Virus Evolution. Lecture 6. Chapter 20, pp. 759 вЂ“ 777. Basic point: Virus evolution is fast вЂўFast generation time вЂўHigh rates of fecundity вЂўHigh rates of mutation Mechanisms of viral evolution вЂў вЂў вЂў вЂў Mutation Recombination Reassortment Selection Virus-infected cells produce large numbers of progeny (fecundity) вЂў Infection of a single cell by poliovirus can yield up to 104 viral particles. вЂў In a person, up to 109 вЂ“ 1011 particles can be produced per day вЂў Enough to infect every person on the planet. High mutation rates: genome replication is inaccurate вЂў Evolution requires mutation вЂў Mutations occur when nucleic acids are copied (i.e. genome replication) вЂў Baseline chemical mutation rate (keto to enol tautamarization of thymidine) = 10-4 вЂў Error rate of human DNA polymerase is approximately 10-9 (3 mutations per replication of the human genome). вЂў Error correction machinery lowers this to 10-11 вЂў Virus RNA and DNA polymerases are much more error prone вЂ“ RNA dependent RNA pol error rates: 10-4 вЂ“ 10-5 вЂ“ DNA polymerases: 10-6 вЂ“ 10-7 Some numbers Given вЂў An RNA virus with a genome of 10 kb (i.e. 104 kb) вЂў RDRP error rate of 10-5 пѓ 10-5/104 = 10-1 = 1 in 10 progeny genomes will contain a mutation. вЂў If 109 viral particles produced in a person per day, then 108 mutant progeny are being produced in that one individual each day of infection! Quasispecies, error threshold, bottlenecks and fitness вЂў Quasispecies: Virus populations as вЂў dynamic distributions of nonidentical вЂў but related replicons. вЂў The error threshold: Too much mutation can be lead to loss of vital information, while too little mutation can lead to host defenses overcoming the virus. Error threshold is a mathematical parameter that measures the complexity of the information that must be maintained to ensure survival of the population. The greatest fitness is when mutation rates approach the error threshold. вЂў Genetic drift: slow accumulation of mutations in a population. Due to constant selective pressure in a single host species. вЂў Genetic shift: a major genetic change caused by mixing of genomes derived from two distinct populations of viruses, e.g. viruses that infect two different species. More Terms вЂў Genetic information exchange: Genetic information is exchanged by recombination of genome segments. Infection of a cell by two different viruses can result in exchange of genetic information, resulting in production of mixed progeny. вЂў Genetic bottleneck: extreme selective pressure on a small population. Results in loss of diversity and accumulation of non-selected mutations. вЂў Fitness: the replicative adaptability of an organism to its environment. Fitness is influenced by all of the above. Quasispecies, population size, bottlenecks and fitness (Fig. 20.1) Two general pathways for virus evolution Co-evolution with host вЂў Advantage: prosperous host = prosperous virus вЂў Disadvantage: virus shares same fate as host. Genetic bottleneck events can be fatal. вЂў Typically used by DNA viruses Infection of multiple host species. вЂў Advantage: if one host species is compromised, virus can replicate in another вЂў Disadvantage: cannot optimize for any one situation. вЂў Typically used by RNA viruses The origin of viruses (Table 20.3). 1. вЂў вЂў вЂў Regressive evolution (parasitism) Viruses degenerated from previously independent life forms Lost many functions Retain only what they needed for parasitic lifestyle 2. Cellular origins вЂў Viruses derived from subcellular functional assemblies of macromolecules that gained the capacity to move from cell to cell. 3. Independent entities вЂў Evolution on course parallel to that of cellular organisms. вЂў Evolved from primitive, pre-biotic self-replicating molecules. вЂў Problem: no fossil record. вЂў Solution: Genomes as the fossil record. вЂў Relationships among different viral genomes provide insight into virus origins. This is the basis of molecular taxonomy. Fig. 20.2 Co-evolution with host populations. вЂў Association of a given viral genome sequence with a particular host group. вЂ“ e.g. different papillomaviruses subtypes are more prevalent in different human populations. вЂў Can use viruses to trace human origins Co-evolution and fitness вЂў Highly virulent virus will kill the host too soon вЂў Too exposed and the host will kill it. пѓ Viruses and hosts tend to co-evolve toward symbiotic or at least mutualistic relationships. Co-evolution and fitness вЂў Example: the yeast killer virus. вЂ“ вЂ“ вЂ“ вЂ“ вЂ“ L-A is a metabolic parasite of the host M is a parasite of L-A However, M confers a selective advantage on host. Host tolerates L-A to maintain M. L-A tolerates M to stay in good graces with host. L-A M1 Dead Cell Toxin Evolution is both constrained and driven by the fundamental properties of viruses вЂў A virus clade can be < 10% divergent вЂў Despite lots of sequence diversity, viral populations maintain stable master or consensus sequences. вЂў Diversity limited to ability to function within certain constraints. These include: вЂ“ Particle geometry: eg. Icosahedral capsids limit genome size by limiting volume. вЂ“ Genomes composed of nucleic acids limits solutions to replication of decoding of viral information. вЂ“ Requirement for interactions with host cell machinery. вЂ“ Requirements for interactions within the host organism. Evolution of new viruses. вЂў Even within constraints, the potential for new mutations is huge. вЂ“ e.g. fully ВЅ of all bases in an RNA genome can be mutated without killing the virus. вЂў For a virus of 104 kb, пѓ 45000 possible sequence permutations due to simple mutation alone. вЂў Even more with recombination. вЂў By contrast, the visible universe contains 4135 atoms. вЂў Conclusion: virus evolution is inescapable and relentless.