Modulation of NKG2D-Mediated Cytotoxic Functions of Natural Killer Cells by Viral Protein R from HIV-1 Primary Isolates
Bibliographic record
Abstract
HIV-1 viral protein R (Vpr) from laboratory-adapted virus strains activates the DNA damage/stress sensor ATR kinase and induces cell cycle arrest at the G(2)/M phase through a process that requires Vpr to engage the DDB1-CUL4A (VprBP/DCAF-1) E3 ligase complex. Activation of this DNA damage/stress checkpoint in G(2) by Vpr was shown to modulate NKG2D-dependent NK cell effector functions via enhancing expression of NKG2D ligands, notably ULBP2. However, it is unknown whether Vpr from HIV-1 primary isolates (groups M, N, O, and P) could modulate NKG2D-mediated cytotoxic functions of NK cells. Here, we report that Vpr from most HIV-1 primary isolates can upregulate ULBP2 expression and induce NKG2D-dependent NK cell killing. Importantly, these activities were always accompanied by an active G(2) cell cycle arrest function. Interestingly, Vpr variants from group P and a clade D isolate of group M were defective at enhancing NKG2D-mediated NK cell lysis owing to their inability to augment ULBP2 expression. However, distinct mechanisms were responsible for their failure to do so. While Vpr from group P was deficient in its ability to engage the DDB1-CUL4A (VprBP/DCAF-1) E3 ligase complex, the Vpr variant from group D was unable to properly localize to the nucleus, underlining the importance of these biological properties in Vpr function. In conclusion, the ability of Vpr from HIV-1 primary isolates to regulate NK cell effector function underscores the importance of this HIV-1 accessory protein in the modulation of the host's innate immune responses.
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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 | 0.000 |
| 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".