The metabolite repair enzyme Nit1 is a dual-targeted amidase that disposes of damaged glutathione in <i>Arabidopsis</i>
Bibliographic record
Abstract
Abstract The tripeptide glutathione (GSH) is implicated in various crucial physiological processes including redox buffering and protection against heavy metal toxicity. GSH is abundant in plants, with reported intracellular concentrations typically in the 1–10 mM range. Various aminotransferases can inadvertently transaminate the amino group of the γ-glutamyl moiety of GSH to produce deaminated glutathione (dGSH), a metabolite damage product. It was recently reported that an amidase known as Nit1 participates in dGSH breakdown in mammals and yeast. Plants have a hitherto uncharacterized homolog of the Nit1 amidase. We show that recombinant Arabidopsis Nit1 (At4g08790) has high and specific amidase activity towards dGSH. Ablating the Arabidopsis Nit1 gene causes a massive accumulation of dGSH and other marked changes to the metabolome. All plant Nit1 sequences examined had predicted plastidial targeting peptides with a potential second start codon whose use would eliminate the targeting peptide. In vitro transcription/translation assays show that both potential translation start codons in Arabidopsis Nit1 were used and confocal microscopy of Nit1–GFP fusions in plant cells confirmed both cytoplasmic and plastidial localization. Furthermore, we show that Arabidopsis enzymes present in leaf extracts convert GSH to dGSH at a rate of 2.8 pmol min−1 mg−1 in the presence of glyoxalate as an amino acceptor. Our data demonstrate that plants have a dGSH repair system that is directed to at least two cellular compartments via the use of alternative translation start sites.
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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) | 0.001 | 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".