HIV-1 Subtype Variability in Vif Derived from Molecular Clones Affects APOBEC3G-Mediated Host Restriction
Bibliographic record
Abstract
BACKGROUND: The host protein APOBEC3G (A3G) can limit HIV-1 replication. Its protective effect is overcome by the HIV-1 'viral infectivity factor' (Vif), which targets A3G for proteosomal degradation. Although Vif is considered to be essential for HIV-1 replication, the effect of Vif variability among commonly used HIV-1 molecular clones of different genetic backgrounds on viral infectiousness and pathogenesis has not been fully determined. METHODS: We cloned the intact Vif coding regions of available molecular clones of different subtypes into expression vectors. Δvif full-length HIV-1 clonal variants were generated from corresponding subtype-specific full-length molecular clones. Replication-competent viruses were produced in 293T cells in the presence or absence of A3G, with Vif being supplied by the full-length HIV-1 clone or in trans. The extent of A3G-mediated restriction was then determined in a viral replication assay using a reporter cell line. RESULTS AND CONCLUSIONS: In the absence of A3G, Vif subtype origin did not impact viral replication. In the presence of A3G the subtype origin of Vif had a differential effect on viral replication. Vif derived from a subtype C molecular clone was less effective at overcoming A3G-mediated inhibition than Vif derived from either subtype B or CRF02_AG molecular clones.
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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 | 0.001 |
| 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".