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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Published on: August 31, 2014
Modeling within-host evolution of HIV: mutation, competition and strain replacement
Colleen L Ball1, Michael A Gilchrist, Daniel Coombs
1Department of Mathematics and Institute of Applied Mathematics, University of British Columbia, 1984 Mathematics Road, Vancouver, BC, V6T 1Z2, Canada.
Bulletin of Mathematical Biology
|June 8, 2007
Summary
Virus evolution within a host leads to strain replacement over time. A novel model reveals a shift from fast-replicating to moderately-replicating virus strains, impacting chronic disease progression.
Area of Science:
- Virology
- Mathematical Biology
- Evolutionary Biology
Background:
- Virus evolution within a single host is a hallmark of chronic viral infections.
- Simple models predict competitive exclusion of minor strains by a dominant, fast-replicating strain.
- Existing models do not fully capture the dynamics of strain replacement during prolonged infection.
Purpose of the Study:
- To investigate virus strain dynamics using a model incorporating a trade-off between replication rate and host cell survival.
- To analyze the progression of dominant virus strains over the course of infection.
- To provide a framework for understanding HIV evolution and mutation.
Main Methods:
- Development of a mathematical model for virus strain competition.
- Inclusion of a convex trade-off between within-cell virus reproduction and host cell longevity.
- Analysis of strain dynamics based on replication rates and host cell survival.
Main Results:
- Observed a progression in dominant virus strains from high to moderate replication rates over time.
- Identified distinct "jumps" in the replication rate of the dominant strain during infection.
- Provided analytical estimates for the replication rates of successive dominant strains.
Conclusions:
- A trade-off between virus reproduction and host cell survival drives strain replacement dynamics.
- Virus populations evolve through distinct phases, with shifts in dominant strain characteristics.
- The model offers a foundation for more complex simulations of viral evolution, applicable to HIV and other pathogens.
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