bioRxivDevelopmental BiologyPreprint
Hippo-deficient cardiac fibroblasts differentiate into osteochondroprogenitors
Chang-Ru TsaiiD, Jong Kyoung KimiD, Xiao LiiD, Paulo CzarnewskiiD, Gang LiiD, Fansen MengiD, Mingjie ZhengiD, Xiaolei ZhaoiD, Jeffrey D. SteimleiD, Francisco Grisanti, Jun Wang, Md. Abul Hassan SameeiD, James F. MartiniD
- Citations
- 12
Abstract
Cardiac fibrosis, a common pathophysiology associated with various heart diseases, occurs from the excess deposition of extracellular matrix (ECM)1. Cardiac fibroblasts (CFs) are the primary cells that produce, degrade, and remodel ECM during homeostasis and tissue repair2. Upon injury, CFs gain plasticity to differentiate into myofibroblasts3 and adipocyte-like4,5 and osteoblast-like6 cells, promoting fibrosis and impairing heart function7. How CFs maintain their cell state during homeostasis and adapt plasticity upon injury are not well defined. Recent studies have shown that Hippo signalling in CFs regulates cardiac fibrosis and inflammation8-11. Here, we used single-nucleus RNA sequencing (snRNA-seq) and spatially resolved transcriptomic profiling (ST) to investigate how the cell state was altered in the absence of Hippo signaling and how Hippo-deficient CFs interact with macrophages during cardiac fibrosis. We found that Hippo-deficient CFs differentiate into osteochondroprogenitors (OCPs), suggesting that Hippo restricts CF plasticity. Furthermore, Hippo-deficient CFs colocalized with macrophages, suggesting their intercellular communications. Indeed, we identified several ligand-receptor pairs between the Hippo-deficient CFs and macrophages. Blocking the Hippo-deficient CF-induced CSF1 signaling abolished macrophage expansion. Interestingly, blocking macrophage expansion also reduced OCP differentiation of Hippo-deficient CFs, indicating that macrophages promote CF plasticity.
- organism: mouse
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: differential expression
- approach: statistical model
- approach: experimental assay
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