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

Alexandra B. Firsova, Sergio Marco Salas, Louis B. Kuemmerle, Xesús M. Abalo, Alexandros Sountoulidis, Ludvig Larsson, Krishnaa T. Mahbubani, Jonas Theelke, Zaneta Andrusivova, Leire Alonso Galicia, Andreas Liontos, Tamás Balassa, Ferenc Kovacs, Peter Horvath, Yuexin Chen, Janine Gote-Schniering, Mircea-Gabriel Stoleriu, Jürgen Behr, Kerstin B. Meyer, Wim Timens, Herbert B. Schiller, Malte D. Luecken, Fabian J. Theis, Joakim Lundeberg, Mats Nilsson, Martijn C. Nawijn and Christos Samakovlis ()
Additional contact information
Alexandra B. Firsova: Science for Life Laboratory
Sergio Marco Salas: Science for Life Laboratory
Louis B. Kuemmerle: Helmholtz Munich
Xesús M. Abalo: Science for Life Laboratory
Alexandros Sountoulidis: Science for Life Laboratory
Ludvig Larsson: Science for Life Laboratory
Krishnaa T. Mahbubani: and Cambridge NIHR Biomedical Research Centre
Jonas Theelke: Science for Life Laboratory
Zaneta Andrusivova: Science for Life Laboratory
Leire Alonso Galicia: Science for Life Laboratory
Andreas Liontos: Science for Life Laboratory
Tamás Balassa: HUN-REN Biological Research Centre
Ferenc Kovacs: HUN-REN Biological Research Centre
Peter Horvath: HUN-REN Biological Research Centre
Yuexin Chen: Helmholtz Munich
Janine Gote-Schniering: University of Bern
Mircea-Gabriel Stoleriu: Member of the German Center for Lung Research (DZL)
Jürgen Behr: Member of the German Center for Lung Research (DZL)
Kerstin B. Meyer: Wellcome Genome Campus
Wim Timens: University Medical Center Groningen
Herbert B. Schiller: Helmholtz Munich
Malte D. Luecken: Helmholtz Munich
Fabian J. Theis: Helmholtz Munich
Joakim Lundeberg: Science for Life Laboratory
Mats Nilsson: Science for Life Laboratory
Martijn C. Nawijn: University Medical Center Groningen
Christos Samakovlis: Science for Life Laboratory

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: 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.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-65704-0

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DOI: 10.1038/s41467-025-65704-0

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