Traditional evolutionary studies involve piecing together past evidence from fossils of extinct species and comparative studies of extant species, an approach that depends on millions of years of evolution of the investigated organisms. Modern evolutionary studies utilise controlled field manipulations or laboratory experiments to explore evolutionary dynamics, and this is termed experimental evolution. One of the first scientists to carry out experimental evolution was William Dallinger in the 19th century (Dallinger, 1888). He cultivated unicellular organisms in an incubator for several years.
At the start, the organisms normally showed signs of distressed growth at 23oC. Dallinger gradually increased the temperature from 15oC – 65oC and at the end of his experiment the population of organisms have adapted to the environmental change and were growing at 65oC. However, the adapted organisms were unable to grow at 15oC.
Microorganisms are particularly useful for experimental evolutionary studies.
There are several reasons for this. Microorganisms have the capacity to produce large populations with short generation times enabling evolution to be studied in real time. Microorganisms’ small sizes allow large populations to be propagated in smaller spaces, while their relatively small genomes facilitate sequencing. Storage and culture is carried out in conditions that are easier to control, and the opportunities for experimental replications make microbes an excellent choice for experimental evolution (reviewed in
Buckling et al., 2009; Kawecki et al., 2012). The use of microorganisms has changed the study of the mechanisms of evolutionary processes and there has been a transformation of evolutionary biology, allowing theories to be tested directly and its studied in real time (Buckling et al., 2009).
A prominent example of experimental evolution utilizing microbes is the E.
coli long-term evolution experiment (LTEE). The LTEE was started in 1988 by Richard Lenski at the University of Michigan, and is still underway. Lenski and colleagues have followed the evolution of 12 populations of E. coli, tracking genetic changes over time in this experiment. At the time of writing, the populations have been growing for over 71,000 generations, and multiple publications have emerged from these experimental data (Barrick et al., 2009; Tenaillon et al., 2016; Good et al., 2017; Lenski et al., 2017). Since then, several evolution experiments have been performed utilizing yeasts, bacteria and viruses. Viruses, as microorganisms, share the same benefits described above and allow researchers to explore a diverse group of
organisms that are extremely numerous. They play a particularly significant role in studies of host-parasite interactions. Viruses are dynamic and their properties and life cycles facilitate rapid adaptation and change, defeating the most creative expectations of many researchers (Manrubia, 2012).
Experimental evolution has led to many new discoveries, providing a wealth of information and knowledge about how evolution works, enabling
evolutionary scientists to test theories directly, revealing answers to multiple long-due evolution questions. The combinations of experimental methods in evolutionary studies and high-throughput sequencing technologies has yielded many valuable approaches for evolutionary studies. The
development of high-throughput sequencing and advanced methods for deep sequencing has facilitate tracking of evolutionary dynamics. The evolution tracking of genotypes within a short period, with capacity of
comparisons of populations assayed from the past, contemporary, and even future predictions can be made. Thus allowing to track evolutionary
processes such as elucidating adaptive mechanisms in organisms.
1.7.1 Experimental evolution of ΦX174
The bacteriophage ΦX174 has been an important model system for experimental evolution studies. This is mostly due to its rapid replication cycle, ease of cultivation (shared with other viral systems) which permit culturing large populations in a short period of time at low cost. Its common laboratory host E. coli C possesses a short generation time and is robust to a wide range of temperatures making it ideal for evolution experiments
(Wichman and Brown, 2010). Detailed structural information is also available for ΦX174, while its particularly small genome (5,386bp) makes it amenable to genetic manipulation and facilitates accurate tracking of genetic changes that might occur during evolution and adaptation. The small target size increases expected sample coverage for a given sequencing yield. It has been employed extensively to study the patterns and processes of evolution including by cataloguing genetic variation in viral populations, tracking evolutionary dynamics across populations, elucidating mutation spectra and rates, and identifying adaptations occurring in varying environments. ΦX174 was first developed as a model organism for experimental studies by J.J. Bull in 1993 (reviewed in Wichman and Brown, 2010).
1.7.1.1 Experimental evolution studies using ΦX174 The first experimental evolution study with ΦX174 used the virus to examine the extent of parallel evolution; the rates of convergent evolution and
substitution were assessed during adaptation at high temperatures in a chemostat on two different hosts (Bull et al., 1997). Bull et al. (1997) found out that among nine lineages, half of the substitutions and one-third of nucleotide sites observed were identical in multiple lineages. In a similar parallel evolution study, Wichman et al. (1999) examined the molecular basis of adaptation under strong selection, discovering that although half of
changes in one line appeared in the other, parallel mutations did not occur in a similar order. The authors also found out that most substitutions were adaptive in the replicate lineages but these parallel substitutions did not
show changes with largest beneficial effects or reflect common evolutionary trajectory pattern of adaptation.
Host-specific adaptation of ΦX174 has also been examined. Crill et al. (2000) observed adaptation of ΦX174 on E. coli C and S. Typhimurium hosts. They found that, when adapted in S. Typhimurium, the virus’s growth rate was reduced on the E. coli host as a result of substitutions in the major capsid gene. When ΦX174 was forced to grow on E. coli, reversion mutations were observed at the same sites. In a different study ΦX174 and a closely related phage, S13, were adapted, in replicate lines, to E. coli C hosts. Viral samples were analysed for accumulated nucleotide changes. It was observed that changes occurred at sites where ΦX174 differed from S13, leading the authors to conclude that there were limited pathways taken by the viruses during evolution (Wichman et al., 2000). In another study, involving evolution of ΦX174 in three E. coli mutants with different LPS host receptors, the authors suggested that evolution of Microviridae may have relatively high levels of variation with mutations not shared between adapted phage; only one mutation occurred in multiple replicate lineages (Pepin et al., 2008).
Based on this evidence, it is likely that evolutionary pathways depend on the starting genotype of the virus as well as on the nature of the environmental shift.
Epistatic effects in the ΦX174 genome have been studied. A study by Bull et al. (2000) investigated the effects of beneficial mutations that occurred when ΦX174 was grown at high temperature. It was noted that mutations occur in the genes encoding the coat and internal scaffolding proteins and coat protein fitness effects exhibited epistasis, supporting a model, diminishing returns epistasis, that beneficial mutation is scaled depending on the opportunity for fitness improvement in the genome. In diminishing returns epistasis, combinations of beneficial mutations that confer an advantage to an organism in a particular environment may reduce in benefit if introduced into a more fit environment (Chou et al., 2011). When fitness effects of two
single mutants and five different combinations of the corresponding double mutants in six conditions were tested, it was observed that epistatic effects differed in degree, sign and variability across host environments, even
between single mutations in the same two sites (Pepin and Wichman, 2007).
Some studies investigated evolutionary dynamics using ΦX174. For
instance, Dickins and Nekrutenko (2009) showed that even at positions with low-frequency genomic variation, it is possible to detect substitution
dynamics occurring during adaptation using deep sequencing. Pepin and Wichman (2008) observed the evolutionary dynamics of ΦX174, while testing for beneficial mutations and clonal inference’s effect on adaptation using genetic data under benign and harsh environments. They recorded that, although clonal interference may be determined by the particular beneficial mutations that arise during adaptation, its occurrence largely depends on selective conditions.
Holder and Bull (2001) investigated fitness and genetic changes during adaptation under inhibitory growth conditions. The role of mutational biases and translational efficiency of engineered ΦX174 was studied to determine evolutionary processes affecting codon compatibility between viruses and their hosts (Kula et al., 2018). Brown et al. (2013) examined the adaptive changes that occurred on ΦX174 genes when ΦX174 was grown for 50 days in a chemostat, and noted that in addition to changes in host recognition and capsid proteins, changes also occurred in genes involved in replication with host environment as a selective pressure. Also, Bull et al. (2006) studied the dynamics and impact of host population density on ΦX174 adaptation and the impact of adaptation on population density using chemostat. The study addressed both ecology and evolution of population density in models and concluded that in a single chambered predator-prey system (figure 1.4), virus maintained low density, while in two-chambered chemostat (figure 1.5), ΦX174 adaptation led to high viral density that favoured competition.
Wichman et al. (2005) tracked ΦX174 evolution in a continuous culture for
180 days, the longest study carried out in a chemostat with ΦX174, and suggested that a continuous molecular evolution may ensure an indefinite arms race of the system as a consequence of co-infection which may lead to genome competing with one another in a bacterial cell.