Glycerol and environmental factors: effects on 1,3-propanediol production and NAD<sup>+</sup> regeneration in <i>Lactobacillus panis </i>PM1
Bibliographic record
Abstract
AIMS: This study was conducted to understand the influences of fermentation factors in NADH recycling and mechanisms of 1,3-propanediol (1,3-PDO) production in Lactobacillus panis PM1. METHODS AND RESULTS: We conducted metabolite analyses, qRT-PCR of the glycerol reductive pathway [glycerol dehydratase (DhaB) and 1,3-PDO dehydrogenase (DhaT)] and DhaT activity assays at different pH, temperature and initial glycerol concentrations. The supplementation of 150 mmol l(-1) glycerol caused a shift in NADH flux from ethanol to 1,3-PDO production, whereas 300 mol l(-1) glycerol negatively affected the regeneration of NAD(+) via 1,3-PDO production. This retardation decreased transcription levels and specific activities of DhaT. The decreased DhaT activity eventually caused the shutdown of 1,3-PDO production. Temperature and pH did not significantly affect the specific activity of DhaT, whereas expression of genes for DhaB and DhaT was activated under acidic conditions. Moreover, fresh glucose addition after its depletion could not restart the glycerol reduction, but increased ethanol production. CONCLUSIONS: Those environmental factors affect 1,3-PDO production in different ways through changing the expression level of enzymes and shifting the NAD(+) regeneration pathways. SIGNIFICANCE AND IMPACT OF THE STUDY: Our findings elucidated a key element to optimize 1,3-PDO production by Lact. panis PM1, which potentially improves 1,3-PDO manufacturing efficiencies.
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 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".