Limit of detection of <i>Salmonella</i> ser. Enteritidis using culture-based versus culture-independent diagnostic approaches
Bibliographic record
Abstract
ABSTRACT To prevent the spread of foodborne illnesses, the presence of pathogens in the food chain is monitored by government agencies and food producers. The culture-based methods currently employed are sensitive but time- and labor-intensive, leading to increasing interest in exploring culture-independent diagnostic tests (CIDTs) for pathogen detection. However, few studies quantify the relative sensitivity and reliability of these CIDTs compared to current approaches. To address this issue, we conducted a comparison of the limit of detection (LOD 50 ) for Salmonella between a culture-based method and three CIDTs: qPCR (targeting invA and stn ), metabarcode (16S) sequencing, and shotgun metagenomic sequencing. Samples of chicken feed and chicken caecal contents were spiked with S . serovar Enteritidis and subjected to culture- and DNA-based detection methods. To explore the impact of non-selective enrichment on LOD 50 , all samples underwent both immediate DNA extraction and overnight enrichment prior to gDNA extraction. In addition to this spike-in experiment, feed and caecal samples acquired from the field were tested with culturing, qPCR, and metabarcoding. In general, LOD 50 was comparable between qPCR and shotgun sequencing methods. Overnight microbiological enrichment resulted in an improvement in LOD 50 with up to a three-log decrease. However, Salmonella reads were detected in some unspiked feed samples, suggesting false-positive detection of Salmonella . In addition, the LOD 50 in feeds was three logs lower than in caecal contents, underscoring the impact of background microbiota on Salmonella detection using all methods. IMPORTANCE The appeal of culture-independent diagnostic tests (CIDTs) is increased speed with lowered cost, as well as the potential to detect multiple pathogen species in a single analysis and to monitor other areas of concern such as antimicrobial resistance genes or virulence factors. This study provides quantitative data on the sensitivity of CIDTs relative to current approaches, which is essential for determining the feasibility of implementing these methods in pathogen surveillance programs.
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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".