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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Published on: June 11, 2015

ProphET, prophage estimation tool: A stand-alone prophage sequence prediction tool with self-updating reference

João L Reis-Cunha^1,2, Daniella C Bartholomeu², Abigail L Manson¹

¹Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.

|October 3, 2019

Summary

This summary is machine-generated.

ProphET is a new tool for identifying prophages (bacterial viruses integrated into genomes) in prokaryotic DNA. It offers a fast and scalable alternative to existing web-based prophage detection methods.

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Last Updated: Jan 6, 2026

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

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Published on: June 11, 2015

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

Area of Science:

Genomics
Microbiology
Bioinformatics

Background:

Prophages significantly influence prokaryotic evolution by transferring genes, impacting virulence and antibiotic resistance.
Phage therapy is a growing area of interest for combating bacterial infections.
Identifying prophages in genomes is crucial for understanding their evolutionary roles and therapeutic potential.

Purpose of the Study:

To develop a user-friendly, installable prophage prediction tool.
To provide a scalable solution for prophage identification in large genomic datasets.
To overcome the limitations of current web-based prophage detection tools.

Main Methods:

ProphET utilizes similarity searches against a prophage gene database.
Input requires bacterial genome sequences (FASTA) and gene annotations (GFF).
The prediction process involves similarity search, prophage gene density calculation, and edge refinement.

Main Results:

ProphET was evaluated against 54 bacterial genomes with 267 manually annotated prophages.
The tool demonstrated high precision in identifying prophages.
ProphET offers a faster and more scalable alternative to existing web-based predictors.

Conclusions:

ProphET is an effective and efficient tool for prophage detection in bacterial genomes.
Its ease of installation and operation makes it suitable for routine genomic analysis.
The tool supports the advancement of research in prophage biology and phage therapy.