bioRxivMolecular BiologyPreprint
MFAP5 Drives Elastic Fiber Disorganization to Promote Pulmonary Fibrosis
Zhen CheniD, Fanhao Kong, Lixin Huang, Wenze Wu, Ziping WangiD, Hanbin CheniD, Junting ZhangiD, Zixin LiuiD, Jin-Song Bian, Xiaowei NieiD
Abstract
BACKGROUNDElastic fibers (EF) disorganization contributes to increased tissue stiffness and impaired lung function in pulmonary fibrosis (PF). However, the complex structural features of EF are difficult to capture using conventional histology. Moreover, the molecular mechanisms governing EF homeostasis during fibrosis remain poorly understood. METHODSA high-dimensional Elastic Fiber Algorithm (EFA) was developed to digitally quantify EF structural features in PF. Gene variation-rate analysis was performed to identify candidate regulators of EF homeostasis. Fibroblast-specific and pathological fibroblast-specific MFAP5 knockout mice were generated to assess the role of MFAP5 in PF rodent models. Bulk RNA sequencing was employed to investigate MFAP5-mediated fibroblast activation and signaling pathways. RESULTSEFA revealed profound EF disorganization in fibrotic lungs, capturing various architectural alterations. Gene variation-rate analysis identified MFAP5 as a candidate regulator of EF homeostasis, with upregulated expression in PF patients and mouse models. Fibroblast-specific deletion of MFAP5 significantly attenuated fibrosis, restored EF architecture, reduced collagen deposition, and improved pulmonary function in PF mouse models. MFAP5-positive fibroblasts displayed a dynamic shift toward pathological states during PF progression. Mechanistically, MFAP5 promoted fibroblast activation and ECM production via v{beta}3 integrin-mediated TGF{beta} signaling. CONCLUSIONSMFAP5 is a key orchestrator of EF remodeling and fibroblast activation in PF. Targeting MFAP5 restores EF homeostasis, reduces fibrotic severity, and represents a potential therapeutic strategy for PF.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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