Ileal microbial microbiome and its secondary bile acids modulate susceptibility to nonalcoholic steatohepatitis in dairy goats
Bibliographic record
Abstract
Liver damage from nonalcoholic steatohepatitis (NASH) presents a significant challenge to the health and productivity of ruminants. However, the regulatory mechanisms behind variations in NASH susceptibility remain unclear. The gut‒liver axis, particularly the enterohepatic circulation of bile acids (BAs), plays a crucial role in regulating the liver diseases. Since the ileum is the primary site for BAs reabsorption and return to the liver, we analysed the ileal metagenome and metabolome, liver and serum metabolome, and liver single-nuclei transcriptome of NASH-resistant and susceptible goats together with a mice validation model to explore how ileal microbial BAs metabolism affects liver metabolism and immunity, uncovering the key mechanisms behind varied NASH pathogenesis in dairy goats. In NASH goats, increased total cholesterol (TC), triglyceride (TG), and primary BAs and decreased secondary BAs in the liver and serum promoted hepatic fat accumulation. Increased ileal Escherichia coli, Erysipelotrichaceae bacterium and Streptococcus pneumoniae as well as proinflammatory compounds damaged ileal histological morphology, and increased ileal permeability contributes to liver inflammation. In NASH-tolerance (NASH-T) goats, increased ursodeoxycholic acid (UDCA), isodeoxycholic acid (isoDCA) and isolithocholic acid (isoLCA) in the liver, serum and ileal contents were attributed to ileal secondary BAs-producing bacteria (Clostridium, Bifidobacterium and Lactobacillus) and key microbial genes encoding enzymes. Meanwhile, decreased T-helper 17 (TH17) cells and increased regulatory T (Treg) cells proportion were identified in both liver and ileum of NASH-T goats. To further validate whether these key BAs affected the progression of NASH by regulating the proliferation of TH17 and Treg cells, the oral administration of bacterial UDCA, isoDCA and isoLCA to a high-fat diet-induced NASH mouse model confirmed the amelioration of NASH through the TH17 cell differentiation/IL-17 signalling/PPAR signalling pathway by these bacterial secondary BAs. This study revealed the roles of ileal microbiome and its secondary BAs in resilience and susceptibility to NASH by affecting the hepatic Treg and TH17 cells proportion in dairy goats. Bacterial UDCA, isoDCA and isoLCA were demonstrated to alleviate NASH and could be novel postbiotics to modulate and improve the liver health in ruminants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".