Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19)1–8. 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 cytometry9 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.
Detailed clinical annotations and demographic characteristics for patients included in the study representing different disease groups (ARDS post -viral influenza (n=2), ARDS post bacterial infection (n=4), bacterial pneumonia (n=3) and COVID-19 ARDS (n=10)) and control group (normal lung (n=4)).
List of metal-tagged antibodies used in imaging mass cytometry. Panel 1 (“Lung_COVID-19”) includes 36 markers characterizing immune cell phenotypes and functional markers related with COVID-19 such as IL-6, IL-1beta, cKIT, pSTAT3 and viral infection component S protein. Panel 2 (Immune activation) includes 38 markers characterizing immune cell activation states.
Statistical testing of difference in abundance for clusters and meta-clusters between disease groups. A two tailed Mann-Whitney U-test was performed and p-values were adjusted with the Benjamini-Hochberg False Discovery Rate method. The uncorrected p-value is in the “p-unc” column, the corrected p-value in the “p-cor” column, and a measure of effect size is given in the “hedges” column, which indicates a Hedge’s g value.
Statistical testing of difference in fraction of cells positive in functional markers for clusters and meta-clusters between disease groups. A two tailed Mann-Whitney U-test was performed and p-values were adjusted with the Benjamini-Hochberg False Discovery Rate method. The uncorrected p-value is in the “p-unc” column, the corrected p-value in the “p-cor” column, and a measure of effect size is given in the “hedges” column, which indicates a Hedge’s g value.
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Rendeiro, A.F., Ravichandran, H., Bram, Y. et al. The spatial landscape of lung pathology during COVID-19 progression. Nature (2021). https://doi.org/10.1038/s41586-021-03475-6