PHI: a Galaxy-based workflow for reproducible prophage-host interaction analysis and standardized viral-genomics reporting

Abstract Background Viruses that infect bacteria, known as bacteriophages or phages, are widespread in nature and play important roles in shaping microbial communities and ecosystem functions. Some phages can integrate into bacterial genomes as “prophages”, where they may influence the biology of their host by carrying genes that affect metabolism, virulence, or environmental adaptation. Despite their importance, studying prophages and their interactions with bacterial hosts remains challenging because it typically requires combining many complex computational tools and can be resource-intensive. Results In this study, we introduce the Prophage-Host Interaction Toolkit (PHI), a user-friendly and automated workflow available through the Galaxy platform. PHI brings together multiple established tools into a single, reproducible pipeline that identifies candidate prophages, evaluates their quality, predicts host relationships, and characterizes key functional genes. Importantly, all results are summarized in an interactive report that simplifies interpretation. Applied to the MBARC22 mock community of 22 bacterial reference genomes as a workflow demonstration, PHI identified 41 candidate prophages across 14 hosts, including high- and medium-quality viral genomes. Most host genomes exhibited > 99% completeness and < 1% contamination, while DefenseFinder identified between 3 and 24 antiviral defense systems per genome. To further evaluate applicability to metagenome-derived assemblies, PHI was also applied to three MAGs and their matched reference genomes. Differences in candidate prophage counts and sequence-level correspondence between MAGs and references demonstrated that prophage recovery can be strongly influenced by genome fragmentation and assembly continuity, even in otherwise high-quality MAGs. Conclusions By removing installation barriers and consolidating the outputs of multiple established tools, PHI lowers the barrier to advanced phage analysis, enabling both specialists and non-experts to explore phage-host interactions and their implications in areas such as microbiome research, biotechnology, and environmental science.

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Publication Details

Journal
BMC Bioinformatics
Published
2026-11-11
DOI
https://doi.org/10.1186/s12859-026-06711-w
Primary Topic
Bacteriophages and microbial interactions
Type
article
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article

PHI: a Galaxy-based workflow for reproducible prophage-host interaction analysis and standardized viral-genomics reporting

Matthias Bernt, Felipe Borim Corrêa, Esteban Emanuel Nieto, Lukas Y. Wick et al.
BMC Bioinformatics
Bacteriophages and microbial interactions
article

PHI: a Galaxy-based workflow for reproducible prophage-host interaction analysis and standardized viral-genomics reporting

Matthias Bernt, Felipe Borim Corrêa, Esteban Emanuel Nieto, Lukas Y. Wick, Nawras Ghanem, Rodolfo Brizola Toscan, J. Saraiva, Antonis Chatzinotas
article en

Abstract

Abstract Background Viruses that infect bacteria, known as bacteriophages or phages, are widespread in nature and play important roles in shaping microbial communities and ecosystem functions. Some phages can integrate into bacterial genomes as “prophages”, where they may influence the biology of their host by carrying genes that affect metabolism, virulence, or environmental adaptation. Despite their importance, studying prophages and their interactions with bacterial hosts remains challenging because it typically requires combining many complex computational tools and can be resource-intensive. Results In this study, we introduce the Prophage-Host Interaction Toolkit (PHI), a user-friendly and automated workflow available through the Galaxy platform. PHI brings together multiple established tools into a single, reproducible pipeline that identifies candidate prophages, evaluates their quality, predicts host relationships, and characterizes key functional genes. Importantly, all results are summarized in an interactive report that simplifies interpretation. Applied to the MBARC22 mock community of 22 bacterial reference genomes as a workflow demonstration, PHI identified 41 candidate prophages across 14 hosts, including high- and medium-quality viral genomes. Most host genomes exhibited > 99% completeness and < 1% contamination, while DefenseFinder identified between 3 and 24 antiviral defense systems per genome. To further evaluate applicability to metagenome-derived assemblies, PHI was also applied to three MAGs and their matched reference genomes. Differences in candidate prophage counts and sequence-level correspondence between MAGs and references demonstrated that prophage recovery can be strongly influenced by genome fragmentation and assembly continuity, even in otherwise high-quality MAGs. Conclusions By removing installation barriers and consolidating the outputs of multiple established tools, PHI lowers the barrier to advanced phage analysis, enabling both specialists and non-experts to explore phage-host interactions and their implications in areas such as microbiome research, biotechnology, and environmental science.

BMC Bioinformatics
Jagiellonian University (PL), Helmholtz Centre for Environmental Research (DE), University of Thessaly (GR), German Centre for Integrative Biodiversity Research (DE), Leipzig University (DE)
Bacteriophages and microbial interactions
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