Identification of a muropeptide precursor transporter from gut microbiota and its role in preventing intestinal inflammation
Bibliographic record
Abstract
The gut microbiota is a considerable source of biologically active compounds that can promote intestinal homeostasis and improve immune responses. Here, we used large expression libraries of cloned metagenomic DNA to identify compounds able to sustain an anti-inflammatory reaction on host cells. Starting with a screen for NF-κB activation, we have identified overlapping clones harbouring a heterodimeric ATP-binding cassette (ABC)-transporter from a Firmicutes. Extensive purification of the clone's supernatant demonstrates that the ABC-transporter allows for the efficient extracellular accumulation of three muropeptide precursor, with anti-inflammatory properties. They induce IL-10 secretion from human monocyte-derived dendritic cells and proved effective in reducing AIEC LF82 epithelial damage and IL-8 secretion in human intestinal resections. In addition, treatment with supernatants containing the muropeptide precursor reduces body weight loss and improves histological parameters in Dextran Sulfate Sodium (DSS)-treated mice. Until now, the source of peptidoglycan fragments was shown to come from the natural turnover of the peptidoglycan layer by endogenous peptidoglycan hydrolases. This is a report showing an ABC-transporter as a natural source of secreted muropeptide precursor and as an indirect player in epithelial barrier strengthening. The mechanism described here might represent an important component of the host immune homeostasis.
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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".