HIV-1 Subtypes and 5’LTR-Leader Sequence Variants Correlate with Seroconversion Status in Pumwani Sex Worker Cohort
Bibliographic record
Abstract
Within the Pumwani sex worker cohort, a subgroup remains seronegative, despite frequent exposure to HIV-1; some of them seroconverted several years later. This study attempts to identify viral variations in 5’LTR-leader sequences (5’LTR-LS) that might contribute to the late seroconversion. The 5’LTR-LS contains sites essential for replication and genome packaging, viz, primer binding site (PBS), major splice donor (SD), and major packaging signal (PS). The 5’LTR-LS of 20 late seroconverters (LSC) and 122 early seroconverters (EC) were amplified, cloned, and sequenced. HelixTree 6.4.3 was employed to classify HIV subtypes and sequence variants based on seroconversion status. We find that HIV-1 subtypes A1.UG and D.UG were overrepresented in the viruses infecting the LSC (P < 0.0001). Specific variants of PBS (Pc < 0.0001), SD1 (Pc < 0.0001), and PS (Pc < 0.0001) were present only in the viral population from EC or LSC. Combinations of PBS [PBS-2 (Pc < 0.0001) and PBS-3 (Pc < 0.0001)] variants with specific SD sequences were only seen in LSC or EC. Combinations of A1.KE or D with specific PBS and SD variants were only present in LSC or EC (Pc < 0.0001). Furthermore, PBS variants only present in LSC co-clustered with PBS references utilizing tRNAArg; whereas, the PBS variants identified only in EC co-clustered with PBS references using tRNALys3 and its variants. This is the first report that specific PBS, SD1, and PS sequence variants within 5’LTR-LS are associated with HIV-1 seroconversion, and it could aid designing effective anti-HIV strategies.
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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) | 0.002 | 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".