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Spatiotemporal mapping of immune and stem cell dysregulation after volumetric muscle loss
Jacqueline A. Larouche, … , Eric Buras, Carlos A. Aguilar
Jacqueline A. Larouche, … , Eric Buras, Carlos A. Aguilar
Published February 23, 2023
Citation Information: JCI Insight. 2023;8(7):e162835. https://doi.org/10.1172/jci.insight.162835.
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Resource and Technical Advance Muscle biology Stem cells

Spatiotemporal mapping of immune and stem cell dysregulation after volumetric muscle loss

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Abstract

Volumetric muscle loss (VML) is an acute trauma that results in persistent inflammation, supplantation of muscle tissue with fibrotic scarring, and decreased muscle function. The cell types, nature of cellular communication, and tissue locations that drive the aberrant VML response have remained elusive. Herein, we used spatial transcriptomics on a mouse model of VML and observed that VML engenders a unique spatial profibrotic pattern driven by crosstalk between fibrotic and inflammatory macrophages and mesenchymal-derived cells. The dysregulated response impinged on muscle stem cell–mediated repair, and targeting this circuit resulted in increased regeneration and reductions in inflammation and fibrosis. Collectively, these results enhance our understanding of the cellular crosstalk that drives aberrant regeneration and provides further insight into possible avenues for fibrotic therapy exploration.

Authors

Jacqueline A. Larouche, Emily C. Wallace, Bonnie D. Spence, Eric Buras, Carlos A. Aguilar

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Figure 1

Spatial transcriptomic profiling 7 days after VML reveals profibrotic spatial patterning in the injured site.

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Spatial transcriptomic profiling 7 days after VML reveals profibrotic sp...
(A) Experiment schematic whereby spatial transcriptomics was performed on VML-injured tibialis anterior muscles at 7 days after injury. (B) Representative image showing tissue annotation into 3 zones — a defect zone, a zone of intact muscle, and a transition zone between them. (C) Representative distribution of unique molecular identifiers shows higher read counts at the location of the defect. (D) GO Term analysis showing upregulated terms within each zone compared with the other 2 zones. Differentially expressed genes were calculated using Wilcoxon Rank Sum Test with post hoc analysis. Log2 fold change > 0.25 and adjusted P < 0.05 was considered significant. (E) Integration of spatial transcriptomics data sets with matched, cell type–annotated scRNA-Seq data sets using Seurat label transfer. (Left) Representative spatial overlays. (Right) Quantification. **P < 0.01, *P < 0.05, by 1-way ANOVA with Tukey’s post hoc analysis. n = 4 muscles from 2 male and 2 female mice. Color bars indicate prediction scores. (F) Immunohistological stains confirm the spGEX-predictions of cell localization within the different zones. (Left) Representative images. Scale bars: 500 μm. (Right) Quantifications. **P < 0.01, *P < 0.05, by 1-way ANOVA with Tukey’s post hoc analysis. n = 3–4 muscles from 2 male and 2 female mice. ***P < 0.001, ****P < 0.0001. Magnification, 20×.

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