Targeted expression, purification, and cleavage of fusion proteins from inclusion bodies in <i>Escherichia coli</i>
Bibliographic record
Abstract
Today, proteins are typically overexpressed using solubility-enhancing fusion tags that allow for affinity chromatographic purification and subsequent removal by site-specific protease cleavage. In this review, we present an alternative approach to protein production using fusion partners specifically designed to accumulate in insoluble inclusion bodies. The strategy is appropriate for the mass production of short peptides, intrinsically disordered proteins, and proteins that can be efficiently refolded in vitro. There are many fusion protein systems now available for insoluble expression: TrpLE, ketosteroid isomerase, PurF, and PagP, for example. The ideal fusion partner is effective at directing a wide variety of target proteins into inclusion bodies, accumulates in large quantities in a highly pure form, and is readily solubilized and purified in commonly used denaturants. Fusion partner removal under denaturing conditions is biochemically challenging, requiring harsh conditions (e.g., cyanogen bromide in 70% formic acid) that can result in unwanted protein modifications. Recent advances in metal ion-catalyzed peptide bond cleavage allow for more mild conditions, and some methods involving nickel or palladium will likely soon appear in more biological applications.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".