Experimental Evolution in Viruses


Experiments in which evolution takes place in real time can help us establish cause–effect relationships that are difficult to infer from the analysis of natural populations. The simplicity, rapid evolution and biomedical relevance of viruses make them a particularly interesting model system for experimental evolution. Bacterial, animal and plant viruses can be passaged under a variety of conditions, either in simple cell culture systems or in vivo to test population biology hypotheses, study the genetic basis of evolution, or predict evolutionary change in nature. Experimental evolution is a conceptually simple and flexible tool which allows us to address issues ranging from the molecular to the ecosystem level. In addition to studying basic processes such as mutation, adaptation, or random genetic drift, viruses can be experimentally evolved to better understand the emergence of drug resistance, explore new antiviral strategies such as lethal mutagenesis, create better attenuated vaccines, or target cancerous cells.

Key Concepts:

  • Experimental evolution can be done with many different model organisms, but microorganisms and viruses offer a series of advantages including their easy manipulation, storability and biomedical relevance.

  • The setup of an evolutionary experiment is conceptually simple and essentially consists of serially transferring viruses from flask to flask or, in vivo, from host to host. However, a careful experimental design is needed to be able to demonstrate which factors are responsible for the evolutionary changes observed in the laboratory.

  • Molecular biology is a powerful tool in virus experimental evolution because it allows us to manipulate viral genomes and to study the molecular basis of evolution.

  • Viruses can adapt to many different laboratory environments, but these adaptations often come at the cost of decreased performance in alternative environments, demonstrating the existence of certain limits to adaptation, or fitness tradeoffs.

  • Viral experimental evolution has both stochastic and deterministic components. Therefore, although viral evolution is not easy to predict, it shows some regular patterns.

  • The role played by population–genetic factors such as the population size or the mutation rate have been extensively studied in viruses, and several important generalisations have been established.

  • Experimental evolution has inspired new strategies to combat viral disease, including the use of selective mutagens to damage viral genomes or the use of less evolvable strains to create more effective and safer vaccines.

Keywords: virology; evolutionary biology; population genetics; biomedicine; molecular biology

Figure 1.

Typical experimental evolution scheme. Founder clones are obtained by picking well‐isolated plaques from a reference stock and used to initiate serial transfers (passages) under predefined conditions. Infections can be carried out in microtubes as shown here or in flasks, plates, and even in vivo. Carrying out replicate evolutionary lines and including control lines is important to establish the statistical significance of the results. Downstream analyses can be of any type, but the most common ones are fitness assays and sequencing. Sample storage at ultra‐low temperature makes it possible to carry out these analyses simultaneously for initial, intermediate, and final time points, thus facilitating comparison. Here, the typical fitness trajectory of large populations passaged in a new environment is shown. Sequences in the right indicate hypothetical genetic changes fixed during the experiment.

Figure 2.

Evolution in Wright's fitness landscapes. A landscape with several peaks is shown. Selection pushes populations towards peaks (adaptation), whereas processes of fitness decay such as random genetic drift and, in some cases, mutagenesis pushes them towards valleys. One population starting at a given low‐fitness region may evolve towards different peaks in different experimental replicates (divergence), and populations starting at different regions may converge to the same peak. Efficient selection guarantees that populations will reach peaks, but these peaks might be only local optima. In the absence of other evolutionary forces, selection may fail to move a population from one peak to another.



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Further Reading

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Elena SF and Lenski RE (2003) Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nature Reviews Genetics 4: 457–469.

Elena SF and Sanjuán R (2007) Virus evolution: insights from an experimental approach. Annual Review of Ecology Evolution and Systematics 38: 27–52.

Holmes EC (2009) The Evolution and Emergence of RNA Viruses. Oxford: Oxford University Press.

Sanjuán R (2008) Quasispeces and experimental evolution of RNA viruses. In: Mahy BWJ and van Regenmorted MHV (eds) Encyclopedia of Virology, pp. 359, 365. Oxford: Elsevier.

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Sanjuán, Rafael, and Domingo‐Calap, Pilar(May 2011) Experimental Evolution in Viruses. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0022857]