Comparison of commercial DNA extraction kits and quantitative PCR systems for better sensitivity in detecting the causative agent of paratuberculosis in dairy cow fecal samples
Bibliographic record
Abstract
Mycobacterium avium ssp. paratuberculosis (MAP) causes ruminant paratuberculosis (Johne's disease) worldwide. Oral-fecal contamination is the most important mode of transmission of paratuberculosis, so eradicating MAP-shedding animals could prevent disease propagation. Fecal culture, a well-known method for MAP diagnosis, requires costly specialized media and a long incubation time that sometimes ends in disappointing bacterial contamination. To facilitate the efforts of control programs, we evaluated the performance of direct fecal quantitative PCR (qPCR) assays for their sensitivity and robustness for MAP detection. Commercial kits use different strategies for extracting DNA, combined with qPCR systems, to detect the presence of MAP in fecal samples. In this study, we compared the sensitivity of 3 commercially available DNA extraction kits (A, B, and C) combined with 2 qPCR systems (T and V) for the detection of MAP in infectious cows. A total of 49 dairy cows from 5 herds were sampled twice a year for 3 yr and diagnosed using fecal culture and ELISA. Eight replicates of their fecal samples from the first sampling were tested using each DNA extraction method and qPCR detection system. Although all 3 of the commercial DNA extraction kits have been previously described as very efficient for the diagnosis of paratuberculosis, kit B provided the highest sensitivity. Indeed, 89% of the cows declared positive for paratuberculosis by both fecal culture and ELISA were identified with kit B, whereas only 23 and 43% of the cows were identified with kits A and C, respectively. Interestingly, kit B was able to detect some low-MAP shedders. The qPCR detection system also played a critical role: system T yielded qPCR with the highest sensitivity. The results of this study suggest that DNA extraction kit B combined with detection system T provides the best amplification of MAP DNA from fecal samples with the highest sensitivity and specificity. Although 1 DNA extraction and qPCR analysis should be adequate to confirm that an animal with diarrhea or other signs of paratuberculosis is positive, detecting low shedders at the highest sensitivity should include repetitive testing. This study demonstrates the importance of repetitions using the most appropriate method for extracting DNA from fecal samples, combined with a compatible qPCR system for identifying MAP-shedding animals.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".