Identification of novel<i>horA</i>-harbouring bacteria capable of spoiling beer
Bibliographic record
Abstract
An ATP-binding cassette (ABC) multi-drug resistance (MDR) gene was found in 4 Gram-positive bacterial isolates of environmental origin and found capable of spoiling beer. The bacteria isolated were Bacillus cereus, Bacillus licheniformis, Paenibacillus humicus, and Staphylococcus epidermidis; all of which were previously unappreciated as beer-spoilage bacteria. The MDR gene found in these bacteria has less than 37% similarity to known ABC MDR proteins described for Bacillus and Staphylococcus, and this is the first finding of an ABC MDR gene in the genus Paenibacillus. The sequenced region of the gene was translated and compared phylogenetically with the closest GenBank matches of the respective species and the closest GenBank matches overall. The ABC MDR proteins from these isolates were found to cluster among known sequences of HorA, sharing 99.5% identity within the sequenced region. In the beer-spoilage-associated genera Lactobacillus and Pediococcus, the presence of the MDR gene horA correlates with the ability to grow in beer. As the unique horA-harbouring isolates described here are capable of growing in beer, it is likely that the presence of the horA gene likewise confers hop resistance to these organisms.
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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) | 0.001 | 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".