Suppression of PGC-1α Drives Metabolic Dysfunction in TGFβ2-Induced EMT of Retinal Pigment Epithelial Cells.
Daisy Y ShuErik R ButcherMagali Saint-GeniezPublished in: International journal of molecular sciences (2021)
PGC-1α, a key orchestrator of mitochondrial metabolism, plays a crucial role in governing the energetically demanding needs of retinal pigment epithelial cells (RPE). We previously showed that silencing PGC-1α induced RPE to undergo an epithelial-mesenchymal-transition (EMT). Here, we show that induction of EMT in RPE using transforming growth factor-beta 2 (TGFβ2) suppressed PGC-1α expression. Correspondingly, TGFβ2 induced defects in mitochondrial network integrity with increased sphericity and fragmentation. TGFβ2 reduced expression of genes regulating mitochondrial dynamics, reduced citrate synthase activity and intracellular ATP content. High-resolution respirometry showed that TGFβ2 reduced mitochondrial OXPHOS levels consistent with reduced expression of NDUFB5. The reduced mitochondrial respiration was associated with a compensatory increase in glycolytic reserve, glucose uptake and gene expression of glycolytic enzymes (PFKFB3, PKM2, LDHA). Treatment with ZLN005, a selective small molecule activator of PGC-1α, blocked TGFβ2-induced upregulation of mesenchymal genes (αSMA, Snai1, CTGF, COL1A1) and TGFβ2-induced migration using the scratch wound assay. Our data show that EMT is accompanied by mitochondrial dysfunction and a metabolic shift towards reduced OXPHOS and increased glycolysis that may be driven by PGC-1α suppression. ZLN005 effectively blocks EMT in RPE and thus serves as a novel therapeutic avenue for treatment of subretinal fibrosis.
Keyphrases
- transforming growth factor
- epithelial mesenchymal transition
- oxidative stress
- diabetic rats
- high glucose
- skeletal muscle
- gene expression
- small molecule
- poor prognosis
- signaling pathway
- high resolution
- stem cells
- dna methylation
- endothelial cells
- cell proliferation
- binding protein
- combination therapy
- mass spectrometry
- metabolic syndrome
- immune response
- electronic health record
- insulin resistance
- reactive oxygen species
- artificial intelligence