PSVI-14 Differentially expressed microRNAs with potential regulatory roles in ileum of Holstein cows with subclinical Johne’s disease
Bibliographic record
Abstract
Abstract Paratuberculosis or Johne’s disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic inflammatory disorder of the intestinal tract of ruminants. The mechanisms of JD pathogenesis remain unclear but MAP can cause chronic inflammatory lesions in the terminal small intestine of cattle. Using microRNA (miRNA) transcriptome analysis, this study investigated the impact of MAP infection on miRNA expression and their potential regulatory roles in JD progression. Ileal tissues were collected from MAP infected Holstein cows (n = 5) and healthy cows (n = 5). Purified total RNA were used to construct libraries followed by next generation sequencing, bioinformatic processing using a standard pipeline, differential miRNA expression analysis with DESeq2 software, and functional enrichment with ClueGo app in Cytoscape. A total of 269 miRNAs were expressed in ileal tissue including three abundantly expressed miRNAs (Bta-miR-143; 54.05% of total read counts), bta-miR-145 (11.54%) and bta-miR-192 (4.31%)). Twenty miRNAs were significantly (P < 0.05) differently expressed (DE) when comparing ileal tissues from MAP infected and uninfected cows. Bta-miR-383 (fold change = -12.93) and bta-miR-1842 (fold-change = 8.17) were the most down- and up-regulated miRNAs, respectively. Amongst the DE miRNAs, bta-miR-146a, bta-miR-146b and bta-miR-393 are inflammation-related miRNAs and considered potential biomarkers of bovine mastitis and other diseases, while bta-miR-370 and bta-miR-383 are associated with lipid metabolism. The predicted target genes of DE miRNAs were enriched (P < 0.05) for gene ontology terms related to regulation of metabolic, cell and developmental processes, and immune system development. KEGG pathway analysis revealed potential involvement in immune regulation (e.g. T-cell receptor signaling and C-type lectin receptor signaling pathways) and pathways in cancer were also enriched (P < 0.05). Our results indicate that some DE miRNAs play important roles by regulating metabolism and immune processes during JD and provide DE miRNAs that might form targets for future development of intervention measures.
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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) | 0.001 | 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".