Work

Highly accurate prophage island detection with PIDE

Year: 2025

Type: article

Abstract: As important mobile elements in prokaryotes, prophages shape the genomic context of their hosts and regulate the structure of bacterial populations. However, it is challenging to precisely identify prophages through computational methods. Here, we introduce PIDE for identifying prophages from bacterial genomes or metagenome-assembled genomes. PIDE integrates a pre-trained protein language model and gene density clustering algorithm to distinguish prophages. Benchmarking with induced prophage sequencing datasets demonstrates that PIDE pinpoints prophages with precise boundaries. Applying PIDE to 4744 human gut representative genomes reveals 24,467 prophages with widespread functional capacity. PIDE is available at https://github.com/chyghy/PIDE , with model training code at https://zenodo.org/records/16457629 .

Source: Genome biology

DOI: 10.1186/s13059-025-03733-0

Authors: Hongyan Gao, Bowen Li, Zihan Guo, Lei Zheng, Junnan Chen, Guanxiang Liang

Institutions: Center for Life Sciences, Tsinghua University, Shanxi Medical University

Language: English

Topic: Bacteriophages and microbial interactions

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $5,490

Funders: National Natural Science Foundation of China, Tsinghua University