Single-cell analysis defines the lineage plasticity of stem cells in cervix epithelium.
Zixian ZhaoYujia WangYingchuan WuDandan LiTing ZhangYu MaXiaoming TengWei ZuoPublished in: Cell regeneration (London, England) (2021)
Information about the dynamic change and post-injury regeneration of cervical epithelium is relatively rare, even though it is tightly related to gynecologic malignancy. Here, using a feeder cell-based culturing system, we stably cloned mouse and human P63 and KRT5 expressing cells from the adult cervix as putative cervical stem/progenitor cells (CVSCs). When subjected to differentiation, the cultured cells gave rise to mature cervical epithelium by differentiating into squamous or glandular cells. The ability of endogenous mouse CVSCs to reconstitute cervical epithelium after injury was also evident from the genetic lineage tracing experiments. Single-cell transcriptomic analysis further classified the CVSCs into three subtypes and delineated their bi-lineage differentiation roadmap by pseudo-time analysis. We also tracked the real-time differentiation routes of two representing single CVSC lines in vitro and found that they recapitulated the predicted roadmap in pseudo-time analysis. Signaling pathways including Wnt, TGF-beta, Notch and EGFR were found to regulate the cervical epithelial hierarchy and implicated the different roles of distinct types of cells in tissue homeostasis and tumorigenesis. Collectively, the above data provide a cloning system to achieve stable in vitro culture of a bi-lineage stem/progenitor cell population in the cervix, which has profound implications for our understanding of the cervix stem/progenitor cell function in homeostasis, regeneration, and disease and could be helpful for developing stem cell-based therapies in future.
Keyphrases
- stem cells
- single cell
- induced apoptosis
- rna seq
- cell cycle arrest
- preterm birth
- signaling pathway
- endothelial cells
- small cell lung cancer
- oxidative stress
- cell death
- healthcare
- mesenchymal stem cells
- magnetic resonance
- genome wide
- intellectual disability
- epithelial mesenchymal transition
- machine learning
- deep learning
- bone marrow
- social media
- big data
- artificial intelligence
- epidermal growth factor receptor
- health information