Gene Co-occurrence Networks Reflect Bacteriophage Ecology and Evolution

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.

Bacteriophages of the lower urinary tract

“…In this scenario, phage lysis spreads intact host plasmids, enabling HGT via transformation. Given the large genetic diversity present within phage communities 83 , we have only begun to scratch the surface of the complexities of phage-host dynamics 84–86 (for a review, see Manrique et al 28 ).…”

ClassiPhages 2.0: Sequence-based classification of phages using Artificial Neural Networks

“…This occurs in families that are closely related to Siphoviridae ( Myoviridae , Podoviridae ), but also in structurally very distinct families such as Fuselloviridae and Inoviridae . This could indicate unexpected gene flux between unrelated phage species (Shapiro & Putonti 2018).…”

Charting the diversity of uncultured viruses of Archaea and Bacteria

“…Second, our method was based on a phylogenomic tree which inferred evolutionary associations among viral genomic sequences. Thus, it differs from network-based methods that have recently been proposed for the classification of viruses [5, 9, 12, 28]. Phylogenomic trees explicitly resolve the evolutionary associations among viral genomes which is a major advantage over network-based approaches.…”