Integrating spatial and single-cell transcriptomics to characterize mouse long bone fracture healing process

Bone fracture healing is a dynamic process that relies on coordinated cellular interactions for effective tissue regeneration. We employ optimized spatial transcriptomics to delineate the locations and interactions of the involved cell types within a mouse femur fracture model on Day 0 before fracture and at Days 5 and 15 postfracture. We improve 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 packages. This approach allows 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 focus 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 explore potential receptor‒ligand pathways that mediate these cellular interactions. The spatial-temporal mapping and molecular characterization performed in this study substantially deepen our understanding of the cellular and molecular processes involved in fracture healing, highlighting spatial transcriptomics as a robust approach for elucidating the mechanisms governing bone regeneration.