Exploring the alternative virulence determinants PB2 S155N and PA S49Y/D347G that promote mammalian adaptation of the H9N2 avian influenza virus in mice
Bibliographic record
Abstract
The occurrence of human infections caused by avian H9N2 influenza viruses has raised concerns regarding the potential for human epidemics and pandemics. The molecular basis of viral adaptation to a new host needs to be further studied. Here, the bases of nucleotides 627 and 701 of PB2 were changed according to the uncoverable purine-to-pyrimidine transversion to block the development of PB2 627K and 701N mutations during serial passaging in mice. The purpose of this experiment was to identify key adaptive mutations in polymerase and NP genes that were obscured by the widely known host range determinants PB2 627K and 701N. Mouse-adapted H9N2 variants were obtained via twelve serial lung-to-lung passages. Sequence analysis showed that the mouse-adapted viruses acquired several mutations within the seven gene segments (PB2, PB1, PA, NP, HA, NA, and NS). One variant isolate with the highest polymerase activity possessed three substitutions, PB2 S155N, PA S49Y and D347G, which contributed to the highly virulent and mouse-adaptative phenotype. Further studies demonstrated that these three mutations resulted in increased polymerase activity, viral transcription and replication in mammalian cells, severe interstitial pneumonia, excessive inflammatory cellular infiltration and increased growth rates in mice. Our results suggest that the substitution of these three amino acid mutations may be an alternative strategy for H9N2 avian influenza viruses to adapt to mammalian hosts. The continued surveillance of zoonotic H9N2 influenza viruses should also include these mammalian adaptation markers as part of our pandemic preparedness efforts.
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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 | 0.000 |
| 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".