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Experimental Model of Pulmonary Inflammation Induced by SARS-CoV-2 Spike Protein and Endotoxin

Puthia, Manoj LU ; Tanner, Lloyd LU ; Petruk, Ganna LU orcid and Schmidtchen, Artur LU (2022) In ACS Pharmacology and Translational Science 5(3). p.141-148
Abstract

COVID-19 is characterized by a dysregulated and excessive inflammatory response and, in severe cases, acute respiratory distress syndrome. We have recently demonstrated a previously unknown high-affinity interaction between the SARS-CoV-2 spike (S) protein and bacterial lipopolysaccharide (LPS), leading to the boosting of inflammation. Here we present a mouse inflammation model employing the coadministration of aerosolized S protein together with LPS to the lungs. Using NF-κB-RE-Luc reporter and C57BL/6 mice followed by combinations of bioimaging, cytokine, chemokine, fluorescence-activated cell sorting, and histochemistry analyses, we show that the model yields severe pulmonary inflammation and a cytokine profile similar to that... (More)

COVID-19 is characterized by a dysregulated and excessive inflammatory response and, in severe cases, acute respiratory distress syndrome. We have recently demonstrated a previously unknown high-affinity interaction between the SARS-CoV-2 spike (S) protein and bacterial lipopolysaccharide (LPS), leading to the boosting of inflammation. Here we present a mouse inflammation model employing the coadministration of aerosolized S protein together with LPS to the lungs. Using NF-κB-RE-Luc reporter and C57BL/6 mice followed by combinations of bioimaging, cytokine, chemokine, fluorescence-activated cell sorting, and histochemistry analyses, we show that the model yields severe pulmonary inflammation and a cytokine profile similar to that observed in COVID-19. Therefore, the model offers utility for analyses of the pathophysiological features of COVID-19 and the development of new treatments.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ARDS, COVID-19 in vivo models, LPS, SARS-CoV-2 spike (S) protein, TCP-25
in
ACS Pharmacology and Translational Science
volume
5
issue
3
pages
8 pages
publisher
The American Chemical Society (ACS)
external identifiers
  • scopus:85124131709
  • pmid:35774232
DOI
10.1021/acsptsci.1c00219
language
English
LU publication?
yes
id
50ecf9d2-4e5c-4fe9-befa-f7a7e16cf218
date added to LUP
2022-04-05 15:31:48
date last changed
2024-06-18 07:00:16
@article{50ecf9d2-4e5c-4fe9-befa-f7a7e16cf218,
  abstract     = {{<p>COVID-19 is characterized by a dysregulated and excessive inflammatory response and, in severe cases, acute respiratory distress syndrome. We have recently demonstrated a previously unknown high-affinity interaction between the SARS-CoV-2 spike (S) protein and bacterial lipopolysaccharide (LPS), leading to the boosting of inflammation. Here we present a mouse inflammation model employing the coadministration of aerosolized S protein together with LPS to the lungs. Using NF-κB-RE-Luc reporter and C57BL/6 mice followed by combinations of bioimaging, cytokine, chemokine, fluorescence-activated cell sorting, and histochemistry analyses, we show that the model yields severe pulmonary inflammation and a cytokine profile similar to that observed in COVID-19. Therefore, the model offers utility for analyses of the pathophysiological features of COVID-19 and the development of new treatments.</p>}},
  author       = {{Puthia, Manoj and Tanner, Lloyd and Petruk, Ganna and Schmidtchen, Artur}},
  keywords     = {{ARDS; COVID-19 in vivo models; LPS; SARS-CoV-2 spike (S) protein; TCP-25}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{141--148}},
  publisher    = {{The American Chemical Society (ACS)}},
  series       = {{ACS Pharmacology and Translational Science}},
  title        = {{Experimental Model of Pulmonary Inflammation Induced by SARS-CoV-2 Spike Protein and Endotoxin}},
  url          = {{http://dx.doi.org/10.1021/acsptsci.1c00219}},
  doi          = {{10.1021/acsptsci.1c00219}},
  volume       = {{5}},
  year         = {{2022}},
}