A single-cell interactome of human tooth germ from growing third molar elucidates signaling networks regulating dental development

Abstract

Background Development of dental tissue is regulated by extensive cell crosstalk based on various signaling molecules, such as bone morphogenetic protein (BMP) and fibroblast growth factor (FGF) pathways. However, an intact network of the intercellular regulation is still lacking. Result To gain an unbiased and comprehensive view of this dental cell interactome, we applied single-cell RNA-seq on immature human tooth germ of the growing third molar, discovered refined cell subtypes, and applied multiple network analysis to identify the central signaling pathways. We found that immune cells made up over 80% of all tooth germ cells, which exhibited profound regulation on dental cells via Transforming growth factor-β, Tumor necrosis factor (TNF) and Interleukin-1. During osteoblast differentiation, expression of genes related to extracellular matrix and mineralization was continuously elevated by signals from BMP and FGF family. As for the self-renewal of apical papilla stem cell, BMP-FGFR1-MSX1 pathway directly regulated the G0-to-S cell cycle transition. We also confirmed that Colony Stimulating Factor 1 secreted from pericyte and TNF Superfamily Member 11 secreted from osteoblast regulated a large proportion of genes related to osteoclast transformation from macrophage and monocyte. Conclusions We constructed the intercellular signaling networks that regulated the essential developmental process of human tooth, which served as a foundation for future dental regeneration engineering and the understanding of oral pathology.

Establishment of inclusive single-cell transcriptome atlases from mouse and human tooth as powerful resource for dental research

“…Regarding mouse, single-cell RNA-sequencing (scRNA-seq) datasets were generated from the constantly (re-)growing incisor and the more static, human-resembling molar at different timepoints, either of whole tooth or specific tissue components ( Sharir et al, 2019 ; Takahashi et al, 2019 ; Chen et al, 2020 ; Chiba et al, 2020 , 2021 ; Krivanek et al, 2020 ; Wen et al, 2020 ; Nagata et al, 2021 ; Zhao et al, 2021 ). Human sc transcriptomic data were predominantly generated from dental pulp and periodontal tissues of molars in both healthy and diseased states ( Krivanek et al, 2020 ; Pagella et al, 2021b ; Shi et al, 2021 ; Yin et al, 2021 ; Hemeryck et al, 2022 ; Lin et al, 2022 ; Opasawatchai et al, 2022 ). All these sc analyses generated deeper insight into the tooth molecular and cellular landscape, furthering the understanding of dental cell type heterogeneity and tooth biology.…”

Single‐cell RNA sequencing in oral science: Current awareness and perspectives

“…Based on the scRNA‐seq data, Notch3 was found as a marker for hDPSC, which was also identified by lineage tracing in mouse tooth injury model 35 . Furthermore, from scRNA‐seq analysis, the fate of hDPSC was possibly determined by the microenvironment it resided 30,32 . It is noteworthy that the cell population analysis on scRNA‐seq data showed that monolayer culture of hDPSCs was significantly different from freshly isolated hDPSCs in cellular composition 36 .…”

“…Therefore, it is necessary to picture the comprehensive expression profiles of human teeth further by scRNA‐seq. The scRNA‐seq was used to discover the cellular heterogeneity and molecular signatures in human pulp 30–33 . From dynamics and differentiation trajectories analysis, endothelial cells exhibit the most dynamic behavior, while only minor differentiation trajectories are found in most dental pulp cell populations 31 .…”

“…The scRNA‐seq was used to discover the cellular heterogeneity and molecular signatures in human pulp. 30 , 31 , 32 , 33 From dynamics and differentiation trajectories analysis, endothelial cells exhibit the most dynamic behavior, while only minor differentiation trajectories are found in most dental pulp cell populations. 31 According to the ligand‐receptor pair analysis among cell populations, the pulp cells communicated the most with other cell types, while T cells communicated the least.…”

“… 35 Furthermore, from scRNA‐seq analysis, the fate of hDPSC was possibly determined by the microenvironment it resided. 30 , 32 It is noteworthy that the cell population analysis on scRNA‐seq data showed that monolayer culture of hDPSCs was significantly different from freshly isolated hDPSCs in cellular composition. 36 Hence, it may affect the application of hDPSC in tooth regeneration engineering.…”