Resident bacteria in the small intestine can shape host drug metabolism through innate lymphoid cell‐derived IL‐22
Bibliographic record
Abstract
The ability of the intestinal microbiota to influence drug metabolism has been recognized, however the mechanisms through which this occurs remain relatively unexplored. Recent work in germ‐free mice has demonstrated that conventionalization with specific pathogen free (SPF) microbiota influences the expression of cytochrome P450 (CYP) enzymes in the liver and small intestine (SI), two important sites for drug metabolism. Given that CYP enzymes, including CYP3A11 in mice, account for roughly 75% of total drug metabolism, we sought to investigate the role of specific gut‐residing microbes in shaping the expression and activity of these enzymes. Utilizing PCR arrays, we found that colonization of SPF mice with the immunomodulatory bacteria segmented filamentous bacteria (SFB) altered the expression of various CYP enzymes in the SI (but not liver), with Cyp3a11 being one of the most downregulated genes. Further analysis showed that SFB‐induced IL‐22 production by type 3 innate lymphoid cells (ILC3) correlated with reduced SI Cyp3a11 expression. Additionally, SFB colonization had no effect on the expression of Cyp3a11 in the SI of IL‐22 −/− mice or RAG1 −/− mice in which ILCs were depleted with anti‐Thy1 antibody. Both SFB colonization and administration of IL‐23, to activate IL‐22 from ILC3, increased the ability of the CYP3A11‐metabolized drug glibenclamide to decrease basal blood glucose levels when administered orally. In mouse SI enteroid cultures, IL‐22 dose‐dependently reduced the expression of Cyp3a11 and decreased the ability of SI enteroids to metabolize CYP3A11 specific substrates, effects that were blocked by the STAT3 inhibitor Stattic. Finally, when applied to human ileal organoids, IL‐22 induced robust changes in the transcriptome, with substantial effects on drug metabolism pathways centred around CYP3A. Our data suggest that specific gut‐resident microbes can influence the expression and activity of the drug metabolizing enzyme CYP3A11. This involves the production of IL‐22 by small intestinal ILC3, which down regulates CYP3A11 in the SI epithelium. These findings provide an understanding of how the intestinal microbiota modulates host drug metabolism, and how microbiota‐immune cell crosstalk may influence the efficacy and toxicity of various drugs. Support or Funding Information Alberta Innovates, Canadian Association of Gastroenterology, Canadian Institute of Health Research
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".