title: Disentangling Interactions in the Microbiome: A Network Perspective.
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.
authors.affiliation: Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Layeghifard
authors.affiliation: Department of Pathology, University Health Network Toronto, Ontario, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
authors.forename: David M
authors.initials: DM
authors.lastname: Hwang
authors.affiliation: 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.
authors.forename: David S
authors.initials: DS
authors.lastname: Guttman
mesh_terms: D000818:Animals; D006801:Humans; D008827:Microbiological Phenomena; D064307:Microbiota / Q000502:physiology*; D008954:Models, Biological
keywords: keystone species; microbial clusters; microbial interactions; microbiome; network