Host factor prioritization for pan-viral genetic perturbation screens using random intercept models and network...

Area of Science:

• Virology
• Genetics
• Computational Biology

Background:

• Genetic screens identify host factors crucial for pathogen replication.
• Previous studies focused on single pathogens and limited gene subsets.
• Identifying pan-pathogen host factors is vital for broad-spectrum antiviral therapies.

Purpose of the Study:

• To develop a novel computational procedure for identifying host factors common to diverse viral replication.
• To apply this method to RNA interference (RNAi) screening data from multiple viruses.
• To discover and validate novel host factors influencing viral life cycles.

Main Methods:

• A two-stage procedure combining random effects models and Markov random walks on a functional interaction network.
• Joint analysis of multiple RNAi screens to infer candidate host genes.
• Network-based analysis to incorporate pathway information and smooth effect sizes.

Main Results:

• The procedure identified novel host factors, including UBC, PLCG1, and DYRK1B, crucial for viral replication.
• Applied to RNAi data from Hepatitis C virus, Chikungunya virus, Dengue virus, and SARS-CoV.
• Experimental validation confirmed the role of identified host factors in pathogen replication.

Conclusions:

• The novel computational approach effectively identifies pan-pathogen host factors.
• UBC, PLCG1, and DYRK1B represent promising targets for broad-spectrum antiviral drug development.
• This method advances the discovery of host-directed antivirals.