Identification and Characterization of Positively Selected Mutations in Nef of Four HIV-1 Major Subtypes from Los Alamos National Laboratory
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus-1 (HIV-1) mutates rapidly to escape host immune pressure. This results in the generation of positively selected mutations (PSM) throughout the viral genome. Escape mutations in Nef, one of the accessory proteins of HIV-1, which plays an important role in viral pathogenicity have previously been identified in several large cohort studies, but the evolution of PSMs overtime in various HIV-1 subtypes remains unknown. METHODS: 161 clade A1, 3093 clade B, 647 clade C and 115 clade D HIV-1 nef sequences were obtained from the HIV Database of Los Alamos National Laboratory and aligned using MEGA 6.0. The sequences from each clade were grouped based on the year of collection. Quasi analysis was used to identify PSMs and the number and locations of PSMs were compared among different subtypes. RESULTS: PSMs for all four subtypes were distributed across the sequence of Nef, and conserved residues F90, W113, PxxPxR (a.a 72-77) remain unaltered overtime. The frequency of PSMs was stable among subtype B sequences but increased overtime for other subtypes. Phylogenetic analysis shows that sequences containing PSMs tend to cluster together at both inter and intra- subtype levels. CONCLUSION: Identification of PSMs and their changes overtime within various subtypes of HIV-1 is important in defining global viral evolutionary patterns that can provide insights for designing therapeutic 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".