Changes, and the Relevance Thereof, in Mitochondrial Morphology during Differentiation into Endothelial Cells.
Ji Won ShinSo Hee ParkYun Gyeong KangYanru WuHyun Ju ChoiJung-Woog ShinPublished in: PloS one (2016)
The roles of mitochondria in various physiological functions of vascular endothelial cells have been investigated extensively. Morphological studies in relation to physiological functions have been performed. However, there have been few reports of morphological investigations related to stem cell differentiation. This was the first morphological study of mitochondria in relation to endothelial differentiation and focused on quantitative analysis of changes in mitochondrial morphology, number, area, and length during differentiation of human mesenchymal stem cells (hMSCs) into endothelial-like cells. To induce differentiation, we engaged vascular endothelial growth factors and flow-induced shear stress. Cells were classified according to the expression of von Willebrand factor as hMSCs, differentiating cells, and almost fully differentiated cells. Based on imaging analysis, we investigated changes in mitochondrial number, area, and length. In addition, mitochondrial networks were quantified on a single-mitochondrion basis by introducing a branch form factor. The data indicated that the mitochondrial number, area per cell, and length were decreased with differentiation. The mitochondrial morphology became simpler with progression of differentiation. These findings could be explained in view of energy level during differentiation; a higher level of energy is needed during differentiation, with larger numbers of mitochondria with branches. Application of this method to differentiation into other lineages will explain the energy levels required to control stem cell differentiation.
Keyphrases
- endothelial cells
- oxidative stress
- induced apoptosis
- high glucose
- cell death
- cell cycle arrest
- high resolution
- poor prognosis
- stem cells
- machine learning
- signaling pathway
- magnetic resonance imaging
- mass spectrometry
- endoplasmic reticulum stress
- diabetic rats
- photodynamic therapy
- big data
- atomic force microscopy
- artificial intelligence
- deep learning
- cell proliferation