Protease-Mediated Suppression of DRG Neuron Excitability by Commensal Bacteria
Bibliographic record
Abstract
Peripheral pain signaling reflects a balance of pronociceptive and antinociceptive influences; the contribution by the gastrointestinal microbiota to this balance has received little attention. Disorders, such as inflammatory bowel disease and irritable bowel syndrome, are associated with exaggerated visceral nociceptive actions that may involve altered microbial signaling, particularly given the evidence for bacterial dysbiosis. Thus, we tested whether a community of commensal gastrointestinal bacteria derived from a healthy human donor (microbial ecosystem therapeutics; MET-1) can affect the excitability of male mouse DRG neurons. MET-1 reduced the excitability of DRG neurons by significantly increasing rheobase, decreasing responses to capsaicin (2 μ m ) and reducing action potential discharge from colonic afferent nerves. The increase in rheobase was accompanied by an increase in the amplitude of voltage-gated K + currents. A mixture of bacterial protease inhibitors abrogated the effect of MET-1 effects on DRG neuron rheobase. A serine protease inhibitor but not inhibitors of cysteine proteases, acid proteases, metalloproteases, or aminopeptidases abolished the effects of MET-1. The serine protease cathepsin G recapitulated the effects of MET-1 on DRG neurons. Inhibition of protease-activated receptor-4 (PAR-4), but not PAR-2, blocked the effects of MET-1. Furthermore, Faecalibacterium prausnitzii recapitulated the effects of MET-1 on excitability of DRG neurons. We conclude that serine proteases derived from commensal bacteria can directly impact the excitability of DRG neurons, through PAR-4 activation. The ability of microbiota-neuronal interactions to modulate afferent signaling suggests that therapies that induce or correct microbial dysbiosis may impact visceral pain. SIGNIFICANCE STATEMENT Commercially available probiotics have the potential to modify visceral pain. Here we show that secretory products from gastrointestinal microbiota derived from a human donor signal to DRG neurons. Their secretory products contain serine proteases that suppress excitability via activation of protease-activated receptor-4. Moreover, from this community of commensal microbes, Faecalibacterium prausnitzii strain 16-6-I 40 fastidious anaerobe agar had the greatest effect. Our study suggests that therapies that induce or correct microbial dysbiosis may affect the excitability of primary afferent neurons, many of which are nociceptive. Furthermore, identification of the bacterial strains capable of suppressing sensory neuron excitability, and their mechanisms of action, may allow therapeutic relief for patients with gastrointestinal diseases associated with pain.
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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 | 0.001 |
| 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".