Engineering E. coli cell surface in order to develop a one-step purification method for recombinant proteins
Bibliographic record
Abstract
Sortases are enzymes mostly found in Gram-positive bacteria which cleave proteins site-specifically. This feature makes them a promising tool in molecular biology and biotechnology. In this study, using bacterial surface display of recombinant proteins and ability of sortase A in site-specifically cleavage of the amino acid sequences, a novel method for one-step purification of recombinant proteins was developed. Using computational program tools, a chimeric protein containing a metallothionein (mt) and chitin binding domain (ChBD) was attached to the C-terminal domain of the truncated outer membrane protein A (Lpp'-ompA) using sortase recognition site (amino acid residues: LPQTG) as a separator. The structure of the chimeric protein was simulated using molecular dynamics to determine if the LPQTG motif is accessible to the sortase active site. The designed chimeric protein was expressed and purified. The purified chimeric protein was also displayed on the surface of E. coli cells. Both purified chimeric protein and the E. coli cells displaying Lpp'-ompA-mt-ChBD carrier protein were then treated with sortase to evaluate the efficiency of sortase-mediated cleavage of purified chimeric protein as well as surface displayed-chimeric protein. It is shown that mt-ChBD protein was successfully cleaved and dissociated from Lpp'-ompA carrier and released into the medium after treatment with sortase in both recombinant protein and surface displayed-chimeric protein. The experimental results confirmed the molecular dynamics analysis results. The presented method could be regarded as a novel strategy for one step expression and purification of recombinant proteins.
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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".