HERV-K–specific T cells eliminate diverse HIV-1/2 and SIV primary isolates
Bibliographic record
Abstract
The genetic diversity of HIV-1 represents a major challenge in vaccine development. In this study, we establish a rationale for eliminating HIV-1-infected cells by targeting cellular immune responses against stable human endogenous retroviral (HERV) antigens. HERV DNA sequences in the human genome represent the remnants of ancient infectious retroviruses. We show that the infection of CD4+ T cells with HIV-1 resulted in transcription of the HML-2 lineage of HERV type K [HERV-K(HML-2)] and the expression of Gag and Env proteins. HERV-K(HML-2)-specific CD8+ T cells obtained from HIV-1-infected human subjects responded to HIV-1-infected cells in a Vif-dependent manner in vitro. Consistent with the proposed mode of action, a HERV-K(HML-2)-specific CD8+ T cell clone exhibited comprehensive elimination of cells infected with a panel of globally diverse HIV-1, HIV-2, and SIV isolates in vitro. We identified a second T cell response that exhibited cross-reactivity between homologous HIV-1-Pol and HERV-K(HML-2)-Pol determinants, raising the possibility that homology between HIV-1 and HERVs plays a role in shaping, and perhaps enhancing, the T cell response to HIV-1. This justifies the consideration of HERV-K(HML-2)-specific and cross-reactive T cell responses in the natural control of HIV-1 infection and for exploring HERV-K(HML-2)-targeted HIV-1 vaccines and immunotherapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".