Multiple infection of cells changes the dynamics of basic viral evolutionary processes.

Area of Science:

• Virology
• Evolutionary Biology
• Computational Biology

Background:

• Viral infection multiplicity significantly influences viral evolution, yet key dynamics are not fully understood.
• Understanding these dynamics is crucial for interpreting experimental data and modeling complex viral processes.

Purpose of the Study:

• To investigate the impact of infection multiplicity on viral mutant fixation probability, generation rate, and invasion timing.
• To elucidate the short-term and long-term effects of multiple infections on neutral and disadvantageous viral mutants.

Main Methods:

• Utilized computational models to simulate viral infection dynamics.
• Analyzed the fitness advantage of rare mutants in high multiplicity infections.
• Examined the influence of infection multiplicity on mutant fixation probabilities under drift and negative selection.

Main Results:

• Rare neutral or disadvantageous mutants initially gain a fitness advantage in high multiplicity infections due to increased entry into target cells.
• This initial advantage is transient, with higher multiplicities ultimately reducing the chances of mutant fixation.
• Increased infection multiplicity promotes short-term mutant presence but hinders long-term fixation.

Conclusions:

• Infection multiplicity presents a complex dynamic in viral evolution, offering initial benefits but long-term suppression of rare mutants.
• Theoretical insights provide a framework for interpreting experimental viral evolution data across different infection multiplicities.
• This work lays the foundation for studying more intricate viral evolutionary processes like recombination and interactions.