Le Saux, C. J. | bioRxiv Science

bioRxiv2023

A fibroblast-derived TGFβ/sFRP2 noncanonical Wnt signaling axis underlies epithelial metaplasia in idiopathic pulmonary fibrosis

Reciprocal interactions between alveolar fibroblasts and epithelial cells are crucial for lung homeostasis, injury repair, and fibrogenesis, but underlying mechanisms remain unclear. To investigate this, we administered the fibroblast-selective TGF{beta}1 signaling inhibitor, epigallocatechin gallate (EGCG), to Interstitial Lung Disease (ILD) patients undergoing diagnostic lung biopsy and conducted single-cell RNA sequencing on spare tissue. Unexposed biopsy samples showed higher fibroblast TGF{beta}1 signaling compared to non-disease donor or end-stage ILD tissues. In vivo, EGCG significantly downregulated TGF{beta}1 signaling and several pro-inflammatory and stress pathways in biopsy samples. Notably, EGCG reduced fibroblast secreted Frizzle-like Receptor Protein 2 (sFRP2), an unrecognized TGF{beta}1 fibroblast target gene induced near type II alveolar epithelial cells (AEC2s). In human AEC2-fibroblast coculture organoids, sFRP2 was essential for AEC2 trans-differentiation to basal cells. Precision cut lung slices (PCLS) from normal donors demonstrated that TGF{beta}1 promoted KRT17 expression and AEC2 morphological change, while sFRP2 was necessary for KRT5 expression in AEC2-derived basaloid cells. Wnt-receptor Frizzled 5 (Fzd5) expression and downstream calcineurin-related signaling in AEC2s were required for sFRP2-induced KRT5 expression. These findings highlight stage-specific TGF{beta}1 signaling in ILD, the therapeutic potential of EGCG in reducing IPF-related transcriptional changes, and identify the TGF{beta}1-non-canonical Wnt pathway crosstalk via sFRP2 as a novel mechanism for dysfunctional epithelial signaling in Idiopathic Pulmonary Fibrosis/ILD.

cell biology↗

bioRxiv2022

Transfer learning of an in vivo-derived senescence signature identifies conserved and tissue-specific senescence across species and diverse pathologies

Senescent cells (SnCs) contribute to normal tissue development and repair but accumulate with aging where they are implicated in a number of pathologies and diseases. Despite their pathological role and therapeutic interest, SnC phenotype and function in vivo remains unclear due to the challenges in identifying and isolating these rare cells. Here, we developed an in vivo-derived senescence gene expression signature using a model of the foreign body response (FBR) fibrosis in a p16Ink4a-reporter mouse, a cell cycle inhibitor commonly used to identify SnCs. We identified stromal cells (CD45-CD31- CD29+) as the primary p16Ink4a expressing cell type in the FBR and collected the cells to produce a SnC transcriptomic signature with bulk RNA sequencing. To computationally identify SnCs in bulk and single-cell data sets across species and tissues, we used this signature with transfer learning to generate a SnC signature score (SenSig). We found senescent pericyte and cartilage-like fibroblasts in newly collected single cell RNAseq (scRNASeq) data sets of murine and human FBR suggesting populations associated with angiogenesis and secretion of fibrotic extracellular matrix, respectively. Application of the senescence signature to human scRNAseq data sets from idiopathic pulmonary fibrosis (IPF) and the basal cell carcinoma microenvironment identified both conserved and tissue-specific SnC phenotypes, including epithelial-derived basaloid and endothelial cells. In a wound healing model, ligand-receptor signaling prediction identified putative interactions between SnC SASP and myeloid cells that were validated by immunofluorescent staining and in vitro coculture of SnCs and macrophages. Collectively, we have found that our SenSig transfer learning strategy from an in vivo signature outperforms in vitro-derived signatures and identifies conserved and tissue-specific SnCs and their SASP, independent of p16Ink4a expression, and may be broadly applied to elucidate SnC identity and function in vivo.

bioengineering↗