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Clonal expansion of alveolar fibroblast progeny drives pulmonary fibrosis in mouse models
Christopher Molina, Tatsuya Tsukui, Imran S. Khan, Xin Ren, Wenli Qiu, Michael Matthay, Paul Wolters, Dean Sheppard
Christopher Molina, Tatsuya Tsukui, Imran S. Khan, Xin Ren, Wenli Qiu, Michael Matthay, Paul Wolters, Dean Sheppard
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Research Article Cell biology Pulmonology

Clonal expansion of alveolar fibroblast progeny drives pulmonary fibrosis in mouse models

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Abstract

Pulmonary fibrosis (PF) has been called a fibroproliferative disease, yet the functional importance of proliferating fibroblasts to PF has not been systematically examined. In response to alveolar injury, quiescent alveolar fibroblasts differentiate into fibrotic fibroblasts that express high amounts of collagens. However, what role, if any, proliferation plays in the accumulation of fibrotic fibroblasts has remained unclear. Using 5-ethynyl-2′-deoxyuridine (EdU) incorporation, genetic lineage tracing, and single-cell RNA-Seq, we delineated the proliferation dynamics of lung fibroblasts during post-injury fibrogenesis. We found substantial DNA replication in progeny of alveolar fibroblasts in 2 independent models of PF. Lineage labeling revealed clonal expansion of these fibroblast descendants principally in regions of fibrotic remodeling. The transcriptome of proliferating fibroblasts closely resembled that of fibrotic fibroblasts, suggesting that fibroblasts can first differentiate into fibrotic fibroblasts and then proliferate. Genetic ablation of proliferating fibroblasts and selective inhibition of cytokinesis in alveolar fibroblast descendants significantly mitigated PF and rescued lung function. Furthermore, fibroblasts in precision-cut lung slices from human fibrotic lungs exhibited higher proliferation rates than did those in nondiseased lungs. Together, this work establishes fibroblast proliferation as a critical driver of PF and suggests that specifically targeting fibroblast proliferation could be a new therapeutic strategy for fibrotic diseases.

Authors

Christopher Molina, Tatsuya Tsukui, Imran S. Khan, Xin Ren, Wenli Qiu, Michael Matthay, Paul Wolters, Dean Sheppard

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ISSN: 0021-9738 (print), 1558-8238 (online)

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