Natural HIV-1 Nef Polymorphisms Impair SERINC5 Downregulation Activity
Bibliographic record
Abstract
HIV-1 Nef enhances virion infectivity by counteracting host restriction factor SERINC5; however, the impact of natural Nef polymorphisms on this function is largely unknown. We characterize SERINC5 downregulation activity of 91 primary HIV-1 subtype B nef alleles, including isolates from 45 elite controllers and 46 chronic progressors. Controller-derived Nef clones display lower ability to downregulate SERINC5 (median 80% activity) compared with progressor-derived clones (median 96% activity) (p = 0.0005). We identify 18 Nef polymorphisms associated with differential function, including two CTL escape mutations that contribute to lower SERINC5 downregulation: K94E, driven by HLA-B ∗ 08, and H116N, driven by the protective allele HLA-B ∗ 57. HIV-1 strains encoding Nef K94E and/or H116N display lower infectivity and replication capacity in the presence of SERINC5. Our results demonstrate that natural polymorphisms in HIV-1 Nef can impair its ability to internalize SERINC5, indicating that variation in this recently described function may contribute to differences in viral pathogenesis.
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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) | 0.002 | 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".