Mitochondria Transplantation to Bone Marrow Stromal Cells Promotes Angiogenesis During Bone Repair.
Yifan WangWenjing LiYusi GuoYing HuangYaru GuoJia SongFeng MeiPeiwen LiaoZijian GongXiaopei ChiXuliang DengPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2024)
Angiogenesis is crucial for successful bone defect repair. Co-transplanting Bone Marrow Stromal Cells (BMSCs) and Endothelial Cells (ECs) has shown promise for vascular augmentation, but it face challenges in hostile tissue microenvironments, including poor cell survival and limited efficacy. In this study, the mitochondria of human BMSCs are isolated and transplanted to BMSCs from the same batch and passage number (BMSCs mito ). The transplanted mitochondria significantly boosted the ability of BMSCs mito -ECs to promote angiogenesis, as assessed by in vitro tube formation and spheroid sprouting assays, as well as in vivo transplantation experiments in balb/c mouse and SD rat models. The Dll4-Notch1 signaling pathway is found to play a key role in BMSCs mito -induced endothelial tube formation. Co-transplanting BMSCs mito with ECs in a rat cranial bone defect significantly improves functional vascular network formation, and improve bone repair outcomes. These findings thus highlight that mitochondrial transplantation, by acting through the DLL4-Notch1 signaling pathway, represents a promising therapeutic strategy for enhancing angiogenesis and improving bone repair. Hence, mitochondrial transplantation to BMSCS as a therapeutic approach for promoting angiogenesis offers valuable insights and holds much promise for innovative regenerative medicine therapies.
Keyphrases
- endothelial cells
- high glucose
- bone marrow
- bone mineral density
- vascular endothelial growth factor
- signaling pathway
- soft tissue
- oxidative stress
- bone loss
- mesenchymal stem cells
- cell therapy
- pi k akt
- postmenopausal women
- reactive oxygen species
- cell proliferation
- wound healing
- epithelial mesenchymal transition
- type diabetes
- insulin resistance
- machine learning
- deep learning
- artificial intelligence
- endoplasmic reticulum stress