Analysis of the Enzymatic Properties of a Broad Family of Alanine Aminotransferases
Bibliographic record
Abstract
Alanine aminotransferase (AlaAT) has been studied in a variety of organisms due to the involvement of this enzyme in mammalian processes such as non-alcoholic hepatocellular damage, and in plant processes such as C4 photosynthesis, post-hypoxic stress response and nitrogen use efficiency. To date, very few studies have made direct comparisons of AlaAT enzymes and fewer still have made direct comparisons of this enzyme across a broad spectrum of organisms. In this study we present a direct kinetic comparison of glutamate:pyruvate aminotransferase (GPAT) activity for seven AlaATs and two glutamate:glyoxylate aminotransferases (GGAT), measuring the K(M) values for the enzymes analyzed. We also demonstrate that recombinant expression of AlaAT enzymes in Eschericia coli results in differences in bacterial growth inhibition, supporting previous reports of AlaAT possessing bactericidal properties, attributed to lipopolysaccharide endotoxin recognition and binding. A probable lipopolysaccharide binding region within the AlaAT enzymes, homologous to a region of a lipopolysaccharide binding protein (LBP) in humans, was also identified in this study. The AlaAT enzyme differences identified here indicate that AlaAT homologues have differentiated significantly and the roles these homologues play in vivo may also have diverged significantly. Specifically, the differing kinetics of AlaAT enzymes and how this may alter the nitrogen use efficiency in plants is discussed.
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 | 0.001 | 0.001 |
| 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".