A streamlined procedure for advancing the detection and isolation of <i>Listeria monocytogenes</i> from artificially contaminated ground beef in a single working day
Bibliographic record
Abstract
ABSTRACT Listeria monocytogenes , a rod-shaped Gram-positive bacterium widely distributed in nature, can contaminate foods and represents a foodborne pathogen of public health significance causing a high mortality rate of 20%–30%. Rapid and reliable identification of foods and food-processing environments contaminated with L. monocytogenes is a crucial step in implementing effective intervention strategies to ensure food safety and limit the transmission of bacteria to humans. This study designed and refined a practical workflow to streamline and accelerate the detection of a low level of L. monocytogenes present in ground beef. The workflow coupled an abbreviated 5 h culture enrichment in PALCAM liquid medium with physical separation (filtration and centrifugation) to preprocess enrichment samples. Specific capture was achieved using magnetic separation with a bacteriophage endolysin-derived cell wall-binding domain in a Hyglos Listeria capture kit. Molecular detection was performed using a MicroSEQ L. monocytogenes RTi-PCR detection kit combined with a nested PCR strategy. Preprocessing of enrichment culture samples using a multi-stage filtration system constructed for the study or commercially available BagFilter Pull-up filter bags, in conjunction with centrifugation, enabled the recovery of ~30 colony-forming units (CFUs) from the enrichment culture of a 25 g ground beef sample artificially contaminated with 1 CFU of L. monocytogenes . Integration of magnetic separation into the workflow for capturing L. monocytogenes cells specifically from preprocessed samples and further cleaning up the samples yielded bacterial counts similar to those obtained by direct plating of preprocessed samples. The RTi-PCR-based molecular detection method integrated into the workflow was capable of detecting pure cultures of L. monocytogenes as low as 12.5 CFUs. Evaluation of the workflow using artificially ground beef demonstrated the consistent detection of L. monocytogenes within an 8 h workday in a 25 g sample unit containing the cell count as low as 2 CFU following a 5 h culture enrichment. IMPORTANCE Consuming foods contaminated with the bacterial pathogen Listeria monocytogenes can lead to the development of human listeriosis, a severe and life-threatening foodborne illness. Timely detection of L. monocytogenes present at a low level in foods and food processing environments is a necessary measure to prevent the spread of the Listeria -associated illness. This study designed and evaluated a multi-step workflow for testing L. monocytogenes in artificially contaminated food samples. The workflow was composed of a short 5 h culture enrichment, filtration-based sample preprocessing, magnetic separation, a single-tube nested RTi-PCR, and culture plating. It allowed L. monocytogenes to be detected within 8 h from a 25 g ground beef sample containing the target cells as low as 2 colony-forming units, significantly improving and streamlining the detection methods for this important foodborne pathogen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".