Unraveling the Transcription Factor Code of Odontoblast Differentiation
| Authors | |
|---|---|
| Year of publication | 2025 |
| Type | Article in Periodical |
| Magazine / Source | Journal of Dental Research |
| MU Faculty or unit | |
| Citation | |
| web | https://journals.sagepub.com/doi/10.1177/00220345251348148 |
| Doi | https://doi.org/10.1177/00220345251348148 |
| Keywords | tooth development; odontogenesis; dentin; bioengineering; cell differentiation; stem cell(s) |
| Description | The molecular mechanisms controlling the differentiation of stem cells into specialized cells and tissues are enormously complex. Deciphering the mechanisms behind this precisely regulated process is essential not only for understanding ontogenesis but also for interpretations of evolutionary dynamics. A deep understanding of differentiation processes in various cell types would open the way for safe and targeted tissue engineering. This was previously limited by technical constraints, but the recent development of multiomic approaches has overcome these barriers, providing unprecedented insight into the intricate workings of this molecular machinery. Based on single-cell RNA-seq analyses of continuously growing mouse teeth, 4 transcription factors (Etv4, Gsc, Sall1, and Nupr1) were selected. Their role during tooth development has not been previously evaluated. Here, we provide evidence about their function in the differentiation of odontoblasts-dental cells responsible for dentin production. Our results revealed that controlled overexpression of specific transcription factors directly in mouse-induced pluripotent stem cells is sufficient to guide their differentiation into cells with an odontoblast-like phenotype, both in vitro and in vivo. The differentiated cells exhibited upregulated expression of odontoblast-specific molecular markers (DMP1 and DSP) as well as production of collagenous and mineralized tissue. We demonstrate that a deep insight into fundamental developmental events can provide a powerful basis for innovative cell differentiation approaches. Taken together, this research might serve as a proof of concept for using large-omics data in the generation of specific, differentiated cell types by controlled expression of a particular transcription factor code. This may represent a turning point in both developmental biology and regenerative medicine fields. |
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