Yohimban acetylation in Rauvolfia is mediated by a leaf-specific acetyltransferase in reserpine biosynthetic gene cluster
Bibliographic record
Abstract
Monoterpenoid indole alkaloids (MIAs) constitute one of the largest and most structurally diverse classes of alkaloids found in nature, with significant pharmacological applications. While significant discoveries have been made in MIA biosynthesis, substantial gaps remain in our understanding of biosynthetic compartmentalization and the evolution of MIA biosynthesis. In this study, we identify and characterize the yohimban O -acetyltransferase (YAT), a BAHD-type acyltransferase tightly clustered with yohimban synthase (YOS) within the reserpine biosynthetic gene cluster (BGC) of Rauvolfi a. YAT specifically acetylates yohimbine and alloyohimbine in R. serpentina leaves, representing a previously unrecognized bifurcation in yohimban alkaloid metabolism. Notably, YAT exhibits a leaf-specific expression pattern, while other genes within the reserpine BGC are predominantly expressed in roots, mirroring alkaloid accumulation trends. Homology modeling and substrate docking experiments further elucidate YAT's active site, providing insights into substrate specificity and catalysis. Our findings establish the enzymatic basis of Rauvolfia MIA biosynthesis and offer insights into the evolutionary dynamics of acetyltransferases in shaping alkaloid diversity. This work also provides a foundation for synthetic biology strategies to engineer acetylated yohimban alkaloids in heterologous systems. • Discovery of YAT, a BAHD acetyltransferase in the Rauvolfia reserpine gene cluster • YAT specifically acetylates yohimbine and alloyohimbine • YAT’s expression is leaf specific, aligning with alkaloid accumulation pattern • Structural modeling reveals active site basis for substrate specificity • The study provides new insight into tissue-specific alkaloid biosynthesis
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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 | 0.000 |
| 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".