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Conflicting Selection Pressures Will Constrain Viral Escape from Interfering Particles: Principles for Designing
Luke I Rast1,2, Igor M Rouzine1, Ganna Rozhnova1
1Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.
Plos Computational Biology
|May 7, 2016
Summary
Therapeutic Interfering Particles (TIPs) can control HIV evolution. Engineered TIPs prevent the spread of resistant HIV mutants by exploiting evolutionary tradeoffs, offering a potential long-term solution for HIV/AIDS.
Area of Science:
- Virology
- Evolutionary Biology
- Computational Modeling
Background:
- Rapid evolution of RNA viruses like HIV challenges conventional treatments and vaccines.
- Therapeutic Interfering Particles (TIPs) were proposed as engineered molecular parasites to control HIV indefinitely.
- A key question is whether TIPs can maintain resistance-proof control at a population scale against transmissible HIV mutants.
Purpose of the Study:
- To model and assess the population-scale efficacy of Therapeutic Interfering Particles (TIPs) against HIV evolution.
- To determine if TIPs can provide indefinite control of HIV by preventing the spread of TIP-resistant mutants.
Main Methods:
- Development of a multi-scale mathematical model to simulate HIV evolution under TIP pressure.
- Analysis of evolutionary tradeoffs associated with HIV developing resistance to TIPs.
- Simulation of viral protein production, replication fitness, and transmission rates in treated and untreated subpopulations.
Main Results:
- TIP-resistant HIV mutants exhibit reduced transmission in TIP-untreated populations.
- TIP-resistant HIV mutants display decreased replicative fitness in both TIP-treated and untreated individuals.
- TIP-susceptible HIV strains consistently outcompete TIP-resistant mutants when TIPs express >3-fold more genomic RNA than HIV.
Conclusions:
- Evolutionary tradeoffs inherently prevent the widespread transmission of TIP-resistant HIV mutants.
- TIPs can maintain indefinite control of HIV at both patient and population levels under specific design constraints.
- Findings provide crucial design parameters for developing population-scale therapies resistant to antiviral drug escape.
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