Strain-specific Recovery of S. sonnei from Artificially Contaminated Baby Carrots: Enhancing Food-safety Investigations with a Customized Shigella Detection Method Based on Genomically predicted Antibiotic Resistance Traits
Bibliographic record
Abstract
Shigella spp. are Gram-negative gastrointestinal bacterial pathogens that cause bacillary dysentery or shigellosis in humans. Isolation of Shigella from outbreak-associated foods is often problematic due to the lack of selectivity of cultural enrichment broths. To facilitate Shigella recovery from foods, we have developed strain-specific enrichment media based on the genomically-predicted antimicrobial resistance (AMR) features of an outbreak-associated Shigella sonnei strain harboring resistance genes for streptomycin (STR) and trimethoprim (TMP). To assess performance of the method, baby carrots were artificially contaminated with the S. sonnei strain at low (2.4 CFU), medium (23.5 CFU), and high levels (235 CFU) along with 10-fold higher levels of a Shigella-inhibiting Escherichia coli strain. The target S. sonnei strain was successfully recovered from artificially-contaminated baby carrots when enriched in modified Tryptone Soya Broth (mTSB) supplemented with TMP, whereas Shigella was not recovered from Shigella broth (SB) or SB supplemented with STR. Quantitative PCR analysis indicated that supplementation of the enrichment broths with TMP or STR increased the relative proportion of S. sonnei in enrichment cultures, except at the lowest inoculation level for STR. Microbiome profiling of the baby carrot enrichment cultures conducted by 16S rRNA gene sequencing indicated that both SB-STR and mTSB-TMP repressed the growth of competing Enterobacteriaceae in the enrichment cultures, relative to SB without supplementation. Overall, improved Shigella recovery was achieved with the addition of the appropriate custom selective agent during cultural enrichments demonstrating that genomically informed custom selective enrichment of Shigella could be a valuable tool for supporting future foodborne shigellosis outbreak investigations.
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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 | 0.001 | 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".