HIV-1 subtype C Nef-mediated SERINC5 down-regulation significantly contributes to overall Nef activity
Bibliographic record
Abstract
BACKGROUND: Nef performs multiple cellular activities that enhance HIV-1 pathogenesis. The role of Nef-mediated down-regulation of the host restriction factor SERINC5 in HIV-1 pathogenesis is not well-defined. We aimed to investigate if SERINC5 down-regulation activity contributes to HIV-1 subtype C disease progression, to assess the relative contribution of this activity to overall Nef function, and to identify amino acids required for optimal activity. We measured the SERINC5 down-regulation activity of 106 subtype C Nef clones, isolated from individuals in early infection, for which the Nef activities of CD4 and HLA-I down-regulation as well as alteration of TCR signalling were previously measured. The relationship between SERINC5 down-regulation and markers of disease progression, and the relative contribution of SERINC5 down-regulation to a Nef fitness model-derived E value (a proxy for overall Nef fitness in vivo), were assessed. RESULTS: T cell decline (p = 0.45). CD4 down-regulation (p = 0.02) and SERINC5 down-regulation (p = 0.003) were significant determinants of E values in univariate analyses, with the greatest relative contribution for SERINC5 down-regulation, and only SERINC5 down-regulation remained significant in the multivariate analysis (p = 0.003). Using a codon-by-codon analysis, several amino acids were significantly associated with increased (10I, 11V, 38D, 51T, 65D, 101V, 188H and, 191H) or decreased (10K, 38E, 65E, 135F, 173T, 176T and, 191R) SERINC5 down-regulation activity. Site-directed mutagenesis experiments of selected mutants confirmed a substantial reduction in SERINC5 down-regulation activity associated with the mutation 173T, while mutations 10K, 135F, and 176T were associated with more modest reductions in activity that were not statistically significant. CONCLUSIONS: These results suggest that SERINC5 down-regulation is a significant contributor to overall Nef function and identify potential genetic determinants of this Nef function that may have relevance for vaccines or therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.035 |
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; both teacher heads agree on what is shown here.
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".