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Record W2550597737 · doi:10.3168/jds.2016-11384

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

2016· article· en· W2550597737 on OpenAlexafffund
D. Fock-Chow-Tho, Edward Topp, E.A. Ibeagha-Awemu, Nathalie Bissonnette

Bibliographic record

VenueJournal of Dairy Science · 2016
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversité de SherbrookeAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsParatuberculosisFecesDNA extractionExtraction (chemistry)BiologyDairy cattleReal-time polymerase chain reactionFood scienceVeterinary medicinePolymerase chain reactionMicrobiologyChromatographyChemistryAnimal scienceMedicineBacteriaGeneticsMycobacterium

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.113
GPT teacher head0.407
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2016
Admission routes2
Has abstractyes

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