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Published on: April 12, 2017
Coevolutionary dynamics of viruses and their defective interfering particles
Shiv Muthupandiyan1, John Yin1
1Wisconsin Institute for Discovery, Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Defective interfering particles (DIPs) are viral mutants that parasitize intact viruses. Modeling virus-DIP coevolution reveals population cycles and trait-based chases, impacting therapeutic strategies.
Area of Science:
- Virology
- Evolutionary Biology
- Mathematical Modeling
Background:
- Defective interfering particles (DIPs) are viral mutants that require intact viruses for replication.
- Their evolutionary interplay with viruses involves complex dynamics poorly understood at the population level.
- Understanding these interactions is crucial for viral evolution and therapeutic development.
Purpose of the Study:
- To develop a phenotype-space model for virus-DIP coevolution.
- To investigate the mechanisms shaping population-level outcomes and trait evolution.
- To identify conditions promoting different evolutionary regimes and inform therapeutic design.
Main Methods:
- Developed a continuous phenotype-space model using coupled partial differential equations.
- Incorporated mutation, phenotype-dependent interference, fitness costs, and de novo DIP generation.
- Analyzed population and trait-level dynamics under strong-mutation regimes.
Main Results:
- Observed predator-prey-like population oscillations (von Magnus effect).
- Identified coevolutionary 'chase' dynamics driven by trait evolution.
- Characterized four regimes: coexistence, chase dynamics, DIP extinction, and mutual extinction.
- Found intermediate interference and low decay rates promote chase dynamics.
Conclusions:
- The model provides a general framework for virus-DIP coevolution.
- Both population dynamics and trait evolution are critical determinants of outcomes.
- Findings have implications for designing more robust DIP-based therapeutics against viral escape.
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