Univ Rennes, Inria, CNRS, IRISA, Rennes, France.
Inria Bordeaux Sud-Ouest, Talence, France.
Elife. 2020 Dec 29;9:e61968. doi: 10.7554/eLife.61968.
To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need for de novo functional screening of genome-scale metabolic networks (GSMNs) at the scale of a metagenome, and the identification of critical species with respect to metabolic cooperation. M2M comprises a flexible pipeline for the characterisation of individual metabolisms and collective metabolic complementarity. In addition, M2M identifies key species, that are meaningful members of the community for functions of interest. We demonstrate that M2M is applicable to collections of genomes as well as metagenome-assembled genomes, permits an efficient GSMN reconstruction with Pathway Tools, and assesses the cooperation potential between species. M2M identifies key organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.
为了捕捉微生物群落的功能多样性,人们必须在数百或数千种微生物中鉴定出具有代谢功能和感兴趣的物种。我们提出了 Metage2Metabo(M2M),这是一种资源,满足了在宏基因组规模上对基因组规模代谢网络(GSMN)进行从头功能筛选以及鉴定代谢合作方面关键物种的需求。M2M 包括一个用于个体代谢和集体代谢互补性特征描述的灵活管道。此外,M2M 还确定了关键物种,这些物种是群落中对感兴趣功能有意义的成员。我们证明 M2M 适用于基因组集合以及宏基因组组装基因组,允许使用 Pathway Tools 进行高效的 GSMN 重建,并评估物种之间的合作潜力。M2M 通过将大规模微生物群落简化为具有等效特性的最小群落来识别关键生物,从而适合进一步分析。