Experimental Evolution of Human Influenza Virus H3 Hemagglutinin in the Mouse Lung Identifies Adaptive Regions in HA1 and HA2
Bibliographic record
Abstract
The genetic basis for virulence and host switching in influenza A viruses (FLUAV) is largely unknown. Because the hemagglutinin (HA) protein is a determinant of these properties, HA evolution was mapped in an experimental model of mouse lung adaptation. Variants of prototype A/Hong Kong/1/68 (H3N2) (wild-type [wt] HK) human virus were selected in both longitudinal and parallel studies of lung adaptation. Mapping of HA mutations found in 11 independently derived mouse-adapted populations of wt HK identified 27 mutations that clustered within two distinct regions in or near the globular frameworks of the HA1 and HA2 subunits. The adaptive mutations demonstrated multiple instances of convergent evolution involving four amino acid positions (162, 210, and 218 in HA1 and 154 in HA2). By use of reverse genetics, convergent HA mutations were shown to affect cell tropism by enhancing infection and replication in primary mouse tracheal epithelial cells in vitro and mouse lung tissue in vivo. Adaptive HA mutations were multifunctional, affecting both median pH of fusion and receptor specificity. Specific mutations within both adaptive regions were shown to increase virulence in a mouse lung model. The occurrence of mutations in the HA1 and HA2 adaptive regions of natural FLUAV host range and virulent variants of avian and mammalian viruses is discussed. This study has identified adaptive sites and regions within the HA1 and HA2 subunits that may guide future studies of viral adaptation and evolution in nature.
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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 | 0.001 | 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 | 0.001 |
| 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".