Cytokines and Lipid Mediators of Inflammation in Lungs of SARS-CoV-2 Infected Mice
Bibliographic record
Abstract
Coronavirus disease 19 (COVID-19) is the clinical manifestation of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection. A hallmark of COVID-19 is a lung inflammation characterized by an abundant leukocyte infiltrate, elevated levels of cytokines/chemokines, lipid mediators of inflammation (LMI) and microthrombotic events. Animal models are useful for understanding the pathophysiological events leading to COVID-19. One such animal model is the K18-ACE2 transgenic mice. Despite their importance in inflammation, the study of LMI in lung of SARS-CoV-2 infected K18-ACE2 mice has yet to be studied to our knowledge. Using tandem mass spectrometry, the lung lipidome at different time points of infection was analyzed. Significantly increased LMI included N-oleoyl-serine, N-linoleoyl-glycine, N-oleoyl-alanine, 1/2-linoleoyl-glycerol, 1/2-docosahexaenoyl-glycerol and 12-hydroxy-eicosapenatenoic acid. The levels of prostaglandin (PG) E1, PGF2α, stearoyl-ethanolamide and linoleoyl-ethanolamide were found to be significantly reduced relative to mock-infected mice. Other LMI were present at similar levels (or undetected) in both uninfected and infected mouse lungs. In parallel to LMI measures, transcriptomic and cytokine/chemokine profiling were performed. Viral replication was robust with maximal lung viral loads detected on days 2-3 post-infection. Lung histology revealed leukocyte infiltration starting on day 3 post-infection, which correlated with the presence of high concentrations of several chemokines/cytokines. At early times post-infection, the plasma of infected mice contained highly elevated concentration of D-dimers suggestive of blood clot formation/dissolution. In support, the presence of blood clots in the lung vasculature was observed during infection. RNA-Seq analysis of lung tissues indicate that SARS-CoV-2 infection results in the progressive modulation of several hundred genes, including several inflammatory mediators and genes related to the interferons. Analysis of the lung lipidome indicated modest, yet significant modulation of a minority of lipids. In summary, our study suggests that SARS-CoV-2 infection in humans and mice share common features, such as elevated levels of chemokines in lungs, leukocyte infiltration and increased levels of circulating D-dimers. However, the K18-ACE2 mouse model highlight major differences in terms of LMI being produced in response to SARS-CoV-2 infection. The potential reasons and impact of these differences on the pathology and therapeutic strategies to be employed to treat severe COVID-19 are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".