Restriction of HIV-1 infectivity by interferon and IFITM3 is counteracted by Nef
Bibliographic record
Abstract
The viral accessory protein Nef is a major determinant of HIV-1 pathogenicity in vivo. Nef is a multifunctional, immunomodulatory protein that downmodulates cell surface proteins, including CD4 and MHC class I (MHC-I), which are important for T cell-mediated immunity. In addition, Nef also regulates cell-intrinsic immunity-Nef boosts the infectivity of virions produced and released from HIV-infected cells, at least in part, by counteracting the antiviral activity of transmembrane proteins SERINC3 and SERINC5. Here, we show that Nef proteins derived from many primary isolates of HIV-1 restore infectivity in interferon-treated cells and confer resistance to the antiviral protein interferon-induced transmembrane protein 3 (IFITM3) in a SERINC3/5-independent manner. Using Nef derived from primary HIV-1 clade C infection, we found that Nef interacts with IFITM3 in membranes, reduces IFITM3 incorporation into HIV-1 virions, and restores HIV-1 fusion with target cells. Our findings reveal a previously unrecognized immunomodulatory role for Nef in the setting of the interferon-induced antiviral state during HIV-1 infection.
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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".