Bioengineering of the Marine Diatom Phaeodactylum tricornutum with Cannabis Genes Enables the Production of the Cannabinoid Precursor, Olivetolic Acid
Bibliographic record
Abstract
The increasing demand for novel natural compounds has prompted the exploration of innovative approaches in bioengineering. This study investigates the bioengineering potential of the marine diatom Phaeodactylum tricornutum through the introduction of cannabis genes, specifically, tetraketide synthase (TKS), and olivetolic acid cyclase (OAC), for the production of the cannabinoid precursor, olivetolic acid (OA). P. tricornutum is a promising biotechnological platform due to its fast growth rate, amenability to genetic manipulation, and ability to produce valuable compounds. Through genetic engineering techniques, we successfully integrated the cannabis genes TKS and OAC into the diatom. P. tricornutum transconjugants expressing these genes showed the production of the recombinant TKS and OAC enzymes, detected via Western blot analysis, and the production of cannabinoids precursor (OA) detected using the HPLC/UV spectrum when compared to the wild-type strain. Quantitative analysis revealed significant olivetolic acid accumulation (0.6–2.6 mg/L), demonstrating the successful integration and functionality of the heterologous genes. Furthermore, the introduction of TKS and OAC genes led to the synthesis of novel molecules, potentially expanding the repertoire of bioactive compounds accessible through diatom-based biotechnology. This study demonstrates the successful bioengineering of P. tricornutum with cannabis genes, enabling the production of OA as a precursor for cannabinoid production and the synthesis of novel molecules with potential pharmaceutical applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".