Spatiotemporal transcriptomic mapping of regenerative inflammation in skeletal muscle reveals a dynamic multilayered tissue architecture
Andreas Patsalos, … , H. Lee Sweeney, Laszlo Nagy
Andreas Patsalos, … , H. Lee Sweeney, Laszlo Nagy
Published August 27, 2024
Citation Information: J Clin Invest. 2024;134(20):e173858. https://doi.org/10.1172/JCI173858.
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Spatiotemporal transcriptomic mapping of regenerative inflammation in skeletal muscle reveals a dynamic multilayered tissue architecture

Abstract

Tissue regeneration is orchestrated by macrophages that clear damaged cells and promote regenerative inflammation. How macrophages spatially adapt and diversify their functions to support the architectural requirements of actively regenerating tissue remains unknown. In this study, we reconstructed the dynamic trajectories of myeloid cells isolated from acutely injured and early stage dystrophic muscles. We identified divergent subsets of monocytes/macrophages and DCs and validated markers (e.g., glycoprotein NMB [GPNMB]) and transcriptional regulators associated with defined functional states. In dystrophic muscle, specialized repair-associated subsets exhibited distinct macrophage diversity and reduced DC heterogeneity. Integrating spatial transcriptomics analyses with immunofluorescence uncovered the ordered distribution of subpopulations and multilayered regenerative inflammation zones (RIZs) where distinct macrophage subsets are organized in functional zones around damaged myofibers supporting all phases of regeneration. Importantly, intermittent glucocorticoid treatment disrupted the RIZs. Our findings suggest that macrophage subtypes mediated the development of the highly ordered architecture of regenerative tissues, unveiling the principles of the structured yet dynamic nature of regenerative inflammation supporting effective tissue repair.

Authors

Andreas Patsalos, Laszlo Halasz, Darby Oleksak, Xiaoyan Wei, Gergely Nagy, Petros Tzerpos, Thomas Conrad, David W. Hammers, H. Lee Sweeney, Laszlo Nagy

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Figure 1

Spatial and single-cell transcriptomics integration and enhanced-resolution clustering resolve the cellular distribution of myeloid subtypes during regenerative inflammation.

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Spatial and single-cell transcriptomics integration and enhanced-resolut...
(A) H&E of TAs at 4 days after CTX injury used for ST. Insets indicate histopathological annotations (red-C1: regenerative muscle; blue-C2: necrotic/inflammatory lesions; green-C3: healthy muscle). C2 shows segmental necrosis of pale fibers with loss of cytoplasmic structures, active phagocytosis, C or delta lesions, and membrane damage (95), compared with C1, which includes inflammatory cells and regenerating myocytes. Scale bars: 50 μm. (B) Spatial clustering (Leiden algorithm; cluster resolution 0.3) identifies 3 discrete regions overlapping with histopathology annotations of A. The number of spots (n = 767) is indicated. (C) Enhanced subspot resolution clustering (BayesSpace) identified 7 spatial domains, not resolved at spot-level clustering. (D) Spatial expression patterns at subspot resolution of genes defining the myeloid subsets characterized by scRNA-Seq (7). Color scale shows log-normalized counts for each subspot. Gene label color corresponds to the classification in left panel of H. (E) Heatmap of the spatial expression of top predicted and curated markers, highlighting the specificity of the spatial BayesSpace clusters. Gpnmb is highlighted. (F) Identification of tissue compartments using NMF-based decomposition and day 4 after CTX reference immune subtype signatures (7). Spatial plots show cell abundance. (G) Dot plot of the estimated NMF weights of subtypes across 7 predicted NMF components. Note the differential abundance of MacII and MacIII subtypes and the overlap of DC subsets with MacIV. MacI, resolution-related MFs; MacII, GFEMs; MacIII, infiltrating monocytes/proinflammatory MFs; MacIV, antigen-presenting MFs (7). (H) Distribution and estimated cell abundance of MF and DC subtypes associated with specific NMF cellular compartments. Insets: histological area on NMF3, predicting MacIII and the formation of LGCs (encircled). The local spatial expression of known markers of LGCs (Ccl2, Ccl7) (58, 86) overlaps with the histological features and other MacIII markers (Ly6c2; D, Plac8; Supplemental Figure 1E). Scale bars: 500 μm. (I) IF detection of LGCs (MacIII) and GFEMs (MacII) by GPNMB, Ly6C, and F4/80 (green) in C57BL/6J animals at day 4 after CTX injury. Split channels are shown. White boxes indicate 2 LGC-like structures. Scale bars: 100 μm. (J) Upper: IF of GPNMB+ MFs and eMyHC+ fibers at day 4 after CTX injury. Lower: high-resolution volume projection confocal image of GPNMB+ MFs and eMyHC+ regenerating fibers preferential spatial proximity (3D reconstruction distances are indicated). Scale bar: 100 μm.