Postprandial metabolic events in mini-pigs: new insights from a combined approach using plasma metabolomics, tissue gene expression, and enzyme activity

• Published in: Metabolomics Vol. 11; no. 4; pp. 964 - 979
• Main Authors: Polakof, Sergio, Rémond, Didier, Rambeau, Mathieu, Pujos-Guillot, Estelle, Sébédio, Jean-Louis, Dardevet, Dominique, Comte, Blandine, Savary-Auzeloux, Isabelle
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2015; Springer Nature B.V; Springer Verlag
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedicine; Cell Biology; Developmental Biology; Food and Nutrition; Life Sciences; Molecular Medicine; Original Article; Metabolomics; Muscle; Mini-pig; Postprandial metabolism; Liver
• ISSN: 1573-3882; 1573-3890
• DOI: 10.1007/s11306-014-0753-8

To unravel metabolic adaptations preceding the occurrence of metabolic dysregulations, a nutritional challenge appears as the best tool capable to reveal metabolic disturbances compared to single-point measurements at the static fasting (PA) state. The aim of the present work was to study the metabolic trajectories at the postprandial (PP) state in a relevant human nutrition animal model combining plasma metabolome analysis with classical metabolism exploration tools. In a first trial, three mini pigs were fed a test meal and arterial blood samples withdrawn before and over 4 h following the meal for plasma metabolites analysis (LC–MS and classical biochemistry). In a second trial, three mini-pigs were euthanized after an overnight fasting and three others 1:15 h after the test meal. The metabolism was explored at the molecular (mRNA levels), biochemical (enzyme activities) and signalling (phosphorylation status) levels in the liver and muscle. As expected, and in accordance with alterations in plasma glucose, urea levels, gluconeogenesis/glycolysis/lipid and amino acid (AA) oxidation genes expression and enzymes activities, the metabolomic approach discriminated the PA from the PP state (R 2 Ycum = 0.991; Q 2 Ycum = 0.921). More interestingly hierarchical cluster analysis revealed that the PP metabolome included actually four types of kinetic profiles. Further, PLS-DA analysis revealed a two-step pattern: 1–2  and 3–4 h (R 2 Ycum = 0.837; Q 2 cum = 0.635). Among the molecules explaining this discrimination, several AAs and phospholipid species were highlighted and their significance in PP metabolism discussed. Our data showed that the combination of these approaches in mini-pigs could be used to investigate PP metabolic adaptations in various physiological and patho-physiological states.