Genomic Markers for Quaternary Ammonium Compound Resistance as a Persistence Indicator for Listeria monocytogenes Contamination in Food Manufacturing Environments
Bibliographic record
Abstract
ABSTRACT: Persistent contamination of food manufacturing environments by Listeria monocytogenes is an important public health risk, because such contamination events defy standard sanitization protocols, for example, the application of quaternary ammonium compounds such as benzalkonium chloride (BC), providing a source for prolonged dissemination of the bacteria in food products. We performed whole genome sequencing analyses of 1,279 well-characterized L. monocytogenes isolates from various foods and food manufacturing environments and identified the bcrABC gene cassette associated with BC resistance in 531 (41.5%) isolates. The bcrABC cassette was significantly associated with L. monocytogenes isolates belonging to clonal complex (CC) 321, CC155, CC204, and CC199, which are among the 10 most prevalent genotypes recovered from foods and food production environments. All but 1 of the 177 CC321 isolates harbored the bcrABC cassette. In addition, 384 (38.6%) of the 994 isolates recovered from foods representing 67 different CCs and 119 (59.2%) of isolates from food manufacturing environmental samples representing 26 different CCs were found to harbor the intact bcrABC cassette. A representative set of 69 isolates with and without bcrABC was assayed for the ability to grow in the presence of BC, and 34 of 35 isolates harboring the bcrABC cassette exhibited MICs of ≥10 μg/mL BC. Determination of bcrABC in isolates could be achieved using both PCR and whole genome sequencing techniques, providing food testing laboratories with options for the characterization of isolates. The ability to determine markers of quaternary ammonium compound resistance such as bcrABC and epidemiologic lineage may provide risk managers with a tool to assess the potential for persistent contamination of the food manufacturing environment and the need for more targeted surveillance to ensure the efficacy of mitigation actions.
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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 | 0.001 |
| 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".