Inhibition of yeast by lactic acid bacteria in continuous culture: nutrient depletion and/or acid toxicity?
Bibliographic record
Abstract
Lactic acid was added to batch very high gravity (VHG) fermentations and to continuous VHG fermentations equilibrated to steady state with Saccharomyces cerevisiae. A 53% reduction in colony-forming units (CFU) ml(-1) of S. cerevisiae was observed in continuous fermentation at an undissociated lactic acid concentration of 3.44% w/v; and greater than 99.9% reduction was evident at 5.35% w/v lactic acid. The differences in yeast cell number in these fermentations were not due to pH, since batch fermentations over a pH range of 2.5-5.0 did not lead to changes in growth rate. Similar fermentations performed in batch showed that growth inhibition with added lactic acid was nearly identical. This indicates that the apparent high resistance of S. cerevisiae to lactic acid in continuous VHG fermentations is not a function of culture mode. Although the total amount of ethanol decreased from 48.7 g l(-1) to 14.5 g l(-1) when 4.74% w/v undissociated lactic acid was added, the specific ethanol productivity increased ca. 3.2-fold (from 7.42 x 10(-7) g to 24.0 x 10(-7) g ethanol CFU(-1) h(-1)), which indicated that lactic acid stress improved the ethanol production of each surviving cell. In multistage continuous fermentations, lactic acid was not responsible for the 83% (CFU ml(-1)) reduction in viable S. cerevisiae yeasts when Lactobacillus paracasei was introduced to the system at a controlled pH of 6.0. The competition for trace nutrients in those fermentations and not lactic acid produced by L. paracasei likely caused the yeast inhibition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".