An epigenetic link between the gut microbiome and immune responses in atopy
Bibliographic record
Abstract
Abstract Atopy is the most common childhood disease in developed countries. Dysbiosis of the microbiome is now understood to be a driving force behind the development and severity of allergy/atopy. We previously showed that antibiotic treatment of newborn mice leads to a life-long perturbation of the gut microbiome marked by reduced bacterial production of the short chain fatty acid, butyrate. These mice exhibit a striking pro-inflammatory phenotype, marked by a heightened Th2 response, that was completely reversible with dietary supplementation of butyrate. Butyrate is known to exert its effects on target cells via inhibition of histone deacetylases that have long term effects on gene expression. Consistent with a role for epigenetic skewing on the hematopoietic compartment of antibiotic treated mice, we found that bone marrow transplantation was sufficient to transfer the pro Th2 inflammatory phenotype into chimeric mice. Strikingly, we found unique regulatory states (H3K27ac) in purified hematopoietic stem and progenitor cells of these Th2 skewed mice. Single cell sequence analyses identified a distinct stem/progenitor cell transcriptomic signature in butyrate depleted mice that was reversed by butyrate supplementation. We identified a metagenomic gene signature present in fecal microbiome samples of 3-month-old children who subsequently developed atopy. Consistent with our observations in mice, this signature included depletion of the bacterial genes required for breakdown of indigestible carbohydrates in breast milk and the loss of genes required for butyrate fermentation. This work provides novel evidence for a butyrate-driven epigenetic process that links the fetal microbiome to long term sculpting of the immune response.
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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 | 0.000 |
| 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".