Date Published: May 30, 2013
Publisher: Public Library of Science
Author(s): Alexander W. Ensminger, Joseph Heitman.
Twenty-five years and over 50,000 bacterial generations ago, one of the longest open-ended experiments in modern times began when the Lenski laboratory started passaging Escherichia coli under conditions of limited glucose as a carbon source . Later that same year, a paper was published describing a new method for DNA sequencing, called pyrosequencing, that would ultimately light a path toward massively parallel (next-generation) sequencing . As of 2013, a raw megabase of DNA costs less than $0.10 , or roughly equivalent to the cost of one petri dish. Combined with access to this affordable, high-throughput sequencing, experimental evolution  represents a sophisticated approach to dissecting host-pathogen interactions and testing models of host range and pathogen adaptation. Here, we review how experimental evolution has been used to directly test models of host-pathogen interactions (Figure 1). We discuss parallels between these laboratory studies and the real-world evolutionary trajectories that have been uncovered through the direct sequencing of clinical isolates.
Laboratory passage has long been recognized as an effective means to modify the host range of pathogens, with successive passage of viruses in nonhuman hosts an early strategy for generating live attenuated vaccines . The principle behind this attenuation is that confined passage in one host species can modify the host range of a pathogen such that it no longer efficiently causes disease in the original host . Armed with modern molecular and genomic tools, several groups have revisited the basic outlines of this approach to directly test how natural host diversity and host cycling influence the evolutionary trajectory of pathogens.
Experimental evolution can also be used to modulate a pathogen’s transmission between hosts. Usually, the conditions of serial passage (back dilution in growth media) in the laboratory do not recapitulate the nuances involved in natural transmission between hosts, selecting instead for mutations that increase within-host replication . Nevertheless, recent work on H5N1 influenza, a deadly but poorly transmitted strain, indicates that this need not always be the case , . Two independent groups used experimental evolution to select for transmissibility by serially passaging the virus between ferrets. One early model of host-pathogen interactions would have predicted a trade-off between within-host virulence and between-host transmissibility, but in recent years the universal applicability of this model has been questioned . Indeed, these experimentally adapted viruses retained their ability to efficiently kill ferrets while showing dramatic improvements in their ability to spread through a population of hosts, which is inconsistent with the simple virulence/transmission trade-off model. Due to the recognized overlap between ferret-to-ferret and person-to-person spread, both the publication of these findings and the continuation of this research remain the subject of considerable debate.
Many of the concepts of experimental evolution are also relevant to the expanding field of genomic epidemiology, where using whole-genome sequencing to track the spread of disease through a population can also provide real-world information about how pathogens adapt to their human host. In particular, concepts such as parallel genome evolution (repeated selection for mutations in the same genes or pathways in independent clones) and fitness trade-offs between human infection and environmental persistence are as important for understanding outbreaks of disease as they are to laboratory adaptation.
Like many fields, experimental evolution has not escaped the transformative effects of next-generation sequencing. By sequencing the genomes of laboratory-adapted strains, it is now possible to define the molecular basis of microbial adaptation to new environments or conditions. Given that, using current technologies—even large bacterial genomes currently cost less than $100 to sequence at >100× coverage—we favor what could best be described as a sequence first and ask questions later approach to understanding the laboratory evolution of pathogens. Indeed, complex population dynamics, including frequent clonal interference between competing clones within a population, are likely to be quite common during these experiments , . To capture these dynamics, either several isolates from intermediate time-points should be sequenced, high-resolution genotyping should be performed , , or metagenomic sequencing of the population should be used to estimate allelic frequencies across the experimental time frame , .
With the increased ability to link laboratory adaptations to specific genetic lesions via affordable, widely accessible sequencing, the application of experimental evolution to study pathogen adaptation has never held more potential (Table 1). Future challenges in experimental design include the development of sequencing and analysis tools that are better designed to identify complex genomic rearrangements and gene duplication, as one recent paper elegantly demonstrated that copy number expansion can be a powerful driving force in the rapid adaptation of viruses to a suboptimal host . Furthermore, as real-world pathogen adaptation is never as simple as one host, one pathogen, a logical next step will be to include coinfections with multiple pathogens  in these laboratory models to allow for interspecies competition as well as horizontal gene transfer between adapting pathogens. Lastly, as the price of sequencing continues to fall, studying the host genome’s response to prolonged pathogen exposure will be a natural extension for the field.