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Record W3134881293 · doi:10.1093/jcag/gwab002.229

A231 THE MICROBIOTA-NOCICEPTORS-MICROGLIA AXIS CONTROLS THE DEVELOPMENT AND MAINTENANCE OF CHRONIC VISCERAL HYPERSENSITIVITY

2021· article· en· W3134881293 on OpenAlexaff
Nasser Abdullah, Christophe Altier

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNociceptorTRPV1MicrogliaDysbiosisVisceral painInflammationMedicineImmunologyChronic painMicrobiomePriming (agriculture)DiseaseGut floraNeuroscienceNociceptionBiologyTransient receptor potential channelBioinformaticsInternal medicineReceptor

Abstract

fetched live from OpenAlex

Abstract Background Pain is the most common cause of disability in inflammatory bowel disease (IBD). Current medical interventions control the debilitating clinical symptoms by reducing gastrointestinal (GI) inflammation. Despite successful treatment of active disease, abdominal pain persists during remission, suggesting a high level of plasticity in pain-sensing circuits (hyperalgesic priming) caused by inflammation. What drives this remodelling has remained elusive. We have identified microglia as active players of hyperalgesic priming in IBD. Furthermore, it was recently shown that commensal bacteria control the maturation of microglia in the CNS, suggesting that dysbiosis could influence visceral sensitivity through regulating colonic nociceptors-microglia interaction. Here we test the hypothesis that microbiome-nociceptors-microglia interactions control visceral sensitivity and pain in IBD. Aims We investigated the role of the microbiota in the developmental regulation of colonic nociceptors that express the pain receptor TRPV1. We will identify the microbial factors that control neuron-microglia interactions during bacterial colonization and post-inflammatory dysbiosis. Methods We have developed a germ-free TRPV1-GFP reporter mouse to be used for a combination of behavioural tests and phenotypic characterization of TRPV1+ nociceptors. RNA-sequencing of FACS isolated TRPV1+ neurons of germ-free mice will be used to identify genes that are under the control of the microbiota. We will restore discrepancies observed in germ-free mice by recolonization to assess the impact of the microbiota. Furthermore, we will investigate the regulation of Ahr in TRPV1+ neurons by the microbiota and the effect of its ligands on microglial activation and post-inflammatory visceral pain. Results Measuring somatic pain sensation in naive germ-free and SPF mice, we showed a 15% reduction in thermal pain threshold, as measured by the Hargreaves test, and a 50% reduction in mechanical pain threshold, as measured by the Von Frey test, in germ-free mice. When looking at the dorsal root ganglia of germ-free and SPF mice, we saw a 15% increase in the percentage of neurons that were TRPV1-GFP positive in germ-free mice. Conclusions Our results thus far highlight the importance of the microbiota in regulating the lineage of nociceptive neurons and the threshold of mechanical and thermal pain responses. These findings suggest a major contribution of the microbiota in shaping the neuro-immune axis, with major implications for visceral sensitization in the context of dysbiosis. My project will be looking further into the phenotype of nociceptors in germ-free mice and the effect of microbial-derived Ahr agonists on the maturation and function of colonic TRPV1+ nociceptors. My work will advance our understanding of mechanisms by which commensal bacteria regulate GI pain. Funding Agencies CIHR

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.027
GPT teacher head0.317
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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