TattleTail: A Rule-Based Tool for Identifying Canonical Pyocin-Encoding Gene Clusters in Pseudomonas aeruginosa

Abstract

Tailocins are phage tail-like bacteriocins derived from prophages that have lost the ability to package viral genomes while retaining bactericidal activity against related bacterial strains. In Pseudomonas aeruginosa, these elements are referred to as pyocins and contribute to ecological fitness and antimicrobial applications. Despite lacking essential phage components, pyocin-encoding gene clusters share substantial sequence homology with phage tail genes, creating a major challenge for genome annotation. Current prophage prediction tools, which rely on phage gene homology, can frequently misclassify pyocins as prophages, potentially confounding genomic analyses and downstream experimental design. Here, we present TattleTail, a rule-based bioinformatic pipeline for identifying canonical pyocin-encoding gene clusters in P. aeruginosa. The current implementation targets the characteristic trpE–trpG-associated genomic architecture of these loci and integrates the detection of conserved pyocin-associated genes with the exclusion of canonical phage features, enabling discrimination between pyocin-encoding gene clusters and prophage regions. Evaluation across manually curated and independently selected P. aeruginosa genomes, together with P. aeruginosa genomes computationally depleted of their pyocin loci and non-P. aeruginosa controls, demonstrated accurate identification of canonical pyocin loci without false-positive predictions. Application to clinical isolates identified representative pyocin clusters, which were experimentally validated by mitomycin C induction, transmission electron microscopy, and bactericidal activity assays, supporting that predicted loci in these isolates correspond to functional pyocin particles. TattleTail complements existing prophage prediction tools and supports accurate annotation of phage-derived elements.