A Single-Cell Atlas of the Upper Respiratory Epithelium Reveals Heterogeneity in Cell Types and Patterning Strategies
Sun, X.; Foote, A.
Show abstract
The upper respiratory tract, organized along the pharyngolaryngeal-to-tracheobronchial axis, is essential for homeostatic functions such as breathing and vocalization. The upper respiratory epithelium is frequently exposed to pollutants and pathogens, making this an area of first-line defense against respiratory injury and infection. The respiratory epithelium is composed of a rich array of specialized cell types, each with unique capabilities in immune defense and injury repair. However, the precise transcriptomic signature and spatial distribution of these cell populations, as well as potential cell subpopulations, have not been well defined. Here, using single cell RNAseq combined with spatial validation, we present a comprehensive atlas of the mouse upper respiratory epithelium. We systematically analyzed our rich RNAseq dataset of the upper respiratory epithelium to reveal 17 cell types, which we further organized into three spatially distinct compartments: the Tmprss11a+ pharyngolaryngeal, the Nkx2-1+ tracheobronchial, and the Dmbt1+ submucosal gland epithelium. We profiled/analyzed the pharyngolaryngeal epithelium, composed of stratified squamous epithelium, and identified distinct regional signatures, including a Keratin gene expression code. In profiling the tracheobronchial epithelium, which is composed of a pseudostratified epithelium-with the exception of the hillock structure-we identified that regional luminal cells, such as club cells and basal cells, show varying gradients of marker expression along the proximal-distal and/or dorsal-ventral axis. Lastly, our analysis of the submucosal gland epithelium, composed of an array of cell types, such as the unique myoepithelial cells, revealed the colorful diversity of between and within cell populations. Our single-cell atlas with spatial validation highlights the distinct transcriptional programs of the upper respiratory epithelium and serves as a valuable resource for future investigations to address how cells behave in homeostasis and pathogenesis. Highlights- Defined three spatially distinct epithelial compartments, Tmprss11a+ pharyngolaryngeal, Nkx2-1+ tracheobronchial, and Dmbt1+ submucosal gland, comprising 17 total cell types - Profiled Keratin gene expression code along proximal-distal and basal-luminal axes and highlighted "stress-induced" Keratins KRT6A and KRT17 at homeostasis - Demarcated expression gradients of Scgb1a1+ and Scgb3a2+ club cells along the proximal-distal axes - Specified submucosal gland cell heterogeneity including Nkx3-1+ mucin-producing cells, with ACTA2+ basal myoepithelial cells exhibiting gene profile for neuroimmune mediated signaling
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium 95%
- Structure-function relationships of mucociliary clearance in human and rat airways 94%
- PRDM3/16 Regulate Chromatin Accessibility Required for NKX2-1 Mediated Alveolar Epithelial Differentiation and Function 94%
Similar papers in this journal
- A single-cell atlas of the human healthy airways 96%
- A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease 96%
- A tracheal aspirate-derived airway basal cell model reveals a pro-inflammatory epithelial defect in congenital diaphragmatic hernia 94%
Similar papers in this journal
- ΔNp63 drives dysplastic alveolar remodeling and restricts epithelial plasticity upon severe lung injury 94%
- Airway basal stem cells are necessary for the maintenance of functional intraepithelial airway macrophages. 94%
- Single-cell and spatial transcriptomics reveal the pathogenesis of chronic granulomatous disease in a natural model 93%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.