Protein body formation in stable transgenic tobacco expressing elastin-like polypeptide and hydrophobin fusion proteins
Bibliographic record
Abstract
BACKGROUND: Plants are recognized as an efficient and inexpensive system to produce valuable recombinant proteins. Two different strategies have been commonly used for the expression of recombinant proteins in plants: transient expression mediated by Agrobacterium; or stable transformation of the plant genome. However, the use of plants as bioreactors still faces two main limitations: low accumulation levels of some recombinant proteins and lack of efficient purification methods. Elastin-like polypeptide (ELP), hydrophobin I (HFBI) and Zera® are three fusion partners found to increase the accumulation levels of recombinant proteins and induce the formation of protein bodies (PBs) in leaves when targeted to the endoplasmic reticulum (ER) in transient expression assays. In this study the effects of ELP and HFBI fusion tags on recombinant protein accumulation levels and PB formation was examined in stable transgenic Nicotiana tabacum. RESULTS: The accumulation of recombinant protein and PB formation was evaluated in two cultivars of Nicotiana tabacum transformed with green fluorescent protein (GFP) fused to ELP or HFBI, both targeted and retrieved to the ER. The ELP and HFBI tags increased the accumulation of the recombinant protein and induced the formation of PBs in leaves of stable transgenic plants from both cultivars. Furthermore, these tags induced the formation of PBs in a concentration-dependent manner, where a specific level of recombinant protein accumulation was required for PBs to appear. Moreover, agro-infiltration of plants accumulating low levels of recombinant protein with p19, a suppressor of post-transcriptional gene silencing (PTGS), increased accumulation levels in four independent transgenic lines, suggesting that PTGS might have caused the low accumulation levels in these plants. CONCLUSION: The use of ELP and HFBI tags as fusion partners in stable transgenic plants of tobacco is feasible and promising. In a constitutive environment, these tags increase the accumulation levels of the recombinant protein and induce the formation of PBs regardless of the cultivar used. However, a specific level of recombinant protein accumulation needs to be reached for PBs to form.
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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".