Structure–Function Relationships of Human Milk Oligosaccharides on the Intestinal Epithelial Transcriptome in Caco‐2 Cells and a Murine Model of Necrotizing Enterocolitis
Bibliographic record
Abstract
SCOPE: Necrotizing enterocolitis (NEC) is a devastating gastrointestinal emergency affecting preterm infants. Breastmilk protects against NEC, partly due to human milk oligosaccharides (HMOs). HMO compositions are highly diverse, and it is unclear if anti-NEC properties are specific to carbohydrate motifs. Here, this study compares intestinal epithelial transcriptomes of five synthetic HMOs (sHMOs) and examines structure-function relationships of HMOs on intestinal signaling. METHODS AND RESULTS: This study interrogates the transcriptome of Caco-2Bbe1 cells in response to five synthetic HMOs (sHMOs) using RNA sequencing: 2'-fucosyllactose (2'-FL), 3-fucosyllactose (3FL), 6'-siallyllactose (6'-SL), lacto-N-tetraose (LNT), lacto-N-neotetraose (LNnT). Protection against intestinal barrier dysfunction and inflammation occurred in an HMO-dependent manner. Each sHMO exerts a unique set of host transcriptome changes and modulated unique signaling pathways. There is clustering between HMOs bearing similar side chains, with little overlap in gene regulation which is shared by all sHMOs. Interestingly, most sHMOs protect pups against NEC, exerting divergent mechanisms on intestinal cell morphology and inflammation. CONCLUSIONS: These results demonstrate that while structurally distinct HMOs impact intestinal physiology, their mechanisms of action differ. This finding establishes the first structure-function relationship of HMOs in the context of intestinal cell signaling responses and offers a functional framework by which to screen and design HMO-like compounds.
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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".