Diversifying Carotenoid Biosynthetic Pathways by Directed Evolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microorganisms and plants synthesize a diverse array of natural products, many of which have proven indispensable to human health and well-being. Although many thousands of these have been characterized, the space of possible natural products--those that could be made biosynthetically--remains largely unexplored. For decades, this space has largely been the domain of chemists, who have synthesized scores of natural product analogs and have found many with improved or novel functions. New natural products have also been made in recombinant organisms, via engineered biosynthetic pathways. Recently, methods inspired by natural evolution have begun to be applied to the search for new natural products. These methods force pathways to evolve in convenient laboratory organisms, where the products of new pathways can be identified and characterized in high-throughput screening programs. Carotenoid biosynthetic pathways have served as a convenient experimental system with which to demonstrate these ideas. Researchers have mixed, matched, and mutated carotenoid biosynthetic enzymes and screened libraries of these "evolved" pathways for the emergence of new carotenoid products. This has led to dozens of new pathway products not previously known to be made by the assembled enzymes. These new products include whole families of carotenoids built from backbones not found in nature. This review details the strategies and specific methods that have been employed to generate new carotenoid biosynthetic pathways in the laboratory. The potential application of laboratory evolution to other biosynthetic pathways is also discussed.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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 it