Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury

Abstract

Severe lung damage in COVID-19 is known to involve complex interactions between diverse populations of immune and stromal cells. 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 immunohistochemistry we performed a targeted sampling of dozens of regions representing a spectrum of diffuse alveolar damage from the post-mortem lung of three COVID-19 patients. Application of a combination of differential gene expression, weighted gene correlation network, pathway and spatial deconvolution analysis stratified the sampled regions into five distinct groups according to degree of alveolar damage, levels of cytotoxic inflammation and innate activation, epithelial reorganization, and fibrosis. Integrative network analysis of the identified groups revealed the presence of proliferating CD8 T and NK cells in severely damaged areas along with signatures of cytotoxicity, interferon signalling and high expression of immune cell chemoattractants (including CXCL9/10/11 and CCL2). Areas of milder damage were marked by innate immune signalling (including TLR response, IL-1, IL-6) together with signatures of antigen presentation, and fibrosis. Based on these data we present a cellular model of tissue damage in terminal COVID-19 that confirms previous observations and highlights novel opportunities for therapeutic intervention.

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus

“…We previously generated selective spatial transcriptomics from 46 areas of postmortem biopsies from patients with critical COVID-19 covering a spectrum of alveolar injury 64 . To explore the expression Fig.…”

“…= 0.55 cm 2 ) for hematoxylin and eosin (H&E) analysis. Sections were analyzed by NanoString GeoMx Digital Spatial Profiling with normalization and downstream analysis by WGCNA 66 and cell deconvolution 65 as described previously 64 . For deconvolution with SpatialDecon in R v.1.0.0, cell profiles were obtained from the Human Cell Atlas healthy lung and scRNA-seq-appended with neutrophil data 105 using the R 'Lung_plus_neut' dataset.…”

Hypoxia inducible factors regulate infectious SARS-CoV-2, epithelial damage and respiratory symptoms in a hamster COVID-19 model

“…Analysing inflammatory gene expression using genes from the molecular signature database (Liberzon et al, 2015) showed that FG-4592 had a modest effect on the lung inflammasome (Supplementary Fig.6) . Of note, expression of the viral entry receptors Ace2 and Tmprss2 were significantly downregulated (log 2 fold change of −1.45 and −1.52 respectively) in the infected tissue, likely reflecting viral cytopathology (Cross et al, 2021). Loss of ciliated epithelial cells is a key feature of COVID-19 resulting from damage to the airway epithelia (Pizzorno et al, 2020; Robinot et al, 2021; Zhu et al, 2020).…”

“…6). Of note, expression of the viral entry receptors Ace2 and Tmprss2 were significantly downregulated (log 2 fold change of -1.45 and -1.52 respectively) in the infected tissue, likely reflecting viral cytopathology (Cross et al, 2021). Loss of ciliated epithelial cells is a key feature of COVID-19 resulting from damage to the airway epithelia (Pizzorno et al, 2020;Robinot et al, 2021;Zhu et al, 2020).…”

“…Under normal physiological conditions, the lungs provide an oxygen rich environment, however, an increasing body of literature shows a role for hypoxia in the inflamed airway epithelium (Page et al, 2021). Transcriptomic analysis of post-mortem COVID-19 pulmonary tissue shows an association between hypoxic signalling and inflammatory responses (Cross et al, 2021;Sposito et al, 2021).…”