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Publication

Myoepithelial Cells of Submucosal Glands Can Function as Reserve Stem Cells to Regenerate Airways after Injury.

Cell stem cell | 2018

Cells demonstrate plasticity following injury, but the extent of this phenomenon and the cellular mechanisms involved remain underexplored. Using single-cell RNA sequencing (scRNA-seq) and lineage tracing, we uncover that myoepithelial cells (MECs) of the submucosal glands (SMGs) proliferate and migrate to repopulate the airway surface epithelium (SE) in multiple injury models. Specifically, SMG-derived cells display multipotency and contribute to basal and luminal cell types of the SMGs and SE. Ex vivo expanded MECs have the potential to repopulate and differentiate into SE cells when grafted onto denuded airway scaffolds. Significantly, we find that SMG-like cells appear on the SE of both extra- and intra-lobular airways of large animal lungs following severe injury. We find that the transcription factor SOX9 is necessary for MEC plasticity in airway regeneration. Because SMGs are abundant and present deep within airways, they may serve as a reserve cell source for enhancing human airway regeneration.

Pubmed ID: 29656943 RIS Download

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Associated grants

Agency: NHLBI NIH HHS, United States
Id: R00 HL127181
Agency: NICHD NIH HHS, United States
Id: T32 HD040372
Agency: NIEHS NIH HHS, United States
Id: U01 ES017219

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Enrichr (tool)

RRID:SCR_001575

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

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