Coronavirus pathogenesis in mice explains the SARS-CoV-2 multi-organ spread by red blood cells hitch-hiking
Bibliographic record
Abstract
ABSTRACT SARS-CoV-2 infection causes a multisystemic disease that affects numerous organs beyond the respiratory system. Thus, it is well known that COVID-19 is associated with a wide range of hematological disorders; however, it remains unclear how the SARS-CoV-2 virus is able to navigate from tissue to tissue. In this work, we performed a comprehensive analysis of the pleiotropic effects of a prototypical coronavirus in its natural host, the validated preclinical model of murine hepatitis virus (MHV). Throughout this study we compared our results with the real-world data from COVID-19 patients (including autopsies). Thus, the presence of viral RNA was only detected in less than 25% of the human serum samples, whereas all had multiple positive nasal swabs for SARS-CoV-2. Notably, we found viral RNA not only in lungs, but also in heart and kidney of deceased COVID-19 patients. Subsequently, we investigated the association between viral organotropism and clinical manifestations employing the MHV murine model. Results from RT-qPCR and viral infectivity showcased the presence of viral RNA and infectious particles in multiple organs including liver, lung, brain, heart, kidney, spleen and pancreas, and even the blood of infected mice. Surprisingly, when comparing plasma and red blood cells (RBCs)-enriched fraction, higher viral load levels were detected in RBCs, with decreased RBC count, and hematocrit and hemoglobin levels in infected mice. Next, we treated infected mice with hemin triggering more aggressive symptoms. Strikingly, when combining hemin treatment with chloroquine (a compound that known to interact with the heme group and induces a conformational change in its structure) the infection and its clinical manifestations were distinctly attenuated. Computational docking suggested that heme is able to bind to MHV Spike protein in a similar way to the one, experimentally observed for SARS-CoV-2. Overall, our results lead to a global perspective of COVID-19 beyond the canonical focus on the respiratory system, and strongly support the multi-organ extent of coronavirus infection through specific interactions with RBC hemoproteins.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".