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Metabolites 2017, 7(4), 62; https://doi.org/10.3390/metabo7040062

Computational Approaches for Integrative Analysis of the Metabolome and Microbiome

1
Institute of Parasitology, McGill University, Montreal, QC H3A 0G4, Canada
2
Department of Animal Science, McGill University, Montreal, QC H3A 0G4, Canada
*
Author to whom correspondence should be addressed.
Received: 26 October 2017 / Revised: 14 November 2017 / Accepted: 16 November 2017 / Published: 18 November 2017
(This article belongs to the Section Thematic Reviews)
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Abstract

The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics) to enable resolution of microbiome-conferred functionalities associated with health. However, analyzing the resulting multi-omics data remains a significant challenge in current microbiome studies. In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation analysis to metabolic network-based modeling approaches. Throughout the process, we strive to present a unified conceptual framework for multi-omics integration and interpretation, as well as point out potential future directions. View Full-Text
Keywords: metabolome; microbiome; multi-omics integration; integrative analysis metabolome; microbiome; multi-omics integration; integrative analysis
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Chong, J.; Xia, J. Computational Approaches for Integrative Analysis of the Metabolome and Microbiome. Metabolites 2017, 7, 62.

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