Genetic determinants of HIV-1 subtype C Nef-mediated SERINC3 down-regulation
Bibliographic record
Abstract
BACKGROUND: Nef-mediated down-regulation of the host restriction factors SERINC3 and SERINC5 significantly enhances HIV-1 infectivity. Natural Nef polymorphisms that affect SERINC3 down-regulation are not as well-characterised as those that affect SERINC5 down-regulation, particularly in HIV-1 subtype C infection. We therefore aimed to identify genetic determinants of SERINC3 down-regulation by subtype C Nef. In addition, we investigated the role of SERINC3 down-regulation activity in disease progression and its contribution to overall Nef function, using Nef fitness model-derived E values as a proxy for overall Nef function in vivo. METHODS: SERINC3 down-regulation activity of 107 participant-derived Nef clones was measured using a flow cytometry-based assay in a T cell line. The relationship between SERINC3 down-regulation activity and viral load set point or rate of CD4 + T cell decline during untreated HIV infection was analysed by linear regression. Quantile regression was used to assess the contribution of SERINC3 down-regulation activity to overall Nef function. Individual Nef amino acids associated with a significantly altered SERINC3 down-regulation activity were identified using codon-by-codon Mann Whitney U tests. RESULTS: SERINC3 down-regulation activity was not a significant predictor of viral load set point nor rate of CD4 + T cell decline. SERINC3 down-regulation activity was a significant predictor of estimated Nef fitness (E values) in univariate analysis (p < 0.0001) and remained significant in multivariate analyses adjusting for other Nef functions that were measured for the same Nef clones (p < 0.02). A total of 30 amino acids were identified to be associated with differential Nef-mediated ability to down-regulate SERINC3 (p < 0.05 and q < 0.3), with 63% of these residues being in the N-terminal domain. CONCLUSION: Although SERINC3 down-regulation did not associate significantly with markers of HIV disease progression, our results nevertheless suggest that SERINC3 down-regulation contributes significantly to overall Nef function and fitness. The identification of Nef amino acids associated with differential SERINC3 down-regulation ability may be useful for rational design of therapeutics and vaccines targeting the Nef region.
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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 | 0.001 |
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".