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Record W2805769668 · doi:10.1136/gutjnl-2017-314472.63

OC-063 Gut microbiota-host bile acid metabolism interactions in clostridium difficile infection: the explanation for the efficacy of faecal microbiota transplantation?

2017· article· en· W2805769668 on OpenAlexaff
Benjamin H. Mullish, J McDonald, DH Kao, JR Allegretti, EO Petrof, Alexandros Pechlivanis, G. R. Barker, SR Atkinson, Mark Thursz, JR Marchesi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsQueen's UniversityUniversity of Alberta
Fundersnot available
KeywordsDeoxycholic acidTaurocholic acidBile acidMicrobiologyBiologyGut floraBacteriaMicrobiomeBiochemistryBioinformatics

Abstract

fetched live from OpenAlex

Introduction Faecal microbiota transplantation (FMT) effectively treats recurrent Clostridium difficile infection (CDI), yet the mechanisms underlying its efficacy are poorly-defined. In vitro, conjugated primary bile salts (i.e. taurocholic acid) promote the germination of C. difficile, whilst secondary bile salts (i.e. deoxycholic acid) inhibit vegetative growth of the organism. As gut microbiota-derived enzymes (i.e. bile salt hydrolases (BSH)) are responsible for bile acid metabolism in vivo, we hypothesised that the efficacy of FMT may reflect transfer of BSH-producing bacteria, with restoration of a gut bile acid profile that inhibit germination/vegetative growth of C. difficile. Method Faecal samples were collected from patients with recurrent CDI pre-FMT (n=26), at 8–12 weeks after successful FMT, and also from stool donors (n=17). Bacterial DNA was used for microbial profiling (via 16S rRNA gene sequencing) and for qPCR of BSH genes. Liquid chromatography-mass spectrometry was used for bile acid profiling. BSH enzyme activity was established using a plate-based precipitation assay. Results Microbial and bile acid profiles from pre-FMT patients were markedly different to those found in the post-FMT and donor groups (p<0.001, PERMANOVA); qPCR confirmed enrichment of BSH-producing organisms post-FMT. Taurocholic acid levels were elevated (and deoxycholic acid levels reduced) pre-FMT compared to donors and post-FMT (p<0.001, Wilcoxon-Mann-Whitney test). By Spearman’s rank, abundance of BSH-producing bacteria negatively correlated with taurocholic acid and positively correlated with deoxycholic acid levels (Figure 1), with p<0.05 for this correlation for levels of both bile acids with Bacteroides vulgatus, Blautia obeum, Dorea longicatena, and Eubacterium rectale. Stool BSH activity was negligible pre-FMT, but was significantly increased post-FMT (p<0.002, Wilcoxon-Mann-Whitney). Conclusion The gut microbiota is enriched with BSH-producing bacterial species post-FMT for CDI, and these organisms are present within the gut microbiota of donors. The increased relative abundance of BSH-producing organisms post-FMT was negatively correlated with gut taurocholic acid levels, positively correlated with deoxycholic acid levels, and associated with increased BSH activity. These data collectively support a hypothesis of transfer of BSH-producing organisms during FMT linked to reconstitution of a gut bile acid profile unfavourable to the germination and growth of C. difficile. Disclosure of Interest None Declared

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.045
GPT teacher head0.352
Teacher spread0.307 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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