Role of Plasmids in Lactobacillus brevis BSO 464 Hop Tolerance and Beer Spoilage
Bibliographic record
Abstract
Specific isolates of lactic acid bacteria (LAB) can grow in the harsh beer environment, thus posing a threat to brew quality and the economic success of breweries worldwide. Plasmid-localized genes, such as horA, horC, and hitA, have been suggested to confer hop tolerance, a trait required for LAB survival in beer. The presence and expression of these genes among LAB, however, do not universally correlate with the ability to grow in beer. Genome sequencing of the virulent beer spoilage organism Lactobacillus brevis BSO 464 revealed the presence of eight plasmids, with plasmids 1, 2, and 3 containing horA, horC, and hitA, respectively. To investigate the roles that these and the other five plasmids play in L. brevis BSO 464 growth in beer, plasmid curing with novobiocin was used to derive 10 plasmid variants. Multiplex PCRs were utilized to determine the presence or absence of each plasmid, and how plasmid loss affected hop tolerance and growth in degassed (noncarbonated) beer was assessed. Loss of three of the eight plasmids was found to affect hop tolerance and growth in beer. Loss of plasmid 2 (horC and 28 other genes) had the most dramatic effect, with loss of plasmid 4 (120 genes) and plasmid 8 (47 genes) having significant, but smaller, impacts. These results support the contention that genes on mobile genetic elements are essential for bacterial growth in beer and that beer spoilage ability is not dependent solely on the three previously described hop tolerance genes or on the chromosome of a beer spoilage LAB isolate.
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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".