Chronic Effects of a High Sucrose Diet on Murine Gastrointestinal Nutrient Sensor Gene and Protein Expression Levels and Lipid Metabolism.
Patrick O'BrienGe HanPriya GanpathyShweta PitreYi ZhangJohn RyanPei Ying SimScott V HardingRobert GrayVictor R PreedyThomas A B SandersChristopher Peter CorpePublished in: International journal of molecular sciences (2020)
The gastrointestinal tract (GIT) plays a key role in regulating nutrient metabolism and appetite responses. This study aimed to identify changes in the GIT that are important in the development of diet related obesity and diabetes. GIT samples were obtained from C57BL/6J male mice chronically fed a control diet or a high sucrose diet (HSD) and analysed for changes in gene, protein and metabolite levels. In HSD mice, GIT expression levels of fat oxidation genes were reduced, and increased de novo lipogenesis was evident in ileum. Gene expression levels of the putative sugar sensor, slc5a4a and slc5a4b, and fat sensor, cd36, were downregulated in the small intestines of HSD mice. In HSD mice, there was also evidence of bacterial overgrowth and a lipopolysaccharide activated inflammatory pathway involving inducible nitric oxide synthase (iNOS). In Caco-2 cells, sucrose significantly increased the expression levels of the nos2, iNOS and nitric oxide (NO) gas levels. In conclusion, sucrose fed induced obesity/diabetes is associated with changes in GI macronutrient sensing, appetite regulation and nutrient metabolism and intestinal microflora. These may be important drivers, and thus therapeutic targets, of diet-related metabolic disease.
Keyphrases
- weight loss
- nitric oxide synthase
- nitric oxide
- high fat diet induced
- gene expression
- type diabetes
- physical activity
- poor prognosis
- genome wide
- insulin resistance
- cardiovascular disease
- dna methylation
- glycemic control
- metabolic syndrome
- cell death
- fatty acid
- signaling pathway
- hydrogen peroxide
- toll like receptor
- drug induced
- weight gain
- small molecule
- endoplasmic reticulum stress
- genome wide analysis