南方医科大学学报2018，Vol.38Issue(3)：251-260,10.DOI:10.3969/j.issn.1673-4254.2018.03.03
基于肠道菌群结构预测摄入益生元后双歧杆菌的变化趋势
A machine learning model based on initial gut microbiome data for predicting changes of Bifidobacterium after prebiotics consumption
摘要
Abstract
Objective To investigate the effects of prebiotics supplementation for 9 days on gut microbiota structure and function and establish a machine learning model based on the initial gut microbiota data for predicting the variation of Bifidobacterium after prebiotic intake.Methods With a randomized double-blind self-controlled design,35 healthy volunteers were asked to consume fructo-oligosaccharides(FOS)or galacto-oligosaccharides(GOS)for 9 days(16 g per day).16S rRNA gene high-throughput sequencing was performed to investigate the changes of gut microbiota after prebiotics intake.PICRUSt was used to infer the differences between the functional modules of the bacterial communities.Random forest model based on the initial gut microbiota data was used to identify the changes in Bifidobacterium after 5 days of prebiotic intake and then to build a continuous index to predict the changes of Bifidobacterium. The data of fecal samples collected after 9 days of GOS intervention were used to validate the model.Results Fecal samples analysis with QIIME revealed that FOS intervention for 5 days reduced the intestinal flora alpha diversity, which rebounded on day 9; in GOS group, gut microbiota alpha diversity decreased progressively during the intervention.Neither FOS nor GOS supplement caused significant changes in β diversity of gut microbiota.The area under the curve(AUC)of the prediction model was 89.6%.The continuous index could successfully predict the changes in Bifidobacterium (R=0.45, P=0.01), and the prediction accuracy was verified by the validation model (R=0.62, P=0.01). Conclusion Short-term prebiotics intervention can significantly decrease α-diversity of the intestinal flora. The machine learning model based on initial gut microbiota data can accurately predict the changes in Bifidobacterium,which sheds light on personalized nutrition intervention and precise modulation of the intestinal flora.关键词
益生元/低聚果糖/低聚半乳糖/肠道菌群/精准膳食/双歧杆菌Key words
prebiotics/fructo-oligosaccharides/galacto-oligosaccharides/microbiota/personalized diet/Bifidobacterium引用本文复制引用
罗月梅,刘斐童,陈慕璇,唐文丽,杨月莲,谭细兰,周宏伟..基于肠道菌群结构预测摄入益生元后双歧杆菌的变化趋势[J].南方医科大学学报,2018,38(3):251-260,10.基金项目
国家自然科学基金优秀青年基金(31322003) （31322003）
国家自然科学基金(31270152) Supported by National Natural Science Foundation of China(31322003, 31270152). （31270152）
