HIV Nef and Vpu protect HIV-infected CD4+ T cells from antibody-mediated cell lysis through down-modulation of CD4 and BST2
Bibliographic record
Abstract
BACKGROUND: HIV proteins Nef and Vpu down-modulate various host factors to evade immune defenses. Indeed, the CD4 receptor is down-regulated by Nef and Vpu, whereas virion-tethering BST2 is depleted by Vpu. Antibody-dependent cell-mediated cytotoxicity (ADCC) is increasingly recognized as a potentially powerful anti-HIV response. Given that epitopes which are specific for ADCC-competent anti-HIV antibodies are transitionally exposed upon CD4-mediated HIV entry, we investigated whether by depleting CD4 and BST2, HIV could negatively affect ADCC function. RESULTS: Using anti-envelope (Env) Abs A32 and 2G12 to trigger ADCC activity, we find that interactions between CD4 and Env within infected cells expose ADCC-targeted epitopes on cell-surface Env molecules, marking infected T cells for lysis by immune cells. We also provide evidence to show that by cross-linking nascent virions at the plasma membrane, hence increasing cell-surface Env density, BST2 further enhances the efficiency of this antiviral process. The heightened susceptibility of T cells infected with a virus lacking Nef and Vpu to ADCC was recapitulated when plasmas from HIV-infected patients were used as an alternative source of Abs. CONCLUSIONS: Our data unveil a mechanism by which HIV Nef and Vpu function synergistically to protect infected cells from ADCC and promote viral persistence. These findings also renew the potential practical relevance of ADCC function in vivo.
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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".