A high fat, high cholesterol diet leads to changes in metabolite patterns in pigs – A metabolomic study

• Published in: Food chemistry Vol. 173; pp. 171 - 178
• Main Authors: Sun, Jianghao, Monagas, Maria, Jang, Saebyeol, Molokin, Aleksey, Harnly, James M., Urban, Joseph F., Solano-Aguilar, Gloria, Chen, Pei
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.04.2015
• Subjects: Animals; Bile Acids and Salts - metabolism; Cholesterol, Dietary - administration & dosage; Chromatography, High Pressure Liquid - methods; Diet pattern; Diet, High-Fat; Fatty Acids - metabolism; Female; High-resolution mass spectrometry; Lipid Metabolism; Mass Spectrometry; Metabolomics; Metabolomics - methods; Principal Component Analysis; Quality Control; Swine; Ultra-high performance liquid chromatography; Metabolomics; High-resolution mass spectrometry; Diet pattern; Ultra-high performance liquid chromatography
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2014.09.161

•We have developed a metabolomic approach to study to pigs fed with high-fat/high cholesterol and regular diet.•A number of metabolite differences were detected in the plasma, urine, and feces of pigs.•We have found that alterations in diet led to metabolic profile changes.•This methodology could be used to identify biomarkers. Non-targeted metabolite profiling can identify biological markers of dietary exposure that lead to a better understanding of interactions between diet and health. In this study, pigs were used as an animal model to discover changes in metabolic profiles between regular basal and high fat/high cholesterol diets. Extracts of plasma, fecal and urine samples from pigs fed high fat or basal regular diets for 11weeks were analysed using ultra-high performance liquid chromatography with high-resolution mass spectrometry (UHPLC–HRMS) and chemometric analysis. Cloud plots from XCMS online were used for class separation of the most discriminatory metabolites. The major metabolites contributing to the discrimination were identified as bile acids (BAs), lipid metabolites, fatty acids, amino acids and phosphatidic acid (PAs), phosphatidylglycerol (PGs), glycerophospholipids (PI), phosphatidylcholines (PCs) and tripeptides. These results suggest the developed approach can be used to identify biomarkers associated with specific feeding diets and possible metabolic disorders related to diet.