A Budding Relationship: Bacterial Extracellular Vesicles in the Microbiota-Gut-Brain Axis
Bibliographic record
Abstract
The discovery of the microbiota-gut-brain axis has revolutionized our understanding of systemic influences on brain function and may lead to novel therapeutic approaches to neurodevelopmental and mood disorders. A parallel revolution has occurred in the field of intercellular communication, with the realization that endosomes, and other extracellular vesicles, rival the endocrine system as regulators of distant tissues. These two paradigms shifting developments come together in recent observations that bacterial membrane vesicles contribute to inter-kingdom signaling and may be an integral component of gut microbe communication with the brain. In this short review we address the current understanding of the biogenesis of bacterial membrane vesicles and the roles they play in the survival of microbes and in intra and inter-kingdom communication. We identify recent observations indicating that bacterial membrane vesicles, particularly those derived from probiotic organisms, regulate brain function. We discuss mechanisms by which bacterial membrane vesicles may influence the brain including interaction with the peripheral nervous system, and modulation of immune activity. We also review evidence suggesting that, unlike the parent organism, gut bacteria derived membrane vesicles are able to deliver cargo, including neurotransmitters, directly to the central nervous system and may thus constitute key components of the microbiota-gut-brain axis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".