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Statistical Mechanics and Thermodynamics of Viral Evolution.

Jones BA, Lessler J, Bianco S, Kaufman JH - PLoS ONE (2015)

Bottom Line: The paper analyzes a model of viral infection and evolution using the "grand canonical ensemble" and formalisms from statistical mechanics and thermodynamics.This paper also reveals a universal relationship that relates the order parameter (as a measure of mutational robustness) to evolvability in agreement with recent experimental and theoretical work.Given that real viruses have finite length RNA segments that encode proteins which determine virus fitness, the approach used here could be refined to apply to real biological systems, perhaps providing insight into immune escape, the emergence of novel pathogens and other results of viral evolution.

View Article: PubMed Central - PubMed

Affiliation: Almaden Research Center, IBM, San Jose, California, United States of America.

ABSTRACT
This paper uses methods drawn from physics to study the life cycle of viruses. The paper analyzes a model of viral infection and evolution using the "grand canonical ensemble" and formalisms from statistical mechanics and thermodynamics. Using this approach we enumerate all possible genetic states of a model virus and host as a function of two independent pressures-immune response and system temperature. We prove the system has a real thermodynamic temperature, and discover a new phase transition between a positive temperature regime of normal replication and a negative temperature "disordered" phase of the virus. We distinguish this from previous observations of a phase transition that arises as a function of mutation rate. From an evolutionary biology point of view, at steady state the viruses naturally evolve to distinct quasispecies. This paper also reveals a universal relationship that relates the order parameter (as a measure of mutational robustness) to evolvability in agreement with recent experimental and theoretical work. Given that real viruses have finite length RNA segments that encode proteins which determine virus fitness, the approach used here could be refined to apply to real biological systems, perhaps providing insight into immune escape, the emergence of novel pathogens and other results of viral evolution.

No MeSH data available.


Related in: MedlinePlus

Model of an Idealized Virus Life Cycle.The barrier height (BE) is equal to the number of mismatches of virus to a target. Viruses with different numbers of genetic matches will see barriers of different height. The probability of a virus passing is based on an activated Arrhenius model.
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pone.0137482.g001: Model of an Idealized Virus Life Cycle.The barrier height (BE) is equal to the number of mismatches of virus to a target. Viruses with different numbers of genetic matches will see barriers of different height. The probability of a virus passing is based on an activated Arrhenius model.

Mentions: The virus has some fitness for crossing these barriers (Fig 1), characterized by a probability of successes which depends on viral fitness and system “temperature”, and is computed using an activated Arrhenius form [23]:ei=exp(fi/T)(1)where ei is the probability of successfully crossing the barrier, fi is viral fitness, and T is the system temperature. At this point one can view T as a parameter that governs how discriminating the barrier is between viruses with different numbers of “matches” to some target receptor. In classical chemistry the barrier height is a function of both reactants and products, while the temperature is a property of the reactants only (viruses in this case). When there is a distribution of energies for the reactants, kBT is the average energy of the most probable distribution. In this model temperature changes the discrimination of the barriers to infection and reproduction. At low temperature viruses with a high match to the target are favored. At very high temperature, virtually all viruses of any match are able to infect and reproduce. As we will see, raising the temperature increases the fraction of viable virions within a quasispecies distribution. We will later demonstrate that temperature in this model is not only a tuning parameter, but also the thermodynamic temperature for the system, providing a distribution of energies for the viruses, which naturally form quasispecies distributions. We will also derive the effective Boltzmann constant relating temperature and the observed energy scales [23–26].


Statistical Mechanics and Thermodynamics of Viral Evolution.

Jones BA, Lessler J, Bianco S, Kaufman JH - PLoS ONE (2015)

Model of an Idealized Virus Life Cycle.The barrier height (BE) is equal to the number of mismatches of virus to a target. Viruses with different numbers of genetic matches will see barriers of different height. The probability of a virus passing is based on an activated Arrhenius model.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4589373&req=5

pone.0137482.g001: Model of an Idealized Virus Life Cycle.The barrier height (BE) is equal to the number of mismatches of virus to a target. Viruses with different numbers of genetic matches will see barriers of different height. The probability of a virus passing is based on an activated Arrhenius model.
Mentions: The virus has some fitness for crossing these barriers (Fig 1), characterized by a probability of successes which depends on viral fitness and system “temperature”, and is computed using an activated Arrhenius form [23]:ei=exp(fi/T)(1)where ei is the probability of successfully crossing the barrier, fi is viral fitness, and T is the system temperature. At this point one can view T as a parameter that governs how discriminating the barrier is between viruses with different numbers of “matches” to some target receptor. In classical chemistry the barrier height is a function of both reactants and products, while the temperature is a property of the reactants only (viruses in this case). When there is a distribution of energies for the reactants, kBT is the average energy of the most probable distribution. In this model temperature changes the discrimination of the barriers to infection and reproduction. At low temperature viruses with a high match to the target are favored. At very high temperature, virtually all viruses of any match are able to infect and reproduce. As we will see, raising the temperature increases the fraction of viable virions within a quasispecies distribution. We will later demonstrate that temperature in this model is not only a tuning parameter, but also the thermodynamic temperature for the system, providing a distribution of energies for the viruses, which naturally form quasispecies distributions. We will also derive the effective Boltzmann constant relating temperature and the observed energy scales [23–26].

Bottom Line: The paper analyzes a model of viral infection and evolution using the "grand canonical ensemble" and formalisms from statistical mechanics and thermodynamics.This paper also reveals a universal relationship that relates the order parameter (as a measure of mutational robustness) to evolvability in agreement with recent experimental and theoretical work.Given that real viruses have finite length RNA segments that encode proteins which determine virus fitness, the approach used here could be refined to apply to real biological systems, perhaps providing insight into immune escape, the emergence of novel pathogens and other results of viral evolution.

View Article: PubMed Central - PubMed

Affiliation: Almaden Research Center, IBM, San Jose, California, United States of America.

ABSTRACT
This paper uses methods drawn from physics to study the life cycle of viruses. The paper analyzes a model of viral infection and evolution using the "grand canonical ensemble" and formalisms from statistical mechanics and thermodynamics. Using this approach we enumerate all possible genetic states of a model virus and host as a function of two independent pressures-immune response and system temperature. We prove the system has a real thermodynamic temperature, and discover a new phase transition between a positive temperature regime of normal replication and a negative temperature "disordered" phase of the virus. We distinguish this from previous observations of a phase transition that arises as a function of mutation rate. From an evolutionary biology point of view, at steady state the viruses naturally evolve to distinct quasispecies. This paper also reveals a universal relationship that relates the order parameter (as a measure of mutational robustness) to evolvability in agreement with recent experimental and theoretical work. Given that real viruses have finite length RNA segments that encode proteins which determine virus fitness, the approach used here could be refined to apply to real biological systems, perhaps providing insight into immune escape, the emergence of novel pathogens and other results of viral evolution.

No MeSH data available.


Related in: MedlinePlus