Relative frequency of 4 major strain types of Mycobacterium avium ssp. paratuberculosis in Canadian dairy herds using a novel single nucleotide polymorphism-based polymerase chain reaction
Bibliographic record
Abstract
Johne's disease is a worldwide concern, as it causes huge economic losses. The etiological agent, Mycobacterium avium ssp. paratuberculosis (MAP), has limited genetic diversity, impeding efforts to understand transmission and distribution of strain types. Whole-genome sequencing was previously performed on a representative set of MAP isolates from Canadian dairy herds and 9 divergent clades were identified. Four clades were of particular interest, as they were either MAP types rarely reported in North America, or they represented a substantial proportion of isolates recovered from dairy farms in Canada. One clade included type I/III isolates, whereas the remaining clades included type II isolates. Variant sites in the MAP genome are often separated by thousands of base pairs, limiting use of single nucleotide polymorphism (SNP)-based genotyping on a single genomic region. Therefore, a SNP-PCR assay was developed to facilitate interrogation of 5 SNP in 2 distant regions of the genome, linking them together in a single PCR reaction for subsequent Sanger sequencing. This high-throughput assay enabled discrimination of 602 MAP isolates from 264 herds (from all 10 provinces). More than 1 isolate was cultured from 133 herds, 14 of which included multiple subtypes. A previously identified dominant type included 87% of isolates, whereas the Bison type was more widespread than previously reported. The latter type and isolates from a second clade of interest were overrepresented in Québec and Saskatchewan, respectively. In conclusion, the distribution and relative frequency of MAP subtypes within Canadian dairy herds were assessed using a novel SNP-based typing assay. These findings will contribute to understanding the clinical relevance and transmission dynamics of MAP in this population and elsewhere.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".