bioRxivBioinformaticsPreprint
Discovery of novel enzybiotic candidates targeting human bacterial pathogens through large-scale viral-host profiling
Abstract
The rise of antibiotic-resistant bacteria demands alternative therapeutic strategies, with bacteriophage (phage) therapy and phage-derived enzybiotics emerging as promising approaches. However, identifying candidate phages against specific pathogens has historically been a bottleneck due to the need for cultivation methods to assess host range and lytic activity. Advances in metagenomic sequencing and the emergence of large-scale viral genome databases now provide an opportunity to accelerate this process computationally. Here, we present a large-scale mining of the MetaVR database to identify phages targeting human bacterial pathogens. By integrating direct host associations with CRISPR-spacer evidence, we linked 196,472 high-quality and complete viral genomes, representing 42,360 vOTUs, to 618 species of pathogenic and opportunistic bacteria. Functional enrichment analysis revealed distinct genomic signatures with viral lifestyle and host-range breadth: virulent phages were enriched in replication and structural functions, whereas temperate and broad host-range phages were enriched in anti-defense and regulatory modules. To characterize their lytic potential we annotated lysis-related protein families and their structural diversity, identifying 76 structurally novel lysis-associated proteins, including candidates targeting WHO priority pathogens. Focused analysis of endolysins revealed 592 structural clusters, with extensive sharing of endolysin repertoires among ESKAPE pathogens, suggesting candidates for broad-spectrum enzybiotic development. Selection analysis identified 167 endolysin families with sites under positive selection within functional domains, highlighting evolutionary diversification potentially associated with phage-host interactions. Together, our results establish a large-scale framework for connecting human bacterial pathogens to phages and their lytic machinery, providing a resource for prioritizing phage therapy and enzybiotic development.
- organism: human
- assay: metagenomics
- research focus: database / resource
- approach: statistical model
- approach: machine learning (classical)
- Citations
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