Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.

Although regeneration through the reprogramming of one cell lineage to another occurs in fish and amphibians, it has not been observed in mammals. We discovered in the mouse that during wound healing, adipocytes regenerate from myofibroblasts, a cell type thought to be differentiated and nonadipogenic. Myofibroblast reprogramming required neogenic hair follicles, which triggered bone morphogenetic protein (BMP) signaling and then activation of adipocyte transcription factors expressed during development. Overexpression of the BMP antagonist Noggin in hair follicles or deletion of the BMP receptor in myofibroblasts prevented adipocyte formation. Adipocytes formed from human keloid fibroblasts either when treated with BMP or when placed with human hair follicles in vitro. Thus, we identify the myofibroblast as a plastic cell type that may be manipulated to treat scars in humans

Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We constructed a database of interactions among ligands, receptors and their cofactors that accurately represents known heteromeric molecular complexes. Based on mass action models, we then developed CellChat, a tool that is able to quantitively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applications of CellChat to several mouse skin scRNA-seq datasets for embryonic development and adult wound healing shows its ability to extract complex signaling patterns, both previously known as well as novel. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build a cell-cell communication atlas in diverse tissues.

Adipocytes have been suggested to be immunologically active, but their role in host defense is unclear. We observed rapid proliferation of preadipocytes and expansion of the dermal fat layer after infection of the skin by Staphylococcus aureus. Impaired adipogenesis resulted in increased infection as seen in Zfp423nur12 mice or in mice given inhibitors of peroxisome proliferator–activated receptor γ. This host defense function was mediated through the production of cathelicidin antimicrobial peptide from adipocytes because cathelicidin expression was decreased by inhibition of adipogenesis, and adipocytes from Camp−/− mice lost the capacity to inhibit bacterial growth. Together, these findings show that the production of an antimicrobial peptide by adipocytes is an important element for protection against S. aureus infection of the skin.

During wound healing in adult mouse skin, hair follicles and then adipocytes regenerate. Adipocytes regenerate from myofibroblasts, a specialized contractile wound fibroblast. Here we study wound fibroblast diversity using single-cell RNA-sequencing. On analysis, wound fibroblasts group into twelve clusters. Pseudotime and RNA velocity analyses reveal that some clusters likely represent consecutive differentiation states toward a contractile phenotype, while others appear to represent distinct fibroblast lineages. One subset of fibroblasts expresses hematopoietic markers, suggesting their myeloid origin. We validate this finding using single-cell western blot and single-cell RNA-sequencing on genetically labeled myofibroblasts. Using bone marrow transplantation and Cre recombinase-based lineage tracing experiments, we rule out cell fusion events and confirm that hematopoietic lineage cells give rise to a subset of myofibroblasts and rare regenerated adipocytes. In conclusion, our study reveals that wounding induces a high degree of heterogeneity among fibroblasts and recruits highly plastic myeloid cells that contribute to adipocyte regeneration.