Abstract
The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive. Using time-series single cell RNA-seq of the bleomycin lung injury model, we resolved transcriptional dynamics for 28 cell types. Trajectory modeling together with lineage tracing revealed that airway and alveolar stem cells converge on a unique Krt8 + transitional stem cell state during alveolar regeneration. These cells have squamous morphology, feature p53 and NFkB activation and display transcriptional features of cellular senescence. The Krt8+ state appears in several independent models of lung injury and persists in human lung fibrosis, creating a distinct cell–cell communication network with mesenchyme and macrophages during repair. We generated a model of gene regulatory programs leading to Krt8+ transitional cells and their terminal differentiation to alveolar type-1 cells. We propose that in lung fibrosis, perturbed molecular checkpoints on the way to terminal differentiation can cause aberrant persistence of regenerative intermediate stem cell states.
Highlights
The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive
Single cell transcriptional profiles were visualized in two dimensions using the Uniform Manifold Approximation and Projection (UMAP) method[21] (Fig. 1a)
Using quantitative comparisons of the gene expression signatures measured in this study we found that this alveolar type-2 pneumocytes (AT2) derived cell state is very similar if not identical to the Krt8+ alveolar differentiation intermediate (ADI) cells discovered by us (Fig. 9d), suggesting that persistence of Krt8+ ADI may directly mediate progressive lung fibrosis
Summary
The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive. Trajectory modeling together with lineage tracing revealed that airway and alveolar stem cells converge on a unique Krt8 + transitional stem cell state during alveolar regeneration. These cells have squamous morphology, feature p53 and NFkB activation and display transcriptional features of cellular senescence. Using single-cell RNA sequencing (scRNAseq) methods it is possible to predict the future state of individual cells based on RNA velocity[14] and model cell fate trajectories in pseudotime[15,16] These methods are highly complementary with traditional lineage tracing and longitudinal single-cell analysis of a dynamic system[17], combined with computational methods is unbiased and allows for discovery in high-throughput. We ask if we can leverage these ideas for the problem of gene regulation during epithelial regeneration
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