Fibroblast mTOR/PPARγ/HGF axis protects against tubular cell death and acute kidney injury.
Yuan GuiQingmiao LuMengru GuMingjie WangYan LiangXingwen ZhuXian XueXiaoli SunWeichun HeJunwei YangAllan Zijian ZhaoBo XiaoChunsun DaiPublished in: Cell death and differentiation (2019)
Kidney fibroblasts play a crucial role in dictating tubular cell fate and the outcome of acute kidney injury (AKI). The underlying mechanisms remain to be determined. Here, we found that mTOR signaling was activated in fibroblasts from mouse kidneys with ischemia/reperfusion injury (IRI). Ablation of fibroblast Rheb or Rictor promoted, while ablation of fibroblast Tsc1 protected against tubular cell death and IRI in mice. In tubular cells cultured with conditioned media (CM) from Rheb-/- or Rictor-/- fibroblasts, less hepatocyte growth factor (HGF) receptor c-met signaling activation or staurosporine-induced cell apoptosis was observed. While CM from Tsc1-/- fibroblasts promoted tubular cell c-met signaling activation and inhibited staurosporine-induced cell apoptosis. In kidney fibroblasts, blocking mTOR signaling downregulated the expression of peroxisome proliferator-activated receptor gamma (PPARγ) and HGF. Downregulating fibroblast HGF expression or blocking tubular cell c-met signaling facilitated tubular cell apoptosis. Notably, renal PPARγ and HGF expression was less in mice with fibroblast Rheb or Rictor ablation, but more in mice with fibroblast Tsc1 ablation than their littermate controls, respectively. Together, these data suggest that mTOR signaling activation in kidney fibroblasts protects against tubular cell death and dictates the outcome of AKI through stimulating PPARγ and HGF expression.
Keyphrases
- high glucose
- acute kidney injury
- cell death
- poor prognosis
- cell proliferation
- endothelial cells
- growth factor
- extracellular matrix
- cell cycle arrest
- insulin resistance
- ischemia reperfusion injury
- binding protein
- cardiac surgery
- single cell
- long non coding rna
- machine learning
- type diabetes
- metabolic syndrome
- electronic health record
- artificial intelligence