Biomaterials induce an immune response and mobilization of macrophages, yet identification and phenotypic characterization of functional macrophage subsets in vivo remain limited. Researchers from Johns Hopkins University School of Medicine performed single-cell RNA sequencing analysis on macrophages sorted from either a biologic matrix [urinary bladder matrix (UBM)] or synthetic biomaterial [polycaprolactone (PCL)]. Implantation of UBM promotes tissue repair through generation of a tissue environment characterized by a T helper 2 (TH2)/interleukin (IL)–4 immune profile, whereas PCL induces a standard foreign body response characterized by TH17/IL-17 and fibrosis. Unbiased clustering and pseudotime analysis revealed distinct macrophage subsets responsible for antigen presentation, chemoattraction, and phagocytosis, as well as a small population with expression profiles of both dendritic cells and skeletal muscle after UBM implantation. In the PCL tissue environment, the researchers identified a CD9hi+IL-36γ+ macrophage subset that expressed TH17-associated molecules. These macrophages were virtually absent in mice lacking the IL-17 receptor, suggesting that they might be involved in IL-17–dependent immune and autoimmune responses.
Single-cell characterization of macrophages in fibrotic and regenerative microenvironments
(A) Experimental overview. A virtual aggregate of macrophages in fibrosis and regeneration generated from scRNAseq after sorting of F4/80hi+CD64+. Cells were isolated from murine volumetric muscle injuries at 1 week, treatment with biomaterials UBM (regenerative, IL-4 tissue environment), synthetic (fibrotic, IL-17–rich environment), or saline (wound control). (B) Heatmap of differentially expressed genes. Up to 200 cells per cluster are shown, ordered by cluster, with the top 10 differentially expressed genes. Functionally relevant genes from terminal clusters are annotated. (C) Dimensional reduction projection of cells onto two dimensions using UMAP. Cells are colored by experimental biomaterial condition (top) and computationally determined cluster (bottom). (D) Summary of cluster differentiation trajectories, composition by experimental origin, markers, and biological functions generated by bioinformatics analysis. (E) Flow cytometry strategy informed by computationally determined markers including CD9, CD301b, and MHCII differentiating in vivo macrophage subsets from UBM or synthetic biomaterial. Subsets are colored equivalent to computational clusters, back-gated into tSNE projection.
Identification and comparison of the unique phenotypical and functional macrophage subsets in mouse and human tissue samples suggest broad relevance of the new classification. These distinct macrophage subsets demonstrate previously unrecognized myeloid phenotypes involved in different tissue responses and provide targets for potential therapeutic modulation in tissue repair and pathology.