An anionic human protein mediates cationic liposome delivery of genome editing proteins into mammalian cells
Bibliographic record
Abstract
Delivery into mammalian cells remains a significant challenge for many applications of proteins as research tools and therapeutics. We recently reported that the fusion of cargo proteins to a supernegatively charged (-30)GFP enhances encapsulation by cationic lipids and delivery into mammalian cells. To discover polyanionic proteins with optimal delivery properties, we evaluate negatively charged natural human proteins for their ability to deliver proteins into cultured mammalian cells and human primary fibroblasts. Here we discover that ProTα, a small, widely expressed, intrinsically disordered human protein, enables up to ~10-fold more efficient cationic lipid-mediated protein delivery compared to (-30)GFP. ProTα enables efficient delivery at low- to mid-nM concentrations of two unrelated genome editing proteins, Cre recombinase and zinc-finger nucleases, under conditions in which (-30)GFP fusion or cationic lipid alone does not result in substantial activity. ProTα may enable mammalian cell protein delivery applications when delivery potency is limiting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".