Simplified cloning and isolation of peptides from “sandwiched” SUMO-peptide-intein fusion proteins
Bibliographic record
Abstract
Abstract Background Some peptides are targets for degradation when heterologously expressed as fusion proteins inE. coli, which can limit yields after isolation and purification. We recently reported that peptide degradation may be prevented by production of a “sandwiched” SUMO-peptide-intein (SPI) fusion protein, which protects the target peptide sequence from truncation and improves yield. This initial system required cloning with two commercially available vectors. It used an N-terminal polyhistidine tagged small ubiquitin-like modifier (SUMO) protein and a C-terminal engineeredMycobacterium xenopiiDNA Gyrase A intein with an inserted chitin binding domain (CBD) to create “sandwiched” fusion proteins of the form: His6-SUMO-peptide-intein-CBD. However, the major drawback of this previously reported fusion protein “sandwich” approach is the increased time and number of steps required to complete the cloning and isolation procedures, relative to the simple procedures to produce recombinant peptides inE. colifrom a single (non-“sandwiched”) fusion protein system. Results In this work we generate the plasmid pSPIH6, which improves upon the previous system by encoding both the SUMO and intein proteins and allows facile construction of a SPI protein in a single cloning step. Additionally, theMxeGyrA intein encoded in pSPIH6 contains a C-terminal polyhistidine tag, resulting in SPI fusion proteins of the form: His6-SUMO-peptide-intein-CBD-His6. The dual polyhistidine tags greatly simplify isolation procedures compared to the original SPI system, which we have here demonstrated with two linear bacteriocin peptides: leucocin A and lactococcin A. The yields obtained for both peptides after purification were also improved compared to the previous SPI system as a result of this streamlined protocol. Conclusions This modified SPI system and its simplified cloning and purification procedures described here may be generally useful as a heterologousE. coliexpression system to obtain pure peptides in high yield, especially when degradation of the target peptide is an issue.
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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".