Single-Cell Transcriptomic Analysis of Human Lung Reveals Complex Multicellular Changes During Pulmonary Fibrosis
Paul A. Reyfman,
James M. Walter,
Kishore R. Anekalla,
Alexandra C. McQuattie-Pimentel,
Francisco J. Gonzalez-Gonzalez,
Kinola J.N. Williams,
Annette S. Flozak,
Trevor T. Nicholson,
Vince K. Morgan,
Cara L. Hrusch,
Robert D. Guzy,
Catherine A. Bonham,
Anne I. Sperling,
Robert B. Hamanaka,
Gökhan M. Mutlu,
Anjana V. Yeldandi,
Stacy A. Marshall,
Luis A.N. Amaral,
Jacob I. Sznajder,
Deborah R. Winter,
A. Christine Argento,
Colin T. Gillespie,
Jane D’Amico Dematte,
Benjamin D. Singer,
Karen M. Ridge,
Cara J. Gottardi,
Anna P. Lam,
Sangeeta M. Bhorade,
GR Scott Budinger,
Alexander V. Misharin
Posted 06 Apr 2018
bioRxiv DOI: 10.1101/296608 (published DOI: 10.1164/rccm.201712-2410OC)
Posted 06 Apr 2018
Pulmonary fibrosis is a devastating disorder that results in the progressive replacement of normal lung tissue with fibrotic scar. Available therapies slow disease progression, but most patients go on to die or require lung transplantation. Single-cell RNA-seq is a powerful tool that can reveal cellular identity via analysis of the transcriptome, but its ability to provide biologically or clinically meaningful insights in a disease context is largely unexplored. Accordingly, we performed single-cell RNA-seq on lung tissue obtained from eight transplant donors and eight recipients with pulmonary fibrosis and one bronchoscopic cryobiospy sample. Integrated single-cell transcriptomic analysis of donors and patients with pulmonary fibrosis identified the emergence of distinct populations of epithelial cells and macrophages that were common to all patients with lung fibrosis. Analysis of transcripts in the Wnt pathway suggested that within the same cell type, Wnt secretion and response are restricted to distinct non-overlapping cells, which was confirmed using in situ RNA hybridization. Single-cell RNA-seq revealed heterogeneity within alveolar macrophages from individual patients, which was confirmed by immunohistochemistry. These results support the feasibility of discovery-based approaches applying next generation sequencing technologies to clinically obtained samples with a goal of developing personalized therapies.
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