Characterization of a highly potent antimicrobial peptide microcin N from uropathogenic<i>Escherichia coli</i>
Bibliographic record
Abstract
Microcin N is a low-molecular weight, highly active antimicrobial peptide produced by uropathogenic Escherichia coli In this study, the native peptide was expressed and purified from pGOB18 plasmid carrying E. coli in low yield. The pure peptide was characterized using mass spectrometry, N-terminal sequencing by Edman degradation as well as trypsin digestion. We found that the peptide is 74-residue long, cationic (+2 total charge), highly hydrophobic and consists of glycine as the first N-terminal residue. The minimum inhibitory concentration of the peptide against Salmonella enteritidis was found to be 150 nM. Evaluation of the solution conformation of the peptide using circular dichroism spectroscopy showed that the peptide is well folded in 40% trifluoroethanol with helical structure whereas the folded structure is lost in aqueous solution. To increase the yield of this potent peptide, we overexpressed GST-tagged microcin N using E. coli BL21. Recombinant GST-tagged microcin N was successfully expressed in E. coli BL21; however, the cleaved mature microcin N did not show activity against the indicator strain (S. enterica) most likely due to the extreme hydrophobic nature of the peptide. Efforts to produce active microcin N in large scale are discussed as this peptide has huge potential to be the next generation antimicrobial agent.
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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 | 0.000 |
| 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 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".