Periodic versus intermittent adaptive cycles in quasispecies coevolution

Area of Science:

• Theoretical biology
• Evolutionary dynamics
• Computational virology

Background:

• Viruses continuously mutate, posing challenges to adaptive immune systems.
• Coevolutionary dynamics between pathogens and hosts are complex and not fully understood.
• Understanding these dynamics is crucial for predicting disease progression and developing effective treatments.

Purpose of the Study:

• To develop an abstract model for the coevolution of mutating viruses and adaptive immunity.
• To investigate the interdependence of delocalization and error thresholds in this system.
• To analyze the factors influencing the transition between periodic and intermittent evolutionary chase dynamics.

Main Methods:

• Abstract modeling of virus-immune system coevolution.
• Sequence space analysis to understand population localization.
• Simulations and stochastic analysis to explore dynamic regimes.

Main Results:

• A novel interdependence between delocalization and error thresholds was identified, contingent on immune response.
• Stochastic fluctuations can induce an evolutionary chase, manifesting as periodic or intermittent cycles.
• The transition between these dynamic regimes is sensitive to mutation rate, immune response strength, and population size.

Conclusions:

• The coevolutionary dynamics between viruses and the immune system are intricate, with immune response playing a critical role in viral evolution.
• The model provides insights into the mechanisms driving evolutionary chases and their cyclical nature.
• Findings highlight the importance of considering mutation rates, immune response, and population size in understanding viral evolution and immune system adaptation.