间歇性禁食调节喂食高脂肪饮食的中年小鼠的肠道微生物群和血清代谢组谱。

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS
Ziru Li, Sufang Chen, Bingbing Yin, Jiacun Wei, Duofei Wang, Huoxiang Zhou, Zhi Sun
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引用次数: 0

摘要

背景:间歇性禁食(IF)作为一种有效的饮食策略受到了广泛关注。现有研究表明,IF是控制体重、改善胰岛素敏感性和降低2型糖尿病(T2DM)患病率的一种有前景的方法。方法:8月龄雄性C57BL/6J小鼠28只,随机分为正常对照组(NC)、高脂饮食组(HFD)和HFD + IF组。每周监测体重(BW)和食物摄入量。20周后,每周依次进行腹腔葡萄糖耐量试验(IPGTT)、口服葡萄糖耐量试验(OGTT)和腹腔胰岛素耐量试验(IPITT)。收集新鲜粪便以检查肠道微生物群的变化,并对血清样本进行血清非靶向代谢物谱分析。结果:IF显著降低高脂饮食喂养的中年小鼠体重增加、脂肪量和肝脏重量,改善葡萄糖耐量和胰岛素敏感性。16s rRNA基因测序结果显示,IF显著降低厚壁菌门/拟杆菌门(F/B)比,增加Muribaculaceae, Bacteroides, Parabacteroides,降低Bilophila, Colidextribacter, Oscillibacter。血清非靶向代谢组学显示,IF可以调节与糖脂代谢相关的差异代谢物和代谢途径。Spearman相关分析显示,关键差异菌群与葡萄糖代谢相关指标及血清代谢物如硬脂酸、奥比胆酸、n -乙酰甘氨酸等存在较强相关性。结论:IF改善了高脂饮食中年小鼠的葡萄糖代谢,调节了肠道微生物群,并改变了血清代谢产物。这为中老年患者糖尿病预防试验提供了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intermittent fasting regulates gut microbiota and serum metabolome profiles in middle-aged mice fed high-fat diet.

Background: Intermittent fasting (IF) has received wide attention as an effective diet strategy. Existing studies showed that IF is a promising approach for weight control, improving insulin sensitivity and reducing type 2 diabetes mellitus (T2DM) prevalence.

Methods: Twenty-eight 8-month-old male C57BL/6J mice were randomly divided into a normal control group (NC), a high-fat diet group (HFD) and an HFD + IF group. Body weight (BW) and food intake were monitored weekly. After 20 weeks, the intraperitoneal glucose tolerance test (IPGTT), oral glucose tolerance test (OGTT), and intraperitoneal insulin tolerance test (IPITT) were performed weekly in sequence. Fresh faeces were collected to examine changes in gut microbiota, and serum untargeted metabolite profiling was conducted on serum samples.

Results: IF significantly reduced weight gain, fat mass and liver weight, improved glucose tolerance and insulin sensitivity in middle-aged mice fed with high-fat diet. 16 S rRNA gene sequencing revealed that IF significantly reduced the Firmicutes/Bacteroidetes (F/B) ratio by increased Muribaculaceae, Bacteroides, Parabacteroides, and decreased Bilophila, Colidextribacter, Oscillibacter. The serum untargeted metabolomics revealed that IF could modulate differential metabolites and metabolic pathways associated with glycolipid metabolism. Spearman's correlation analysis indicated that key differential microbiota were strongly correlated with glucose metabolism-related indicators and serum metabolites such as stearic acid, obeticholic acid, and N-acetylglycine.

Conclusions: IF improves glucose metabolism, regulates gut microbiota, and alters serum metabolites in middle-aged mice fed a high-fat diet. This provides a new pathway for trials testing diabetes prevention in middle-aged and elderly patients.

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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
期刊介绍: Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.
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