Relationship between within-Host Fitness and Virulence in the Vesicular Stomatitis Virus: Correlation with Partial Decoupling
Bibliographic record
Abstract
Given the parasitic nature of viruses, it is sometimes assumed that rates of viral replication and dissemination within hosts (within-host fitness) correlate with virulence. However, there is currently little empirical evidence supporting this principle. To test this, we quantified the fitness and virulence of 21 single- or double-nucleotide mutants of the vesicular stomatitis virus in baby hamster kidney cells (BHK-21). We found that, overall, these two traits correlated positively, but significant outliers were identified. Particularly, a single mutation in the conserved C terminus of the N nucleocapsid (U1323A) had a strongly deleterious fitness effect but did not alter or even slightly increased virulence. We also found a double mutant of the M matrix protein and G glycoprotein (U2617G/A3802G mutant) with high fitness yet low virulence. We further characterized these mutants in primary cultures from mouse brain cells and in vivo and found that their relative fitness values were similar to those observed in BHK-21 cells. The mutations had weak effects on the virus-induced death rate of total brain cells, although they specifically reduced neuron death rates. Furthermore, increased apoptosis levels were detected in neurons infected with the U2617G/A3802G mutant, consistent with its known inability to block interferon secretion. In vivo, this mutant had reduced virulence and, despite its low brain titer, it retained a relatively high fitness value owing to its ability to suppress competitor viruses. Overall, our results are in broad agreement with the notion that viral fitness and virulence should be positively correlated but show that certain mutations can break this association and that the fitness-virulence relationship can depend on complex virus-host and virus-virus interactions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".