, amino acids, choline, B-vitamins, purines and pyrimidines. The HFD-induced metabolic variations were detectable in rat urine a week after HFD-intakes and showed clear dependence on the intake duration. B-vitamins and gut microbiota played important roles in the obesity development and progression together with changes in TCA cycle intermediates (citrate, α-ketoglutarate, succinate, and fumarate). 83-days HFD-intakes caused significant metabolic alterations in rat liver highlighted with the enhancements in lipogenesis, lipid accumulation and lipid-oxidation, suppression of glycolysis, up-regulation of gluconeogenesis and glycogenesis together with altered metabolisms of choline, amino acids and nucleotides. HFD intakes reduced the PUFA-to-MUFA ratio in both plasma and liver indicating the HFD-induced oxidative stress. These findings provided essential biochemistry information about the dynamic metabolic responses to the development and progression of HFD-induced obesity. This study also demonstrated the combined metabonomic analysis of multiple biological matrices as a powerful approach for understanding the molecular basis of pathogenesis and disease progression.