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

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Antimicrobial resistance necessitates novel therapeutic strategies.
• Phage therapy offers a promising alternative to antibiotics.
• Selecting safe and effective phages requires thorough genomic analysis.

Purpose of the Study:

• To develop an automated bioinformatics pipeline, Sphae, for rapid genomic screening of phage therapy candidates.
• To streamline the identification of genomic markers indicating potential risks in phages.
• To expedite the assessment of phage suitability for therapeutic applications.

Main Methods:

• Development of Sphae, an automated bioinformatics pipeline using Snakemake.
• Integration of tools for quality control, assembly, genome assessment, and annotation specific to phage biology.
• Automated detection of virulence factors, antimicrobial resistance genes, and lysogeny indicators.

Main Results:

• Sphae assesses phage therapeutic potential in under ten minutes.
• Benchmarking on 65 phage sequences revealed varying outcomes: 28 showed potential, 8 failed assembly, 22 had undesirable markers, and 23 contained multiple genomes.
• The pipeline generates comprehensive reports for rapid safety and suitability assessment.

Conclusions:

• Sphae significantly accelerates the genomic evaluation of phages for therapeutic use.
• The pipeline enhances the safety and efficiency of phage selection for clinical applications.
• Sphae's scalability and portability facilitate its deployment across diverse computing platforms.