SUMMARY
The oral mucosa is one of the most rapidly dividing tissues in the body and serves as a barrier to physical and chemical insults from mastication, food, and microorganisms. Breakdown of this barrier can lead to significant morbidity and potentially life-threatening infections for patients. Determining the identity and organization of oral epithelial progenitor cells (OEPCs) is therefore paramount to understanding their roles in homeostasis and disease. Using lineage tracing and label retention experiments, we show that rapidly-dividing OEPCs are located broadly within the basal layer of the mucosa throughout the oral cavity. Quantitative clonal analysis demonstrated that OEPCs undergo population asymmetrical divisions following neutral drift dynamics and that they respond to chemotherapyinduced damage by altering daughter cell fates. Finally, using single cell RNAseq, we establish the basal layer population structure and propose a model that defines the organization of cells within the basal layer.
The identification and characterization of stem cells is a major focus of developmental biology and regenerative medicine. The advent of genetic inducible fate mapping techniques has made it possible to precisely label specific cell populations and to follow their progeny over time. When combined with advanced mathematical and statistical methods, stem cell division dynamics can be studied in new and exciting ways. Despite advances in a number of tissues, relatively little attention has been paid to stem cells in the oral epithelium. This review will focus on current knowledge about adult oral epithelial stem cells, paradigms in other epithelial stem cell systems that could facilitate new discoveries in this area and the potential roles of epithelial stem cells in oral disease.
Highlights d Single assay to identify and characterize all major human immune cell lineages d Readily available and extensively validated antibody panel d Additional (>10) targets can be added to meet specific hypotheses d Allows identification of disease-associated immune signatures and biomarkers
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