MicroRNAomes of Cattle Intestinal Tissues Revealed Possible miRNA Regulated Mechanisms Involved in Escherichia coli O157 Fecal Shedding
Bibliographic record
Abstract
Cattle have been suggested as the primary reservoirs of E. coli O157 mainly as a result of colonization of the recto-anal junction (RAJ) and subsequent shedding into the environment. Although a recent study reported different gene expression at RAJ between super-shedders (SS) and non-shedders (NS), the regulatory mechanisms of altered gene expression is unknown. This study aimed to investigate whether bovine non-coding RNAs play a role in regulating the differentially expressed (DE) genes between SS and NS, thus further influencing E. coli O157 shedding behavior in the animals through studying miRNAomes of the whole gastrointestinal tract including duodenum, proximal jejunum, distal jejunum, cecum, spiral colon, descending colon and rectum. The number of miRNAs detected in each intestinal region ranged from 390 ± 13 (duodenum) to 413 ± 49 (descending colon). Comparison between SS and NS revealed the number of differentially expressed (DE) miRNAs ranged from one (in descending colon) to eight (in distal jejunum), and through the whole gut, seven miRNAs were up-regulated and seven were down-regulated in SS. The distal jejunum and rectum were the regions where the most DE miRNAs were identified (eight and seven, respectively). The miRNAs, bta-miR-378b, bta-miR-2284j, and bta-miR-2284d were down-regulated in both distal jejunum and rectum of SS (log2fold-change: −2.7 to −3.8), bta-miR-2887 was down-regulated in the rectum of SS (log2fold-change: −3.2), and bta-miR-211 and bta-miR-29d-3p were up-regulated in the rectum of SS (log2fold-change: 4.5 and 2.2). Functional analysis of these miRNAs indicated their potential regulatory role in host immune functions, including hematological system development and immune cell trafficking. Our findings suggest that altered expression of miRNA in the gut of SS may lead to differential regulation of immune functions involved in E. coli O157 super-shedding in cattle.
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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".