Impact of the compensation effect on the production of recombinant CD81-functionalized HIV-1 Gag virus-like particles and extracellular vesicles in HEK293 cells
Bibliographic record
Abstract
CD81 is a membrane protein of the tetraspanin family present in the tetraspanin-enriched microdomains (TEMs). CD81 is incorporated in the surface of both Human Immunodeficiency Virus type 1 (HIV-1) virions and extracellular vesicles (EVs). Using this feature a recombinant CD81 variant, incorporating a hexahistidine tag (His-tag) within its variable region, was designed to enable surface peptide display in HIV-1 Gag::eGFP virus-like particles (VLPs) and EVs. Immunofluorescence and immunogold analyses confirmed the correct localization of CD81-His-tag in the plasma membrane and its incorporation into both VLPs and EVs. However, co-expression of CD81-His-tag with Gag::eGFP led to a significant reduction (6.8-fold) in Gag::eGFP VLP production, that could be attributed to the overexpression burden associated to the co-expression of two recombinant proteins through transient transfection. Additionally, to study the compensation effect on the production and functionalization of VLPs and EVs, shRNA-mediated knockdowns were performed targeting proteins known to interact with CD81 in TEMs, including CD9, CD63, EWI-2, and EWI-F. The compensation effect on CD81-His-tag caused by shCD9 and shCD81-WT knockdowns allowed to maintain the levels of CD81-His-tag per particle while increasing particle production. These findings contribute to the development of engineered vesicles as platforms for peptide display in drug delivery, vaccines, and therapeutic applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".