Generation of human alveolar epithelial type I cells from pluripotent stem cells.

Alveolar epithelial type I cells (AT1s) line the gas exchange barrier of the distal lung and have been historically challenging to isolate or maintain in cell culture. Here, we engineer a human in vitro AT1 model system via directed differentiation of induced pluripotent stem cells (iPSCs). We use primary adult AT1 global transcriptomes to suggest benchmarks and pathways, such as Hippo-LATS-YAP/TAZ signaling, enriched in these cells. Next, we generate iPSC-derived alveolar epithelial type II cells (AT2s) and find that nuclear YAP signaling is sufficient to promote a broad transcriptomic shift from AT2 to AT1 gene programs. The resulting cells express a molecular, morphologic, and functional phenotype reminiscent of human AT1 cells, including the capacity to form a flat epithelial barrier producing characteristic extracellular matrix molecules and secreted ligands. Our results provide an in vitro model of human alveolar epithelial differentiation and a potential source of human AT1s.

scTOP: physics-inspired order parameters for cellular identification and visualization.

Advances in single-cell RNA sequencing provide an unprecedented window into cellular identity. The abundance of data requires new theoretical and computational frameworks to analyze the dynamics of differentiation and integrate knowledge from cell atlases. We present 'single-cell Type Order Parameters' (scTOP): a statistical, physics-inspired approach for quantifying cell identity given a reference basis of cell types. scTOP can accurately classify cells, visualize developmental trajectories and assess the fidelity of engineered cells. Importantly, scTOP does this without feature selection, statistical fitting or dimensional reduction (e.g. uniform manifold approximation and projection, principle components analysis, etc.). We illustrate the power of scTOP using human and mouse datasets. By reanalyzing mouse lung data, we characterize a transient hybrid alveolar type 1/alveolar type 2 cell population. Visualizations of lineage tracing hematopoiesis data using scTOP confirm that a single clone can give rise to multiple mature cell types. We assess the transcriptional similarity between endogenous and donor-derived cells in the context of murine pulmonary cell transplantation. Our results suggest that physics-inspired order parameters can be an important tool for understanding differentiation and characterizing engineered cells. scTOP is available as an easy-to-use Python package.

Durable alveolar engraftment of PSC-derived lung epithelial cells into immunocompetent mice.

Durable reconstitution of the distal lung epithelium with pluripotent stem cell (PSC) derivatives, if realized, would represent a promising therapy for diseases that result from alveolar damage. Here, we differentiate murine PSCs into self-renewing lung epithelial progenitors able to engraft into the injured distal lung epithelium of immunocompetent, syngeneic mouse recipients. After transplantation, these progenitors mature in the distal lung, assuming the molecular phenotypes of alveolar type 2 (AT2) and type 1 (AT1) cells. After months in vivo, donor-derived cells retain their mature phenotypes, as characterized by single-cell RNA sequencing (scRNA-seq), histologic profiling, and functional assessment that demonstrates continued capacity of the engrafted cells to proliferate and differentiate. These results indicate durable reconstitution of the distal lung's facultative progenitor and differentiated epithelial cell compartments with PSC-derived cells, thus establishing a novel model for pulmonary cell therapy that can be utilized to better understand the mechanisms and utility of engraftment.

Multipotent Embryonic Lung Progenitors: Foundational Units of In Vitro and In Vivo Lung Organogenesis.

Transient, tissue-specific, embryonic progenitors are important cell populations in vertebrate development. In the course of respiratory system development, multipotent mesenchymal and epithelial progenitors drive the diversification of fates that results to the plethora of cell types that compose the airways and alveolar space of the adult lungs. Use of mouse genetic models, including lineage tracing and loss-of-function studies, has elucidated signaling pathways that guide proliferation and differentiation of embryonic lung progenitors as well as transcription factors that underlie lung progenitor identity. Furthermore, pluripotent stem cell-derived and ex vivo expanded respiratory progenitors offer novel, tractable, high-fidelity systems that allow for mechanistic studies of cell fate decisions and developmental processes. As our understanding of embryonic progenitor biology deepens, we move closer to the goal of in vitro lung organogenesis and resulting applications in developmental biology and medicine.

scTOP: physics-inspired order parameters for cellular identification and visualization.

Advances in single-cell RNA-sequencing (scRNA-seq) provide an unprecedented window into cellular identity. The increasing abundance of data requires new theoretical and computational frameworks for understanding cell fate determination, accurately classifying cell fates from expression data, and integrating knowledge from cell atlases. Here, we present single-cell Type Order Parameters (scTOP): a statistical-physics-inspired approach for constructing "order parameters" for cell fate given a reference basis of cell types. scTOP can quickly and accurately classify cells at a single-cell resolution, generate interpretable visualizations of developmental trajectories, and assess the fidelity of engineered cells. Importantly, scTOP does this without using feature selection, statistical fitting, or dimensional reduction (e.g., UMAP, PCA, etc.). We illustrate the power of scTOP utilizing a wide variety of human and mouse datasets (both in vivo and in vitro ). By reanalyzing mouse lung alveolar development data, we characterize a transient perinatal hybrid alveolar type 1/alveolar type 2 (AT1/AT2) cell population that disappears by 15 days post-birth and show that it is transcriptionally distinct from previously identified adult AT2-to-AT1 transitional cell types. Visualizations of lineage tracing data on hematopoiesis using scTOP confirm that a single clone can give rise to as many as three distinct differentiated cell types. We also show how scTOP can quantitatively assess the transcriptional similarity between endogenous and transplanted cells in the context of murine pulmonary cell transplantation. Finally, we provide an easy-to-use Python implementation of scTOP. Our results suggest that physics-inspired order parameters can be an important tool for understanding development and characterizing engineered cells.