Dynamic network approach for the modelling of genomic sub-complexes in multi-segmented viruses

Area of Science:

• Virology
• Molecular Biology
• Bioinformatics

Background:

• Viruses with segmented genomes, like influenza and Bluetongue virus (BTV), must accurately package specific genetic segments.
• Incorrect packaging can lead to non-infectious viral particles.

Purpose of the Study:

• To develop a novel network approach for predicting RNA-RNA interactions between viral genomic segments.
• To identify and validate specific sites involved in segment selection and packaging.

Main Methods:

• Development of a network approach to predict RNA-RNA interactions.
• Experimental validation using Bluetongue virus (BTV) genomic segments.
• Biochemical and molecular techniques, including mutagenesis and reverse genetics.

Main Results:

• The network approach successfully predicted RNA-RNA interactions between BTV genomic segments.
• Specific sites, termed segment assortment signals (SASs), were identified as crucial for inter-segment interactions.
• Mutagenesis and reverse genetics confirmed the role of SASs in segment assortment and viral genome packaging.

Conclusions:

• The novel network approach is effective in predicting RNA-RNA interactions critical for viral genome packaging.
• Identified segment assortment signals (SASs) are key determinants of viral segment selection.
• These findings open new avenues for antiviral drug targets to inhibit viral assembly or create defective particles.