Characterization of Linoleate 10-Hydratase of Lactobacillus plantarum and Novel Antifungal Metabolites
Bibliographic record
Abstract
Lactobacilli convert linoleic acid to the antifungal compound 10-hydroxy-12-octadecenoic acid (10-HOE) by linoleate 10-hydratase (10-LAH). However, the effect of this conversion on cellularmembrane physiology and properties of the cell surface have not been demonstrated. Moreover, L. plantarum produces 13-hydroxy-9-octadecenoic acid (13-HOE) in addition to 10-HOE, but the antifungal activity of 13-HOE was unknown. Phylogenetic analyses conducted in this study did not differentiate between 10-LAH and linoleate 13-hydratase (13-LAH). Thus, linoleate hydratases (LAHs) must be characterized through their differences in their activities of linoleate conversion. Four genes encoding putative LAHs from lactobacilli were cloned, heterologous expressed, purified and identified as FAD-dependent 10-LAH. The unsaturated fatty acid substrates stimulated the growth of lactobacilli. We also investigated the role of 10-LAH in ethanol tolerance, membrane fluidity and hydrophobicity of cell surfaces in lactobacilli by disruption of 10-lah. Compared with the L. plantarum 10-lah deficient strain, 10-LAH in wild-type strain did not exert effect on cell survival and membrane fluidity under ethanol stress, but influenced the cell surface hydrophobicity. Moreover, deletion of 10-LAH in L. plantarum facilitated purification of 13-HOE and demonstration of its antifungal activity against Penicillium roquefortii and Aspergillus niger.
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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".