This article is a Preprint
Preprints are preliminary research reports that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preprints posted online allow authors to receive rapid feedback and the entire scientific community can appraise the work for themselves and respond appropriately. Those comments are posted alongside the preprints for anyone to read them and serve as a post publication assessment.
Unbiased single cell spatial analysis localises inflammatory clusters of immature neutrophils-CD8 T cells to alveolar progenitor cells in fatal COVID-19 lungs (preprint)
medrxiv; 2022.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2022.12.21.22283654
ABSTRACT
Single cell spatial interrogation of the immune-structural interactions in COVID -19 lungs is challenging, mainly because of the marked cellular infiltrate and architecturally distorted microstructure. To address this, we developed a suite of mathematical tools to search for statistically significant co-locations amongst immune and structural cells identified using 37-plex imaging mass cytometry. This unbiased method revealed a cellular map interleaved with an inflammatory network of immature neutrophils, cytotoxic CD8 T cells, megakaryocytes and monocytes co-located with regenerating alveolar progenitors and endothelium. Of note, a highly active cluster of immature neutrophils and cytotoxic CD8 T cells, was found spatially linked with alveolar progenitor cells, and temporally with the diffuse alveolar damage stage. These findings provide new insights into how immune cells interact in the lungs of severe COVID-19 disease. We provide our pipeline [Spatial Omics Oxford Pipeline (SpOOx)] and visual-analytical tool, Multi-Dimensional Viewer (MDV) software, as a resource for spatial analysis.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
Teratoma
/
Adenocarcinoma, Bronchiolo-Alveolar
/
COVID-19
Language:
English
Year:
2022
Document Type:
Preprint
Similar
MEDLINE
...
LILACS
LIS