Ability of Novel ATP-Binding Cassette Multidrug Resistance Genes to Predict Growth of <i>Pediococcus</i> Isolates in Beer
Bibliographic record
Abstract
We have recently shown that the horA gene is highly accurate for determining the beer-spoilage potential of lactobacilli isolates but not as good for predicting the beer-spoilage ability of pediococci isolates. Our goal in this study was to identify genetic markers for assessing the beer-spoilage potential of Pediococcus isolates. Lactobacillus and Pediococcus isolates negative for the putative beer-spoilage associated genes hitA, horA, horC, and ORF5, yet capable of growing in beer, were screened using degenerate PCR primers designed to the ATP-binding cassette region of multidrug resistance (ABC MDR) genes, and amplicons were sequenced to reveal possible identity and function. Six novel ABC MDR genes were found. Specific PCR primers were designed to each gene and used to screen 84 Lactobacillus and 48 Pediococcus isolates. Three genes had no correlation with hop resistance or ability to grow in beer. Another gene correlated with hop resistance but only in isolates incapable of growing in beer. The remaining two genes, bsrA and bsrB (beer-spoilage related), were highly correlated with the beer-spoilage ability and hop resistance of Pediococcus isolates. Although sharing a low percent identity with one another or other known proteins, both BsrA and BsrB contained conserved motifs typical of ABC MDR-type proteins. The bsrA and bsrB genes were not found in any Lactobacillus isolates, regardless of whether they were able to grow in beer, making them the first genetic markers capable of differentiating between beer-spoilage lactobacilli and pediococci.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".