Sublethal Concentrations of Pleurocidin-Derived Antimicrobial Peptides Inhibit Macromolecular Synthesis in <i>Escherichia coli</i>
Bibliographic record
Abstract
Cationic bactericidal peptides are components of natural host defenses against infections. While the mode of antibacterial action of cationic peptides remains controversial, several targets, including the cytoplasmic membrane and macromolecular synthesis, have been identified for peptides acting at high concentrations. The present study identified peptide effects at lower, near-lethal inhibitory concentrations. An amidated hybrid of the flounder pleurocidin and the frog dermaseptin (P-Der), two other pleurocidin derivatives, and pleurocidin itself were studied. At 2 microg/ml, the MIC, P-Der inhibited Escherichia coli growth in a broth dilution assay but did not cause bacterial death within 30 min, as estimated by viable count analysis. Consistent with this, P-Der demonstrated a weak ability to permeabilize membranes but was able to translocate across the lipid bilayer of unilamellar liposomes. Doses of 20 microg/ml or more reduced bacterial viable counts by about 2 log orders of magnitude within 5 min after peptide treatment. Abrupt loss of cell membrane potential, observed with a fluorescent dye, dipropylthiacarbocyanine, paralleled bacterial death but did not occur at the sublethal, inhibitory concentrations. Both lethal and sublethal concentrations of P-Der affected macromolecular synthesis within 5 min, as demonstrated by incorporation of [3H]thymidine, [3H]uridine, and [3H]histidine, but the effects were qualitatively distinct at the two concentrations. Variations of the inhibition pattern described above were observed for pleurocidin and two other derivatives. Our results indicate that peptides at their lowest inhibitory concentrations may be less capable of damaging cell membranes, while they maintain their ability to inhibit macromolecular synthesis. Better understanding of the effects of peptides acting at their MICs will contribute to the design of new peptides effective at lower, less toxic concentrations.
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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) | 0.001 | 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".