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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月5日

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  • 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,
  • Christos Samakovlis

摘要

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.