A secondary metabolite of Limosilactobacillus reuteri R2lc drives strain-specific pathology in a spontaneous mouse model of multiple sclerosis
Bibliographic record
Abstract
Limosilactobacillus reuteri is an immunomodulatory bacterium enriched in non-industrialized microbiomes, making it a therapeutic candidate for chronic diseases. However, effects of L. reuteri strains in mouse models of multiple sclerosis have been contradictory. Here, we show that treatment of spontaneous relapsing-remitting experimental autoimmune encephalomyelitis (EAE) mice with L. reuteri R2lc, a strain that activates the aryl hydrocarbon receptor (AhR) through the pks gene cluster, resulted in severe pathology. In contrast, a pks mutant and a pks-negative strain (PB-W1) failed to exacerbate EAE and exhibited reduced pathology compared to R2lc despite earlier disease onset in PB-W1 mice. Differences in pathology occurred in parallel with a pks-dependent downregulation of AhR-related genes, reduced occludin expression in the forebrain, and altered concentrations of immune cells. This work establishes a molecular foundation for strain-specific effects on autoimmunity, which has implications for our understanding of how microbes contribute to chronic conditions and the selection of microbial therapeutics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".