Metabolomic Investigation of Brain and Liver in Rats Fed Docosahexaenoic Acid in Regio- and Enantiopure Triacylglycerols

MOLECULAR NUTRITION & FOOD RESEARCH(2024)

引用 0|浏览2
暂无评分
摘要
ScopeN-3 polyunsaturated fatty acids (n-3 PUFAs) play important roles in cognitive functions. However, there is a lack of knowledge on the metabolic impact of regio- and stereo-specific positioning of n-3 PUFAs in dietary triacylglycerols.Methods and resultsRats in a state of mild n-3 PUFA deficiency are fed daily with 360 mg triacylglycerols containing DHA (docosahexaenoic acid) at sn (stereospecific numbering)-1, 2, or 3 positions and 18:0 at remaining positions, or an equal amount of tristearin for 5 days. Groups fed with n-3 deficient diet and normal n-3 adequate diet are included as controls. The metabolic profiles of the brain and liver are studied using NMR (nuclear magnetic resonance)-based metabolomics. Several metabolites of significance in membrane integrity and neurotransmission, and glutamate, in particular, are significantly lower in the brain of the groups fed with sn-1 and sn-3 DHA compared to the sn-2 DHA group. Further, the tristearin and DHA groups show a lower lactate level compared to the groups fed on normal or n-3 deficient diet, suggesting a prominent role of C18:0 in regulating energy metabolism.ConclusionThis study sheds light on the impact of stereospecific positioning of DHA in triacylglycerols and the role of dietary stearic acid on metabolism in the brain and liver. Rats with mild n-3 PUFA deficiency are fed 360 mg of triacylglycerols containing DHA at different positions (sn-1, sn-2, or sn-3) or tristearin for 5 days. The location of DHA in the triacylglycerols had varying effects. Rats fed sn-1 and sn-3 DHA had significantly lower levels of key metabolites related to membrane integrity and neurotransmission, particularly glutamate, compared to the sn-2 DHA group. image
更多
查看译文
关键词
brain and liver,Docosahexaenoic acid,metabolomics,stearic acid,structured lipids
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要