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Record W3007605981 · doi:10.1093/jcag/gwz047.041

A42 MICROBIAL METABOLISM OF DIETARY TRYPTOPHAN ENHANCES ARYL HYDROCARBON RECEPTOR ACTIVATION: IMPLICATIONS FOR IBD

2020· article· en· W3007605981 on OpenAlexaff
L Rondeau, Alexandra Clarizio, Jennifer Jury, D L Gibson, P Bercík, Harry Sokol, A Caminero Fernandez

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusMcMaster University
Fundersnot available
KeywordsAryl hydrocarbon receptorImmune systemColitisInflammatory bowel diseaseGut floraPathogenesisBiologyImmunologyMucinMicrobiologyChemistryInternal medicineMedicineBiochemistryTranscription factorDisease

Abstract

fetched live from OpenAlex

Abstract Background Intestinal immune homeostasis is maintained by the interplay between microbiota and the mucosal immune system. Changes in gut microbiota have been associated with chronic intestinal conditions, such as inflammatory bowel disease (IBD). The aryl hydrocarbon receptor (AhR) is a transcription factor that is activated by dietary and environmental stimuli to control immune responses in the gut and homeostatic mechanisms at mucosal surfaces. In IBD, AhR expression is downregulated. Major agonists of AhR in the gut include microbial tryptophan metabolites such as indole derivatives, which are decreased in IBD patients. The mechanisms involved in tryptophan metabolism by bacteria and their implications in AhR activation and thus IBD pathogenesis are not well understood. Aims To investigate whether tryptophan metabolism by intestinal bacteria participates in AhR activation and IBD pathogenesis. Methods Microbiota profiles (16S rRNA Illumina) and activation of AhR (luciferase reporter assay) were determined in fecal samples from IBD patients (n=10) and healthy volunteers (n=10). Germ-free C57BL/6 mice were colonized with fecal slurries of 2 healthy subjects and 4 IBD patients (n=4 mice/donor) by oral gavage (humanized-mice). All mice were fed irradiated tryptophan diets with 0.1% or 1% tryptophan content for 14 days. Simultaneously, SPF Mucin 2 (Muc2) deficient mice (C57BL/6 background), which develop colitis spontaneously, were fed tryptophan diets (0.1%, 0.3% and 1% content). Activation of AhR was measured in feces using an AhR luciferase reporter assay. Inflammation was determined by immunohistochemistry and the characterization of immune infiltrate in colon cross-sections. Bacteria from human and mouse fecal samples were isolated and screened for their ability to produce indoles using biochemical reagents. Positive bacteria were identified by colony PCR and 16S rRNA Sanger sequencing. Results IBD patients had an altered fecal microbiota with a lower capacity to activate AhR compared to healthy subjects. Colonization of mice with microbiota from healthy subjects induced greater activation of AhR compared to mice colonized with microbiota from patients with IBD. Furthermore, increasing dietary tryptophan composition rescued the capacity to activate AhR. In Muc2 deficient mice, dietary tryptophan treatment enhanced AhR activation capacity and reduced infiltration of innate immune cells before the onset of colitis. Several AhR agonist producing bacterial species were identified and will be used in future experiments. Conclusions Activation of AhR is dependent on the gut microbiota and disease status of the donor. Dietary intervention with tryptophan enhances AhR activation capacity and may be a potential therapeutic avenue in IBD individuals with intestinal dysbiosis. Funding Agencies Farncombe Family Digestive Health Research Institute, Biocodex Microbiota Foundation

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.239
Teacher spread0.227 · 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 designObservational
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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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