HIV-1 strains belonging to large phylogenetic clusters show accelerated escape from integrase inhibitors in cell culture compared with viral isolates from singleton/small clusters
Bibliographic record
Abstract
Objectives: Viral phylogenetics revealed two patterns of HIV-1 spread among MSM in Quebec. While most HIV-1 strains ( n = 2011) were associated with singleton/small clusters (cluster size 1-4), 30 viral lineages formed large networks (cluster size 20-140), contributing to 42% of diagnoses between 2011 and 2015. Herein, tissue culture selections ascertained if large cluster lineages possessed higher replicative fitness than singleton/small cluster isolates, allowing for viral escape from integrase inhibitors. Methods: Primary HIV-1 isolates from large 20+ cluster ( n = 11) or singleton/small cluster ( n = 6) networks were passaged in vitro in escalating concentrations of dolutegravir, elvitegravir and lamivudine for 24-36 weeks. Sanger and deep sequencing assessed genotypic changes under selective drug pressure. Results: Large cluster HIV-1 isolates selected for resistance to dolutegravir, elvitegravir and lamivudine faster than HIV-1 strains forming small clusters. With dolutegravir, large cluster HIV-1 variants acquired solitary R263K ( n = 7), S153Y ( n = 1) or H51Y ( n = 1) mutations as the dominant quasi-species within 8-12 weeks as compared with small cluster lineages where R263K ( n = 1/6), S153Y (1/6) or WT species (4/6) were observed after 24 weeks. Interestingly, dolutegravir-associated mutations compromised viral replicative fitness, precluding escalations in concentrations beyond 5-10 nM. With elvitegravir, large cluster variants more rapidly acquired first mutations (T66I, A92G, N155H or S147G) by week 8 followed by sequential accumulation of multiple mutations leading to viral escape (>10 μM) by week 24. Conclusions: Further studies are needed to understand virological features of large cluster viruses that may favour their transmissibility, replicative competence and potential to escape selective antiretroviral drug pressure.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".