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. 2015 May 6;5:9884.
doi: 10.1038/srep09884.

A Metabolomic Study of the PPARδ Agonist GW501516 for Enhancing Running Endurance in Kunming Mice

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Free PMC article

A Metabolomic Study of the PPARδ Agonist GW501516 for Enhancing Running Endurance in Kunming Mice

Wei Chen et al. Sci Rep. .
Free PMC article

Abstract

Exercise can increase peroxisome proliferator-activated receptor-δ (PPARδ) expression in skeletal muscle. PPARδ regulates muscle metabolism and reprograms muscle fibre types to enhance running endurance. This study utilized metabolomic profiling to examine the effects of GW501516, a PPARδ agonist, on running endurance in mice. While training alone increased the exhaustive running performance, GW501516 treatment enhanced running endurance and the proportion of succinate dehydrogenase (SDH)-positive muscle fibres in both trained and untrained mice. Furthermore, increased levels of intermediate metabolites and key enzymes in fatty acid oxidation pathways were observed following training and/or treatment. Training alone increased serum inositol, glucogenic amino acids, and branch chain amino acids. However, GW501516 increased serum galactose and β-hydroxybutyrate, independent of training. Additionally, GW501516 alone raised serum unsaturated fatty acid levels, especially polyunsaturated fatty acids, but levels increased even more when combined with training. These findings suggest that mechanisms behind enhanced running capacity are not identical for GW501516 and training. Training increases energy availability by promoting catabolism of proteins, and gluconeogenesis, whereas GW501516 enhances specific consumption of fatty acids and reducing glucose utilization.

Figures

Figure 1
Figure 1. The effects of GW501516 on running performance, blood glucose, and blood lactate in sedentary and trained KM mice.
Forced wheel running endurance tests were performed following 3 weeks of treatment. (a) shows the total distance ran by mice in each group. Blood glucose (b) and serum lactate (c) levels are shown for all groups both before and after running tests (n = 10–11 per group).*p < 0.05, **p < 0.01 compared to the NN group; #p < 0.05 compared to the TN group.
Figure 2
Figure 2. Metabolomic analysis of serum fatty acids.
(a) shows PCA scores trajectory plots, (b) shows the representative heat map of untrained (NN and NG) and trained (TN and TG) mice. In the heat map, samples are sorted by row and metabolites are sorted by column. Green diamond, NN; Red triangle, NG; Black circle, TN; Blue square, TG;
Figure 3
Figure 3. Differences in metabolite concentrations between groups.
(a) shows PLS-DA score plots of groups based on serum spectral data from GC × GC–TOFMS. The score plots distinctly cluster the GW501516 treatment groups (NG and TG) compared to either control group (NN and NG). Furthermore, the trained groups (TN and TG) are distinctly clustered compared to their respective controls (NN and TG). (b) and (c) show changes in the relative concentrations of metabolites in the four groups. Two-tailed parametric t tests were used to compare concentration changes in each metabolite between groups (n = 10–11 per group). *p < 0.05, **p < 0.01 compared to the NN group, #p < 0.05, ##p < 0.01 versus TN; †p < 0.05, ††p < 0.01 compared to the NG group.
Figure 4
Figure 4. Pathway analysis of fatty acid metabolomics data
Serum metabolites that were altered between groups are shown in red.
Figure 5
Figure 5. Changes in metabolites from whole serum.
(a) shows the total ion chromatogram (TIC) of serum samples following GC-TOFMS. (b) shows the OPLS-DA score plot of serum samples for cross-validation.
Figure 6
Figure 6. Metabolites that were significantly different between groups
(a) shows serum glucose, galactose, hydroxybutyrate, and inositol. (b) shows serum glucogenic amino acid levels and (c) shows levels of branched chain amino acids (n = 10–11 per group). *p < 0.05, **p < 0.01 compared to the NN group; #p < 0.05 compared to the TN group.
Figure 7
Figure 7. The effects of GW501516 treatment on skeletal muscle gene expression in trained and sedentary KM mice
Gene expression was measured by QPCR (n = 4 per group). *p < 0.05, **p < 0.01 compared to the NN group; #p < 0.05, ##p < 0.01 compared to the TN group.
Figure 8
Figure 8. The effects of GW501516 on SDH-positive fibres in skeletal muscle of sedentary and trained KM mice
(a) shows representative cross sections of a metachromatically stained gastrocnemius from each group of mice. Type-I fibres are stained blue. (b) shows quantification of SDH-positive fibres in all groups (n = 3). *p < 0.05 compared to the NN group.

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