Purification of the recombinant green fluorescent protein from tobacco plants using alcohol/salt aqueous two-phase system and hydrophobic interaction chromatography
Bibliographic record
Abstract
BACKGROUND: The green fluorescent protein (GFP) has been regarded as a valuable tool and widely applied as a biomarker in medical applications and diagnostics. A cost-efficient upstream expression system and an inexpensive downstream purification process will meet the demands of the GFP protein with high-purity. RESULTS: The recombinant GFP was transiently expressed in an active form in agoinoculated Nicotiana benthamiana leaves by using Tobacco mosaic virus (TMV) RNA-based overexpression vector (TRBO). The yield of recombinant GFP was up to ~ 60% of total soluble proteins (TSP). Purification of recombinant GFP from the clarified lysate of N. benthaniana leaves was achieved by using an alcohol/salt aqueous two-phase system (ATPS) and following with a further hydrophobic interaction chromatography (HIC). The purification process takes only ~ 4 h and can recover 34.1% of the protein. The purity of purified GFP was more than 95% and there were no changes in its spectroscopic characteristics. CONCLUSIONS: The strategy described here combines the advantages of both the economy and efficiency of plant virus-based expression platform and the simplicity and rapidity of environmentally friendly alcohol/salt ATPS. It has a considerable potential for the development of a cost-efficient alternative for production of recombinant GFP.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.002 |
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".