mBio (May 2018)

Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution

  • Jason W. Shapiro,
  • Catherine Putonti

DOI
https://doi.org/10.1128/mBio.01870-17
Journal volume & issue
Vol. 9, no. 2

Abstract

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ABSTRACT Bacteriophages are the most abundant and diverse biological entities on the planet, and new phage genomes are being discovered at a rapid pace. As more phage genomes are published, new methods are needed for placing these genomes in an ecological and evolutionary context. Phages are difficult to study by phylogenetic methods, because they exchange genes regularly, and no single gene is conserved across all phages. Here, we demonstrate how gene-level networks can provide a high-resolution view of phage genetic diversity and offer a novel perspective on virus ecology. We focus our analyses on virus host range and show how network topology corresponds to host relatedness, how to find groups of genes with the strongest host-specific signatures, and how this perspective can complement phage host prediction tools. We discuss extensions of gene network analysis to predicting the emergence of phages on new hosts, as well as applications to features of phage biology beyond host range. IMPORTANCE Bacteriophages (phages) are viruses that infect bacteria, and they are critical drivers of bacterial evolution and community structure. It is generally difficult to study phages by using tree-based methods, because gene exchange is common, and no single gene is shared among all phages. Instead, networks offer a means to compare phages while placing them in a broader ecological and evolutionary context. In this work, we build a network that summarizes gene sharing across phages and test how a key constraint on phage ecology, host range, corresponds to the structure of the network. We find that the network reflects the relatedness among phage hosts, and phages with genes that are closer in the network are likelier to infect similar hosts. This approach can also be used to identify genes that affect host range, and we discuss possible extensions to analyze other aspects of viral ecology.

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