bioRxivSystems BiologyPreprint
Spatio-temporal dynamics of the fibrotic niche in cardiac repair
Andy ChaniD, Joachim GreineriD, Tomás A. Brennan, Ankit AgrawaliD, Helene HemmeriD, Katrin SinningiD, Lisa Marschhäuser, Wing Lam Cheung, Zafar IqbaliD, Alexander KleseniD, Thomas SeideliD, Martin VaethiD, Eva A. Rog‐ZielinskaiD, Peter Karl KohliD, Franziska Schneider‐WarmeiD, Dominic GrüniD
Abstract
The heart is one of the least regenerative organs in humans, and ischemic heart disease is the leading cause of death worldwide. Understanding the cellular and molecular processes that occur during cardiac wound healing is an essential prerequisite to reducing health burden and improve cardiac function after myocardial tissue damage. By integrating single-cell RNA-sequencing with imaging-based spatial transcriptomics, we reconstructed the spatio-temporal dynamics of the fibrotic niche after ventricular injury in adult mice. Our analysis reveals dynamic regulation of local cell communication niches over time. We identified interactions that regulate cardiac repair, including fibroblast proliferation silencing by Trem2high macrophages that prevents excessive fibrosis. Moreover, we discovered a rare population of dedifferentiating cardiomyocytes during early post-lesion stages, which was sustained by signals from myeloid and lymphoid cells. Culturing non-regenerative mouse cardiomyocytes or human heart tissue with these niche factors reactivated progenitor gene expression and cell cycle activity. In summary, this spatio-temporal cell type atlas provides valuable insights into the heterocellular interactions that control cardiac repair. HighlightsO_LIscRNA-seq and in situ sequencing reveal spatio-temporal dynamics of heart repair C_LIO_LILocal heterocellular communication niches coordinate overall wound response C_LIO_LIFibroblast cell cycle silencing by Trem2high macrophages suppresses excessive fibrosis C_LIO_LICardiomyocyte plasticity is promoted by myeloid and lymphoid cells C_LI
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 7
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