Viral chimeras decrypt the role of enterovirus capsid proteins in viral tropism, acid sensitivity and optimal growth temperature
Bibliographic record
Abstract
Despite their genetic similarities, enteric and respiratory enteroviruses (EVs) have highly heterogeneous biophysical properties and cause a vast diversity of human pathologies. In vitro differences include acid sensitivity, optimal growth temperature and tissue tropism, which reflect a preferential in vivo replication in the respiratory or gastrointestinal tract and are thus key determinants of EV virulence. To investigate the underlying cause of these differences, we generated chimeras at the capsid-level between EV-D68 (a respiratory EV) and EV-D94 (an enteric EV). Although some chimeras were nonfunctional, EV-D94 with both the capsid and 2A protease or the capsid only of EV-D68 were both viable. Using this latter construct, we performed several functional assays, which indicated that capsid proteins determine acid sensitivity and tropism in cell lines and in respiratory, intestinal and neural tissues. Additionally, capsid genes were shown to also participate in determining the optimal growth temperature, since EV-D94 temperature adaptation relied on single mutations in VP1, while constructs with EV-D68 capsid could not adapt to higher temperatures. Finally, we demonstrate that EV-D68 maintains residual binding-capacity after acid-treatment despite a loss of infectivity. In contrast, non-structural rather than capsid proteins modulate the innate immune response in tissues. These unique biophysical insights expose another layer in the phenotypic diversity of one of world's most prevalent pathogens and could aid target selection for vaccine or antiviral development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".