Honey Glycoproteins Containing Antimicrobial Peptides, Jelleins of the Major Royal Jelly Protein 1, Are Responsible for the Cell Wall Lytic and Bactericidal Activities of Honey
Bibliographic record
Abstract
We have recently identified the bacterial cell wall as the cellular target for honey antibacterial compounds; however, the chemical nature of these compounds remained to be elucidated. Using Concavalin A-affinity chromatography, we found that isolated glycoprotein fractions (glps), but not flow-through fractions, exhibited strong growth inhibitory and bactericidal properties. The glps possessed two distinct functionalities: (a) specific binding and agglutination of bacterial cells, but not rat erythrocytes and (b) non-specific membrane permeabilization of both bacterial cells and erythrocytes. The isolated glps induced concentration- and time-dependent changes in the cell shape of both E. coli and B. subtilis as visualized by light and SEM microscopy. The appearance of filaments and spheroplasts correlated with growth inhibition and bactericidal effects, respectively. The time-kill kinetics showed a rapid, >5-log10 reduction of viable cells within 15 min incubation at 1xMBC, indicating that the glps-induced damage of the cell wall was lethal. Unexpectedly, MALDI-TOF and electrospray quadrupole time of flight mass spectrometry, (ESI-Q-TOF-MS/MS) analysis of glps showed sequence identity with the Major Royal Jelly Protein 1 (MRJP1) precursor that harbors three antimicrobial peptides: Jelleins 1, 2, and 4. The presence of high-mannose structures explained the lectin-like activity of MRJP1, while the presence of Jelleins in MRJP1 may explain cell wall disruptions. Thus, the observed damages induced by the MRJP1 to the bacterial cell wall constitute the mechanism by which the antibacterial effects were produced. Antibacterial activity of MRJP1 glps directly correlated with the overall antibacterial activity of honey, suggesting that it is honey's active principle responsible for this activity.
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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) | 0.001 | 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".