Use of adenovirus protein IX (pIX) to display large polypeptides on the virion—generation of fluorescent virus through the incorporation of pIX-GFP
Bibliographic record
Abstract
The adenovirus (Ad) protein IX (pIX) is a minor component of the Ad capsid and associates with the hexons that make up the facets of the icosahedron. In this study, we investigated whether a large protein tag could be fused to pIX without compromising the Ad vector itself. As proof-of-principle, we generated a pIX-green fluorescent protein (GFP) fusion protein. We show that a virus encoding the pIX-GFP can be generated and that pIX-GFP fusion protein was incorporated into the Ad capsid as efficiently as native pIX. In tissue culture, translocation of Ad/pIX-GFP from the outside of the cell to the nucleus could be followed using fluorescence microscopy, and the timing of migration to the nucleus was similar to that previously reported for Ad. We also could track the virus after injection into the tibialis anterior muscle of mice. Shortly after injection, the majority of the Ad/pIX-GFP accumulated in pockets adjacent to the muscle fibers, with some migration of the virus between fibers. Our ability to attach GFP to the Ad virion, through fusion to pIX, provides a valuable tool for virus tracking in vitro and in vivo. Moreover, our data indicate that pIX can be used as a platform to anchor proteins to the Ad capsid, such as large ligands for cell-type-specific targeting of the vector.
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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".