Plant recombinant erythropoietin attenuates inflammatory kidney cell injury
Bibliographic record
Abstract
Human erythropoietin (EPO) is a pleiotropic cytokine with remarkable tissue-protective activities in addition to its well-established role in red blood cell production. Unfortunately, conventional mammalian cell cultures are unlikely to meet the anticipated market demands for recombinant EPO because of limited capacity and high production costs. Plant expression systems may address these limitations to enable practical, cost-effective delivery of EPO in tissue injury prevention therapeutics. In this study, we produced human EPO in tobacco and demonstrated that plant-derived EPO had tissue-protective activity. Our results indicated that targeting to the endoplasmic reticulum (ER) provided the highest accumulation levels of EPO, with a yield approaching 0.05% of total soluble protein in tobacco leaves. The codon optimization of the human EPO gene for plant expression had no clear advantage; furthermore, the human EPO signal peptide performed better than a tobacco signal peptide. In addition, we found that glycosylation was essential for the stability of plant recombinant EPO, whereas the presence of an elastin-like polypeptide fusion had a limited positive impact on the level of EPO accumulation. Confocal microscopy showed that apoplast and ER-targeted EPO were correctly localized, and N-glycan analysis demonstrated that complex plant glycans existed on apoplast-targeted EPO, but not on ER-targeted EPO. Importantly, plant-derived EPO had enhanced receptor-binding affinity and was able to protect kidney epithelial cells from cytokine-induced death in vitro. These findings demonstrate that tobacco plants may be an attractive alternative for the production of large amounts of biologically active EPO.
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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".