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Record W4213194554 · doi:10.1093/jcag/gwab049.046

A47 MICROBIAL FUNCTIONS AS BIOMARKERS OF PRO-INFLAMMATORY RESPONSE TO SELECT DIETARY FIBERS IN IBD

2022· article· en· W4213194554 on OpenAlexaff
Heather Armstrong, Michael Bording‐Jorgensen, Rosica Valcheva, Zhengxiao Zhang, Juan Jovel, A Petrova, Matthew Carroll, Hien Q. Huynh, Levinus A. Dieleman, Eytan Wine

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEx vivoFructanFermentationInflammatory bowel diseaseImmune systemIn vivoUlcerative colitisGut floraCrohn's diseaseMicrobiologyInulinBiologyCytokinePrebioticFecesImmunologyFood scienceMedicineDiseaseInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

Abstract Background Dietary fibers are not digested in the bowel; they are fermented by microbes, typically promoting gut health. However, IBD patients experience sensitivity to consumption of fibers. Our previous findings offered the first mechanistic evidence demonstrating that unfermented dietary β-fructans (inulin and FOS) can induce pro-inflammatory cytokines in a subset of pediatric IBD colonic biopsies cultured ex vivo, and in the SYNERGY-1 (β-fructan) clinical study of adult remission UC patients. Incubating FOS with whole-microbiota intestinal washes from non-IBD or remission IBD patients improved fermentation and reduced pro-inflammatory responses, but not from patients with active disease. Fibre-induced immune responses correlated with microbe functions, luminal metabolites, and fibre avoidance. Aims Here we aimed to expand on our findings and define the role of microbial functions in mediating host response to β-fructans. Methods Colonic biopsies cultured ex vivo and cell lines in vitro were incubated with FOS (5g/L), or fermentation supernatants (24hr anaerobic fermentation). Immune responses (cytokine secretion [ELISA/MSD] and expression [qPCR]) were assessed. Taxonomic classification of microbial fermentation cultures was conducted with Kraken2 and metabolic profiling by HUMAnN2. HPLC and gas chromatography volatile fatty acid (CG-VFA) analysis were used to identify concentrations of remaining fibre and SCFAs following anaerobic fermentation. Results 7 microbial enzymes were identified to be predictive of cytokine (IL-1β, IL23, IL-5, IL-8, MIP-1α) secretion in ex vivo colonic biopsies from pediatric Crohn disease (CD; n=38), ulcerative colitis (UC; n=20), and non-IBD (n=21) patients, in response to β-fructans; their use as biomarkers of response was determined in patient stool from the SYNERGY-1 clinical study cohort. Fermentation of FOS by whole-microbe intestinal washes from only non-IBD or remission IBD patients reduced cytokine secretion, and our findings demonstrate that this was due to a combination of reduction of β-fructan present and production of a precise combination of anti-inflammatory SCFAs. Conclusions Our findings suggest that intolerance and avoidance of fibers in select IBD patients is associated with the inability to ferment these fibers, mediated by altered microbial functions (enzymes), leading to worsened inflammation. Data indicate that gut microbial function, not composition, predicts patient pro-inflammatory response to β-fructans, supporting our hypothesis that overall community function impacts fibre fermentation and affects associated pro-inflammatory effects. Our work highlights select disease state scenarios in which administration of fermentable fibers should be avoided and tailored dietary interventions considered. Funding Agencies CIHRWeston Foundation, Mitacs

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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
Published2022
Admission routes1
Has abstractyes

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