Production of biologically active human interleukin‐4 in transgenic tobacco and potato
Bibliographic record
Abstract
Interleukin-4 (IL-4) is a pleiotropic cytokine that plays a key regulatory role in the immune system. Recombinant human IL-4 (rhIL-4) offers great potential for the treatment of cancer, viral and autoimmune diseases. Unfortunately, the high production cost of IL-4 associated with conventional expression systems has, until now, limited broader clinical testing, particularly with regard to the more convenient and safer oral delivery of IL-4 as opposed to parenteral injection in patients. In this study, we investigated the feasibility of transgenic plants for the cost-effective production of rhIL-4. IL-4 expression vectors with different modifications under the control of a constitutive cauliflower mosaic virus 35S (CaMV 35S) promoter were introduced into tobacco by Agrobacterium-mediated transformation. Transgenic tobaccos expressing various levels of rhIL-4 protein were generated. Higher expression was achieved through IL-4 retention in the endoplasmic reticulum (ER), with the maximal accumulation being approximately 0.1% of total soluble protein (TSP) in the leaves. No improvement in expression was further achieved by replacing the native signal peptide of IL-4 with the plant signal peptide. The best rhIL-4-expressing vector shown in tobacco was selected and further transferred into potato plants. The analysis of transgenic tubers also revealed various levels of rhIL-4, with the highest being 0.08% of TSP. Sensitive in vitro T-cell proliferation assays showed that plant-derived rhIL-4 retained full biological activity. These results suggest that plants can be used to produce biologically active rhIL-4 and probably many other mammalian proteins of medical significance. Moreover, the production of plants expressing rhIL-4 will enable the testing of plant rhIL-4 by oral delivery for the treatment of clinical diseases.
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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 | 0.001 |
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".