Cell free biosynthesis of isoprenoids from isopentenol
Bibliographic record
Abstract
Cell-free systems are growing in importance for the biosynthesis of complex molecules. These systems combine the precision of traditional chemistry with the versatility of biology in creating superior overall processes. Recently, a new synthetic pathway for the biosynthesis of isoprenoids using the substrate isopentenol, dubbed the isopentenol utilization pathway (IUP), was demonstrated to be a promising alternative to the native 2C-methyl-d-erythritol-4-phosphate (MEP) and mevalonate (MVA) pathways. This simplified pathway, which contains a minimum of four enzymes to produce basic monoterpenes and only depends on ATP and isopentenol as substrates, allows for a highly flexible approach to the commercial synthesis of isoprenoid products. In this work, we use metabolic reconstitution to characterize this new pathway in vitro and demonstrate its use for the cell-free synthesis of mono-, sesquit-, and diterpenoids. Kinetic modeling and sensitivity analysis were also used to identify the most significant parameters for taxadiene productivity, and metabolic control analysis was employed to elucidate protein-level interactions within this pathway, which demonstrated that the IUP enzymatic system is primarily controlled by the concentration and kinetics of choline kinase (CK) and not regulated by any pathway intermediates. This is a significant advantage over the natural MEP or MVA pathways as it greatly simplifies future metabolic engineering efforts, both in vitro and in vivo, aiming at improving the kinetics of CK. Finally, we used the insights gathered to demonstrate an in vitro IUP system that can produce 220 mg/L of the diterpene taxadiene, in 9 hr, almost 3-fold faster than any system reported thus far.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".