Identifying New Clusterons: Application of TBEV Analyzer 3.0

Area of Science:

• Bioinformatics
• Virology
• Computational Biology

Background:

• Early characterization of emerging viruses is critical for public health.
• Theoretical models of viral evolution are essential for understanding virus dynamics.
• The clusteron approach offers a hierarchical network structure for viral population analysis.

Purpose of the Study:

• To introduce TBEV Analyzer 3.0, an enhanced bioinformatics platform for tick-borne encephalitis virus (TBEV) strain characterization.
• To improve theoretical models and practical functionality for analyzing TBEV genetic patterns.
• To facilitate rapid identification and exploration of TBEV strains for surveillance purposes.

Main Methods:

• Utilized the clusteron approach, analyzing E protein fragment genetic patterns.
• Updated the clusteron structure model by analyzing available TBEV strains from GenBank.
• Optimized workflow and simplified parameter settings in TBEV Analyzer 3.0.

Main Results:

• The TBEV Analyzer 3.0 platform demonstrates enhanced theoretical and practical capabilities.
• Eleven novel clusterons, primarily from the European subtype, were identified.
• Expanded strain sets for prior clusterons were incorporated into the updated model.

Conclusions:

• TBEV Analyzer 3.0 provides an effective tool for rapid TBEV strain characterization.
• The platform supports analytical and exploratory functions crucial for TBEV surveillance.
• The updated clusteron model improves the understanding of TBEV population structure and evolution.