Skeletal stem cells from the suture mesenchyme, which are referred to as suture stem cells (SuSCs), exhibit long-term self-renewal, clonal expansion, and multipotency. These SuSCs reside in the suture midline and serve as the skeletal stem cell population responsible for calvarial development, homeostasis, injury repair, and regeneration. The ability of SuSCs to engraft in injury site to replace the damaged skeleton supports their potential use for stem cell–based therapy. Here, we identified BMPR1A as essential for SuSC self-renewal and SuSC-mediated bone formation. SuSC-specific disruption of Bmpr1a in mice caused precocious differentiation, leading to craniosynostosis initiated at the suture midline, which is the stem cell niche. We found that BMPR1A is a cell surface marker of human SuSCs. Using an ex vivo system, we showed that SuSCs maintained stemness properties for an extended period without losing the osteogenic ability. This study advances our knowledge base of congenital deformity and regenerative medicine mediated by skeletal stem cells.

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For decades, we have relied on population and time-averaged snapshots of dynamic molecular scale events to understand how genes are regulated during development and beyond. The advent of techniques to observe single-molecule kinetics in increasingly endogenous contexts, progressing from in vitro studies to living embryos, has revealed how much we have missed. Here, we provide an accessible overview of the rapidly expanding family of technologies for single-molecule tracking (SMT), with the goal of enabling the reader to critically analyse single-molecule studies, as well as to inspire the application of SMT to their own work. We start by overviewing the basics of and motivation for SMT experiments, and the trade-offs involved when optimizing parameters. We then cover key technologies, including fluorescent labelling, excitation and detection optics, localization and tracking algorithms, and data analysis. Finally, we provide a summary of selected recent applications of SMT to study the dynamics of gene regulation.

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