Deciphering <i>S</i>‐methylcysteine biosynthesis in common bean by isotopic tracking with mass spectrometry
Bibliographic record
Abstract
The suboptimal content of sulfur-containing amino acids methionine and cysteine prevents common bean (Phaseolus vulgaris) from being an excellent source of protein. Nutritional improvements to this significant crop require a better understanding of the biosynthesis of sulfur-containing compounds including the nonproteogenic amino acid S-methylcysteine and the dipeptide γ-glutamyl-S-methylcysteine, which accumulate in seed. In this study, seeds were incubated with isotopically labelled serine, cysteine or methionine and analyzed by reverse phase chromatography-high resolution mass spectrometry to track stable isotopes as they progressed through the sulfur metabolome. We determined that serine and methionine are the sole precursors of free S-methylcysteine in developing seeds, indicating that this compound is likely to be synthesized through the condensation of O-acetylserine and methanethiol. BSAS4;1, a cytosolic β-substituted alanine synthase preferentially expressed in developing seeds, catalyzed the formation of S-methylcysteine in vitro. A higher flux of labelled serine or cysteine was observed in a sequential pathway involving γ-glutamyl-cysteine, homoglutathione and S-methylhomoglutathione, a likely precursor to γ-glutamyl-S-methylcysteine. Preferential incorporation of serine over cysteine supports a subcellular compartmentation of this pathway, likely to be in the chloroplast. The origin of the methyl group in S-methylhomoglutathione was traced to methionine. There was substantial incorporation of carbons from methionine into the β-alanine portion of homoglutathione and S-methylhomoglutathione, suggesting the breakdown of methionine by methionine γ-lyase and conversion of α-ketobutyrate to β-alanine via propanoate metabolism. These findings delineate the biosynthetic pathways of the sulfur metabolome of common bean and provide an insight that will aid future efforts to improve nutritional quality.
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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".