Multiplex PCR detection of clinical and environmental strains of<i>Vibrio vulnificus</i>in shellfish
Bibliographic record
Abstract
In this study, we developed a PCR-based rapid detection method for clinically important pathogenic strains of Vibrio vulnificus. Positive amplification of the 504-bp viuB fragment was seen in all 22 clinical isolates tested but only in 8 out of 33 environmental isolates. The combination of the species-specific 205-bp vvh fragment along with viuB in a multiplexed PCR enabled us to confirm the presence of potentially pathogenic strains of V. vulnificus. No amplification of other Vibrio spp. or non-Vibrio bacteria was evidenced, suggesting a high specificity of detection by this method. The sensitivity of detection for both targeted genes was 10 pg of purified DNA, which correlated with 103V. vulnificus CFU in 1 mL of pure culture or 1 g un-enriched seeded oyster tissue homogenate. This sensitivity was improved to 1 CFU per gram of oyster tissue homogenate in overnight-enriched samples. A SYBR Green I based real-time PCR method was also developed that was shown to produce results consistent with the conventional PCR method. Application of the multiplexed real-time PCR to natural oyster tissue homogenates exhibited positive detection of vvh in 51% of the samples collected primarily during the summer months; however, only 15% of vvh positive samples exhibited viuB amplicons. The rapid, sensitive, and specific detection of clinically important pathogenic V. vulnificus in shellfish would be beneficial in reducing illnesses and deaths caused by this pathogen.Key words: Vibrio, multiplex PCR, shellfish, SYBR Green I, real-time PCR.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".