Profiling the rainbow trout hepatic miRNAome under diet-induced hyperglycemia
Bibliographic record
Abstract
Carnivorous rainbow trout exhibit prolonged postprandial hyperglycemia when fed a diet exceeding 20% carbohydrate content. This poor capacity to utilize carbohydrates has led to rainbow trout being classified as “glucose-intolerant” (GI). The metabolic phenotype has spurred research to identify the underlying cellular and molecular mechanisms of glucose intolerance, largely because carbohydrate-rich diets provide economic and ecological advantages over traditionally used fish meal, considered unsustainable for rainbow trout aquaculture operations. Evidence points to a contribution of hepatic intermediary carbohydrate and lipid metabolism, as well as upstream insulin signaling. Recently, microRNAs (miRNAs), small noncoding RNAs acting as negative posttranscriptional regulators affecting target mRNA stability and translation, have emerged as critical regulators of hepatic control of glucose-homeostasis in mammals, revealing that dysregulated hepatic miRNAs might play a role in organismal hyperglycemia in metabolic disease. To determine whether hepatic regulatory miRNA networks may contribute to GI in rainbow trout, we induced prolonged postprandial hyperglycemia in rainbow trout by using a carbohydrate-rich diet and profiled genome-wide hepatic miRNAs in hyperglycemic rainbow trout compared with fasted trout and trout fed a diet devoid of carbohydrates. Using small RNA next-generation sequencing and real-time RT-PCR validation, we identified differentially regulated hepatic miRNAs between these groups and used an in silico approach to predict bona fide mRNA targets and enriched pathways. Diet-induced hyperglycemia resulted in differential regulation of hepatic miRNAs compared with fasted fish. Some of the identified miRNAs, such as miRNA-27b-3p and miRNA-200a-3p, are known to be responsive to hyperglycemia in the liver of hyperglycemic glucose-tolerant fish and mammals, suggesting an evolutionary conserved regulation. Using Gene Ontology term-based enrichment analysis, we identify intermediate carbohydrate and lipid metabolism and insulin signaling as potential targets of posttranscriptional regulation by hyperglycemia-regulated miRNAs and provide correlative expression analysis of specific predicted miRNA-target pairs. This study identifies hepatic miRNAs in rainbow trout that exhibit differential postprandial expression in response to diets with different carbohydrate content and predicts posttranscriptionally regulated target mRNAs enriched for pathways involved in glucoregulation. Together, these results provide a framework for testable hypotheses of functional involvement of specific hepatic miRNAs in GI in rainbow trout.
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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".