Diets, Gut Microbiota and Metabolites

肠道菌群 生物 基因组 微生物群 疾病 代谢组学 人口 非酒精性脂肪肝 脂肪肝 生物信息学 免疫学 遗传学 医学 环境卫生 内科学 基因
作者
Yilian Liu,Wanglei Zhong,Xiao Li,Feng Shen,Xiaonan Ma,Qi Yang,Shangyu Hong,Yan Sun
出处
期刊:Phenomics [Springer Nature]
卷期号:3 (3): 268-284 被引量:14
标识
DOI:10.1007/s43657-023-00095-0
摘要

The gut microbiota refers to the gross collection of microorganisms, estimated trillions of them, which reside within the gut and play crucial roles in the absorption and digestion of dietary nutrients. In the past decades, the new generation ‘omics’ (metagenomics, transcriptomics, proteomics, and metabolomics) technologies made it possible to precisely identify microbiota and metabolites and describe their variability between individuals, populations and even different time points within the same subjects. With massive efforts made, it is now generally accepted that the gut microbiota is a dynamically changing population, whose composition is influenced by the hosts’ health conditions and lifestyles. Diet is one of the major contributors to shaping the gut microbiota. The components in the diets vary in different countries, religions, and populations. Some special diets have been adopted by people for hundreds of years aiming for better health, while the underlying mechanisms remain largely unknown. Recent studies based on volunteers or diet-treated animals demonstrated that diets can greatly and rapidly change the gut microbiota. The unique pattern of the nutrients from the diets and their metabolites produced by the gut microbiota has been linked with the occurrence of diseases, including obesity, diabetes, nonalcoholic fatty liver disease, cardiovascular disease, neural diseases, and more. This review will summarize the recent progress and current understanding of the effects of different dietary patterns on the composition of gut microbiota, bacterial metabolites, and their effects on the host's metabolism.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
chansey发布了新的文献求助10
1秒前
研友_ZzaKqn完成签到,获得积分0
1秒前
所所应助乐乐乐乐乐乐乐采纳,获得10
1秒前
小鱼完成签到 ,获得积分10
4秒前
wx发布了新的文献求助10
5秒前
chansey完成签到,获得积分10
5秒前
艺阳发布了新的文献求助10
6秒前
像个间谍完成签到 ,获得积分10
6秒前
坦率的丹云完成签到,获得积分10
7秒前
9秒前
swayqur完成签到,获得积分10
11秒前
11秒前
大力的飞莲完成签到,获得积分10
12秒前
木木完成签到,获得积分10
13秒前
科研小白发布了新的文献求助10
14秒前
光亮学姐发布了新的文献求助30
15秒前
15秒前
Zhaonanyu发布了新的文献求助10
16秒前
16秒前
超人完成签到,获得积分10
18秒前
小马甲应助WWW采纳,获得10
18秒前
18秒前
阔达的背包完成签到 ,获得积分10
19秒前
littlepuppy完成签到,获得积分10
19秒前
波恩奥本海默绝热近似完成签到,获得积分10
19秒前
20秒前
20秒前
21秒前
余其钵完成签到,获得积分10
21秒前
21秒前
fuguier发布了新的文献求助10
21秒前
玲家傻妞发布了新的文献求助10
21秒前
yq完成签到 ,获得积分10
22秒前
22秒前
砼砼完成签到,获得积分10
22秒前
25秒前
mao发布了新的文献求助10
25秒前
lvlv发布了新的文献求助10
26秒前
26秒前
YXL发布了新的文献求助10
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 2000
Digital Twins of Advanced Materials Processing 2000
Social Cognition: Understanding People and Events 1200
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6036932
求助须知:如何正确求助?哪些是违规求助? 7757565
关于积分的说明 16216337
捐赠科研通 5183017
什么是DOI,文献DOI怎么找? 2773710
邀请新用户注册赠送积分活动 1756985
关于科研通互助平台的介绍 1641334