Dataset Information

Dietary fat and gut microbiota interactions determine diet-induced obesity in mice.

ABSTRACT:

Objective

Gut microbiota may promote positive energy balance; however, germfree mice can be either resistant or susceptible to diet-induced obesity (DIO) depending on the type of dietary intervention. We here sought to identify the dietary constituents that determine the susceptibility to body fat accretion in germfree (GF) mice.

Methods

GF and specific pathogen free (SPF) male C57BL/6N mice were fed high-fat diets either based on lard or palm oil for 4 wks. Mice were metabolically characterized at the end of the feeding trial. FT-ICR-MS and UPLC-TOF-MS were used for cecal as well as hepatic metabolite profiling and cecal bile acids quantification, respectively. Hepatic gene expression was examined by qRT-PCR and cecal gut microbiota of SPF mice was analyzed by high-throughput 16S rRNA gene sequencing.

Results

GF mice, but not SPF mice, were completely DIO resistant when fed a cholesterol-rich lard-based high-fat diet, whereas on a cholesterol-free palm oil-based high-fat diet, DIO was independent of gut microbiota. In GF lard-fed mice, DIO resistance was conveyed by increased energy expenditure, preferential carbohydrate oxidation, and increased fecal fat and energy excretion. Cecal metabolite profiling revealed a shift in bile acid and steroid metabolites in these lean mice, with a significant rise in 17?-estradiol, which is known to stimulate energy expenditure and interfere with bile acid metabolism. Decreased cecal bile acid levels were associated with decreased hepatic expression of genes involved in bile acid synthesis. These metabolic adaptations were largely attenuated in GF mice fed the palm-oil based high-fat diet. We propose that an interaction of gut microbiota and cholesterol metabolism is essential for fat accretion in normal SPF mice fed cholesterol-rich lard as the main dietary fat source. This is supported by a positive correlation between bile acid levels and specific bacteria of the order Clostridiales (phylum Firmicutes) as a characteristic feature of normal SPF mice fed lard.

Conclusions

In conclusion, our study identified dietary cholesterol as a candidate ingredient affecting the crosstalk between gut microbiota and host metabolism.

SUBMITTER: Kubeck R

PROVIDER: S-EPMC5123202 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

Dietary fat and gut microbiota interactions determine diet-induced obesity in mice.

Kübeck Raphaela R Bonet-Ripoll Catalina C Hoffmann Christina C Walker Alesia A Müller Veronika Maria VM Schüppel Valentina Luise VL Lagkouvardos Ilias I Scholz Birgit B Engel Karl-Heinz KH Daniel Hannelore H Schmitt-Kopplin Philippe P Haller Dirk D Clavel Thomas T Klingenspor Martin M

Molecular metabolism 20161013 12

<h4>Objective</h4>Gut microbiota may promote positive energy balance; however, germfree mice can be either resistant or susceptible to diet-induced obesity (DIO) depending on the type of dietary intervention. We here sought to identify the dietary constituents that determine the susceptibility to body fat accretion in germfree (GF) mice.<h4>Methods</h4>GF and specific pathogen free (SPF) male C57BL/6N mice were fed high-fat diets either based on lard or palm oil for 4 wks. Mice were metabolicall ...[more]

PMID: 27900259

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Project description:The gut microbiota is important in the occurrence and development of obesity. It can not only via its metabolites, but also through microbiota-gut-brain-liver interactions, directly or indirectly, influence obesity. Quinoa, known as one kind of pseudocereals and weight loss food supplements, has been high-profile for its high nutritional value and broad applications. In this context, we produced high-fat diet-induced (HFD) obese mouse models and assessed the efficacy of quinoa with saponin and quinoa without saponin on obesity. We explored the potential therapeutic mechanisms of quinoa using methods such as 16S rRNA, Western blotting, Immunohistochemical (IHC). Our results indicated that quinoa can improve the obese symptoms significantly on HFD mice, as well as aberrant glucose and lipid metabolism. Further analyses suggest that quinoa can regulate microbiota in the colon and have predominantly regulation on Bacteroidetes, Actinobacteria and Desulfovibrio, meanwhile can decrease the F/B ratio and the abundance of Blautia. Contemporaneously, quinoa can upregulate the expression of TGR5 in the colon and brain, as well as GLP-1 in the colon, liver and brain. while downregulate the expression of TLR4 in the colon and liver, as well as markers of ER stress and oxidative stress in livers and serums. Beyond this, tight junctional proteins in colons and brains are also increased in response to quinoa. Therefore, quinoa can effectively reduce obesity and may possibly exert through microbiota-gut-brain-liver interaction mechanisms. IMPORTANCE Gut microbiota has been investigated extensively, as a driver of obesity as well as a therapeutic target. Studies of its mechanisms are predominantly microbiota-gut-brain axis or microbiota-gut-liver axis. Recent studies have shown that there is an important correlation between the gut-brain-liver axis and the energy balance of the body. Our research focus on microbiota-gut-brain-liver axis, as well as influences of quinoa in intestinal microbiota. We extend this study to the interaction between microbiota and brains, and the result shows obvious differences in the composition of the microbiome between the HFD group and others. These observations infer that besides the neurotransmitter and related receptors, microbiota itself may be a mediator for regulating bidirectional communication, along the gut-brain-liver axis. Taken together, these results also provide strong evidence for widening the domain of applicability of quinoa.

Dataset Information

Dietary fat and gut microbiota interactions determine diet-induced obesity in mice.

Objective

Methods

Results

Conclusions

Publications

Dietary fat and gut microbiota interactions determine diet-induced obesity in mice.

Similar Datasets

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