BST-2 Expression Modulates Small CD4-Mimetic Sensitization of HIV-1-Infected Cells to Antibody-Dependent Cellular Cytotoxicity
Bibliographic record
Abstract
ABSTRACT Antibodies recognizing conserved CD4-induced (CD4i) epitopes on human immunodeficiency virus type 1 (HIV-1) Env and able to mediate antibody-dependent cellular cytotoxicity (ADCC) have been shown to be present in sera from most HIV-1-infected individuals. These antibodies preferentially recognize Env in its CD4-bound conformation. CD4 downregulation by Nef and Vpu dramatically reduces exposure of CD4i HIV-1 Env epitopes and therefore reduce the susceptibility of HIV-1-infected cells to ADCC mediated by HIV-positive (HIV+) sera. Importantly, this mechanism of immune evasion can be circumvented with small-molecule CD4 mimetics (CD4mc) that are able to transition Env into the CD4-bound conformation and sensitize HIV-1-infected cells to ADCC mediated by HIV+ sera. However, HIV-1 developed additional mechanisms to avoid ADCC, including Vpu-mediated BST-2 antagonism, which decreases the overall amount of Env present at the cell surface. Accordingly, BST-2 upregulation in response to alpha interferon (IFN-α) was shown to increase the susceptibility of HIV-1-infected cells to ADCC despite the activity of Vpu. Here we show that BST-2 upregulation by IFN-β and interleukin-27 (IL-27) also increases the surface expression of Env and thus boosts the ability of CD4mc to sensitize HIV-1-infected cells to ADCC by sera from HIV-1-infected individuals. IMPORTANCEHIV-1 evolved sophisticated strategies to conceal Env epitopes from ADCC-mediating antibodies present in HIV+ sera. Vpu-mediated BST-2 downregulation was shown to decrease ADCC responses by limiting the amount of Env present at the cell surface. This effect of Vpu was shown to be attenuated by IFN-α treatment. Here we show that in addition to IFN-α, IFN-β and IL-27 also affect Vpu-mediated BST-2 downregulation and greatly enhance ADCC responses against HIV-1-infected cells in the presence of CD4mc. These findings may inform strategies aimed at HIV prevention and eradication.
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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".