Fusion order controls expression level and activity of elastin‐like polypeptide fusion proteins
Bibliographic record
Abstract
We have previously developed a method to purify recombinant proteins, termed inverse transition cycling (ITC) that eliminates the need for column chromatography. ITC exploits the inverse solubility phase transition of an elastin-like polypeptide (ELP) that is fused to a protein of interest. In ITC, a recombinant ELP fusion protein is cycled through its phase transition, resulting in separation of the ELP fusion protein from other Escherichia coli contaminants. Herein, we examine the role of the position of the ELP in the fusion protein on the expression levels and yields of purified protein for four recombinant ELP fusion proteins. Placing the ELP at the C-terminus of the target protein (protein-ELP) results in a higher expression level for the four ELP fusion proteins, which also translates to a greater yield of purified protein. The position of the fusion protein also has a significant impact on its specific activity, as ELP-protein constructs have a lower specific activity than protein-ELP constructs for three out of the four proteins. Our results show no difference in mRNA levels between protein-ELP and ELP-protein fusion constructs. Instead, we suggest two possible explanations for these results: first, the translational efficiency of mRNA may differ between the fusion protein in the two orientations and second, the lower level of protein expression and lower specific activity is consistent with a scenario that placement of the ELP at the N-terminus of the fusion protein increases the fraction of misfolded, and less active conformers, which are also preferentially degraded compared to fusion proteins in which the ELP is present at the C-terminal end of the protein.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".