Similar Features, Different Behaviors: A Comparative In VitroStudy of the Adipogenic Potential of Stem Cells from Human Follicle, Dental Pulp, and Periodontal Ligament.
Melissa D Mercado-RubioErick Pérez-ArguetaAlejandro ZepedaFernando Javier Aguilar-AyalaRicardo Peñaloza-CuevasAngela Kú-GonzálezRafael Antonio Rojas-HerreraBeatriz A Rodas-JuncoGeovanny Iran Nic-CanPublished in: Journal of personalized medicine (2021)
Dental tissue-derived mesenchymal stem cells (DT-MSCs) are a promising resource for tissue regeneration due to their multilineage potential. Despite accumulating data regarding the biology and differentiation potential of DT-MSCs, few studies have investigated their adipogenic capacity. In this study, we have investigated the mesenchymal features of dental pulp stem cells (DPSCs), as well as the in vitro effects of different adipogenic media on these cells, and compared them to those of periodontal ligament stem cells (PLSCs) and dental follicle stem cells (DFSCs). DFSC, PLSCs, and DPSCs exhibit similar morphology and proliferation capacity, but they differ in their self-renewal ability and expression of stemness markers (e.g OCT4 andc-MYC). Interestingly, DFSCs and PLSCs exhibited more lipid accumulation than DPSCs when induced to adipogenic differentiation. In addition, the mRNA levels of adipogenic markers (PPAR, LPL, and ADIPOQ) were significantly higher in DFSCs and PLSCs than in DPSCs, which could be related to the differences in the adipogenic commitment in those cells. These findings reveal that the adipogenic capacity differ among DT-MSCs, features that might be advantageous to increasing our understanding about the developmental origins and regulation of adipogenic commitment.
Keyphrases
- stem cells
- mesenchymal stem cells
- induced apoptosis
- endothelial cells
- signaling pathway
- cell therapy
- high glucose
- human health
- umbilical cord
- adipose tissue
- epithelial mesenchymal transition
- atomic force microscopy
- cell proliferation
- optical coherence tomography
- metabolic syndrome
- transcription factor
- gene expression
- deep learning
- endoplasmic reticulum stress
- high resolution
- risk assessment
- oxidative stress
- dna methylation
- diabetic retinopathy
- single cell
- artificial intelligence
- stress induced