Microbial bile salt hydrolases mediate the efficacy of faecal microbiota transplant in the treatment of recurrent <i>Clostridioides difficile</i> infection
Bibliographic record
Abstract
Objective Faecal microbiota transplant (FMT) effectively treats recurrent Clostridioides difficile infection (rCDI), but its mechanisms of action remain poorly defined. Certain bile acids affect C. difficile germination or vegetative growth. We hypothesised that loss of gut microbiota-derived bile salt hydrolases (BSHs) predisposes to CDI by perturbing gut bile metabolism, and that BSH restitution is a key mediator of FMT’s efficacy in treating the condition. Design Using stool collected from patients and donors pre-FMT/post-FMT for rCDI, we performed 16S rRNA gene sequencing, ultra performance liquid chromatography mass spectrometry (UPLC-MS) bile acid profiling, BSH activity measurement, and qPCR of bsh / bai CD genes involved in bile metabolism. Human data were validated in C. difficile batch cultures and a C57BL/6 mouse model of rCDI. Results From metataxonomics, pre-FMT stool demonstrated a reduced proportion of BSH-producing bacterial species compared with donors/post-FMT. Pre-FMT stool was enriched in taurocholic acid (TCA, a potent C. difficile germinant); TCA levels negatively correlated with key bacterial genera containing BSH-producing organisms. Post-FMT samples demonstrated recovered BSH activity and bsh / bai CD gene copy number compared with pretreatment (p<0.05). In batch cultures, supernatant from engineered bsh -expressing E. coli and naturally BSH-producing organisms ( Bacteroides ovatus, Collinsella aerofaciens, Bacteroides vulgatus and Blautia obeum ) reduced TCA-mediated C. difficile germination relative to culture supernatant of wild-type (BSH-negative) E. coli. C. difficile total viable counts were ~70% reduced in an rCDI mouse model after administration of E. coli expressing highly active BSH relative to mice administered BSH-negative E. coli (p<0.05). Conclusion Restoration of gut BSH functionality contributes to the efficacy of FMT in treating rCDI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".