The Polymorphic Nature of HIV Type 1 <i>env</i> V4 Affects the Patterns of Potential N-Glycosylation Sites in Proviral DNA at the Intrahost Level
Bibliographic record
Abstract
We have previously shown that env V4 from HIV-1 plasma RNA is highly heterogeneous within a single patient, due to indel-associated polymorphism. In this study, we have analyzed the variability of V4 in proviral DNA from unfractionated PBMC and sorted T and non-T cell populations within individual patients. Our data show that the degree of sequence variability and length polymorphism in V4 from HIV provirus is even higher than we previously reported in plasma. The data also show that the sequence of V4 depends largely on the experimental approach chosen. We could observe no clear trend for compartmentalization of V4 variants in specific cell types. Of interest is the fact that some variants that had been found to be predominant in plasma were not detected in any of the cell subsets analyzed. Consistently with our observations in plasma, V3 was found to be relatively conserved at both interpatient and intrapatient level. Our data show that V4 polymorphism involving insertions and deletions in addition to point mutations results in changes in the patterns of sequons in HIV-1 proviral DNA as well as in plasma RNA. These rearrangements may result in the coexistence, within the same individual, of a swarm of different V4 regions, each characterized by a different carbohydrate surface shield. Further studies are needed to investigate the mechanism responsible for the variability observed in V4 and its role in HIV pathogenesis.
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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 | 0.000 | 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".