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.