Dataset Open Access

The spatial landscape of lung pathology during COVID-19 progression - immunohistochemistry data

Rendeiro, Andre Figueiredo; Ravichandran, Hiranmayi; Bram, Yaron; Kim, Junbum; Meydan, Cem; Park, Jiwoon; Foox, Jonathan; Hether, Tyler; Warren, Sarah; Kim, Youngmi; Reeves, Jason; Salvatore, Steven; Mason, Christopher E.; Swanson, Eric C.; Borczuk, Alain; Elemento, Olivier; Schwartz, Robert Edward

Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19). However thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking. We use high parameter imaging mass cytometry targeting the expression of 36 proteins, to investigate at single cell resolution, the cellular composition and spatial architecture of human acute lung injury including SARS-CoV-2. This spatially resolved, single-cell data unravels the disordered structure of the infected and injured lung alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyper-inflammatory cell state associated with lung damage. By leveraging the temporal range of COVID-19 severe fatal disease in relation to the time of symptom onset, we observe increased macrophage extravasation, mesenchymal cells, and fibroblasts abundance concomitant with increased proximity between these cell types as the disease progresses, possibly as an attempt to repair the damaged lung tissue. This spatially resolved single-cell data allowed us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. This spatial single-cell landscape enabled the pathophysiological characterization of the human lung from its macroscopic presentation to the single-cell, providing an important basis for the understanding of COVID-19, and lung pathology in general.

We make available 323 OME-TIFF files with images of lung tissue stained for two antigens with conventional hematoxylin-diaminobenzidine (H-DAB) immunohistochemistry (IHC). In addition, each image has a segmented mask for nuclei which was used for quantification of signal intensity from deconvolved color, and discretization in negative/positive nuclei for DAB signal. Companion deposit to https://doi.org/10.5281/zenodo.4110560
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14.1 MB Download
data/ihc/MPO/pneumonia a19-100 alveolar4.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-100 alveolar4.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-100 vessel 1.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-100 vessel 1.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-100 vessel2.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-100 vessel2.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 airway1.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 airway1.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 airway2.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 airway2.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 1.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 1.tif
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data/ihc/MPO/pneumonia a19-127 alveolar 2.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 2.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 3.stardist_mask.tiff
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data/ihc/MPO/pneumonia a19-127 alveolar 3.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 4.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 alveolar 4.tif
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14.1 MB Download
data/ihc/MPO/pneumonia a19-127 vessel1.stardist_mask.tiff
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data/ihc/MPO/pneumonia a19-127 vessel1.tif
md5:ab35b533925eb5c2d33e3312668fc6c9
14.1 MB Download
data/ihc/MPO/pneumonia a19-127 vessel2.stardist_mask.tiff
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9.4 MB Download
data/ihc/MPO/pneumonia a19-127 vessel2.tif
md5:7940c6bfe945656c4fd21b31a09f28a0
14.1 MB Download
data/ihc/quantification_hdab.gated_by_image.csv
md5:0a491456172e91343776173b7e4a1b0f
51.2 MB Download
metadata/ihc_metadata.csv
md5:c9d4f8dc4a97220dfcd0c7a80ea155bb
297.3 kB Download
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