Mgll Knockout Mouse Resistance to Diet-Induced Dysmetabolism Is Associated with Altered Gut Microbiota
Bibliographic record
Abstract
Monoglyceride lipase (MGLL) regulates metabolism by catabolizing monoacylglycerols (MAGs), including the endocannabinoid 2-arachidonoyl glycerol (2-AG) and some of its bioactive congeners, to the corresponding free fatty acids. Mgll knockout mice (Mgll−/−) exhibit elevated tissue levels of MAGs in association with resistance to the metabolic and cardiovascular perturbations induced by a high fat diet (HFD). The gut microbiome and its metabolic function are disrupted in obesity in a manner modulated by 2-arachidonoyl glycerol (2-AG’s) main receptors, the cannabinoid CB1 receptors. We therefore hypothesized that Mgll−/− mice have an altered microbiome, that responds differently to diet-induced obesity from that of wild-type (WT) mice. We subjected mice to HFD and assessed changes in the microbiomes after 8 and 22 weeks. As expected, Mgll−/− mice showed decreased adiposity, improved insulin sensitivity, and altered circulating incretin/adipokine levels in response to HFD. Mgll−/− mice on a chow diet exhibited significantly higher levels of Hydrogenoanaerobacterium, Roseburia, and Ruminococcus than WT mice. The relative abundance of the Lactobacillaceae and Coriobacteriaceae and of the Lactobacillus, Enterorhabdus, Clostridium_XlVa, and Falsiporphyromonas genera was significantly altered by HFD in WT but not Mgll−/− mice. Differently abundant families were also associated with changes in circulating adipokine and incretin levels in HFD-fed mice. Some gut microbiota family alterations could be reproduced by supplementing 2-AG or MAGs in culturomics experiments carried out with WT mouse fecal samples. We suggest that the altered microbiome of Mgll−/− mice contributes to their obesity resistant phenotype, and results in part from increased levels of 2-AG and MAGs.
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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 | 0.000 | 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) | 0.001 | 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".