[Isolation and characterization of normal mandibular periosteal stem cells from human and macaca mulatta and cross-species single-cell analysis].
Z S WangY Y LiH T WangD H ZouZ Y ZhangPublished in: Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology (2024)
Objective: To investigate the presence of a distinct stem cell populations different from mesenchymal stem cells in the mandibular periosteum of both human and non-human primates (macaca mulatta), to explore its properties during intramembranous osteogenesis and to establish standard protocols for the isolation, culturing and expanding of mandibular periosteal stem cells (PSCs) distinguished from other PSCs in other anatomical regions. Methods: Periosteum was harvested from the bone surface during flap bone removal in patients aged 18-24 years undergoing third molar extraction and from the buccal side of the mandibular premolar region of 1-year-old macaca mulatta respectively, and then subjected to single-cell sequencing using the Illumina platform Novaseq 6000 sequencer. Cross-species single-cell transcriptome sequencing results were compared using homologous gene matching. PSCs were isolated from primary tissues using two digestion methods with body temperature and low temperature, and their surface markers (CD200, CD31, CD45 and CD90) were identified by cell flow cytometry. Then, the ability of cell proliferation and three-lineage differentiation of PSCs expanded to the third generation in vitro in different species were evaluated. Finally, the similarities and differences in osteogenic properties of periosteal stem cells and bone marrow mesenchymal stem cells were compared. Results: The single-cell sequencing results indicated that 18 clusters of cell populations were identified after homologous gene matching for dimensionality reduction, and manual cellular annotation was conducted for each cluster based on cell marker databases. The comparison of different digestion protocols proved that the low-temperature overnight digestion protocol can stably isolate periosteal stem cells from the human and m. mulatta mandibular periosteum and the cells exhibited a fibroblast-like morphology. This research confirmed that periosteal stem cells of human and m. mulatta had similar proliferation capabilities through the cell counting kit-8 assay. Flow cytometry analysis was then used to identify the cells isolated from the periosteum expressed CD200(+), CD31(-), CD45(-), CD90(-). Then, human and m. mulatta periosteal stem cells were induced into osteogenesis, adipogenesis, and chondrogenesis to demonstrate their corresponding multi-lineage differentiation capabilities. Finally, comparison with bone marrow mesenchymal stem cells further clarified the oesteogenesis characteristics of periosteal stem cells. The above experiments proved that the cells isolated from the periosteum were peiosteal cells with characteristics of stem cells evidenced by their cell morphology, proliferation ability, surface markers, and differentiation ability, and that this group of periosteal stem cells possessed characteristics different from traditional mesenchymal stem cells. Conclusions: In this study, normal mandibular periosteal stem cells from humans and m. mulatta were stably isolated and identified for the first time, providing a cellular foundation for investigating the mechanism of mandibular intramembranous osteogenesis, exploring ideal non-human primate models and establishing innovative strategies for clinically mandibular injury repair.
Keyphrases
- single cell
- stem cells
- rna seq
- endothelial cells
- cell therapy
- mesenchymal stem cells
- induced apoptosis
- high throughput
- induced pluripotent stem cells
- flow cytometry
- cell proliferation
- bone marrow
- gene expression
- high glucose
- dna methylation
- endoplasmic reticulum stress
- randomized controlled trial
- cell cycle arrest
- genome wide
- transcription factor
- dna damage
- skeletal muscle
- copy number
- ejection fraction
- type diabetes
- bone mineral density
- artificial intelligence
- pi k akt
- insulin resistance
- data analysis