A V106M mutation in HIV-1 clade C viruses exposed to efavirenz confers cross-resistance to non-nucleoside reverse transcriptase inhibitors
Bibliographic record
Abstract
OBJECTIVE: We have shown that HIV-1 clade C variants contain a valine codon 106 polymorphism (GTG) that facilitates a V106M transition (GTG<--ATG) after selection with efavirenz (EFV). This study evaluates the prevalence of V106 (GTG) and 106M (ATG) codons in clinical isolates as well as the effects of V106M on resistance to non-nucleoside reverse transcriptase inhibitors (NNRTI). METHODS: Genotypic analysis ascertained sequence diversity at codon 106, including both valine polymorphisms (GTA and GTG) and the V106A (GCA) and V106M (ATG) resistance-conferring mutations in B (n = 440) and non-B (n = 84) clinical isolates. Cell-based phenotypic assays were performed to determine the effects of V106M and V106A on levels of resistance to EFV, nevirapine and delavirdine. RESULTS: Most subtype B isolates harbored GTA (valine) at codon 106 (97% of cases) while the GTG (valine) polymorphism was generally present in clade C viruses (94% of cases). Under conditions of EFV but not nevirapine or delavirdine pressure (n = 8) in tissue culture, clade C isolates developed the V106M mutation (GTG<--ATG), conferring high-level (100-1000-fold) cross-resistance to all NNRTI. Generation of V106M recombinant viruses by site-directed mutagenesis confirmed the ability of V106M to confer NNRTI cross-resistance. This mutation also developed in three of six EFV-treated patients harboring clade C infections. In current genotypic interpretative reports (including 15 algorithmic databases), V106A is listed as an nevirapine-specific mutation while V106M is not recognized. CONCLUSIONS: V106M may be a signature mutation in clade C patients treated with EFV and may have the potential to confer high-level multi-NNRTI resistance.
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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".