Whole genome sequencing reveals genetic diversity in Mycobacterium avium subspecies paratuberculosis population circulating in Irish cattle
Bibliographic record
Abstract
Mycobacterium avium subspecies paratuberculosis (MAP) causes Johne’s Disease (JD), a chronic enteritis, in cattle. Whole genome sequencing (WGS) has been applied to many pathogen systems, where its unprecedented resolution has greatly enhanced our understanding of the molecular epidemiology of pathogen transmission. However, WGS has seen limited application to MAP; understanding the transmission dynamics of MAP will inform control of JD. We report the first study into the application of WGS to MAP in Ireland. DNA was extracted from 167 MAP isolates sourced from cattle across Ireland. Libraries were prepared and sequenced on an Illumina-NextSeq500 platform. Sequencing data were processed using an in-house bioinformatic pipeline, which trimmed reads, aligned them to the reference genome MAP K10, followed by variant calling, quality filtering and construction of a maximum-likelihood phylogeny. DNA extracts were also used for MIRU-VNTR typing. The resulting phylogeny shows that the MAP population present in Irish cattle is genetically diverse, which may have resulted from importation of MAP strains from across Europe into Ireland. Similar diversity was observed in a WGS study that noted the impact of cattle imports on the Canadian MAP population. Some Irish isolates were genetically similar to European and Canadian isolates. Comparing our WGS data with MIRU-VNTR indicates that MIRU-VNTR has limited resolution for discriminating MAP strains, and often does not distinguish isolates to sufficient resolution. The genomic data presented here provide the first snapshot of genetic diversity of Irish MAP and a baseline for future studies into spread and persistence of MAP in Irish cattle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".