The Morphoregulatory Role of Thidiazuron: Metabolomics-Guided Hypothesis Generation for Mechanisms of Activity
Bibliographic record
Abstract
Thidiazuron (TDZ) is a diphenylurea synthetic herbicide and plant growth regulator used to defoliate cotton crops and to induce regeneration of recalcitrant species in plant tissue culture. In vitro cultures of African violet thin petiole sections are an ideal model system for studies of TDZ-induced morphogenesis. TDZ induces de novo shoot organogenesis at low concentrations and somatic embryogenesis at higher concentrations of exposure. We used an untargeted metabolomics approach to identify metabolites in control and TDZ-treated tissues. Statistical analysis including metabolite clustering, pattern and pathway tools, logical algorithms, synthetic biotransformations and hormonomics identified TDZ-induced changes in metabolism. A total of 18,602 putative metabolites with extracted masses and predicted formulae were identified with 1412 features that were found only in TDZ-treated tissues and 312 that increased in response to TDZ. The monomer of TDZ was not detected intact in the tissues but putative oligomers were found in the database and we hypothesize that these may form by a Diels-Alder reaction. Accumulation oligomers in the tissue may act as a reservoir, slowly releasing the active TDZ monomer over time. Cleavage of the amide bridge released TDZ-metabolites into the tissues including organic nitrogen and sulfur containing compounds. Metabolomics data analysis generated six novel hypotheses that can be summarized as an overall increase in uptake of sugars from the culture media, increase in primary metabolism, redirection of terpene metabolism and mediation of stress metabolism via indoleamine and phenylpropanoid metabolism. Further research into the specific mechanisms hypothesized is likely to unravel the mode of action of TDZ and to provide new insights into the control of plant morphogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".