Highly Sensitive and Specific PCR Assay for Reliable Detection of <i>Cyclospora cayetanensis</i> Oocysts
Bibliographic record
Abstract
Multiple outbreaks of food-borne gastroenteritis caused by the coccidian parasite Cyclospora cayetanensis have been reported annually in North America since 1995. Detection of C. cayetanensis contamination typically relies on laborious and subjective microscopic examination of produce washes. Molecular detection methods based on nested PCR, restriction fragment length polymorphism, or multiplex PCR have been developed for C. cayetanensis; however, they have not been adequately validated for use on food products. Further challenges include reliably extracting DNA from coccidian oocysts since their tough outer wall is resistant to lysis and overcoming PCR inhibitors in sample matrices. We describe preliminary validation of a reliable DNA extraction method for C. cayetanensis oocysts and a sensitive and specific novel PCR assay. The sensitivity and repeatability of the developed methods were evaluated by multiple DNA extractions and PCR amplifications using 1,000-, 100-, 10-, or 1-ooycst aliquots of C. cayetanensis oocysts in water or basil wash sediment. Successful PCR amplification was achieved on 15 and 5 replicates extracted from aliquots containing 1,000 oocysts in water and basil wash, respectively. All 45 replicates of the 100-oocyst aliquots in water and 5 in basil wash were amplified successfully, as were 43/45 and 41/45 of the 10- and 1-oocyst aliquots in water and 9/15 and 2/15 in basil wash, respectively. The developed primers showed no cross-reactivity when tested against bacteria, nematodes, and protozoans, including Eimeria, Giardia, and Cryptosporidium. Our results indicate that these methods are specific, can reliably detect a single oocyst, and overcome many of the limitations of microscopic diagnosis.
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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 | 0.001 |
| 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".