Integrating spatial and single-cell transcriptomics to characterize mouse long bone fracture healing process
Bone fracture healing is a complex and dynamic processhat requires a detailed understanding of the cellular interactions crucial for successful tissue regeneration. We employs optimized spatial transcriptomics to precisely delineate the locations and interactions of these cells within a mouse femur fracture model at day 0 before fracture and days 5, 15 post-fracture. We improved RNA quality significantly by optimizing our decalcification method using Morse's solution, coupled with the use of the Visium CytAssist platform and integrated analyses through the Seurat, CARD, and Monocle frameworks. This approach allowed us to accurately localize critical cell populations, such as periosteum progenitor cells, and identify pivotal transcription factors that regulate their activation and differentiation into chondrocytes or osteogenic cells. We particularly focused on the transformation from mesenchymal progenitor cells (MPCs) to regenerative MPCs (rMPCs), revealing how these cells recruit macrophages near the fracture line during early healing stages and their involvement in fracture healing. Furthermore, using CellChat, we explored potential receptor-ligand pathways that mediate these cellular interactions. This spatial-temporal mapping and molecular characterization substantially deepen our understanding of the cellular and molecular processes involved in fracture healing, highlighting spatial transcriptomics as a robust approach for elucidating the fundamental mechanisms governing bone regeneration. Overall design: We conducted high-quality spatial transcriptomic sequencing of long bone periosteal cells at different time points (Day 0, 5 and 15), enabling a more precise exploration of their temporal changes and roles in fracture repair.