Spatial transcriptomic characterization of the lung parenchyma during COVID-19 pneumonitis

ABSTRACT: Severe lung damage in COVID-19 is known to involve complex interactions between diverse populations of immune and stromal cells. The pneumonitis manifesting in COVID-19 and acute respiratory distress syndrome results in spatially heterogenous manifestations of injury, such as infiltrates, loss of epithelial integrity and fibrosis. In this study, we applied a spatial transcriptomics approach to better delineate the cells, pathways and genes responsible for promoting and perpetuating severe tissue pathology in COVID-19 pneumonitis. Guided by tissue histology and multiplex immunofluorescence, we performed a targeted sampling of dozens of regions representing a spectrum of diffuse alveolar damage (mild to severe) from the post-mortem lung of three COVID-19 patients. These microscopic sites of injury had varying known compositions of CD3+ lymphocytes, CD68+ myeloid cells and panCK+ epithelial cells. DCC files are the processed sequencing files using the NanoString DND pipeline. The "Initial Dataset.xlsx" is represents raw gene counts for each probe replicate (n=47). "Post Biological Probe QC.xlsx" removes a sample (n=46) with failed sequencing (no rawReads) and conducts biological probe quality controls to collapse probe replicates into a single count per target gene using the GeoMx Analysis suite (version 2.1.0.102). "qn.exprs.tsv" is the matrix of quantile normalised gene expression by segment (n=46) and "qn.exprs.corrected.tsv" is the matrix of quantile normalised and batch corrected matrix of gene expression by segment (n=46). Rendered multichannel immunofluorescent microscopy png images corresponding to each area of interest (AOI with the acquistion borders outlined in white) are included. Further images can be made available upon request.

ORGANISM(S): Homo sapiens

PROVIDER: GSE186213 | GEO | 2023/01/27

REPOSITORIES: GEO