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MetOrigin:区分微生物代谢物的来源以进行肠道微生物组和代谢组的综合分析。

MetOrigin: Discriminating the origins of microbial metabolites for integrative analysis of the gut microbiome and metabolome.

作者信息

Yu Gang, Xu Cuifang, Zhang Danni, Ju Feng, Ni Yan

机构信息

The Children's Hospital, Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou Zhejiang China.

Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering Westlake University Hangzhou Zhejiang China.

出版信息

Imeta. 2022 Mar 21;1(1):e10. doi: 10.1002/imt2.10. eCollection 2022 Mar.

Abstract

The interactions between the gut microbiome and metabolome play an important role in human health and diseases. Current studies mainly apply statistical correlation analysis between the gut microbiome and all the identified metabolites to explore their relationship. However, it remains challenging to identify the specific metabolic functions of microbes without in vitro culture experiments for validation. Discriminating the microbial metabolites from others (e.g., host, food, or environment) and exploring their metabolic functions and correlations with microbiome specifically may improve the efficiency and accuracy of biomarker discovery. So far, there have been no such bioinformatics tools available. Herein, we developed MetOrigin, an interactive web server that discriminates metabolites originating from the microbiome, performs the origin-based metabolic pathway enrichment analysis, and integrates the statistical correlations and biological relationships in the database using Sankey network visualization. MetOrigin not only enables the quick identification of microbial metabolites and their metabolic functions but also facilitates the discovery of specific bacterial species that are closely associated with metabolites statistically and biologically. MetOrigin is freely available at http://metorigin.met-bioinformatics.cn/.

摘要

肠道微生物群与代谢组之间的相互作用在人类健康和疾病中起着重要作用。目前的研究主要应用肠道微生物群与所有已鉴定代谢物之间的统计相关性分析来探索它们之间的关系。然而,在没有体外培养实验进行验证的情况下,确定微生物的特定代谢功能仍然具有挑战性。将微生物代谢物与其他物质(如宿主、食物或环境)区分开来,并专门探索它们的代谢功能以及与微生物群的相关性,可能会提高生物标志物发现的效率和准确性。到目前为止,还没有这样的生物信息学工具。在此,我们开发了MetOrigin,一个交互式网络服务器,它可以区分源自微生物群的代谢物,进行基于来源的代谢途径富集分析,并使用桑基网络可视化在数据库中整合统计相关性和生物学关系。MetOrigin不仅能够快速识别微生物代谢物及其代谢功能,还有助于发现与代谢物在统计学和生物学上密切相关的特定细菌物种。可通过http://metorigin.met-bioinformatics.cn/免费使用MetOrigin。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/10989983/ffd539432048/IMT2-1-e10-g005.jpg

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