Bioconversion of glycerol to 1,3-propanediol in thin stillage-based media by engineered <i>Lactobacillus panis</i> PM1
Bibliographic record
Abstract
Thin stillage (TS) is a waste residue that remains after bioethanol production, and its disposal reflects the high costs of bioethanol production. Thus, the development of cost-effective ways to process TS is a pending issue in bioethanol plants. The aim of this study was to evaluate the utilization of TS for the production of the valuable chemical, 1,3-propanediol (1,3-PDO), by Lactobacillus panis PM1. Different fermentation parameters, including temperature, pH and strains [wild-type and a recombinant strain expressing a NADPH-dependent aldehyde reductase (YqhD) gene] were tested in batch and fed-batch cultivations. The highest 1,3-PDO concentration (12.85 g/L) and yield (0.84 g/g) were achieved by batch fermentation at pH-4.5/30 °C by the YqhD recombinant strain. Furthermore, pH-controlled batch fermentation reduced the total fermentation period, resulting in the maximal 1,3-PDO concentration of 16.23 g/L and yield of 0.72 g/g in TS without an expensive nutrient or nitrogen (e.g., yeast extract, beef extract, and peptone) supplementation. The addition of two trace elements, Mg(2+) and Mn(2+), in TS increased 1,3-PDO yield (0.74 g/g) without 3-hydroxypropionaldehyde production, the only intermediate of 1,3-PDO biosynthetic pathway in L. panis PM1. Our results suggest that L. panis PM1 can offer a cost-effective process that utilizes the TS to produce a value-added chemical, 1,3-PDO.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".