The role of interleukin-10 receptor alpha (IL10Rα) in Mycobacterium avium subsp. paratuberculosis infection of a mammary epithelial cell line
Bibliographic record
Abstract
BACKGROUND: Johne's disease is a chronic wasting disease caused by the bacterium Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease is highly contagious and MAP infection in dairy cattle can eventually lead to death. With no available treatment for Johne's disease, genetic selection and improvements in management practices could help reduce its prevalence. In a previous study, the gene coding interleukin-10 receptor subunit alpha (IL10Rα) was associated with Johne's disease in dairy cattle. Our objective was to determine how IL10Rα affects the pathogenesis of MAP by examining the effect of a live MAP challenge on a mammary epithelial cell line (MAC-T) that had IL10Rα knocked out using CRISPR/cas9. The wild type and the IL10Rα knockout MAC-T cell lines were exposed to live MAP bacteria for 72 h. Thereafter, mRNA was extracted from infected and uninfected cells. Differentially expressed genes were compared between the wild type and the IL10Rα knockout cell lines. Gene ontology was performed based on the differentially expressed genes to determine which biological pathways were involved. RESULTS: Immune system processes pathways were targeted to determine the effect of IL10Rα on the response to MAP infection. There was a difference in immune response between the wild type and IL10Rα knockout MAC-T cell lines, and less difference in immune response between infected and not infected IL10Rα knockout MAC-T cells, indicating IL10Rα plays an important role in the progression of MAP infection. Additionally, these comparisons allowed us to identify other genes involved in inflammation-mediated chemokine and cytokine signalling, interleukin signalling and toll-like receptor pathways. CONCLUSIONS: Identifying differentially expressed genes in wild type and ILR10α knockout MAC-T cells infected with live MAP bacteria provided further evidence that IL10Rα contributes to mounting an immune response to MAP infection and allowed us to identify additional potential candidate genes involved in this process. We found there was a complex immune response during MAP infection that is controlled by many genes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".