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

Open access
Yu, Gang, Xu, Cuifang, Zhang, Danni, Ju, Feng, Ni, Yan·2022·iMeta

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/.

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Metadata

Authors
Yu, G., Xu, C., Zhang, D., Ju, F., & Ni, Y.
Venue
iMeta
Publisher
Wiley
Published
2022-03
Volume
1
Issue
1
Pages
e10-e10
ISSN
2770-596X (ISSN-L)
OpenAlex
W4220753051
Cited by
204
References
4
FWCI
13.26
Type
journal article
Language
en
Open access
gold

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