bioRxivBioinformaticsPreprint
Defining the ESKAPE pathogen prophage repertoire with PHORAGER
Xena DyballiD, Alise Jany PonseroiD, James A D DochertyiD, Andrea TelatiniD, Emmanuelle H. CrostiD, Nathalie JugeiD, Ryan CookiD, Evelien M. AdriaenssensiD
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Abstract
Prophages are major drivers of bacterial evolution, mediating horizontal gene transfer and lysogenic conversion to alter host phenotypes. Nevertheless, identifying prophages within bacterial genomes remains challenging due to their heterogeneity and similarity to other mobile genetic elements. Here we present PHORAGER (Prophage Hunting, vOtu Retrieval, Annotation and Genomic ExploRation), a scalable Nextflow pipeline for the standardised identification and quality assessment of prophages from bacterial genomes. PHORAGER incorporates bacterial genome pre-processing, consolidation of predictions from multiple mining tools, annotation-based filtering to reduce false positives, and generation of ready-to-analyse summary tables. We validated PHORAGER using 30,824 publicly available ESKAPE pathogen genomes. PHORAGER recovered more high-quality prophages than individual mining tools alone, and through extensive quality assessments removed a substantial number of false-positive predictions. In total 23,132 putative prophages were identified, the majority belonging to the class Caudoviricetes, and exhibiting a high degree of host-specificity. Putative antimicrobial resistance genes were detected in 0.48% of prophages, whereas virulence factors were most abundant in S. aureus prophages. ESKAPE prophages also frequently encoded anti-phage defence systems. PHORAGER is freely available as open-source software and the ESKAPE prophage collection generated in this study provides a reusable resource for further investigations. GRAPHICAL ABTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/742953v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1ce582org.highwire.dtl.DTLVardef@11fc004org.highwire.dtl.DTLVardef@17765f5org.highwire.dtl.DTLVardef@1c6f0ff_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: benchmarking
- approach: statistical model
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