Antarctic Thraustochytrids as Sources of Carotenoids and High-Value Fatty Acids
Bibliographic record
Abstract
Eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and carotenoids are needed as human dietary supplements and are essential components in commercial feeds for the production of aquacultured seafood. Microorganisms such as thraustochytrids are potential natural sources of these compounds. This research reports on the lipid and carotenoid production capacity of thraustochytrids that were isolated from coastal waters of Antarctica. Of the 22 isolates, 21 produced lipids containing EPA+DHA, and the amount of these fatty acids exceeded 20% of the total fatty acids in 12 isolates. Ten isolates were shown to produce carotenoids (27.4–63.9 μg/g dry biomass). The isolate RT2316-16, identified as Thraustochytrium sp., was the best producer of biomass (7.2 g/L in five days) rich in carotenoids (63.9 μg/g) and, therefore, became the focus of this investigation. The main carotenoids in RT2316-16 were β-carotene and canthaxanthin. The content of EPA+DHA in the total lipids (34 ± 3% w/w in dry biomass) depended on the stage of growth of RT2316-16. Lipid and carotenoid content of the biomass and its concentration could be enhanced by modifying the composition of the culture medium. The estimated genome size of RT2316-16 was 44 Mb. Of the 5656 genes predicted from the genome, 4559 were annotated. These included genes of most of the enzymes in the elongation and desaturation pathway of synthesis of ω-3 polyunsaturated fatty acids. Carotenoid precursors in RT2316-16 were synthesized through the mevalonate pathway. A β-carotene synthase gene, with a different domain organization compared to the gene in other thraustochytrids, explained the carotenoid profile of RT2316-16.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".