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Trends Microbiol. 2017 Mar;25(3):217-228. doi: 10.1016/j.tim.2016.11.008. Epub 2016 Dec 2.

Disentangling Interactions in the Microbiome: A Network Perspective.

Author information

1
Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
2
Department of Pathology, University Health Network Toronto, Ontario, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
3
Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada; Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, Ontario, Canada. Electronic address: david.guttman@utoronto.ca.

Abstract

Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we highlight recent advances in network theory and their applicability to microbiome research. We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions that occur within microbiomes. Network-based analytical approaches have the potential to help disentangle complex polymicrobial and microbe-host interactions, and thereby further the applicability of microbiome research to personalized medicine, public health, environmental and industrial applications, and agriculture.

KEYWORDS:

keystone species; microbial clusters; microbial interactions; microbiome; network

PMID:
27916383
DOI:
10.1016/j.tim.2016.11.008
[Indexed for MEDLINE]

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