Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.

Integration of scRNA-seq data from millions of cells revealed a high diversity of cell types in the healthy and diseased human lung. In a large and complex organ, constantly exposed to external agents, it is crucial to understand the influence of lung tissue topography or external factors on gene expression variability within cell types. Here, we apply three spatial transcriptomics approaches, to: (i) localize the majority of lung cell types, including rare epithelial cells within the tissue topography, (ii) describe consistent anatomical and regional gene expression variability within and across cell types, and (iii) reveal distinct cellular neighborhoods in specific anatomical regions and examine gene expression variations in them. We thus provide a spatially resolved tissue reference atlas in three representative regions of the healthy human lung. We further demonstrate its utility by defining previously unknown imbalances of epithelial cell type compositions in chronic obstructive pulmonary disease lungs. Our topographic atlas enables a precise description of characteristic regional cellular responses upon experimental perturbations or during disease progression.

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Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2025-11-05
DOI
https://doi.org/10.48620/92307
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.

Open Access CRIS of the University of Bern
Single-cell and spatial transcriptomics
article

Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.

article en

Abstract

Integration of scRNA-seq data from millions of cells revealed a high diversity of cell types in the healthy and diseased human lung. In a large and complex organ, constantly exposed to external agents, it is crucial to understand the influence of lung tissue topography or external factors on gene expression variability within cell types. Here, we apply three spatial transcriptomics approaches, to: (i) localize the majority of lung cell types, including rare epithelial cells within the tissue topography, (ii) describe consistent anatomical and regional gene expression variability within and across cell types, and (iii) reveal distinct cellular neighborhoods in specific anatomical regions and examine gene expression variations in them. We thus provide a spatially resolved tissue reference atlas in three representative regions of the healthy human lung. We further demonstrate its utility by defining previously unknown imbalances of epithelial cell type compositions in chronic obstructive pulmonary disease lungs. Our topographic atlas enables a precise description of characteristic regional cellular responses upon experimental perturbations or during disease progression.

Open Access CRIS of the University of Bern
Center for Rheumatology (US)
Good health and well-being
Openalex Percentile: Top 43%
Single-cell and spatial transcriptomics
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Spatial single-cell atlas reveals regional variations in healthy and diseased human lung. · Open Access CRIS of the University of Bern (2025) | TGRS Research Map | TGRS