Uncommon Pathways of Immune Escape Attenuate HIV-1 Integrase Replication Capacity
Bibliographic record
Abstract
An attenuation of the HIV-1 replication capacity (RC) has been observed for immune-mediated escape mutations in Gag restricted by protective HLA alleles. However, the extent to which escape mutations affect other viral proteins during natural infection is not well understood. We generated recombinant viruses encoding plasma HIV-1 RNA integrase sequences from antiretroviral-naïve individuals with early (n = 88) and chronic (n = 304) infections and measured the in vitro RC of each. In contrast to data from previous studies of Gag, we observed little evidence that host HLA allele expression was associated with integrase RC. A modest negative correlation was observed between the number of HLA-B-associated integrase polymorphisms and RC in chronic infection (R = -0.2; P = 0.003); however, this effect was not driven by mutations restricted by protective HLA alleles. Notably, the integrase variants S119R, G163E, and I220L, which represent uncommon polymorphisms associated with HLA-C*05, -A*33, and -B*52, respectively, correlated with lower RC (all q < 0.2). We identified a novel C*05-restricted epitope (HTDNGSNF(114-121)) that likely contributes to the selection of the S119R variant, the polymorphism most significantly associated with lower RC in patient sequences. An NL4-3 mutant encoding the S119R polymorphism displayed a ~35%-reduced function that was rescued by a single compensatory mutation of A91E. Together, these data indicate that substantial HLA-driven attenuation of integrase is not a general phenomenon during HIV-1 adaptation to host immunity. However, uncommon polymorphisms selected by HLA alleles that are not conventionally regarded to be protective may be associated with impaired protein function. Vulnerable epitopes in integrase might therefore be considered for future vaccine 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 | 0.000 |
| 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 | 0.001 |
| 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".