Arresting Evolution
Authors: James J. Bull, Jeffrey E. Barrick
Journal: Trends in Genetics (2017)

Evolution is sometimes unwanted or harmful to our purposes, especially in organisms we want to control. An understanding of evolutionary principles, specifically of natural selection, can be used to limit evolution. These traditional approaches can restrict the opportunity for evolution even without a molecular understanding of a system. Our multicellular bodies seem to have evolved many of these same strategies for restricting evolution within our bodies (e.g., cancer) and in the germ line. Genetic engineering opens fundamentally new avenues for limiting evolution. It can be used to design genomes that have limited evolutionary capacity or to introduce elements that spread and reverse evolution in populations. Evolution in the form of selective breeding has long been harnessed as a useful tool by humans. However, rapid evolution can also be a danger to our health and a stumbling block for biotechnology. Unwanted evolution can underlie the emergence of drug and pesticide resistance, cancer, and weeds. It makes live vaccines and engineered cells inherently unreliable and unpredictable, and therefore potentially unsafe. Yet, there are strategies that have been and can possibly be used to stop or slow many types of evolution. We review and classify existing population genetics-inspired methods for arresting evolution. Then, we discuss how genome editing techniques enable a radically new set of approaches to limit evolution. Evolution in the form of selective breeding has long been harnessed as a useful tool by humans. However, rapid evolution can also be a danger to our health and a stumbling block for biotechnology. Unwanted evolution can underlie the emergence of drug and pesticide resistance, cancer, and weeds. It makes live vaccines and engineered cells inherently unreliable and unpredictable, and therefore potentially unsafe. Yet, there are strategies that have been and can possibly be used to stop or slow many types of evolution. We review and classify existing population genetics-inspired methods for arresting evolution. Then, we discuss how genome editing techniques enable a radically new set of approaches to limit evolution. Short-term evolution has been both good and bad for humankind. Fueled by artificial selection, it has been critical to the development of modern agriculture, providing high-yielding crops and improved animal breeds [1Diamond J. Evolution, consequences and future of plant and animal domestication.Nature. 2002; 418: 700-707Crossref PubMed Scopus (963) Google Scholar, 2Purugganan M.D. Fuller D.Q. The nature of selection during plant domestication.Nature. 2009; 457: 843-848Crossref PubMed Scopus (603) Google Scholar]. On a smaller physical scale, the practice of directed evolution – the biochemical equivalent of artificial selection – has generated molecules and microbial strains useful to industry and medicine. However, evolution is not assured of working toward human goals, and rapid evolution also causes many problems (Table 1, Key Table). Being able to curtail evolution under these circumstances would have considerable practical benefits.Table 1Key TableContextProblemIndustrial cultures and strainsProduction decays during large-scale or long-term propagationLive vaccinesVaccine strains evolve back to high virulence (poliovirus)Drug resistanceBacteria and viruses evolve to resist drugsPesticide resistanceCrop pests evolve to resist chemical control agentsWeedsWeeds evolve to mimic crops, leading to greater crop contaminationCancerCells evolve through multiple stages to escape controls on cell division and programmed cell deathStem cellsCells potentially used for therapy evolve cancerous properties after culture in the laboratoryOpportunistic infectionsPathogens sometimes evolve to invade new species or locations in the body Open table in a new tab Evolution may indeed be unavoidable if a population is allowed to reproduce unfettered, but there are interventions that can misdirect or slow evolution, block it completely, or even erase it. Some of these approaches mostly require only an understanding of population genetics and assume little to nothing about the underlying molecular biology of a system. They include centuries-old practices and others introduced recently as ostensibly 'evolution-proof' interventions for biocontrol [3Read A.F. et al.How to make evolution-proof insecticides for malaria control.PLoS Biol. 2009; 7: e1000058Crossref PubMed Scopus (187) Google Scholar]. Other strategies have only become evident or possible with recent advances in genomics and genetic engineering. In this review, we classify existing approaches for arresting evolution and describe new methods that are now becoming feasible. There is a long history of selective breeding in agriculture, and civilization has been the beneficiary. A close coupling of population (and quantitative) genetics theory with breeding programs provided the foundations for classical evolutionary theory [4Falconer D.S. Mackay T.F.C. Quantitative Genetics.4th edn. Pearson Education, 1996Google Scholar]. A dominant issue with selective breeding was obtaining a strong and appropriate response to the human-applied, artificial selection to improve the yield of a desired trait (e.g., livestock weight or fruit size). Progress was slow or nonexistent if there was too little selectable variation for the trait of interest, or when variation had been exhausted during early phases of selection. The contexts for halting unwanted evolution are different and are not ones in which an absence of variation is expected. For example, an engineered cell may produce a useful protein or chemical compound at the expense of its own growth. We wish to avoid the loss in yield that will occur as cells evolve to jettison this burdensome function over many generations in a bioreactor. Or we may be trying to suppress a population of pests, and individuals evolve that escape our lethal treatment. We want the population to retain its sensitivity so that we can continue to suppress it in the future. Genetic variation to return the organism to its previous (unengineered) state or for it to develop resistance will either already be present or will be easily accessed by mutation. An understanding of how natural selection works (Box 1) has led to various protocols for reducing unwanted evolution (Figure 1A). What we classify as traditional approaches are those that rely on manipulating population dynamics, breeding, or selection to thwart evolution. They require and are justified by an understanding of these principles, but one does not need to understand the genetic basis of the desirable property or its loss to use them. In fact, our own bodies have evolved to use several of these mechanisms to prevent cancer (Box 2).Box 1The Speed of Adaptive EvolutionThe process of adaptive evolution has been studied for over a century, and the key components are now well understood [61Crow J.F. Kimura M. An Introduction to Population Genetics Theory. Burgess, 1970Google Scholar, 62Hartl D.L. Clark A.G. Principles of Population Genetics.4th edn. Sinauer Associates, 2006Google Scholar]. Arresting evolution requires interfering with one or more of them. Among the most important are:MutationEvolutionary change requires genetic variation. If those variants can be prevented from arising, there will be no raw material for evolution. There is natural variation in mutation rates, and there has been some success with reducing mutation rates of microbes. Alternatively, subpopulations with genetic changes can sometimes be discarded.SelectionAdaptive evolution requires fitness differences among alternative genotypes/alleles. If selective differences can be eliminated, then evolution occurs only from mutation and neutral processes, which are slow. Reducing or altering selection is often a viable approach to controlling evolution. Owing to genetic drift and other stochastic processes, small populations are much less prone to respond to natural selection than are large populationsInheritanceIn this category, we include a wide range of influences, such as population size and structure, mating system, recombination, and epistasis. Although these have important consequences for the speed of evolution, they are not always easily manipulated. Population size and mating system (e.g., inbreeding vs. outbreeding) can sometimes be controlled.Box 2How Multicellular Organisms Limit Evolution withinOrganisms are endowed with mechanisms that have been interpreted as limiting the potential for deleterious evolution within somatic cells (i.e., cancer) and in the germ line. Several of these strategies are conceptually similar to the ones noted in Figure 1A.Cairns [63Cairns J. Mutation selection and the natural history of cancer.Nature. 1975; 255: 197-200Crossref PubMed Scopus (1248) Google Scholar] analyzed the cellular organization of the body from the perspective of preventing cancer. His proposed mechanisms include stem cells that undergo limited cell division (because this is a mutagenic process) and the physical loss of cells derived from stem cells from the body, so that any mutations making them cancer prone would be discarded with them. He also proposed that asymmetric inheritance of newly synthesized DNA strands to derivatives of stem cells would help maintain low mutational input to the resident stem cell population. Programmed cell death (apoptosis) is another mechanism that helps limit evolution of stem cell progeny.Multicellular organisms prevent undesirable somatic mutation from contaminating the germ line by going through a single-cell bottleneck at each generation (e.g., most cancers and other forms of selfish cells are excluded, [64Kondrashov A.S. Mutation load under vegetative reproduction and cytoplasmic inheritance.Genetics. 1994; 137: 311-318PubMed Google Scholar]). Likewise, the germ line of vertebrates typically undergoes few cell divisions. If a gamete is defective in being able to produce a viable organism, this is often detected early in development and it is discarded.In a similar vein, it has been suggested that some viruses have evolved to limit their own evolution when growing within the host [65Lythgoe K.A. et al.Short-sighted virus evolution and a germline hypothesis for chronic viral infections.Trends Microbiol. 2017; 25: 336-348Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar]. During long-lasting, chronic infections, within-host evolution can accumulate to the point that the changes thwart transmission to new hosts. By limiting within-host evolution, a larger fraction of viruses will retain the capacity for transmission. The process of adaptive evolution has been studied for over a century, and the key components are now well understood [61Crow J.F. Kimura M. An Introduction to Population Genetics Theory. Burgess, 1970Google Scholar, 62Hartl D.L. Clark A.G. Principles of Population Genetics.4th edn. Sinauer Associates, 2006Google Scholar]. Arresting evolution requires interfering with one or more of them. Among the most important are: Mutation Evolutionary change requires genetic variation. If those variants can be prevented from arising, there will be no raw material for evolution. There is natural variation in mutation rates, and there has been some success with reducing mutation rates of microbes. Alternatively, subpopulations with genetic changes can sometimes be discarded. Selection Adaptive evolution requires fitness differences among alternative genotypes/alleles. If selective differences can be eliminated, then evolution occurs only from mutation and neutral processes, which are slow. Reducing or altering selection is often a viable approach to controlling evolution. Owing to genetic drift and other stochastic processes, small populations are much less prone to respond to natural selection than are large populations Inheritance In this category, we include a wide range of influences, such as population size and structure, mating system, recombination, and epistasis. Although these have important consequences for the speed of evolution, they are not always easily manipulated. Population size and mating system (e.g., inbreeding vs. outbreeding) can sometimes be controlled. Organisms are endowed with mechanisms that have been interpreted as limiting the potential for deleterious evolution within somatic cells (i.e., cancer) and in the germ line. Several of these strategies are conceptually similar to the ones noted in Figure 1A. Cairns [63Cairns J. Mutation selection and the natural history of cancer.Nature. 1975; 255: 197-200Crossref PubMed Scopus (1248) Google Scholar] analyzed the cellular organization of the body from the perspective of preventing cancer. His proposed mechanisms include stem cells that undergo limited cell division (because this is a mutagenic process) and the physical loss of cells derived from stem cells from the body, so that any mutations making them cancer prone would be discarded with them. He also proposed that asymmetric inheritance of newly synthesized DNA strands to derivatives of stem cells would help maintain low mutational input to the resident stem cell population. Programmed cell death (apoptosis) is another mechanism that helps limit evolution of stem cell progeny. Multicellular organisms prevent undesirable somatic mutation from contaminating the germ line by going through a single-cell bottleneck at each generation (e.g., most cancers and other forms of selfish cells are excluded, [64Kondrashov A.S. Mutation load under vegetative reproduction and cytoplasmic inheritance.Genetics. 1994; 137: 311-318PubMed Google Scholar]). Likewise, the germ line of vertebrates typically undergoes few cell divisions. If a gamete is defective in being able to produce a viable organism, this is often detected early in development and it is discarded. In a similar vein, it has been suggested that some viruses have evolved to limit their own evolution when growing within the host [65Lythgoe K.A. et al.Short-sighted virus evolution and a germline hypothesis for chronic viral infections.Trends Microbiol. 2017; 25: 336-348Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar]. During long-lasting, chronic infections, within-host evolution can accumulate to the point that the changes thwart transmission to new hosts. By limiting within-host evolution, a larger fraction of viruses will retain the capacity for transmission. The simplest traditional approach is to discard the evolving population and start anew with the ancestral stock – all mutations are erased. But discarding the final population after it has performed its function is possible only in specific applications, typically in industrial cultures, where one controls the cells that go into a bioreactor, or in agriculture, when using seeds that are planted in a field and entirely harvested after a single generation for consumption (Figure 1B). A related strategy is to subdivide or bottleneck a population of cells and grow each subpopulation separately, discarding those that experience unwanted evolution and continuing from the ones that do not. Extreme bottlenecking is the goal when streaking out bacteria to colonies derived from single cells on agar to create stocks with as little genetic variation as possible. Scale-up of industrial cell-based processes involves developing 'seed trains' that limit the total number of cell divisions before full-scale production [5Kloth C. et al.Inoculum expansion methods, animal cell lines.in: Flickinger M.C. Upstream Industrial Biotechnology. 1st edn. John Wiley & Sons, 2013: 297-310Google Scholar]. These stocks can be individually tested for function, discarding any that are suboptimal, thus preventing mutants from contaminating the full-scale production culture. A recent update to this method, proposed especially for stem cells, is to sequence cell populations after the passages needed to expand their cell number to determine whether they are compromised through mutations in tumor-suppressor genes that can give a growth advantage in the laboratory [6Merkle F.T. et al.Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations.Nature. 2017; 545: 229-233Crossref PubMed Scopus (286) Google Scholar]. When the population cannot be fully replaced, adding back the ancestral genotype may achieve nearly the same effect. The original genotype may be able to outcompete and displace some of the evolved population under certain circumstances [7Paquin C.E. Adams J. Relative fitness can decrease in evolving asexual populations of S. cerevisiae.Nature. 1983; 306: 368-370Crossref PubMed Scopus (137) Google Scholar]. Either that or the ancestor may be able to hybridize with enough evolved individuals, in essence breeding back to the seed, such that a desirable trait or ancestral state replaces one that evolved in the population. Again, many contexts preclude this approach. Returning to a seed stock is a form of limiting the number of generations of growth in cultivation. The opportunity for evolution typically increases with time or number of generations, so limiting these will restrict many types of evolution (Figure 1C). This is one factor in designing seed trains to populate industrial bioreactors. Another interesting application of this principle concerns methods for DNA amplification: compared to isothermal (continuous) DNA amplification methods, PCR amplifies its template with higher fidelity by limiting the number of amplification opportunities for every DNA molecule to a fixed number of generations (cycles) [8Bull J.J. Pease C.M. Why is the polymerase chain reaction resistant to in vitro evolution?.J. Mol. Evol. 1995; 41: 1160-1164Crossref Scopus (12) Google Scholar]. At the other end of the traditional approach spectrum, selection is altered. Selection may be weakened to delay evolution or increased to kill intermediates along an evolutionary trajectory to prevent a lineage from reaching an unwanted extreme (Figure 1D). Both approaches are used or advocated in blocking drug-resistance evolution in bacteria. It has been suggested that weakened selection for resistance be achieved by only using antibiotics in appropriate medical situations and by limiting their use in agriculture [9Bell B.G. et al.A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance.BMC Infect. Dis. 2014; 14: 13Crossref PubMed Scopus (627) Google Scholar, 10Gyssens I.C. Antibiotic policy.Int. J. Antimicrob. 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Limiting selection to old individuals within a vector population (e.g., mosquitos) can theoretically reduce the magnitude of selection while effectively preventing disease transmission (e.g., of malaria, [3Read A.F. et al.How to make evolution-proof insecticides for malaria control.PLoS Biol. 2009; 7: e1000058Crossref PubMed Scopus (187) Google Scholar]). A version of changing selection that also incorporates the breed-back-to-seed approach is used to delay the ascent of insect resistance to Bt toxin in crops: 'refuges' of nontoxic crops are intermingled with the Bt crops to ensure that any resistant (necessarily homozygous) pests outbreed to produce heterozygous offspring – the latter being sensitive to the toxin [14Jin L. et al.Large-scale test of the natural refuge strategy for delaying insect resistance to transgenic Bt crops.Nat. Biotechnol. 2015; 33: 169-174Crossref PubMed Scopus (142) Google Scholar]. Manipulating ecology by introducing competitors may also delay evolution in at least two ways. First, if multiple species are competing in the same niche, a competitor can restrict the population size of the focal species, making it less likely to sample adaptive mutations. Second, a competitor can occupy a niche that might otherwise be invaded by descendants of the focal species and lead to undesired evolution (Figure 1E). In an experimental system, evolution of bacterial resistance to viruses depended on whether a competitor was also present for this reason [15Harcombe W.R. Bull J.J. Impact of phages on two-species bacterial communities.Appl. Environ. Microbiol. 2005; 71: 5254-5259Crossref PubMed Scopus (60) Google Scholar]. In the same vein, monocultures of bacteria are known to evolve substrains that specialize on the high concentrations of waste metabolites of the parent strain [16Herron M.D. Doebeli M. Parallel evolutionary dynamics of adaptive diversification in Escherichia coli.PLoS Biol. 2013; 11: e1001490Crossref PubMed Scopus (138) Google Scholar]. Presumably, addition of a competitor that already specialized on the waste (and could not utilize the main nutrient) would prevent this evolution. Competitive interactions like these may normally impede evolution in host-associated microbiomes. For example, there is evidence that Escherichia coli evolve more slowly in the guts of immunodeficient Rag2−/− mice than in wild-type mice, which has been interpreted as being due to Rag2−/− mice having a more diverse gut microbiota [17Barroso-Batista J. et al.Adaptive immunity increases the pace and predictability of evolutionary change in commensal gut bacteria.Nat. Commun. 2015; 68945Crossref PubMed Scopus (54) Google Scholar]. Probiotics can be added as competitors to a microbiome to occupy niches that might be left vacant after a disturbance, such as antibiotic treatment. These types of probiotics will directly protect against the establishment of pathogens [18Bäumler A.J. Sperandio V. Interactions between the microbiota and pathogenic bacteria in the gut.Nature. 2016; 535: 85-93Crossref PubMed Scopus (693) Google Scholar]. They may also preclude the evolution of surviving native species into opportunistic pathogens that exploit a newly unoccupied niche. It remains to be seen if this secondary effect of slowing evolution is important for any protective effects of probiotics. The ability to create genomes of arbitrary composition, when combined with the knowledge of how those genomes function and evolve, opens new avenues for blocking evolution. These approaches may be applied to constrain evolution of a genome that we construct, but it is also possible to release a small number of engineered individuals and have them suppress or reverse evolution in a larger nonengineered population. Evolution may not be totally prevented, but either the rate of fitness increase or the final fitness itself is suppressed. Many of these strategies require that the engineered genome be asexual, or at least that it not recombine with other genomes in ways that could simply replace the engineered genome sections with their corresponding wild-type sequences. There are limits to adaptive evolution, at least in the near term. The concept of a fitness limit may be little more than a fuzzy upper boundary to the fitness trajectory in a particular environment, or a scaling down of the trajectory of fitness increase over time [19Wiser M.J. et al.Long-term dynamics of adaptation in asexual populations.Science. 2013; 342: 1364-1367Crossref PubMed Scopus (296) Google Scholar]. It arises from the simple fact that organisms are not infinitely adaptable, even when the same selective pressure is applied gradually and for long periods of time. Genetic engineering allows one to edit genomes to lower this fitness limit, meaning that modified organisms cannot evolve to the same fitness level as would the wild type on a given timescale (Figure 2A). One application is the design of live attenuated vaccines (Box 3). Such vaccines use variants of a microbe with a lower growth rate or reduced pathogenicity [20Hanley K.A. The double-edged sword: how evolution can make or break a live-attenuated virus vaccine.Evolution (N. Y.). 2011; 4: 635-643PubMed Google Scholar, 21Lauring A.S. et al.Rationalizing the development of live attenuated virus vaccines.Nat. Biotechnol. 2010; 28: 573-579Crossref PubMed Scopus (185) Google Scholar]. They need to be designed to elicit protection while minimizing the chances that they evolve to be harmful after being administered to a patient. By engineering viruses with genome rearrangements or deletions of nonessential but useful regions, it has been possible to not only lower initial fitness [22Berkhout B. et al.Genetic instability of live, attenuated human immunodeficiency virus type 1 vaccine strains.J. Virol. 1999; 73: 1138-1145Crossref PubMed Google Scholar, 23Flanagan E.B. et al.Rearrangement of the genes of vesicular stomatitis virus eliminates clinical disease in the natural host: new strategy for vaccine development.J. Virol. 2001; 75: 6107-6114Crossref PubMed Scopus (82) Google Scholar] but also to limit the fitness they attain on sustained adaptation [22Berkhout B. et al.Genetic instability of live, attenuated human immunodeficiency virus type 1 vaccine strains.J. Virol. 1999; 73: 1138-1145Crossref PubMed Google Scholar, 24Cecchini N. et al.Evolutionarily stable attenuation by genome rearrangement in a virus.G3 (Bethesda). 2013; 3: 1389-1397Crossref PubMed Scopus (13) Google Scholar]. These genomes will typically evolve a fitness above their starting value, but they cannot catch up with wild type.Box 3Methods to Engineer Attenuated Viruses Stable against Evolutionary ReversionAttenuated viruses are live viruses with a reduced capacity to grow compared to their wild-type counterparts. Historically, methods to attenuate viruses were haphazard processes of adaptation to novel environments, on the hope that adaptation to the new conditions would compromise growth in the original host. Genome engineering now enables a variety of attenuation methods that provide greater control and repeatability. Achieving attenuation – growth rate reduction – is now routine, but a more challenging issue is whether the attenuated virus undergoes evolutionary reversion and can recover higher fitness when grown for long periods of time. Different methods of attenuation have different consequences for reversion.Codon (Pair) DeoptimizationThis method engineers viral protein coding sequences to have different codons while retaining the same amino acid sequence [27Burns C.C. et al.Modulation of poliovirus replicative fitness in HeLa cells by deoptimization of synonymous codon usage in the capsid region.J. Virol. 2006; 80: 3259-3272Crossref PubMed Scopus (192) Google Scholar, 28Coleman J.R. et al.Virus attenuation by genome-scale changes in codon pair bias.Science. 2008; 320: 1784-1787Crossref PubMed Scopus (470) Google Scholar]. Viral growth rate can be adjusted by recoding longer or shorter sequences, but typically hundreds of codons are changed. On the assumption that each codon change has a small fitness effect, full evolutionary reversion should require reversing all the changes and thus be very slow and possibly incomplete. In practice, reversion is faster than predicted and occurs with relatively few changes, but reversions are still acceptably slow [66Bull J.J. Evolutionary reversion of live viral vaccines: can genetic engineering subdue it?.Virus Evol. 2015; 1: vev005Crossref PubMed Scopus (36) Google Scholar].Genome RearrangementsReordering a viral genome has regulatory effects that lower fitness in the few viruses in which this method has been attempted. On extended adaptation, the engineered genomes do not re-establish the wild-type gene order. Partial evolutionary reversion is possible, but it falls short of returning to wild-type levels [24Cecchini N. et al.Evolutionarily stable attenuation by genome rearrangement in a virus.G3 (Bethesda). 2013; 3: 1389-1397Crossref PubMed Scopus (13) Google Scholar, 67Wertz G.W. et al.Gene rearrangement attenuates expression and lethality of a nonsegmented negative strand RNA virus.Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 3501-3506Crossref PubMed Scopus (156) Google Scholar].DeletionsDeleting nonessential genes or parts of genes is easily used to cause fitness reductions. However, this method has not proven especially recalcitrant to evolutionary recovery [66Bull J.J. Evolutionary reversion of live viral vaccines: can genetic engineering subdue it?.Virus Evol. 2015; 1: vev005Crossref PubMed Scopus (36) Google Scholar]. Genomes are prone to evolve in response to the deletion, offsetting its effect by adjusting gene expression or even by replacing deleted sequences. Attenuated viruses are live viruses with a reduced capacity to grow compared to their wild-type counterparts. Historically, methods to attenuate viruses were haphazard processes of adaptation to novel environments, on the hope that adaptation to the new conditions would compromise growth in the original host. Genome engineering now enables a variety of attenuation methods that provide greater control and repeatability. Achieving attenuation – growth rate reduction – is now routine, but a more challenging issue is whether the attenuated virus undergoes evolutionary reversion and can recover higher fitness when grown for long periods of time. Different methods of att