Synthetic Reconstruction of Zoonotic and Early Human Severe Acute Respiratory Syndrome Coronavirus Isolates That Produce Fatal Disease in Aged Mice
Bibliographic record
Abstract
The severe acute respiratory syndrome (SARS) epidemic was characterized by high mortality rates in the elderly. The molecular mechanisms that govern enhanced susceptibility of elderly populations are not known, and robust animal models are needed that recapitulate the increased pathogenic phenotype noted with increasing age. Using synthetic biology and reverse genetics, we describe the construction of a panel of isogenic SARS coronavirus (SARS-CoV) strains bearing variant spike glycoproteins that are representative of zoonotic strains found in palm civets and raccoon dogs, as well as isolates spanning the early, middle, and late phases of the SARS-CoV epidemic. The recombinant viruses replicated efficiently in cell culture and demonstrated variable sensitivities to neutralization with antibodies. The human but not the zoonotic variants replicated efficiently in human airway epithelial cultures, supporting earlier hypotheses that zoonotic isolates are less pathogenic in humans but can evolve into highly pathogenic strains. All viruses replicated efficiently, but none produced clinical disease or death in young animals. In contrast, severe clinical disease, diffuse alveolar damage, hyaline membrane formation, alveolitis, and death were noted in 12-month-old mice inoculated with the palm civet HC/SZ/61/03 strain or early-human-phase GZ02 variants but not with related middle- and late-phase epidemic or raccoon dog strains. This panel of SARS-CoV recombinants bearing zoonotic and human epidemic spike glycoproteins will provide heterologous challenge models for testing vaccine efficacy against zoonotic reintroductions as well as provide the appropriate model system for elucidating the complex virus-host interactions that contribute to more-severe and fatal SARS-CoV disease and acute respiratory distress in the elderly.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".