Screening, characterization and growth of γ-aminobutyric acid-producing probiotic candidates from food origin under simulated colonic conditions
Bibliographic record
Abstract
Abstract Aims This study aims to isolate probiotic bacteria candidates from various starter cultures and fermented foods and characterize their ability to produce γ-aminobutyric acid (GABA). GABA is a major inhibitory neuromediator of the central and enteric nervous systems with a role in several health disorders. Methods and Results Fourteen strains of lactic acid bacteria were isolated from food environment and screened for the presence of the glutamate decarboxylase (gadB) gene using PCR and GAD enzymatic assay. The identified potent GABA-producers included Strep. thermophilus, Lactiplantibacillus plantarum and Lact. delbrueckii subsp. bulgaricus. GC-FID analyses confirmed the high GABA production capacity of Strep. thermophilus ST16 (1641.5 ± 154.15 μmol l−1), Strep. thermophilus ST8 (1724.5 ± 48.08 μmol/L). To a lesser extent, Bif. animalis ST20, Lact. acidophilus LP16-2 and Ent. faecium ST3 produced 947.5 ± 70.71, 918.0 ± 121.42, and 907.83 ± 55.15 μmol/L of GABA, respectively. These potent strains were able to grow and produce GABA in MRS broth and pre-fermented Macfarlane broth, the latter medium mimicking the nutrient and metabolome composition encountered in the colon. The identified bioactive strains exhibited strong biological safety and probiotic potential profiles as indicated by sensitivity to antibiotics, absence of virulence factors and survival in gastrointestinal conditions. Conclusions Several GABA producing probiotic candidates, including Bif. animals ST20, Strep. thermophilus ST8, Lact. acidophilus LP16-2, L. plantarum LP6 & LP9, and Ent. faecium ST3, have shown potential to grow under simulated colonic conditions. Significance and Impact of Study Findings from this study provide evidence of the suitability of the isolated GABA-producing probiotic candidates for the development of health-oriented functional food products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".