Genetic Variability in the Hop-Tolerance <i>horC</i> Gene of Beer-Spoiling Lactic Acid Bacteria
Bibliographic record
Abstract
horC is often targeted in rapid molecular tests for lactic acid bacteria (LAB) beer-spoilage ability. Discovery of a 27 bp horC deletion in a LAB unable to spoil beer led us to examine 27 horC+ isolates across two LAB genera and seven species to assess horC conservation. Nineteen (70%) of the isolates had the gap, with eight (30%) additionally containing a 3 bp gap yielding a cysteine excision and 14 conserved amino acid substitutions, thus defining three horC orthologs. Pediococcus-specific horC point mutations were also found. horC could not be sequenced in four cases (15%), pointing to horC paralog(s) indistinguishable by the original multiplex polymerase chain reaction (PCR). In contrast, the sequence of the putative horC transcriptional regulator horB was uniformly conserved, suggesting horB is essential for horC function. Modeling of protein structure and hop-compound binding revealed the horC orthologs produce proteins with similar function. Transcriptional analysis, however, found that between and within orthologs, horC expression was not proportional to the hops level present. Transcription analysis also suggested that horB repressed horC in the absence of hops. Thus, it is concluded that different horC orthologs are not uniformly active in response to hops, and targeting short gene sequences during PCR testing for LAB beer-spoilage potential is problematic.
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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 | 0.000 | 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".