Tomato pollen tube growth requires flavonol glycosylation
Bibliographic record
Abstract
Flavonols are a subclass of flavonoids widely found in plants and typically exist in glycosylated forms, decorated with various sugars at different positions on the flavonol aglycone. The composition and abundance of flavonol glycosides vary across species and among tissues within a species. Although flavonols are collectively known for their antioxidant activity, the specific physiological functions of individual flavonol structures remain poorly understood. Here, we show that 2 flavonol glycosides, kaempferol 3-O-glucosyl(1 → 2)galactoside (K2) and quercetin 3-O-glucosyl(1 → 2)galactoside (Q2), predominantly accumulate in the pollen of Solanaceae plants. K2 is evolutionarily conserved across Solanaceae, while Q2 has been lost in species such as tomato (Solanum lycopersicum). Our transcriptome profiling and biochemical analysis revealed SlUGT78D-B (78-B) as a pollen-specific flavonol 3-O-galactosyltransferase responsible for K2 production in tomato. Disruption of 78-B abolished K2 accumulation, leading to defective pollen tube growth in our in vitro assays. Supplementation with kaempferol 3-O-galactoside (K2 precursor) restores pollen tube growth, whereas quercetin 3-O-galactoside (Q2 precursor) or flavonol aglycones do not, suggesting distinct roles for individual flavonol structures. We further show that 3 key amino acid residues of 78-B dictate its sugar specificity, favoring galactosylation over glucosylation. Substitution of any one of these residues enables 78-B to acquire glucosyltransferase activity. However, 78-B remains evolutionarily constrained from gaining this activity, suggesting selective pressure to maintain flavonol galactoside accumulation in pollen. These findings indicate that individual flavonol glycosides can have specific physiological roles beyond enhancing solubility and stability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
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".