Evolution of Oseltamivir Resistance Mutations in Influenza A(H1N1) and A(H3N2) Viruses during Selection in Experimentally Infected Mice
Bibliographic record
Abstract
The evolution of oseltamivir resistance mutations during selection through serial passages in animals is still poorly described. Herein, we assessed the evolution of neuraminidase (NA) and hemagglutinin (HA) genes of influenza A/WSN/33 (H1N1) and A/Victoria/3/75 (H3N2) viruses recovered from the lungs of experimentally infected BALB/c mice receiving suboptimal doses (0.05 and 1 mg/kg of body weight/day) of oseltamivir over two generations. The traditional phenotypic and genotypic methods as well as deep-sequencing analysis were used to characterize the potential selection of mutations and population dynamics of oseltamivir-resistant variants. No oseltamivir-resistant NA or HA changes were detected in the recovered A/WSN/33 viruses. However, we observed a positive selection of the I222T NA substitution in the recovered A/Victoria/3/75 viruses, with a frequency increasing over time and with an oseltamivir concentration from 4% in the initial pretherapy inoculum up to 28% after two lung passages. Although the presence of mixed I222T viral populations in mouse lungs only led to a minimal increase in oseltamivir 50% enzyme-inhibitory concentrations (IC50s) (by a mean of 5.7-fold) compared to that of the baseline virus, the expressed recombinant A/Victoria/3/75 I222T NA protein displayed a 16-fold increase in the oseltamivir IC50 level compared to that of the recombinant wild type (WT). In conclusion, the combination of serial in vivo passages under neuraminidase inhibitor (NAI) pressure and temporal deep-sequencing analysis enabled, for the first time, the identification and selection of the oseltamivir-resistant I222T NA mutation in an influenza H3N2 virus. Additional in vivo selection experiments with other antivirals and drug combinations might provide important information on the evolution of antiviral resistance in influenza viruses.
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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) | 0.000 | 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 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".