Validation of the Applied Biosystems RapidFinder Shiga Toxin–Producing E. coli (STEC) Detection Workflow
Bibliographic record
Abstract
The Applied Biosystems™ RapidFinder™ STEC Detection Workflow (Thermo Fisher Scientific) is a complete protocol for the rapid qualitative detection of Escherichia coli (E. coli) O157:H7 and the "Big 6" non-O157 Shiga-like toxin-producing E. coli (STEC) serotypes (defined as serogroups: O26, O45, O103, O111, O121, and O145). The RapidFinder STEC Detection Workflow makes use of either the automated preparation of PCR-ready DNA using the Applied Biosystems PrepSEQ™ Nucleic Acid Extraction Kit in conjunction with the Applied Biosystems MagMAX™ Express 96-well magnetic particle processor or the Applied Biosystems PrepSEQ Rapid Spin kit for manual preparation of PCR-ready DNA. Two separate assays comprise the RapidFinder STEC Detection Workflow, the Applied Biosystems RapidFinder STEC Screening Assay and the Applied Biosystems RapidFinder STEC Confirmation Assay. The RapidFinder STEC Screening Assay includes primers and probes to detect the presence of stx1 (Shiga toxin 1), stx2 (Shiga toxin 2), eae (intimin), and E. coli O157 gene targets. The RapidFinder STEC Confirmation Assay includes primers and probes for the "Big 6" non-O157 STEC and E. coli O157:H7. The use of these two assays in tandem allows a user to detect accurately the presence of the "Big 6" STECs and E. coli O157:H7. The performance of the RapidFinder STEC Detection Workflow was evaluated in a method comparison study, in inclusivity and exclusivity studies, and in a robustness evaluation. The assays were compared to the U.S. Department of Agriculture (USDA), Food Safety and Inspection Service (FSIS) Microbiology Laboratory Guidebook (MLG) 5.09: Detection, Isolation and Identification of Escherichia coli O157:H7 from Meat Products and Carcass and Environmental Sponges for raw ground beef (73% lean) and USDA/FSIS-MLG 5B.05: Detection, Isolation and Identification of Escherichia coli non-O157:H7 from Meat Products and Carcass and Environmental Sponges for raw beef trim. No statistically significant differences were observed between the reference method and the individual or combined kits forming the candidate assay using either of the DNA preparation kits (manual or automated extraction). For the inclusivity and exclusivity evaluation, the RapidFinder STEC Detection Workflow, comprising both RapidFinder STEC screening and confirmation kits, correctly identified all 50 target organism isolates and correctly excluded all 30 nontarget strains for both of the assays evaluated. The results of these studies demonstrate the sensitivity and selectivity of the RapidFinder STEC Detection Workflow for the detection of E. coli O157:H7 and the "Big 6" STEC serotypes in both raw ground beef and beef trim. The robustness testing demonstrated that minor variations in the method parameters did not impact the accuracy of the assay and highlighted the importance of following the correct incubation temperatures.
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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 | 0.048 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.019 |
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".