Induction of Fatty Acid Composition Modifications and Tolerance to Biocides in <i>Salmonella enterica</i> Serovar Typhimurium by Plant-Derived Terpenes
Bibliographic record
Abstract
To enhance food safety and stability, the food industry tends to use natural antimicrobials such as plant-derived compounds as an attractive alternative to chemical preservatives. Nonetheless, caution must be exercised in light of the potential for bacterial adaptation to these molecules, a phenomenon previously observed with other antimicrobials. The aim of this study was to characterize the adaptation of Salmonella enterica serovar Typhimurium to sublethal concentrations of four terpenes extracted from aromatic plants: thymol, carvacrol, citral, and eugenol, or combinations thereof. Bacterial adaptation in these conditions was demonstrated by changes in membrane fatty acid composition showing (i) limitation of the cyclization of unsaturated fatty acids to cyclopropane fatty acids when cells entered the stationary phase and (ii) bacterial membrane saturation. Furthermore, we demonstrated an increased cell resistance to the bactericidal activity of two biocides (peracetic acid and didecyl dimethyl ammonium bromide). The implications of membrane modifications in terms of hindering the penetration of antimicrobials through the bacterial membrane are discussed.
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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) | 0.000 | 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".