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不同身体质量指数人群肠道菌群结构及共存网络解析
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国家重点研发计划(2019YFF0217601)


feature and co-occurrence network of gut microbiota in different body mass index (BMI) populations
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    摘要:

    [背景] 人体能量稳态失衡表现为体重过轻、超重和肥胖,肠道菌群与人体能量稳态的维持有关,但不同身体质量指数(Body Mass Index,BMI)人群的肠道菌群特征仍需进一步探究。[目的] 基于美国肠道计划公开数据库,解析4类BMI人群肠道菌群的特征,并探究4类BMI人群肠道菌群共存网络特征及差异,为基于肠道菌群来干预肥胖及体重过轻等不健康状态提供新的理论依据。[方法] 从美国肠道计划数据集中筛选具有BMI信息的肠道菌群样本,并根据世界卫生组织规定的BMI划分标准将筛选后的样本分为4类:体重过轻(BMI<18.5 kg/m2),正常体重(18.5 kg/m22),超重(25 kg/m22),肥胖(BMI>30 kg/m2);通过计算和比较肠道菌群的α多样性和β多样性探究4类BMI人群肠道菌群的整体结构特征及差异;通过多元线性回归模型对不同BMI分类与肠道菌群进行相关性分析,并且将地域、年龄、性别因素作为混杂因素加入到模型中进行校正;采用SparCC分别计算4类BMI人群肠道菌群中菌属相关性,并分别构建肠道菌群共存网络。[结果] 经过Wilcoxon秩和检验,发现体重过轻、超重、肥胖人群的肠道菌群α多样性都显著低于正常体重人群;β多样性分析结果表明4类BMI人群肠道菌群的整体结构存在显著差异;4类BMI人群肠道中厚壁菌门(Firmicutes)和拟杆菌门(Bacteroidetes)的相对含量无显著差异;通过MaAsLin分析,并且将地域、年龄、性别因素作为混杂因素加入到模型中进行校正,共得到49个与BMI类型显著相关的物种;4类BMI人群肠道菌群共存网络的拓扑结构具有一定差异,体重过轻和正常体重人群肠道菌群共存网络的复杂度较高,超重和肥胖人群肠道菌群共存网络的复杂度较低。[结论] 4类BMI人群肠道菌群的多样性、整体结构和共存网络间均存在差异。

    Abstract:

    [Background] The imbalance of human energy homeostasis is characterized by underweight, overweight and obesity. Gut microbiota is related to the maintenance of human energy homeostasis, but the feature of gut microbiota in different body mass index (BMI) populations need to be further explored. [Objective] To explore the feature and the co-occurrence network of gut microbiota of four BMI groups based on the American gut project (AGP), and to provide new theoretical basis for intervention of obesity and underweight based on gut microbiota. [Methods] Screen the gut microbiota samples with BMI information from AGP dataset, and divide the screened samples into four categories according to the BMI classification standards set by the World Health Organization:underweight (BMI<18.5 kg/m2), normal weight (18.52), overweight (252), obesity (BMI>30 kg/m2). By calculating and comparing the alpha diversity and beta diversity of gut microbiota, the overall feature and differences of gut microbiota in four BMI groups were explored. Use Microbiome Multivariable Association with Linear Models (MaAsLin) to analyze the correlation between different BMI groups and gut microbiota, and add geographical, age, and gender factors as confounding factors to the model for correction. SparCC was used to calculate the correlation of gut microbiota among the four BMI groups, and the gut microbiota co-occurrence network of four groups was constructed. [Results] The decreasing trend of alpha diversity in the underweight, overweight and obese population compared to the normal weight population was observed after the Wilcoxon-rank-sum analysis. As for the beta diversity, the significant difference of the structure of gut microbiota between the four BMI groups was found. There was no significant difference in the relative contents of Firmicutes and Bacteroidetes. Through MaAsLin analysis, and adding geographical, age, and gender factors as confounding factors to the model for correction, a total of 49 bacteria that were significantly related to BMI types were obtained. The topological structure of the co-occurrence network of the four groups of BMI populations were different. The networks of underweight and normal-weight population were more complex, while the networks of overweight and obese populations were less complex. [Conclusion] There were differences in the diversity, overall feature and co-occurrence network of the gut microbiota among the four BMI groups.

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袁维维,王鸿超,陈宇涛,戎一格,陆文伟,赵建新,张灏,陈卫. 不同身体质量指数人群肠道菌群结构及共存网络解析[J]. 微生物学通报, 2021, 48(10): 3776-3790

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  • 收稿日期:2020-12-24
  • 最后修改日期:
  • 录用日期:2021-02-09
  • 在线发布日期: 2021-10-12
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