Systematic evaluation and optimization of TaqMan qPCR assays targeting F <i>57</i> , ISMAP <i>02</i> , and IS <i>900</i> for multiplex detection of <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i>
Bibliographic record
Abstract
ABSTRACT This study aimed to develop a multiplex quantitative PCR (qPCR) assay for the detection of Mycobacterium avium subsp. paratuberculosis (MAP), the etiological agent of paratuberculosis disease, a chronic and endemic infectious disease affecting ruminant livestock worldwide. Infected animals may remain asymptomatic for years while intermittently shedding MAP into their environment through feces, contributing to ongoing transmission. To develop a robust multiplex qPCR assay, we reviewed all TaqMan qPCR studies published since 1990 and selected 18 primer-probe combinations targeting the MAP-specific F 57 gene and the repetitive sequence elements ISMAP 02 and IS 900 . In samples with moderate to high MAP levels, all combinations performed well, with only minor differences in analytical performance. However, in low-abundance samples, several TaqMan designs yielded unreliable results, indicating limited specificity in complex matrices. Among the evaluated assays, the IS 900 -Herthnek design demonstrated significantly higher diagnostic sensitivity, detecting MAP in 81% of low-abundance samples, compared to 0% and 3% for the IS 900 -Kim and IS 900 -Slana assays, respectively. For ISMAP 02 , only the ISMAP 02 -Sevilla assay produced reliable results. For F 57 , Herthnek provided the most consistent and accurate quantification. Similar trends were observed in environmental sample testing. Based on these findings, we recommend a multiplex qPCR assay incorporating the IS 900 -Herthnek, ISMAP 02 -Sevilla, and F 57 -Herthnek TaqMan designs for the detection of MAP in fecal and environmental samples. This combination offers high analytical sensitivity and specificity, making it a valuable and accurate tool for the diagnosis of paratuberculosis and for environmental surveillance on dairy farms to identify herds potentially harboring MAP-infected animals. IMPORTANCE Mycobacterium avium subsp. paratuberculosis (MAP) is the etiological agent of Johne’s disease (JD) in ruminant livestock industries and has been associated with Crohn’s disease in humans. Emerging scientific evidence also links MAP to other human conditions, including inflammatory bowel disease, autoimmune disorders, colorectal cancer, and Alzheimer’s disease. This potential public health threat has intensified interest in developing more sensitive diagnostic tools and effective control strategies to eradicate MAP from dairy herds. Infected ruminants typically remain in the subclinical stage of the disease for 2–5 years, during which they shed MAP in their feces and contaminate the environment. Diagnosis during this stage is particularly challenging, as the pathogen evades the host’s immune response, rendering serological tests insufficiently sensitive. In contrast, fecal PCR offers greater sensitivity than serum ELISA and traditional culture methods. Multiplex quantitative PCR is especially promising due to its high specificity and sensitivity for detecting MAP-infected animals and identifying herds with active shedders. Herd-level environmental screening, followed by individual animal testing, represents a robust national biosecurity strategy. This approach is a critical step toward reducing MAP transmission and improving herd health within the dairy industry.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".