bioRxivDevelopmental BiologyPreprint
Macrophage metabolism directs regenerative versus fibrotic healing through BMP signaling in the mouse digit tip
Mimi C. SammarcoiD, Siqi Liu, Ni SuiD, Madhumidha Ramesh, Charlotte Raymond, John Carleton, Anne LeiD, Alexander J. TrostleiD, Robert ToweriD, Jennifer SimkiniD
Abstract
Macrophages play a central role in determining the outcomes of healing, coordinating regeneration in some injuries and scar formation in others. In both cases, this coordination involves the cross-talk between macrophages and surrounding cells. But what drives the different cross-communication pathways to determine healing outcomes is not well known. In this study, we make use of the mouse digit tip amputation model, in which an amputation through the third phalangeal element (P3) is able to completely regenerate whereas an amputation through the second phalangeal element (P2) forms a scar. We identify a population of macrophages that is specific to the P3 regenerating digit. By integrating single-cell RNAseq, spatial transcriptomics, and metabolomic analyses, we show that this population localizes specifically to the growing bone front, express BMP ligands that drive downstream BMP activation in neighboring osteoblasts and is governed by a two-part metabolic switch involving increased fatty acid oxidation coupled with reduced glycolytic activity. This spatially restricted, BMP-expressing macrophage population is entirely absent in the scar-forming P2 injury, and our data indicate that environmental conditions unique to the regenerating digit are responsible for its emergence. Together these findings identify a regeneration-specific macrophage signaling center for patterned bone formation and suggest that targeting the metabolic conditions that drive this population could improve the efficacy of regenerative therapies.
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- assay: metabolomics
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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