Contribution of the Nuclear Localization Sequences of Influenza A Nucleoprotein to the Nuclear Import of the Influenza Genome in Infected Cells
Bibliographic record
Abstract
Replication of the RNA genome of influenza A virus occurs in the nucleus of infected cells. The influenza nucleoprotein (NP) associated with the viral RNA into ribonucleoprotein complexes (vRNPs) is involved in the nuclear import of the viral genome. NP has two nuclear localization sequences (NLSs), NLS1 and NLS2. Most studies have concentrated on the role of NP's NLSs using in vitro-assembled or purified vRNPs, which may differ from incoming vRNPs released in the cytoplasm during an infection. Here, we study the contribution of the NP's NLSs to the nuclear import of vRNPs in a cell culture model system for influenza infection: human lung carcinoma cells infected with viruses containing NP-carrying mutations in NLS1 or NLS2 (NLS2MT), generated by reverse genetics. We found that cells infected with these mutant viruses were defective in the nuclear import of incoming vRNPs and produced reduced amounts of newly synthesized NP, newly assembled vRNP, and progeny virus. In addition, NLS2MT-infected cells were also defective in the nucleolar accumulation of NP, confirming the nucleolar localization role of NLS2. Our findings indicate that both NLS1 and NLS2 have to be present for successful infection and demonstrate the crucial role of these two NLSs in the infection cycle of the influenza A virus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".