Targeted Cell-to-Cell Delivery of Protein Payloads via the Granzyme-Perforin Pathway
Bibliographic record
Abstract
There is great potential for engineering cellular therapeutics by repurposing biological systems. Here, we report utilization of the granzyme-perforin pathway of cytotoxic lymphocytes as a cell-to-cell protein delivery module. We designed and constructed granzyme B-derived chaperone molecules fused to a fluorescent protein payload and expressed these constructs in natural killer (NK) cells. Using confocal microscopy and flow cytometry, we investigated the co-localization of the chaperones with lytic granules and the chaperone-mediated transfer of the fluorescent protein payload from NK to target cells in co-culture experiments. A synthetic chaperone consisting of the granzyme B ER signal peptide and a domain encompassing putative N-linked glycosylation sites in granzyme B is insufficient for payload transfer to target cells, whereas full-length granzyme B is sufficient for payload delivery. Combining our functional data with an analysis of the crystal structure of granzyme B suggests that the necessary motifs for granzyme B loading into lytic granules are dispersed throughout the primary amino acid sequence and are only functional when contiguous in the tertiary structure. These results illustrate that by using granzyme B as a molecular chaperone the granzyme-perforin pathway can be exploited as a programmable molecular delivery system for cell-based therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".