Characterization of a recombinant <scp>10‐linoleic</scp> acid hydratase from <i>Lactiplantibacillus plantarum</i><scp>ZS2058</scp> and biosynthesis of 10‐ hydroxy‐<i>cis</i>‐12‐octadecenoic acid
Bibliographic record
Abstract
Abstract BACKGROUND 10‐Hydroxy‐cis‐12‐octadecenoic acid (10‐HOE, 10‐OH C18:1), an emerging functional fatty acid, has anti‐fungal and anti‐inflammatory effects. 10‐HOE is synthesized by bacterial 10‐linoleic acid hydratase (10‐LHT) with linoleic acid as the substate. However, the characterization of 10‐LHT and its targeted synthesis of 10‐HOE have been rarely reported. In this study, the recombinant 10‐LHT from Lactiplantibacillus plantarum ZS2058 was characterized, and the biocatalysis of 10‐HOE using crude enzyme was optimized. RESULTS The recombinant 10‐LHT catalyzed the conversion of linoleic acid (C18:2) to 10‐HOE as identified using gas chromatography‐mass spectrometry (GC–MS). It showed a molecular weight of about 70 kDa on sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS‐PAGE), and was a flavin adenine dinucleotide (FAD)‐dependent enzyme. The activity of 10‐LHT was optimal at pH 6.5 and 25 °C, and it was pH‐stable but thermo‐sensitive. The optimal condition for the 10‐HOE biosynthesis using crude enzyme was 5 g L−1 linoleic acid (C18:2), 148.0 U mL−1 10‐LHT, 0.05 mmol L−1 FAD, 2% methanol and 100 mmol L−1 sodium chloride at 25 °C and pH 6.5. A conversion yield of 47.8 ± 1.5% and the corresponding 10‐HOE concentration of 2.4 ± 0.1 g L−1 were achieved at 48 h under the optimal reaction conditions. CONCLUSION This work achieved the highest conversion yield of 10‐HOE with the highest substrate concentration, and provides some useful information for the industrial production of 10‐HOE. © 2021 Society of Chemical Industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".