Integration of single-cell datasets depicts profiles of macrophages and fibro/adipogenic progenitors in dystrophic muscle

Single-cell technologies have recently expanded the possibilities for researchers to gain, at an unprecedented resolution level, knowledge about tissue composition, cell complexity, and heterogeneity. Moreover, the integration of data coming from different technologies and sources also offers, for the first time, the possibility to draw a holistic portrait of how cells behave to sustain tissue physiology during the human lifespan and disease. Here, we interrogated and integrated publicly available single-cell RNAseq data to advance the understanding of how macrophages, fibro/adipogenic progenitors, and other cell types establish gene regulatory networks and communicate with each other in the muscle tissue. We identified altered gene signatures and signaling pathways associated with the dystrophic condition, including an enhanced Spp1-Cd44 signaling in dystrophic macrophages. We shed light on the differences among dystrophic muscle aging, considering wild type, mdx, and more severe conditions as in the case of the mdx-2d model. Contextually, we provided details on existing communication relations between muscle niche cell populations, highlighting increased interactions and distinct signaling events that these cells stablish in the dystrophic microenvironment. We believe our findings can help scientists to formulate and test new hypotheses by moving towards a more complete understanding of muscle regeneration and immune system biology.

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Publication Details

Journal
Experimental Cell Research
Published
2024-08-05
DOI
https://doi.org/10.1016/j.yexcr.2024.114197
Citations
9
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
2.10

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article

Integration of single-cell datasets depicts profiles of macrophages and fibro/adipogenic progenitors in dystrophic muscle

Alessio Reggio, Marta Colletti, Alessandra Vitaliti, Angela Galardi et al.
9 citations
Experimental Cell Research
Extracellular vesicles in disease
2.10
article

Integration of single-cell datasets depicts profiles of macrophages and fibro/adipogenic progenitors in dystrophic muscle

Alessio Reggio, Marta Colletti, Alessandra Vitaliti, Angela Galardi, Alessandro Palma
article en
9 citations

Abstract

Single-cell technologies have recently expanded the possibilities for researchers to gain, at an unprecedented resolution level, knowledge about tissue composition, cell complexity, and heterogeneity. Moreover, the integration of data coming from different technologies and sources also offers, for the first time, the possibility to draw a holistic portrait of how cells behave to sustain tissue physiology during the human lifespan and disease. Here, we interrogated and integrated publicly available single-cell RNAseq data to advance the understanding of how macrophages, fibro/adipogenic progenitors, and other cell types establish gene regulatory networks and communicate with each other in the muscle tissue. We identified altered gene signatures and signaling pathways associated with the dystrophic condition, including an enhanced Spp1-Cd44 signaling in dystrophic macrophages. We shed light on the differences among dystrophic muscle aging, considering wild type, mdx, and more severe conditions as in the case of the mdx-2d model. Contextually, we provided details on existing communication relations between muscle niche cell populations, highlighting increased interactions and distinct signaling events that these cells stablish in the dystrophic microenvironment. We believe our findings can help scientists to formulate and test new hypotheses by moving towards a more complete understanding of muscle regeneration and immune system biology.

Experimental Cell ResearchVol. 442(1)
University of Rome Tor Vergata (IT), Bambino Gesù Children's Hospital (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Sapienza University of Rome (IT)
European Commission, AFM-Téléthon
Openalex Percentile: Top 13%
Extracellular vesicles in disease
2.10
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