Identification of α-Tomatine 23-Hydroxylase Involved in the Detoxification of a Bitter Glycoalkaloid
Bibliographic record
Abstract
Tomato plants (Solanum lycopersicum) contain steroidal glycoalkaloid α-tomatine, which functions as a chemical barrier to pathogens and predators. α-Tomatine accumulates in all tissues and at particularly high levels in leaves and immature green fruits. The compound is toxic and causes a bitter taste, but its presence decreases through metabolic conversion to nontoxic esculeoside A during fruit ripening. This study identifies the gene encoding a 23-hydroxylase of α-tomatine, which is a key to this process. Some 2-oxoglutarate-dependent dioxygenases were selected as candidates for the metabolic enzyme, and Solyc02g062460, designated Sl23DOX, was found to encode α-tomatine 23-hydroxylase. Biochemical analysis of the recombinant Sl23DOX protein demonstrated that it catalyzes the 23-hydroxylation of α-tomatine and the product spontaneously isomerizes to neorickiioside B, which is an intermediate in α-tomatine metabolism that appears during ripening. Leaves of transgenic tomato plants overexpressing Sl23DOX accumulated not only neorickiioside B but also another intermediate, lycoperoside C (23-O-acetylated neorickiioside B). Furthermore, the ripe fruits of Sl23DOX-silenced transgenic tomato plants contained lower levels of esculeoside A but substantially accumulated α-tomatine. Thus, Sl23DOX functions as α-tomatine 23-hydroxylase during the metabolic processing of toxic α-tomatine in tomato fruit ripening and is a key enzyme in the domestication of cultivated tomatoes.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".