Saccharomyces cerevisiae secretion of recombinant bacteriophage endolysin LysKB317 inhibits Limosilactobacillus fermentum in corn mash fermentation
Bibliographic record
Abstract
This study investigated the secretion of endolysin LysKB317 integrated into the HO locus of Saccharomyces cerevisiae strain NRRL Y-2034 to enable the yeast to simultaneously perform ethanol fermentation and control bacterial contaminants frequently present in ethanol refineries. The cell wall hydrolase gene was expressed using TEF1 and NAT5 promoter and terminator sequences with α-MF secretion signal and an N-terminus poly-histidine tag. LysKB317 was detectable by western blot analysis, which showed a molecular weight slightly larger than the 33 kDa native protein, presumably due to residual amino acids from the α-MF secretion signal peptide or S. cerevisiae glycosylation. Secreted LysKB317 was confirmed to be active using turbidity reduction and cell viability assay. Contaminated corn mash fermentations with yeast secreting LysKB317 demonstrated a significant reduction in bacterial contamination by at least 2-log compared to the contamination controls without LysKB317 expression. Moreover, LysKB317 expression led to a 73% decrease in acetic acid concentration and a 67% decrease in lactic acid levels. Contaminated fermentations with yeast expressing LysKB317 also exhibited a 16% improvement in ethanol production over the contamination controls without LysKB317, with no significant difference observed when compared to yeast-only controls during a 72-h corn mash fermentation. These findings suggest that a yeast endolysin secretion platform holds promise for mitigating bacterial contamination in biorefineries and potentially reducing reliance on antibiotics usage.
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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) | 0.000 | 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 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".