Bacterial species selective toxicity of two isomeric α/β-peptides: Role of membrane lipids
Bibliographic record
Abstract
We have studied how membrane interactions of two synthetic cationic antimicrobial peptides with alternating alpha- and beta-amino acid residues ("alpha/beta-peptides") impact toxicity to different prokaryotes. Electron microscopic examination of thin sections of Escherichia coli and of Bacillus subtilis exposed to these two alpha/beta-peptides reveals different structural changes in the membranes of these bacteria. These two peptides also have very different effects on the morphology of liposomes composed of phosphatidylethanolamine and phosphatidylglycerol in a 2:1 molar ratio. Freeze fracture electron microscopy indicates that with this lipid mixture, alpha/beta-peptide I induces the formation of a sponge phase. 31P NMR and X-ray diffraction are consistent with this conclusion. In contrast, with alpha/beta-peptide II and this same lipid mixture, a lamellar phase is maintained, but with a drastically reduced d-spacing. alpha/beta-Peptide II is more lytic to liposomes composed of these lipids than is I. These findings are consistent with the greater toxicity of alpha/beta-peptide II, relative to alpha/beta-peptide I, to E. coli, a bacterium having a high content of phosphatidylethanolamine. In contrast, both alpha/beta-peptides display similar toxicity toward B. subtilis, in accord with the greater anionic lipid composition in its membrane. This work shows that variations in the selectivity of these peptidic antimicrobial peptides toward different strains of bacteria can be partly determined by the lipid composition of the bacterial cell membrane.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".