A molecular single-cell lung atlas of lethal COVID-19
Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand–receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.
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Atlas
Analysis Portals

Project Label
LethalCovidLungAtlasSpecies
Homo sapiens
Sample Type
specimens
Anatomical Entity
pair of lungs
Organ Part
Unspecified
Selected Cell Types
Unspecified
Disease Status (Specimen)
Disease Status (Donor)
Development Stage
human adult stage
Library Construction Method
10x 3' v3
Nucleic Acid Source
single nucleus
Paired End
falseAnalysis Protocol
analysis_file_generation, quality_control_filteringFile Format
Cell Count Estimate
116.0kDonor Count
26