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Pulmonary fibrosis (PF) is a form of chronic lung disease characterized by pathologic epithelial remodeling and accumulation of extracellular matrix (ECM). To comprehensively define the cell types, mechanisms, and mediators driving fibrotic remodeling in lungs with PF, we performed single-cell RNA sequencing of single-cell suspensions from 10 nonfibrotic control and 20 PF lungs. Analysis of 114,396 cells identified 31 distinct cell subsets/states. We report that a remarkable shift in epithelial cell phenotypes occurs in the peripheral lung in PF and identify several previously unrecognized epithelial cell phenotypes, including a KRT5−/KRT17+ pathologic, ECM-producing epithelial cell population that was highly enriched in PF lungs. Multiple fibroblast subtypes were observed to contribute to ECM expansion in a spatially discrete manner. Together, these data provide high-resolution insights into the complexity and plasticity of the distal lung epithelium in human disease and indicate a diversity of epithelial and mesenchymal cells contribute to pathologic lung fibrosis.

Organ- and body-scale cell atlases have the potential to transform our understanding of human biology. To capture the variability present in the population, these atlases must include diverse demographics such as age and ethnicity from both healthy and diseased individuals. The growth in both size and number of single-cell datasets, combined with recent advances in computational techniques, for the first time makes it possible to generate such comprehensive large-scale atlases through integration of multiple datasets. Here, we present the integrated Human Lung Cell Atlas (HLCA) combining 46 datasets of the human respiratory system into a single atlas spanning over 2.2 million cells from 444 individuals across health and disease. The HLCA contains a consensus re-annotation of published and newly generated datasets, resolving under- or misannotation of 59% of cells in the original datasets. The HLCA enables recovery of rare cell types, provides consensus marker genes for each cell type, and uncovers gene modules associated with demographic covariates and anatomical location within the respiratory system. To facilitate the use of the HLCA as a reference for single-cell lung research and allow rapid analysis of new data, we provide an interactive web portal to project datasets onto the HLCA. Finally, we demonstrate the value of the HLCA reference for interpreting disease-associated changes. Thus, the HLCA outlines a roadmap for the development and use of organ-scale cell atlases within the Human Cell Atlas.

Lung organogenesis requires precise timing and coordination to effect spatial organization and function of the parenchymal cells. To provide a systematic broad-based view of the mechanisms governing the dynamic alterations in parenchymal cells over crucial periods of development, we performed a single-cell RNA-sequencing time-series yielding 102,571 epithelial, endothelial and mesenchymal cells across nine time points from embryonic day 12 to postnatal day 14 in mice. Combining computational fate-likelihood prediction with RNA in situ hybridization and immunofluorescence, we explore lineage relationships during the saccular to alveolar stage transition. The utility of this publicly searchable atlas resource (www.sucrelab.org/lungcells) is exemplified by discoveries of the complexity of type 1 pneumocyte function and characterization of mesenchymal Wnt expression patterns during the saccular and alveolar stages – wherein major expansion of the gas-exchange surface occurs. We provide an integrated view of cellular dynamics in epithelial, endothelial and mesenchymal cell populations during lung organogenesis.

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