PSVI-15 Transcriptome analysis of ileal lymph nodes identifies key microRNAs affecting disease progression in Holstein cows with subclinical Johne’s disease
Bibliographic record
Abstract
Abstract Johne’s disease (JD) is a chronic enteric disease of ruminants caused by Mycobacterium avium subsp. Paratuberculosis (MAP) but immune and metabolic mechanisms affecting JD progression have not been clearly elucidated. MicroRNAs (miRNA) have been reported to play important roles in numerous biological processes by regulating gene expression. In this study, miRNA expression in ileal lymph nodes (ILLN) from MAP positive (JD subclinical stage) Holstein cows (n = 5) and MAP negative cows (n = 5) were characterized by high throughput sequencing. MiRNA-sequence data was processed using a standard pipeline followed by functional enrichment with ClueGo app in Cytoscape. Among 324 expressed miRNAs, 37 were differently expressed (DE) (18 up-regulated and 19 down-regulated) in MAP infected cows relative to MAP negative cows. Bta-miR-100 (fold change = -2.29), a down-regulated miRNA, has previously been associated with Streptococcus uberis and MAP infections in cows, while bta-miR-330 (fold change = 63.42), the most up-regulated miRNA, was previously reported to be present in the sera of MAP infected calves. Predicted target genes of 37 DE miRNAs were enriched (P < 0.05) in gene ontology terms related to metabolic, cellular and developmental processes, and immune system development, as well as pathways related to cancer and Th17 cell differentiation, and lysosome compartmentalization. This suggests that miRNAs DE following MAP infection may be involved in regulating a wide variety of processes. In addition, 5 DE miRNAs were negatively correlated (P < 0.05) with 39 DE mRNAs (mRNAs expressed in the same tissue), comprising 42 negatively correlated DE miRNA-mRNA pairs. Bta-miR-2447 was negatively correlated with 29 DE mRNAs, suggesting it may be an important hub miRNA in the regulation of MAP infection in ILLN tissue. Our data thus suggest that bta-miR-100, bta-miR-330 and bta-miR-2447, which are implicated in the Th17 cell differentiation pathway, may be key regulators of the host response during MAP infection in ILLN.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".