HIV‐1 Vpu Antagonizes BST‐2 by Interfering Mainly with the Trafficking of Newly Synthesized BST‐2 to the Cell Surface
Bibliographic record
Abstract
Bone marrow stromal cell antigen-2 (BST-2) inhibits human immunodeficiency virus type 1 (HIV-1) release by cross-linking nascent virions on infected cell surface. HIV-1 Vpu is thought to antagonize BST-2 by downregulating its surface levels via a mechanism that involves intracellular sequestration and lysosomal degradation. Here, we investigated the functional importance of cell-surface BST-2 downregulation and the BST-2 pools targeted by Vpu using an inducible proviral expression system. Vpu established a surface BST-2 equilibrium at ∼60% of its initial levels within 6 h, a condition that coincided with detection of viral release. Analysis of BST-2 post-endocytic trafficking revealed that the protein is engaged in a late endosomal pathway independent of Vpu. While Vpu moderately enhanced cell-surface BST-2 clearance, it strongly affected the protein resupply to the plasma membrane via newly synthesized proteins. Noticeably, Vpu affected clearance of surface BST-2 more substantially in Jurkat T cells than in HeLa cells, suggesting a cell-dependent impact of Vpu on the pool of surface BST-2. Collectively, our data reveal that Vpu imposes a new BST-2 equilibrium, incompatible with efficient restriction of HIV-1 release, by combining an acceleration of surface BST-2 natural clearance, whose degree might be cell-type dependent, to a severe impairment of the protein resupply to the plasma membrane.
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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".