Back to the plant: overcoming roadblocks to the microbial production of pharmaceutically important plant natural products
Bibliographic record
Abstract
Microbial fermentation platforms offer a cost-effective and sustainable alternative to plant cultivation and chemical synthesis for the production of many plant-derived pharmaceuticals. Plant alkaloids, particularly benzylisoquinoline alkaloids and monoterpene indole alkaloids, and recently cannabinoids have become attractive targets for microbial biosynthesis owing to their medicinal importance. Recent advances in the discovery of pathway components, together with the application of synthetic biology tools, have facilitated the assembly of plant alkaloid and cannabinoid pathways in the microbial hosts Escherichia coli and Saccharomyces cerevisiae. This review highlights key aspects of these pathways in the framework of overcoming bottlenecks in microbial production to further improve end-product titers. We discuss the opportunities that emerge from a better understanding of the pathway components by further study of the plant, and strategies for generation of new and advanced medicinal compounds.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".