Untargeted Metabolomics Identifies Faecal Filtrate-Derived Metabolites That Disrupt Clostridioides difficile Metabolism and Confer Gut Barrier Cytoprotection
Bibliographic record
Abstract
Recurrent Clostridioides difficile infection (rCDI) remains a major therapeutic challenge. Although faecal microbiota transplantation (FMT) is highly effective and thought to restore microbial composition and metabolic function, the mechanisms underlying its success are not fully understood. In particular, the contribution of non-bacterial components such as soluble metabolites remains unclear. Therefore, further investigation is needed to identify the mechanistic drivers of FMT efficacy and clarify how non-bacterial factors contribute to therapeutic outcomes. Here, we applied untargeted three-dimensional Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) to profile faecal metabolic reprogramming in rCDI patients pre- and post-FMT, alongside C. difficile cultures exposed to sterile faecal filtrates. FMT induced extensive metabolic shifts, restoring glyoxylate/dicarboxylate and glycerophosphoinositol pathways and normalising disrupted bile acid and amino acid profiles. Faecal filtrate exposure caused strain-specific metabolic disruption in C. difficile, depleting proline, fumarate and succinate while enriching tryptophan. While multiple metabolite classes were profiled, the most significant functional changes were observed in lipids. Lipidomics identified >3.8-fold enrichment of phosphatidylinositol (PI) species, which localised to bacterial membranes and conferred cytoprotection against C. difficile toxins and other epithelial insults. Spatial metabolomics imaging revealed, for the first time, metabolite compartmentalisation within C. difficile, with proline and succinate broadly distributed across the cell surface and fumarate confined to distinct microdomains, highlighting functional heterogeneity in pathogen metabolism. Collectively, these findings demonstrate that soluble metabolites within faecal filtrates mediate pathogen suppression and epithelial barrier protection, establishing metabolite-driven mechanisms underlying FMT efficacy and identifying PI lipids as candidate post-biotic therapeutics for 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) | 0.000 | 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".