Recombinant production of omega-3 fatty acids in Escherichia coli using a gene cluster isolated from Shewanella baltica MAC1
Bibliographic record
Abstract
AIM: To isolate eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) genes from Shewanella baltica MAC1 and to examine recombinant production of EPA and DHA in E. coli to investigate cost-effective, sustainable and convenient alternative sources for fish oils. METHODS AND RESULTS: A fosmid library was prepared from the genomic DNA of S. baltica MAC1 and was screened for EPA and DHA genes by colony hybridization using a partial fragment of the S. baltica MAC1 pfaA and pfaD genes as probes. Analysis of total fatty acids isolated from transgenic E. coli positive for pfaA and pfaD genes by gas chromatography and gas chromatography-mass spectrometry indicated recombinant production of both EPA and DHA. Analysis of the complete nucleotide sequence for the isolated gene cluster showed 16 putative open reading frames (ORFs). Among those, four ORFs showed homology with pfaA, pfaB, pfaC and pfaD genes of the EPA and/or DHA biosynthesis gene clusters; however, the protein domains of these genes were different from other EPA/DHA biosynthesis genes. CONCLUSIONS: The EPA and DHA gene cluster was cloned successfully. The transgenic E. coli strain carrying the omega-3 gene cluster was able to produce both EPA and DHA. The isolated gene cluster contained all the genes required for the recombinant production of both EPA and DHA in E. coli. SIGNIFICANCE AND IMPACT OF THE STUDY: These findings have implications for any future use of the EPA and DHA gene cluster in other micro-organisms, notably those being used for fermentation. Recombinant production of both EPA and DHA by E. coli or any other micro-organism has great potential to add economic value to a variety of industrial and agricultural products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".