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高通量基因组规模建模预测微生物的维生素需求有助于肠道微生物群落结构。

High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure.

机构信息

School of Chemical and Biomolecular Engineering, the University of Sydney, Sydney, Australia.

Centre for Advanced Food Engineering, the University of Sydney, Sydney, Australia.

出版信息

Gut Microbes. 2022 Jan-Dec;14(1):2118831. doi: 10.1080/19490976.2022.2118831.

Abstract

Human gut microbiome structure and emergent metabolic outputs impact health outcomes. However, what drives such community characteristics remains underexplored. Here, we rely on high throughput genomic reconstruction modeling, to infer the metabolic attributes and nutritional requirements of 816 gut strains, via a framework termed GEMNAST. This has been performed in terms of a group of human vitamins to examine the role vitamin exchanges have at different levels of community organization. We find that only 91 strains can satisfy their vitamin requirements (prototrophs) while the rest show various degrees of auxotrophy/specialization, highlighting their dependence on external sources, such as other members of the microbial community. Further, 79% of the strains in our sample were mapped to 11 distinct vitamin requirement profiles with low phylogenetic consistency. Yet, we find that human gut microbial community enterotype indicators display marked metabolic differences. strains display a metabolic profile that can be complemented by strains from other genera often associated with the enterotype and agrarian diets, while strains occupy a prototrophic profile. Finally, we identify pre-defined interaction modules (IMs) of gut species from human and mice predicted to be driven by, or highly independent of vitamin exchanges. Our analysis provides mechanistic grounding to gut microbiome stability and to co-abundance-based observations, a fundamental step toward understanding emergent processes that influence health outcomes. Further, our work opens a path to future explorations in the field through applications of GEMNAST to additional nutritional dimensions.

摘要

人类肠道微生物组结构和新兴代谢产物会影响健康结果。然而,是什么驱动了这些群落特征仍未得到充分探索。在这里,我们依赖高通量基因组重建建模,通过称为 GEMNAST 的框架来推断 816 种肠道菌株的代谢属性和营养需求。这是通过一组人类维生素来完成的,以研究维生素交换在不同社区组织水平上的作用。我们发现只有 91 株可以满足它们的维生素需求(原养型),而其余的则表现出不同程度的营养缺陷/专业化,突出了它们对外部来源的依赖,例如微生物群落中的其他成员。此外,我们样本中的 79%的菌株被映射到 11 个不同的维生素需求图谱上,具有低系统发育一致性。然而,我们发现人类肠道微生物群落的 enterotype 指标显示出明显的代谢差异。菌株显示出一种代谢模式,可以通过与 enterotype 和农业饮食相关的其他属的菌株来补充,而菌株则占据原养型模式。最后,我们确定了来自人类和小鼠的肠道物种的预定义相互作用模块(IMs),这些模块被预测是由维生素交换驱动的,或者高度独立于维生素交换。我们的分析为肠道微生物组的稳定性和基于共丰度的观察提供了机制基础,是理解影响健康结果的新兴过程的重要一步。此外,我们的工作通过将 GEMNAST 应用于其他营养维度,为该领域的未来探索开辟了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4079/9480837/99836843f2f3/KGMI_A_2118831_F0001_OC.jpg

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