The HIV-1 accessory proteins Nef and Vpu downregulate total and cell surface CD28 in CD4+ T cells
Bibliographic record
Abstract
The HIV-1 accessory proteins Nef and Vpu alter cell surface levels of multiple host proteins to modify the immune response and increase viral persistence. Nef and Vpu can downregulate cell surface levels of the co-stimulatory molecule CD28, however the mechanism of this function has not been completely elucidated. Here, we provide evidence that Nef and Vpu decrease cell surface and total cellular levels of CD28. Moreover, using inhibitors we implicate the cellular degradation machinery in the downregulation of CD28. We shed light on the mechanisms of CD28 downregulation by implicating the Nef LL 165 and DD 175 motifs in decreasing cell surface CD28 and Nef DD 175 in decreasing total cellular CD28. Moreover, the Vpu LV 64 and S 52/56 motifs were required for cell surface CD28 downregulation, while, unlike for CD4 downregulation, Vpu W 22 was dispensable. The Vpu S 52/56 motif was also critical for Vpu-mediated decreases in total CD28 protein level. Finally, the ability of Vpu to downregulate CD28 is conserved between multiple group M Vpu proteins and infection with viruses encoding or lacking Nef and Vpu have differential effects on activation upon stimulation. We report that Nef and Vpu downregulate cell surface and total cellular CD28 levels. We identified inhibitors and mutations within Nef and Vpu that disrupt downregulation, shedding light on the mechanisms utilized to downregulate CD28. The conservation and redundancy between the abilities of two HIV-1 proteins to downregulate CD28 highlight the importance of this function, which may contribute to the development of latently infected cells.
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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".