Mimicking and Understanding the Agglutination Effect of the Antimicrobial Peptide Thanatin Using Model Phospholipid Vesicles
Bibliographic record
Abstract
Thanatin is a cationic 21-residue antimicrobial and antifongical peptide found in the spined soldier bug Podisus maculiventris. It is believed that it does not permeabilize membranes but rather induces the agglutination of bacteria and inhibits cellular respiration. To clarify its mode of action, lipid vesicle organization and aggregation propensity as well as peptide secondary structure have been studied using different membrane models. Dynamic light scattering and turbidimetry results show that specific mixtures of negatively charged and zwitterionic phospholipid vesicles are able to mimic the agglutination effect of thanatin observed on Gram-negative and Gram-positive bacterial cells, while monoconstituent ("conventional") models cannot reproduce this phenomenon. The model of eukaryotic cell reveals no particular interaction with thanatin, which is consistent with the literature. Infrared spectroscopy shows that under the conditions under which vesicle agglutination occurs, thanatin exhibits a particular spectral pattern in the amide I' region and in the region associated with Arg side chains. The data suggest that thanatin mainly retains its hairpin structure, Arg residues being involved in strong interactions with anionic groups of phospholipids. In the absence of vesicle agglutination, the peptide conformation and Arg side-chain environment are similar to those observed in solution. The data show that a negatively charged membrane is required for thanatin to be active, but this condition is insufficient. The activity of thanatin seems to be modulated by the charge surface density of membranes and thanatin concentration.
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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 | 0.001 |
| 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".