Common Distribution of gad Operon in Lactobacillus brevis and its GadA Contributes to Efficient GABA Synthesis toward Cytosolic Near-Neutral pH
Bibliographic record
Abstract
Many strains of lactic acid bacteria (LAB) and bifidobacteria have exhibited strain-specific capacity to produce γ-aminobutyric acid (GABA) via their glutamic acid decarboxylase (GAD) system, which is one of amino acid-dependent acid resistance (AR) systems in bacteria. However, the linkage between bacterial AR and GABA production capacity has not been well established. Meanwhile, limited evidence has been provided to the global diversity of GABA-producing LAB and bifidobacteria, and their mechanisms of efficient GABA synthesis. In this study, genomic survey identified common distribution of gad operon-encoded GAD system in Lactobacillus brevis for its GABA production among varying species of LAB and bifidobacteria. Importantly, among four commonly distributed amino acid-dependent AR systems in Lb. brevis, its GAD system was a major contributor to maintain cytosolic pH homeostasis by consuming protons via GABA synthesis. This highlights that Lb. brevis applies GAD system as the main strategy against extracellular and intracellular acidification demonstrating its high capacity of GABA production. In addition, the abundant GadA retained its activity towards near-neutral pH (pH 5.5-6.5) of cytosolic acidity thus contributing to efficient GABA synthesis in Lb. brevis. This is the first global report illustrating species-specific characteristic and mechanism of efficient GABA synthesis in Lb. brevis.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".