HIV-1 Group O Resistance Against Integrase Inhibitors
Bibliographic record
Abstract
BACKGROUND: HIV-1 group O (HIV-O) is a rare variant that is characterized by a high number of natural polymorphisms in the integrase coding region that may impact on susceptibility to integrase strand transfer inhibitors (INSTIs) and on the emergence of resistance substitutions. We previously reported that HIV-O is more susceptible to RAL than HIV-1 group M (HIV-M). METHODS: The aim of this study was to assess pathways of resistance to INSTIs in group 0 variants. Accordingly, we selected for resistance to each of raltegravir (RAL), elvitegravir (EVG), and dolutegravir (DTG) in cord blood mononuclear cells using HIV group O subtypes A and B, an HIV-O divergent isolate, and HIV-1 group M (subtype B, which served as a reference). Site-directed mutagenesis was performed on the pCOM2.5 HIV group 0 infectious clone to ascertain the impact of INSTI resistance substitutions at positions Q148R, N155H, and R263K within integrase on susceptibility to INSTIs and infectiousness. RESULTS: Cell culture selections of group O variants yielded similar patterns of resistance to RAL, EVG, and DTG as observed for subtype B. In the DTG selections, subtype B yielded S153Y, whereas a natural S153A polymorphism sometimes led to A153V in group O. The pCMO2.5/Q148R and pCMO2.5/N155H variants displayed far higher levels of resistance to DTG (>1000 FC) than was seen for group M viruses. CONCLUSIONS: HIV-O harboring Q148R and N155H shows higher resistance to DTG compared with HIV-M subtype B.
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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".