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Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis

机译:人类肠道菌群的全球代谢相互作用网络,用于特定环境下的社区规模分析

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A system-level framework of complex microbe–microbe and host–microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ~570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut.
机译:一个复杂的微生物-微生物和宿主-微生物化学相互作用的系统级框架将有助于阐明肠道菌群在健康和疾病中的作用。在这里,我们报告了人类肠道微生物群的一种名为NJS16的文献策划的种间网络。这是一个广泛的数据资源,由约570种微生物和3种人类细胞类型组成,它们通过> 4,400小分子转运和大分子降解事件进行代谢相互作用。根据我们网络的内容,我们开发一种数学方法来阐明给定人群(例如疾病队列)中肠道微生物群落的代表性微生物和代谢特征。将该策略应用于来自2型糖尿病患者的微生物组数据,揭示了肠道微生物生态系统的特定环境基础设施,具有较大代谢影响的核心微生物实体以及可能指示相关社区代谢过程的频繁产生的代谢化合物。我们的网络为人类肠道内社区规模的微生物活动的综合研究奠定了基础。

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