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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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This content will become publicly available on February 5, 2026
Towards a unifying phylogenomic framework for tailed phages
Classifying viruses systematically has remained a key challenge of virology due to the absence of universal genes and vast genetic diversity of viruses. In particular, the most dominant and diverse group of viruses, the tailed double-stranded DNA viruses of prokaryotes belonging to the classCaudoviricetes, lack sufficient similarity in the genetic machinery that unifies them to reconstruct an inclusive, stable phylogeny of these genes. While previous approaches to organize tailed phage diversity have managed to distinguish various taxonomic levels, these methods are limited in scalability, reproducibility, and the inclusion of modes of evolution, like gene gains and losses, remain key challenges. Here, we present a novel, comprehensive, and reproducible framework for examining evolutionary relationships of tailed phages. In this framework, we compare phage genomes based on the presence and absence of a fixed set of gene families which are used as binary trait data that is input into maximum likelihood models. Our resulting phylogeny stably recovers known taxonomic families of tailed phages, with and without the inclusion of metagenome-derived phages. We also quantify the mosaicism of replication and structural genes among known families, and our results suggest that these exchanges likely underpin the emergence of new families. Additionally, we apply this framework to large phages (>100 kilobases) to map emergences of traits associated with genome expansion. Taken together, this evolutionary framework for charting and organizing tailed phage diversity improves the systemization of phage taxonomy, which can unify phage studies and advance our understanding of their evolution.
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- Award ID(s):
- 2141862
- PAR ID:
- 10659156
- Editor(s):
- Malik, Harmit S
- Publisher / Repository:
- PLOS Genetics
- Date Published:
- Journal Name:
- PLOS Genetics
- Volume:
- 21
- Issue:
- 2
- ISSN:
- 1553-7404
- Page Range / eLocation ID:
- e1011595
- Subject(s) / Keyword(s):
- Viruses, Evolution, Phylogenetics, Genomics
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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