Improved production of the antidiabetic metabolite montbretin A in <i>Nicotiana benthamiana</i>: discovery, characterization, and use of <i>Crocosmia</i> shikimate shunt genes
Bibliographic record
Abstract
The plant-specialized metabolite montbretin A (MbA) is being developed as a new treatment option for type-2 diabetes, which is among the ten leading causes of premature death and disability worldwide. MbA is a complex acylated flavonoid glycoside produced in small amounts in below-ground organs of the perennial plant Montbretia (Crocosmia × crocosmiiflora). The lack of a scalable production system limits the development and potential application of MbA as a pharmaceutical or nutraceutical. Previous efforts to reconstruct montbretin biosynthesis in Nicotiana benthamiana (Nb) resulted in low yields of MbA and higher levels of montbretin B (MbB) and montbretin C (MbC). MbA, MbB, and MbC are nearly identical metabolites differing only in their acyl moieties, derived from caffeoyl-CoA, coumaroyl-CoA, and feruloyl-CoA, respectively. In contrast to MbA, MbB and MbC are not pharmaceutically active. To utilize the montbretia caffeoyl-CoA biosynthesis for improved MbA engineering in Nb, we cloned and characterized enzymes of the shikimate shunt of the general phenylpropanoid pathway, specifically hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase (CcHCT), p-coumaroylshikimate 3'-hydroxylase (CcC3'H), and caffeoylshikimate esterase (CcCSE). Gene expression patterns suggest that CcCSE enables the predominant formation of MbA, relative to MbB and MbC, in montbretia. This observation is supported by results from in vitro characterization of CcCSE and reconstruction of the shikimate shunt in yeast. Using CcHCT together with montbretin biosynthetic genes in multigene constructs resulted in a 30-fold increase of MbA in Nb. This work advances our understanding of the phenylpropanoid pathway and features a critical step towards improved MbA production in bioengineered Nb.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".