Genomic characterization of Listeria monocytogenes recovered from dairy facilities in British Columbia, Canada from 2007 to 2017
Bibliographic record
Abstract
Listeria monocytogenes is a foodborne pathogen of concern in dairy processing facilities, with the potential to cause human illness and trigger regulatory actions if found in the product. Monitoring for Listeria spp. through environmental sampling is recommended to prevent establishment of these microorganisms in dairy processing environments, thereby reducing the risk of product contamination. To inform on L. monocytogenes diversity and transmission, we analyzed genome sequences of L. monocytogenes strains (n = 88) obtained through the British Columbia Dairy Inspection Program. Strains were recovered from five different dairy processing facilities over a 10 year period (2007–2017). Analysis of whole genome sequences (WGS) grouped the isolates into nine sequence types and 11 cgMLST types (CT). The majority of isolates (93%) belonged to lineage II. Within each CT, single nucleotide polymorphism (SNP) differences ranged from 0 to 237 between isolates. A highly similar (0–16 SNPs) cluster of over 60 isolates, collected over 9 years within one facility (#71), was identified suggesting a possible persistent population. Analyses of genome content revealed a low frequency of genes associated with stress tolerance, with the exception of widely disseminated cadmium resistance genes cadA1 and cadA2. The distribution of virulence genes and mutations within internalin genes varied across the isolates and facilities. Further studies are needed to elucidate their phenotypic effect on pathogenicity and stress response. These findings demonstrate the diversity of L. monocytogenes isolates across dairy facilities in the same region. Findings also showed the utility of using WGS to discern potential persistence events within a single facility over time.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".