Context-dependent regulation of endothelial cell metabolism: differential effects of the PPARβ/δ agonist GW0742 and VEGF-A.
Ashton FaulknerEleanor LynamRobert PurcellColeen JonesColleen LopezMary BoardKay-Dietrich WagnerNicole WagnerCarolyn A CarrCaroline Wheeler-JonesPublished in: Scientific reports (2020)
Peroxisome proliferator activated receptor β/δ (PPARβ/δ) has pro-angiogenic functions, but whether PPARβ/δ modulates endothelial cell metabolism to support the dynamic phenotype remains to be established. This study characterised the metabolic response of HUVEC to the PPARβ/δ agonist, GW0742, and compared these effects with those induced by VEGF-A. In HUVEC monolayers, flux analysis revealed that VEGF-A promoted glycolysis at the expense of fatty acid oxidation (FAO), whereas GW0742 reduced both glycolysis and FAO. Only VEGF-A stimulated HUVEC migration and proliferation whereas both GW0742 and VEGF-A promoted tubulogenesis. Studies using inhibitors of PPARβ/δ or sirtuin-1 showed that the tubulogenic effect of GW0742, but not VEGF-A, was PPARβ/δ- and sirtuin-1-dependent. HUVEC were reliant on glycolysis and FAO, and inhibition of either pathway disrupted cell growth and proliferation. VEGF-A was a potent inducer of glycolysis in tubulogenic HUVEC, while FAO was maintained. In contrast, GW0742-induced tubulogenesis was associated with enhanced FAO and a modest increase in glycolysis. These novel data reveal a context-dependent regulation of endothelial metabolism by GW0742, where metabolic activity is reduced in monolayers but enhanced during tubulogenesis. These findings expand our understanding of PPARβ/δ in the endothelium and support the targeting of PPARβ/δ in regulating EC behaviour and boosting tissue maintenance and repair.
Keyphrases
- endothelial cells
- vascular endothelial growth factor
- fatty acid
- high glucose
- insulin resistance
- signaling pathway
- nitric oxide
- adipose tissue
- single cell
- skeletal muscle
- computed tomography
- metabolic syndrome
- oxidative stress
- magnetic resonance imaging
- artificial intelligence
- big data
- drug delivery
- deep learning
- stress induced
- electron transfer