Insights into cannabinoid biosynthesis in Chlamydomonas reinhardtii : successes with NphB and limitations of CBDAS expression
Bibliographic record
Abstract
The growing legalization of Cannabis has increased demand for cannabinoids (CBs). Currently, pharmaceutically relevant CBs are primarily extracted from Cannabis, a process that presents challenges related to yield variability and purity. To overcome these limitations, microbial platforms are being explored for the sustainable production of specific CBs. Compared to conventional microbial hosts, the photosynthetic microalga Chlamydomonas reinhardtii offers plant-like post-translational modifications, low-cost cultivation, CO 2 fixation, and low endotoxin contamination, making it a potential chassis for CB biosynthesis. Here, we expressed a codon-optimized, soluble aromatic prenyltransferase ( NphB G286S/Y288A ) from Streptomyces and Cannabis sativa cannabidiolic acid synthase ( CBDAS ) in the nuclear genome of C. reinhardtii ; transformants were screened for integration, gene expression, protein accumulation, enzymatic activity, and CB production. Our results provide evidence of functional NphB expression in C. reinhardtii , with in vitro CBGA production reaching up to 633 ± 58 μg/L. Although CBDAS transcripts were detected under multiple construct designs, neither protein nor CBDA was accumulated, suggesting limitations in expression, localization, or post-translational processing in C. reinhardtii . Our study provides the first demonstration of in vitro CBGA biosynthesis in the photosynthetic model microalga C. reinhardtii , highlighting its potential as a future platform for CB production. It also highlights key challenges in nuclear expression of plant-derived enzymes, such as CBDAS, emphasizing that improved regulatory control, subcellular targeting, and mRNA processing will be required to achieve full pathway reconstruction in C. reinhardtii .
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".