TASmania: A bacterial Toxin-Antitoxin Systems database

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Bacterial toxin-antitoxin systems (TAS) are crucial for plasmid maintenance, phage defense, persistence, and virulence.
• TAS are widespread across bacterial phyla and classified into six types, with Type II being the most studied.
• Existing methods for TAS discovery are limited, necessitating new computational approaches.

Purpose of the Study:

• To develop and implement a novel in silico pipeline, TASmania, for the discovery of bacterial toxin-antitoxin systems (TAS).
• To identify and classify known and uncharacterized TAS loci, including orphan toxins and antitoxins, across a large bacterial genomic database.
• To provide a robust classification of two-component TAS families and explore their phylum-specific distribution.

Main Methods:

• Developed TASmania, an in silico discovery pipeline utilizing curated HMMs for protein annotation.
• Mined >41,000 bacterial assemblies from the EnsemblBacteria database.
• Organized candidate loci into pseudo-operon structures and applied unsupervised classification for 'popTA' models.

Main Results:

• Identified >2.1 million candidate TAS loci, including orphan toxins and antitoxins.
• Generated 1567 'popTA' models for robust classification of two-component TAS families.
• Discovered six putative novel TAS candidates in Mycobacterium tuberculosis through preliminary in vivo validation.

Conclusions:

• TASmania is an effective tool for discovering and classifying bacterial toxin-antitoxin systems.
• The findings provide insights into TAS modular structures and phylum-specific characteristics.
• The identified TAS candidates, particularly in M. tuberculosis, warrant further investigation for their biological roles.