SPI “sandwich”: Combined <scp>SUMO‐Peptide‐Intein</scp> expression system and isolation procedure for improved stability and yield of peptides
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Recombinant peptide production in Escherichia coli is often accomplished through cloning and expression of a fusion protein. The fusion protein partner generally has two requirements: (a) it contains an affinity tag to assist with purification and (b) it can be cleaved off to leave only the desired peptide sequence behind. Common soluble fusion partners include small ubiquitin‐like modifier protein (SUMO), maltose‐binding protein (MBP), glutathione S‐transferase (GST), or intein proteins. However, heterologously expressed peptides can suffer from proteolytic degradation or instability. This degradation can pose a major issue for applications requiring a large amount of purified peptide, such as NMR structural assignments or biochemical assays. Improving peptide yield by testing various expression and isolation conditions requires a significant amount of effort and may not lead to improved results. Here, we cloned and expressed four different peptides as SUMO fusion proteins. These peptides (lactococcin A, leucocin A, faerocin MK, neopetrosiamide A) were truncated during expression and isolation as SUMO fusions, resulting in low yields of purified peptide. To prevent this degradation and improve yield, we designed a new expression system to create a “sandwiched” fusion protein of the form: His 6 ‐SUMO‐peptide‐intein (SPI). These sandwiched peptides were more stable and protected against degradation, resulting in improved yields (up to 17‐fold) under a set of standard expression and isolation procedures. This SPI expression system uses only two commercially available vectors and standard protein purification techniques, and therefore may offer an economical and facile route to improve yields for peptides that undergo degradation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it