Vaccination against Endogenous Retrotransposable Element Consensus Sequences Does Not Protect Rhesus Macaques from SIVsmE660 Infection and Replication
Bibliographic record
Abstract
The enormous sequence diversity of HIV remains a major roadblock to the development of a prophylactic vaccine and new approaches to induce protective immunity are needed. Endogenous retrotransposable elements (ERE) such as endogenous retrovirus K (ERV)-K and long interspersed nuclear element-1 (LINE-1) are activated during HIV-1-infection and could represent stable, surrogate targets to eliminate HIV-1-infected cells. Here, we explored the hypothesis that vaccination against ERE would protect macaques from acquisition and replication of simian immunodeficiency virus (SIV). Following vaccination with antigens derived from LINE-1 and ERV-K consensus sequences, animals mounted immune responses that failed to delay acquisition of SIVsmE660. We observed no differences in acute or set point viral loads between ERE-vaccinated and control animals suggesting that ERE-specific responses were not protective. Indeed, ERE-specific T cells failed to expand anamnestically in vivo following infection with SIVsmE660 and did not recognize SIV-infected targets in vitro, in agreement with no significant induction of targeted ERE mRNA by SIV in macaque CD4+ T cells. Instead, lower infection rates and viral loads correlated significantly to protective TRIM5α alleles. Cumulatively, these data demonstrate that vaccination against the selected ERE consensus sequences in macaques did not lead to immune-mediated recognition and killing of SIV-infected cells, as has been shown for HIV-infected human cells using patient-derived HERV-K-specific T cells. Thus, further research is required to identify the specific nonhuman primate EREs and retroviruses that recapitulate the activity of HIV-1 in human cells. These results also highlight the complexity in translating observations of the interplay between HIV-1 and human EREs to animal models.
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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 | 0.001 | 0.001 |
| 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".