A Novel γ-Hydroxybutyrate Dehydrogenase
Bibliographic record
Abstract
In plants, gamma-aminobutyrate (GABA), a non-protein amino acid, accumulates rapidly in response to a variety of abiotic stresses such as oxygen deficiency. Under normoxia, GABA is catabolized to succinic semialdehyde and then to succinate with the latter reaction being catalyzed by succinic semialdehyde dehydrogenase (SSADH). Complementation of an SSADH-deficient yeast mutant with an Arabidopsis cDNA library enabled the identification of a novel cDNA (designated as AtGH-BDH for Arabidopsis thaliana gamma-hydroxybutyrate dehydrogenase), which encodes a 289-amino acid polypeptide containing an NADP-binding domain. Constitutive expression of AtGHBDH in the mutant yeast enabled growth on 20 mm GABA and significantly enhanced the cellular concentrations of gamma-hydroxybutyrate, the product of the GHDBH reaction. These data confirm that the cDNA encodes a polypeptide with GHBDH activity. Arabidopsis plants subjected to flooding-induced oxygen deficiency for up to 4 h possessed elevated concentrations of gamma-hydroxybutyrate as well as GABA and alanine. RNA expression analysis revealed that GHBDH transcription was not up-regulated by oxygen deficiency. These findings suggest that GHBDH activity is regulated by the supply of succinic semialdehyde or by redox balance. It is proposed that GHBDH and SSADH activities in plants are regulated in a complementary fashion and that GHBDH and gamma-hydroxybutyrate function in oxidative stress tolerance.
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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 | 0.001 | 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".