Protease‐dependent excitation of nodose ganglion neurons by commensal gut bacteria
Bibliographic record
Abstract
Key points The vagus nerve has been implicated in mediating behavioural effects of the gut microbiota on the central nervous system. This study examined whether the secretory products of commensal gut bacteria can modulate the excitability of vagal afferent neurons with cell bodies in nodose ganglia. Cysteine proteases from commensal bacteria increased the excitability of vagal afferent neurons via activation of protease‐activated receptor 2 and modulation of the voltage dependence of Na+ conductance activation. Lipopolysaccharide, a component of the cell wall of gram‐negative bacteria, increased the excitability of nodose ganglia neurons via TLR4‐dependent activation of nuclear factor kappa B. Our study identified potential mechanisms by which gut microbiota influences the activity of vagal afferent pathways, which may in turn impact on autonomic reflexes and behaviour. Abstract Behavioural studies have implicated vagal afferent neurons as an important component of the microbiota‐gut‐brain axis. However, the mechanisms underlying the ability of the gut microbiota to affect vagal afferent pathways are unclear. We examined the effect of supernatant from a community of 33 commensal gastrointestinal bacterial derived from a healthy human donor (microbial ecosystem therapeutics; MET‐1) on the excitability of mouse vagal afferent neurons. Perforated patch clamp electrophysiology was used to measure the excitability of dissociated nodose ganglion (NG) neurons. NG neuronal excitability was assayed by measuring the amount of current required to elicit an action potential, the rheobase. MET‐1 supernatant increased the excitability of NG neurons by hyperpolarizing the voltage dependence of activation of Na+ conductance. The increase in excitability elicited by MET‐1 supernatant was blocked by the cysteine protease inhibitor E‐64 (30 nm). The protease activated receptor‐2 (PAR2) antagonist (GB 83, 10 μm) also blocked the effect of MET‐1 supernatant on NG neurons. Supernatant from Lactobacillus paracasei 6MRS, a component of MET‐1, recapitulated the effect of MET‐1 supernatant on NG neurons. Lastly, we compared the effects of MET‐1 supernatant and lipopolysaccharide (LPS) from Escherichia coli 05:B5 on NG neuron excitability. LPS increased the excitability of NG neurons in a toll‐like receptor 4 (TLR4)‐dependent and PAR2‐independent manner, whereas the excitatory effects of MET‐1 supernatant were independent of TLR4 activation. Together, our findings suggest that cysteine proteases from commensal bacteria increase the excitability of vagal afferent neurons by the activation of PAR2.
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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".