Dataset Information

Development of novel in vitro human alveolar epithelial cell models to study distal lung biology and disease [scRNA-seq]

ABSTRACT: To address the need for human alveolar epithelial cell (AEC)-derived lines to more suitably model distal lung diseases, we have generated and characterized novel immortalized cell lines derived from human AECs. We used a combination of the ROCK inhibitor, Y-27632, and lentiviral transduction of SV40 Large T antigen of previously cryopreserved isolated human alveolar epithelial type 2 (AT2) cells to generate immortalized AECs. These AEC lines proliferate well on standard tissue culture dishes forming an epithelial monolayer and express lung progenitor markers SOX9 and SOX2. When grown in 3D culture with lung fibroblasts, the cells form NKX2-1+ organoids expressing more mature alveolar lung markers, AQP5 and GPRC5A. Single cell RNA-sequencing of one AEC line comparing cells in 2D versus 3D revealed increased cellular heterogeneity and an induction of cytokine and lipoprotein signaling in 3D culture, reflecting interactions with the microenvironment during organoid formation. Taken together, these data show our novel progenitor-like AEC lines retain a genetic and structural memory of their alveolar cell lineage despite long-term expansion, providing a valuable new system to model the distal lung in vitro.

ORGANISM(S): Homo sapiens

PROVIDER: GSE164514 | GEO | 2022/01/10

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Disruption of alveolar epithelial cell (AEC) differentiation is implicated in implicated in distal lung diseases such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung adenocarcinoma that impact morbidity and mortality worldwide. Elucidating underlying disease pathogenesis requires a mechanistic molecular understanding of AEC differentiation. Previous studies have focused on changes of individual transcription factors, and to date no study has comprehensively characterized the dynamic, global epigenomic alterations that facilitate this critical differentiation process in humans. We comprehensively profiled the epigenomic states of human AECs during type 2 to type 1-like cell differentiation, including the methylome and chromatin functional domains, and integrated this with transcriptome-wide RNA expression data. Enhancer regions were drastically altered during AEC differentiation. Transcription factor binding analysis within enhancer regions revealed diverse interactive networks with enrichment for many transcription factors, including NKX2-1 and FOXA family members, as well as transcription factors with less well characterized roles in AEC differentiation, such as members of the MEF2, TEAD, and AP1 families. Additionally, associations among transcription factors changed during differentiation, implicating a complex network of heterotrimeric complex switching in driving differentiation. Integration of AEC enhancer states with the catalog of enhancer elements in the Roadmap Epigenomics Mapping Consortium and Encyclopedia of DNA Elements (ENCODE) revealed that AECs have similar epigenomic structures to other profiled epithelial cell types, including human mammary epithelial cells (HMECs), with NKX2-1 serving as a distinguishing feature of distal lung differentiation. Enhancer regions are hotspots of epigenomic alteration that regulate AEC differentiation. Furthermore, the differentiation process is regulated by dynamic networks of transcription factors acting in concert, rather than individually. These findings provide a roadmap for understanding the relationship between disruption of the epigenetic state during AEC differentiation and development of lung diseases that may be therapeutically amenable.

Dataset Information

Development of novel in vitro human alveolar epithelial cell models to study distal lung biology and disease [scRNA-seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets