P851 Oral delivery of Human β-defensin 2 is reversibly increasing microbiome diversity and is effective in the treatment of experimental colitis
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD), Crohn’s disease and ulcerative colitis, are characterised by complex deficiencies of the mucosal antimicrobial barrier. Different epithelial secreted antimicrobial peptides protect the surface and regulate the gut luminal microbial community while ensuring a beneficial homeostasis. Disrupting this balance by an excessive or dysregulated immune response also results in a so-called “dysbiosis” but cause and consequence is still unclear. Independent of this causality debate, a decreased complexity and diversity of the gut microbiota are common features of chronic inflammation in IBD. The aim of this study was to translate these changes in disease understanding into a clear therapeutic approach. In detail, we tested the human host defence endogenous antimicrobial defensin in terms of (A) microbiome modulation and (B) therapeutic efficacy in experimental colitis. Mice were treated orally with a dose of 1.2 mg/kg per day for one week. Alterations in bacterial composition were analysed by next-generation sequencing on day 0, day 7 and day 14. Based on these results we tested the bacteriocidal and static effect of hBD2 on different commensal species using MIC in vitro. In a second approach, we tested oral administration of hBD2 in an experimental induced DSS colitis mouse model, compared with the standard therapy with prednisolone. Analysing the gut microbiome, a significant increase of diversity was observed during hBD2 treatment. Of note, these changes shift backwards after stopping the application. Hypothesis-driven MIC experiments were consistent with deep sequencing results of overall analysis. Testing the same dose in an experimental colitis model, the treatment resulted in a significantly lower weight loss (p < 0.05) and a strongly improved disease activity index (p < 0.001). Furthermore hBD2 reduced mucosal damage (p < 0.001). In this setting, the oral administration of hBD2 significantly improved the health in DSS colitis model. It seems that this effect is dependent on the ability of hBD2 to modulate the microbiome towards homeostasis.HBD2 shows promising effect in experimental DSS colitis model. The results and the better effect than prednisolone support a therapeutic application as a drug for IBD. These findings suggest the possibility of hBD2 be used alone or in combination with anti-inflammatory substances in microbiome associated diseases.
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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".