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Cell Rep. 2018 Mar 27;22(13):3625-3640. doi: 10.1016/j.celrep.2018.03.010.

Single-Cell Deconvolution of Fibroblast Heterogeneity in Mouse Pulmonary Fibrosis.

Author information

1
Department of Medicine, Division of Pulmonary and Critical Care Medicine, Women's Guild Lung Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. Electronic address: ting.xie@cshs.org.
2
Genomics Core, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
3
Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
4
Department of Medicine, Division of Pulmonary and Critical Care Medicine, Women's Guild Lung Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
5
Department of Medicine, Division of Pulmonary and Critical Care Medicine, Women's Guild Lung Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. Electronic address: paul.noble@cshs.org.
6
Department of Medicine, Division of Pulmonary and Critical Care Medicine, Women's Guild Lung Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. Electronic address: dianhua.jiang@cshs.org.

Abstract

Fibroblast heterogeneity has long been recognized in mouse and human lungs, homeostasis, and disease states. However, there is no common consensus on fibroblast subtypes, lineages, biological properties, signaling, and plasticity, which severely hampers our understanding of the mechanisms of fibrosis. To comprehensively classify fibroblast populations in the lung using an unbiased approach, single-cell RNA sequencing was performed with mesenchymal preparations from either uninjured or bleomycin-treated mouse lungs. Single-cell transcriptome analyses classified and defined six mesenchymal cell types in normal lung and seven in fibrotic lung. Furthermore, delineation of their differentiation trajectory was achieved by a machine learning method. This collection of single-cell transcriptomes and the distinct classification of fibroblast subsets provide a new resource for understanding the fibroblast landscape and the roles of fibroblasts in fibrotic diseases.

KEYWORDS:

fibroblast; fibrosis; lung mesenchymal cells; single-cell RNA-seq

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