63 DNA methylome wide profile associates differentially methylated loci and regions with cow’s ileal lymph node response to Mycobacterium avium subsp. paratuberculosis
Bibliographic record
Abstract
Abstract Johne’s Disease (JD), caused by Mycobacterium avim spp paratuberculosis (MAP), is a chronic and incurable disease of ruminants with devastating consequences to the dairy industry. MAP can alter the expression of genes and biological processes during the progression of JD. While some studies have examined the role of gene expression regulators like microRNA in the pathogenesis of JD, no study has explored the role of DNA methylation. This study therefore examined the effect of MAP on DNA methylation profile in the ileum lymph node (ILLN) of cows with subclinical MAP infection. DNA from ILLN tissues from five cows positive for MAP (MAP positive) and five negative cows (MAP negative) were extracted and subjected to whole genome bisulfite sequencing and bioinformatics analysis. A total of 6,394 differentially methylated cytosines (DMCs) and 3,946 differentially methylated regions (DMRs) (FDR < 0.05) were identified between MAP positive and negative cows. DMRs were annotated to 2,488 genes, including the promoters of 238 genes. Some genes with hypermethylated promoters like GRB10, EIF4E, SLC30A3, SOX30 or hypomethylated promoters like SLC11A1, HOXA4, SLC18A1 have been associated with JD or mycobacterial infections in cattle and/or humans. Functional annotation of DMR genes indicated enrichment in pathways previously associated with JD or human diseases with similar pathological conditions as JD, such as T/B cell receptor signaling pathway, Th17 cell differentiation, Cell adhesion molecules, Leukocyte transendothelial migration, HIF-1 signaling pathway and Chagas disease. Furthermore, enriched gene ontology terms like negative regulation of immune system process, negative regulation of cytokine secretion/production and negative regulation of inflammatory response suggest that MAP prevented or reduced the host immune response. Our data demonstrate that DNA methylation changes contribute to regulation of host immune responses to MAP infection and may be one of the mechanisms that MAP uses to subvert host immune responses for its long-term survival.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".