Plant defensin antibacterial mode of action against Pseudomonas species
Bibliographic record
Abstract
BACKGROUND: Though many plant defensins exhibit antibacterial activity, little is known about their antibacterial mode of action (MOA). Antimicrobial peptides with a characterized MOA induce the expression of multiple bacterial outer membrane modifications, which are required for resistance to these membrane-targeting peptides. Mini-Tn5-lux mutant strains of Pseudomonas aeruginosa with Tn insertions disrupting outer membrane protective modifications were assessed for sensitivity against plant defensin peptides. These transcriptional lux reporter strains were also evaluated for lux gene expression in response to sublethal plant defensin exposure. Also, a plant pathogen, Pseudomonas syringae pv. syringae was modified through transposon mutagenesis to create mutants that are resistant to in vitro MtDef4 treatments. RESULTS: Plant defensins displayed specific and potent antibacterial activity against strains of P. aeruginosa. A defensin from Medicago truncatula, MtDef4, induced dose-dependent gene expression of the aminoarabinose modification of LPS and surface polycation spermidine production operons. The ability for MtDef4 to damage bacterial outer membranes was also verified visually through fluorescent microscopy. Another defensin from M. truncatula, MtDef5, failed to induce lux gene expression and limited outer membrane damage was detected with fluorescent microscopy. The transposon insertion site on MtDef4 resistant P. syringae pv. syringae mutants was sequenced, and modifications of ribosomal genes were identified to contribute to enhanced resistance to plant defensin treatments. CONCLUSIONS: MtDef4 damages the outer membrane similar to polymyxin B, which stimulates antimicrobial peptide resistance mechanisms to plant defensins. MtDef5, appears to have a different antibacterial MOA. Additionally, the MtDef4 antibacterial mode of action may also involve inhibition of translation.
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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".