Complementing muscle regeneration-fibro-adipogenic progenitor and macrophage-mediated repair of elderly human skeletal muscle

Abstract

The capacity to regenerate skeletal muscle after injury requires a complex and well-coordinated cellular response, which is challenged in aged skeletal muscle. Here, we unravel the intricate dynamics of elderly human skeletal muscle regeneration by combining spatial, temporal, and single cell transcriptomics. Using spatial RNA sequencing (n = 3), we profile the expression of human protein-coding genes in elderly human skeletal muscle biopsies before as well as 2-, 8-, and 30-day post injury (NCT03754842). Single Cell-Spatial deconvolution analysis highlights monocytes/macrophages and fibro-adipogenic progenitors (FAPs) as pivotal players in human muscle regeneration. By utilizing flow cytometry (n = 9) and cell sorting we confirm the increased cellular content and activity during regeneration. Spatial correlation analysis unveils FAPs and monocytes/macrophages co-localization and intercellular communication, mediated by complement factor C3. Immunostaining confirms C3 expression in FAPs and FAP secretion of C3, suggesting a role in phagocytosis of necrotic muscle cells. Finally, functional assays demonstrate C3's impact on human monocyte metabolism, survival and phagocytosis, unveiling its involvement in skeletal muscle regeneration. These insights elucidate the FAP-macrophage interplay in aged human muscle with perspectives for future therapeutic interventions to reduce the age-induced decline in regenerative capacity.

Fig. 1. Spatial transcriptome analysis of regenerating human skeletal muscle.

A Schematic illustration of the muscle injury protocol and analysis (Created in BioRender. Farup, J. (2025) https://BioRender.com/qyf7ywo). Elderly human subjects were recruited and exposed to electrically induced skeletal muscle injury in the vastus lateralis part of the quadriceps femoris muscle, wherefrom biopsies were obtained before (pre), 2, 8, and 30 days post injury. H&E staining of cryosections confirmed substantial tissue injury. Spatial transcriptome analysis was carried out in muscle tissue from three individual subjects using the 10X Visium platform. B Clustering of single spatial tissue spots during the time course of regeneration. Spots were independently divided in 9 clusters based on expression pattern. Every dot represents a single spatial spot. Spots containing transcripts from cluster 6, 7, and 8 were highly present after injury (marked). C Change in gene expression during regeneration based on gene clusters. D Fraction of cluster 0-5 was decreased, whereas cluster 6, 7, and 8 revealed an increased presence after injury (*p < 0.05, n = 3, biological replicates, one-way ANOVA with Holm-Sidak’s multiple comparisons test). E Gene Ontology analysis of cluster 6, 7, and 8 shows enrichment of genes related to extracellular matrix, immune response, and myofiber development, respectively (adjusted p < 0.05 using hypergeometric test with adjusting using Benjamini–Hochberg False-Discovery Rate procedure). F Representative spatial expression of top gene clusters from Gene Ontology analysis with wide spatial increase most intensive 8 days post injury (dpi = days post injury).

Fig. 2. Cellular deconvolution and spatiotemporal associations in regeneration.

A Schematic illustration of the cellular deconvolution approach using spatial transcriptomic and single-cell sequencing data from human skeletal muscle (Created in BioRender. Farup, J. (2025) https://BioRender.com/uxex51k). B Fractional distribution of specific cell type transcripts during the course of regeneration shows FAPs and monocytes/macrophages to constitute the two cell populations with largest relative increase (n = 3, biological replicates, curves represents means). C Change in cell content during regeneration quantified from tissue homogenate by flow cytometry. Monocyte content was increased in the early phase of regeneration whereas lymphocyte, Muscle stem cell (MuSC), Fibro-adipogenic progenitors (FAP) and endothelial cell content was increased at later time points (# = p < 0.05 pre vs. 2dpi; (* = p < 0.05 pre vs. 8dpi; + = p < 0.05 pre vs. 30dpi) (Monocyte, MuSCs, endothelial cells, lymphocytes: n = 10; FAPs: n = 9, biological replicates, one-way ANOVA with Dunnett’s test for multiple comparisons, graph represents median ± interquartile range). D Cell-cell proportion correlation revealed that FAPs were spatiotemporally correlated with monocytes/macrophages, lymphocytes, and endothelial cells (n = 3, biological replicates). E Spatial distribution of spots containing FAP and monocyte/macrophage transcript at different time points. F Immunostaining of FAPs (PDGFR-α) and macrophages (CD68) 8dpi shows a close spatial proximity in injured areas (this was repeated at baseline and day 8 for n = 10 subjects with similar results depending on the magnitude of tissue regeneration). Scale bar represents 62.5 µm. Arrows mark PDGFR-α expressing cells (dpi = days post injury). Source data are provided as a Source Data file.

Fig. 3. FAP derived complement factor C3 is a mediator for monocyte/macrophage interaction.

A Receptor-ligand analysis of mononuclear cells from human skeletal muscle identifies diverse communicative pathways from fibro-adipogenic progenitors (FAPs) to endothelial cells, lymphatic endothelial cells, and monocytes/macrophages. B Communicative pathways from resident mononuclear cells to macrophages shows a large degree of interaction between FAPs and monocytes/macrophages with C3- and MIF-pathways having the highest probability (significant interactions identified by Wilcoxon rank-sum test). C Computed centrality scores heatmap of complement signaling in human skeletal muscle is specific for FAP-monocyte/macrophage communication. D FAP expression of C3 compared to other mononuclear cell populations in human skeletal muscle. E, F FAP ability for C3 production and secretion was confirmed by C3 immunostaining (n = 4, biological replicates) and ELISA (n = 8, biological replicates, one-way ANOVA and Dunnett’s test to correct for multiple comparisons) of C3 in conditioned media from freshly isolated FAPs (CD34⁺CD31^-CD56^-CD45^-) using MuSCs (CD56⁺CD82⁺CD31^-CD34^-CD45^-) and Endothelial cells (CD31⁺CD45^-) as a control populations (n = 8, biological replicates). Scale bar represents 75 µm. G C3 expression was increased in response to injury in spatial transcriptomic data (n = 3, biological replicates). Mono/macro = monocyte/macrophage.

Fig. 4. Complement factor C3 and monocyte/macrophages in muscle regeneration.

A, B Tissue content of CD11c + -Monocytes/macrophages increased in the early phase of regeneration whereas CD11c- -Monocytes/macrophage content increased later in regeneration (n = 10, biological replicates). * = p < 0.05. ** = p < 0.01. *** = p < 0.001 (one-way ANOVA with Dunnett’s test to correct for multiple comparisons). C Association between fibro-adipogenic progenitor (FAP) size and CD11c + -monocyte/macrophage count indicates that tissue content of pro-inflammatory monocytes partly depends on FAP size (Linear regression with an F-test for difference from zero). D C3 protein decrease migration of monocytes. E Schematic illustration of macrophage phagocytosis experiment using apoptotic fluorescent labeled C2C12 myoblasts and flow cytometry (Created in BioRender. Farup, J. (2025) https://BioRender.com/nx0h3j0). F Macrophage phagocytosis of apoptotic myoblasts showed that presence of C3 protein increases phagocytic activity (n = 12, biological replicates, one-way ANOVA with Dunnett’s test to correct for multiple comparisons). G Macrophage basal glycolysis and proton leak was increased with C3 mediated phagocytosis but C3 alone also increased basal glycolysis indicating a role for metabolic priming with C3 (* = p < 0.05, n = 6, biological replicates, paired, two-sided t-test).