Synergy of two low-affinity NLSs determines the high avidity of influenza A virus nucleoprotein NP for human importin α isoforms
Bibliographic record
Abstract
The influenza A virus nucleoprotein (NP) is an essential multifunctional protein that encapsidates the viral genome and functions as an adapter between the virus and the host cell machinery. NPs from all strains of influenza A viruses contain two nuclear localization signals (NLSs): a well-studied monopartite NLS1 and a less-characterized NLS2, thought to be bipartite. Through site-directed mutagenesis and functional analysis, we found that NLS2 is also monopartite and is indispensable for viral infection. Atomic structures of importin α bound to two variants of NLS2 revealed NLS2 primarily binds the major-NLS binding site of importin α, unlike NLS1 that associates with the minor NLS-pocket. Though peptides corresponding to NLS1 and NLS2 bind weakly to importin α, the two NLSs synergize in the context of the full length NP to confer high avidity for importin α7, explaining why the virus efficiently replicates in the respiratory tract that exhibits high levels of this isoform. This study, the first to functionally characterize NLS2, demonstrates NLS2 plays an important and unexpected role in influenza A virus infection. We propose NLS1 and NLS2 form a bipartite NLS in trans, which ensures high avidity for importin α7 while preventing non-specific binding to viral RNA.
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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".