Gut commensal microvesicles reproduce parent bacterial signals to host immune and enteric nervous systems
Bibliographic record
Abstract
Ingestion of a commensal bacteria, Lactobacillus rhamnosus JB-1, has potent immunoregulatory effects, and changes nerve-dependent colon migrating motor complexes (MMCs), enteric nerve function, and behavior. How these alterations occur is unknown. JB-1 microvesicles (MVs) are enriched for heat shock protein components such as chaperonin 60 heat-shock protein isolated from Escherichia coli (GroEL) and reproduce regulatory and neuronal effects in vitro and in vivo. Ingested labeled MVs were detected in murine Peyer's patch (PP) dendritic cells (DCs) within 18 h. After 3 d, PP and mesenteric lymph node DCs assumed a regulatory phenotype and increased functional regulatory CD4(+)25(+)Foxp3+ T cells. JB-1, MVs, and GroEL similarly induced phenotypic change in cocultured DCs via multiple pathways including C-type lectin receptors specific intercellular adhesion molecule-3 grabbing non-integrin-related 1 and Dectin-1, as well as TLR-2 and -9. JB-1 and MVs also decreased the amplitude of neuronally dependent MMCs in an ex vivo model of peristalsis. Gut epithelial, but not direct neuronal application of, MVs, replicated functional effects of JB-1 on in situ patch-clamped enteric neurons. GroEL and anti-TLR-2 were without effect in this system, suggesting the importance of epithelium neuron signaling and discrimination between pathways for bacteria-neuron and -immune communication. Together these results offer a mechanistic explanation of how Gram-positive commensals and probiotics may influence the host's immune and nervous systems.
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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".