Sphae: an automated toolkit for predicting phage therapy candidates from sequencing data.

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Phage therapy is a promising alternative to antibiotics for bacterial infections.
• Genomic screening of bacteriophages is crucial for identifying safe and effective therapeutic candidates.
• Current genomic screening methods are time-consuming and labor-intensive, delaying clinical application.

Purpose of the Study:

• To develop an automated bioinformatics pipeline, Sphae, for rapid and comprehensive genomic evaluation of bacteriophages.
• To streamline the assessment of phage safety and therapeutic suitability.
• To accelerate the deployment of phage therapy by reducing the time for genomic analysis.

Main Methods:

• Development of Sphae, an automated bioinformatics pipeline using the Snakemake workflow manager.
• Integration of tools for phage quality control, assembly, genome assessment, and annotation.
• Automated detection of key genomic markers: virulence factors, antimicrobial resistance genes, and lysogeny indicators (integrase, recombinase, transposase).

Main Results:

• Sphae analyzes phage genomes in under 10 minutes.
• Out of 65 analyzed phage sequences, 28 were identified as having therapeutic potential.
• Identified issues in other phages, including low sequencing depth (8), prophage/virulent markers (22), and multiple phage genomes (23).

Conclusions:

• Sphae significantly accelerates the genomic evaluation of bacteriophages for therapeutic use.
• The pipeline provides a rapid assessment of phage safety and suitability for therapy.
• Sphae is scalable, portable, and readily deployable on various computing platforms, facilitating wider adoption in phage research and clinical applications.