Synergistic PA and HA mutations confer mouse adaptation of a contemporary A/H3N2 influenza virus
Bibliographic record
Abstract
The mouse is the most widely used animal model for influenza virus research. However, the susceptibility of mice to seasonal influenza virus depends on the strain of mouse and on the strain of the influenza virus. Seasonal A/H3N2 influenza viruses do not replicate well in mice and therefore they need to be adapted to this animal model. In this study, we generated a mouse-adapted A/H3N2 virus (A/Switzerland/9715293/2013 [MA-H3N2]) by serial passaging in mouse lungs that exhibited greater virulence compared to the wild-type virus (P0-H3N2). Seven mutations were found in the genome of MA-H3N2: PA(K615E), NP(G384R), NA(G320E) and HA(N122D, N144E, N246K, and A304T). Using reverse genetics, two synergistically acting genes were found as determinants of the pathogenicity in mice. First, the HA substitutions were shown to enhanced viral replication in vitro and, second, the PA-K615E substitution increased polymerase activity, although did not alter virus replication in vitro or in mice. Notably, single mutations had only limited effects on virulence in vitro. In conclusion, a co-contribution of HA and PA mutations resulted in a lethal mouse model of seasonal A/H3N2 virus. Such adapted virus is an excellent tool for evaluation of novel drugs or vaccines and for study of influenza pathogenesis.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".