Deconstructing pulmonary fibrosis at single‐cell resolution

Rationale Despite years of research, the fundamental mechanisms driving the pathogenesis of pulmonary fibrosis remain unclear. Numerous histopathologic patterns of pulmonary fibrosis have been identified in association with different patterns of risk factors, but to date it remains unclear as to what mechanisms are shared across different forms of pulmonary fibrosis and which drive distinct pathologies and outcomes. We hypothesize that using single‐cell transcriptomic approaches, we can decipher both the conserved and distinct mechanisms driving pulmonary fibrosis phenotypes. Methods At the time of lung transplantation, single‐cell suspensions were generated from the lung parenchyma of pulmonary fibrosis patients and from declined donor lungs (controls). Unsorted single‐cell suspensions and CD45 depleted fractions were used for scRNA‐seq. Single‐cell RNA‐sequencing library preparation was performed using the 10X Genomics 3′ or 5′ kit, and sequencing was performed on an Illumina hiSeq4000 or Novaseq. Following alignment, demultiplexing was performed using Cell Ranger. Graph‐based clustering and scRNA‐seq analysis was performed using the Seurat package in R. Developmental lineage reconstruction was performing using Monocle and p‐Creode. Diagnoses were assigned based on clinical interpretation of explant pathology. Results Joint graph‐based clustering and canonical correlation analysis of scRNA‐seq profiles from >30,000 cells from control (n=7), IPF (n=7), chronic hypersensitivity pneumonitis (cHP, n=4), and nonspecific interstitial pneumonia (NSIP, n=3) identified 21 distinct clusters, representing the major known subtypes in the lung, as well as numerous intermediate/transitional cell types and/or states. Strikingly, across pulmonary fibrosis phenotypes, collagen and ECM gene expression was highly enriched in ACTA2 low , PDGFRa + fibroblasts, while collagen and ECM gene expression were lower in ACTA2 hi myofibroblasts; few collagen‐expressing inflammatory or epithelial cells were identified. A series of cell types co‐expressing AT1 and AT2 markers were identified in both fibrotic and control lungs. Compared to NSIP and cHP, IPF epithelial cells demonstrated increased senescence markers. Conclusions Across different histopathologic forms of pulmonary fibrosis, both shared and divergent pathologic gene expression programs can be identified. Further study is needed to more comprehensively define the common gene expression programs that drive progressive pulmonary fibrosis. Support or Funding Information This work was supported by NIH/NHLBI, the Doris Duke Charitable Foundation, and Boehringer Ingleheim. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .