Cranberry-Derived Proanthocyanidin and Its Gut Microbial Metabolites Affect the Intestinal miRNome in a Distinct Manner In Vitro
Bibliographic record
Abstract
Polyphenols are emerging as novel prebiotic compounds. Cranberries are a rich source of polyphenols, such as proanthocyanidin (PAC), which has known benefits including anti-cancer properties. In the colon, PACs are catabolized by the gut microbiota into 3,4-dihydroxyphenylacetic acid (DHPAA) and 3-(4-hydroxyphenyl) propionic acid (HPPA), which may mediate prebiotic effects. Mechanisms are unknown but may involve host microRNA (miRNA). The objective of this study was to investigate the effects of nutritionally relevant doses of cranberry PAC, DHPAA, and HPPA on the human intestinal miRNome. Differentiated Caco-2BBe1 colonic epithelial cells, a morphologically homogenous subclone of Caco-2 cells, were treated with cranberry extract containing 94% PAC (Ocean Spray Cranberries, 50 μg/ml), DHPAA, HPPA (5 μg/ml) or control vehicle (Dulbecco's Modified Eagle Medium) for 24 hours. Experiments were repeated 3 times. Cell viability was assessed by fluorescence microscopy. Cell RNA was extracted and used for miRNA profiling via NanoString Technology. Data were processed and normalized in nSolverTM 4.0, statistics and hierarchical clustering were done with R and ClustVis. Gene targets were predicted with miRNet and pathway enrichment analysis was done in PathDIP. The treatments had no effect on cell viability. Of the 829 miRNAs assessed, 248 were expressed. Five miRNAs were differentially expressed among groups (ANOVA, P < 0.01; FDR < 5%). Unsupervised hierarchical clustering with these miRNAs revealed perfect separation based on treatment. These miRNAs were found to target 686 genes, enriched in 116 KEGG pathways including “miRNAs in cancer” and “pathways in cancer”. Treatment-specific responses included increased miR-2116-5p, miR-6721-5p, and miR-1290 for PAC, DHPAA, and HPPA, respectively. Pathways in glucagon signaling and central carbon metabolism in cancer were enriched in response to DHPPA only. Cranberry PAC and polyphenol metabolites at concentrations representing dietary intakes elicit different miRNA signatures in colonic cells, providing a novel mechanism to explain their effects on intestinal health. Cranberry-mediated miRNA modulation may represent a potential strategy for preventing chronic disease. NSERC, Ocean Spray Cranberries, Inc., NSERC Graduate Scholarship.
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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".