Association between gp120 envelope V1V2 and V4V5 variable loop profiles in a defined HIV-1 transmission cluster
Bibliographic record
Abstract
OBJECTIVE: Variations in the HIV-1 gp120 Env variable loop sequences correlate with virus phenotypes associated with transmission and/or disease progression. We aimed to identify whether signature sequences could be identified in the gp120 Env between acute infection and chronic infection viruses obtained from a group of individuals infected with closely related viruses. METHODS: To analyse acute infection versus chronic infection viruses, we studied a transmission cluster of 11 individuals, in which six presented during acute infection and five during chronic infection. Multiple HIV-1 gp120 Env clones were sequenced from each patient with predicted amino acid sequences compared between the groups. RESULTS: Cluster analysis of V1V5 Env sequences (n = 215) identified that acute infection viruses had lower potential N-linked glycosylation site (PNGS) densities than viruses from chronic infection, with a higher amino acid length/PNGS ratio. We found a negative correlation between the V1V2 and V4V5 regions for both amino acid length (Pearson P < 0.01) and PNGS numbers (Pearson P < 0.01) during HIV-1 transmission. This association was lost following seroconversion. These findings were confirmed by analysing sequences from the Los Alamos database that were selected and grouped according to timing of transmission. This included acute infection sequences collected 0-10 days (n = 400) and chronic infection sequences 0.5-3 years postseroconversion (n = 394). CONCLUSION: Our observations are consistent with a structural association between the V1V2 and V4V5 gp120 regions that is lost following viral transmission. These structural considerations should be taken into consideration when devising HIV-1 immunogens aimed at inducing protective antibody responses targeting transmitted viruses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".