A Systematic Bioinformatics Approach for Mapping the Minimal Set of a Viral Peptidome

Area of Science:

• Virology
• Bioinformatics
• Computational Biology

Background:

• Viral sequence diversity is key to immune evasion and therapeutic challenges.
• Large sequence datasets offer opportunities for studying viral adaptation.
• Alignment-dependent methods have limitations in analyzing viral diversity.

Purpose of the Study:

• To present a novel alignment-free protocol for analyzing viral sequence diversity.
• To introduce the UNIQmin tool for generating minimal sequence sets.
• To demonstrate the protocol's utility using Monkeypox virus (MPX) data.

Main Methods:

• Utilizing the UNIQmin tool for an alignment-free analysis of viral sequence data.
• Generating a minimal set of sequences representing peptidome diversity.
• Applying the protocol across different taxonomic lineage ranks.
• Conducting a case study with Monkeypox virus (MPX) sequence data.

Main Results:

• The UNIQmin tool effectively identifies minimal sequence sets for viral diversity analysis.
• The protocol allows for alignment-free analysis at any taxonomic rank.
• Demonstrated systematic approach for studying viral sequence diversity.
• MPX data used as a case study to validate the methodology.

Conclusions:

• The developed protocol and UNIQmin tool provide a powerful, alignment-free method for viral diversity studies.
• This approach is crucial for preparedness against viral epidemics, especially with abundant data.
• Facilitates understanding of viral evolution and immune evasion mechanisms.