|
| Status |
Public on Jan 27, 2023 |
| Title |
Spatial transcriptomic characterization of the lung parenchyma during COVID-19 pneumonitis |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
Other
|
| Summary |
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.
|
| |
|
| Overall design |
RNA expression was assessed in selected areas within the lung parenchyma from three COVID-19 patients. Tissues were obtained rapidly postmortem, through open biopsy. At least, 14 spatially distinct areas (AOI) per tissue section were sampled to demonstrate the breadth of inflammation and injury within the alveolar region (total AOI = 46). The areas (AOI) were classified by the severity of alveolar tissue and the presence of proximal SARS-CoV-2 nucelocapsid in aligned non-sequential tissue sections. These microscopic sites of injury had varying known compositions of CD3+ lymphocytes, CD68+ myeloid cells and panCK+ epithelial cells. The genes measured were included in the NanoString Cancer Transcriptome Atlas (CTA) panel and those included in the COVID-19 spike-in gene panel for added respiratory-related and SARS-CoV-2 genes. The raw count matrix, the quantile normalized expression matrix and the metadata (including the calculated CD3+ and CD68+ cell composition, and the severity of alveolar damage) are provided. The corresponding immunofluorescence images of each AOI and the whole tissue scan can be provided upon request.
|
| |
|
| Contributor(s) |
Cross AR, Sansom SN, Issa F |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| |
| Submission date |
Oct 20, 2021 |
| Last update date |
Jan 30, 2023 |
| Contact name |
Amy Rachael Cross |
| E-mail(s) |
amy.cross@nds.ox.ac.uk
|
| Organization name |
University of Oxford
|
| Department |
NDS
|
| Lab |
TRIG
|
| Street address |
John Radcliffe Hospital
|
| City |
Oxford |
| ZIP/Postal code |
OX38DU |
| Country |
United Kingdom |
| |
|
| Platforms (1) |
|
| Samples (47)
|
|
| Relations |
| BioProject |
PRJNA772979 |
| SRA |
SRP342276 |
Less...
More...