The speed of evolution and maintenance of variation in asexual populations

Dynamics of Critical Cascades in Interdependent Networks

The failure of interdependent networks, as well as similar avalanche phenomena, is driven by cascading failures. At the critical point, the cascade begins as a critical branching process, where each failing node (element) triggers, on average, the failure of one other node. As nodes continue to fail, the network becomes increasingly fragile, and the branching factor grows. If the failure process does not reach extinction during its critical phase, the network undergoes an abrupt collapse. Here, we implement the analogy between this dynamic and birth-death processes to derive new analytical results and significantly optimize numerical calculations. Using this approach, we analyze three key aspects of the dynamics: the probability of collapse, the duration of avalanches, and the length of the cascading plateau phase preceding a collapse. This analysis quantifies how the system size and the intensity of the initial triggering event influence these characteristics.

'Domesticability': were some species predisposed for domestication?

Crop domestication arises from a coevolutionary process between plants and humans, resulting in predictable and improved resources for humans. Of the thousands of edible species, many were collected or cultivated for food, but only a few became domesticated and even fewer supply the bulk of the plant-based calories consumed by humans. Why so few species became fully domesticated is not understood. Here we propose three aspects of plant genomes and phenotypes that could have promoted the domestication of only a few wild species, namely differences in plasticity, trait linkage, and mutation rates. We can use contemporary biological knowledge to identify factors underlying why only some species are amenable to domestication. Such studies will facilitate future domestication and improvement efforts.

Compensatory Evolution to DNA Replication Stress is Robust to Nutrient Availability

Evolutionary repair refers to the compensatory evolution that follows perturbations in cellular processes. While evolutionary trajectories are often reproducible, other studies suggest they are shaped by genotype-by-environment (GxE) interactions. Here, we test the predictability of evolutionary repair in response to DNA replication stress-a severe perturbation impairing the conserved mechanisms of DNA synthesis, resulting in genetic instability. We conducted high-throughput experimental evolution on Saccharomyces cerevisiae experiencing constitutive replication stress, grown under different glucose availabilities. We found that glucose levels impact the physiology and adaptation rate of replication stress mutants. However, the genetics of adaptation show remarkable robustness across environments. Recurrent mutations collectively recapitulated the fitness of evolved lines and are advantageous across macronutrient availability. We also identified a novel role of the mediator complex of RNA polymerase II in adaptation to replicative stress. Our results highlight the robustness and predictability of evolutionary repair mechanisms to DNA replication stress and provide new insights into the evolutionary aspects of genome stability, with potential implications for understanding cancer development.

Direct and indirect selection in a proofreading polymerase

The traits that affect evolvability are subject to indirect selection, as these traits affect the course of evolution over many generations rather than the direct replicative fitness of an individual. However, the evolution of evolvability-determining traits is often difficult to study because putative evolvability alleles often have confounding direct fitness effects of unknown origin and size. Here, we study theoretically and experimentally the evolution of mutation rates in proofreading polymerases with orthogonal control of direct and indirect selection. Mutagenic DNA polymerases enjoy a long-time fitness advantage by enhancing the rate of acquiring beneficial mutations. However, this is offset by a short-time fitness penalty, which we trace to a counterintuitive trade-off between mutation rates and activity in proofreading polymerases. Since these fitness effects act on different timescales, no one number characterizes the fitness of a mutator allele. We find unusual dynamic features in the resulting evolutionary dynamics, such as kinetic exclusion, selection by dynamic environments, and Rock-Paper-Scissors dynamics in the absence of ecology. Our work has implications for the evolution of mutation rates and more broadly, evolution in the context of an anti-correlation between mutation rates and short term fitness.

Accumulating waves of random mutations before fixation

Mutations provide variation for evolution to emerge. A quantitative analysis of how mutations arising in single individuals expand and possibly fixate in a population is essential for studying evolutionary processes. While it is intuitive to expect that a continuous influx of mutations will lead to a continuous flow of mutations fixating in a stable constant population, joint fixation of multiple mutations occur frequently in stochastic simulations even under neutral selection. We quantitatively measure and analyze the distribution of joint fixation events of neutral mutations in constant populations and discussed the connection with previous results. We propose a new concept, the mutation "waves," where multiple mutations reach given frequencies simultaneously. We show that all but the lowest frequencies of the variant allele frequency distribution are dominated by single mutation "waves," which approximately follow an exponential distribution in terms of size. Consequently, large swaths of empty frequencies are observed in the variant allele frequency distributions, with a few frequencies having numbers of mutations far in excess of the expected average values over multiple realizations. We quantify the amount of time each frequency is empty of mutations and further show that the discrete mutation waves average out to a continuous distribution named as the wave frequency distribution, the shape of which is predictable based on few model parameters.

Widespread fungal-bacterial competition for magnesium lowers bacterial susceptibility to polymyxin antibiotics

Fungi and bacteria coexist in many polymicrobial communities, yet the molecular basis of their interactions remains poorly understood. Here, we show that the fungus Candida albicans sequesters essential magnesium ions from the bacterium Pseudomonas aeruginosa. To counteract fungal Mg2+ sequestration, P. aeruginosa expresses the Mg2+ transporter MgtA when Mg2+ levels are low. Thus, loss of MgtA specifically impairs P. aeruginosa in co-culture with C. albicans, but fitness can be restored by supplementing Mg2+. Using a panel of fungi and bacteria, we show that Mg2+ sequestration is a general mechanism of fungal antagonism against gram-negative bacteria. Mg2+ limitation enhances bacterial resistance to polymyxin antibiotics like colistin, which target gram-negative bacterial membranes. Indeed, experimental evolution reveals that P. aeruginosa evolves C. albicans-dependent colistin resistance via non-canonical means; antifungal treatment renders resistant bacteria colistin-sensitive. Our work suggests that fungal-bacterial competition could profoundly impact polymicrobial infection treatment with antibiotics of last resort.

Operator model for evolutionary dynamics

Drift, selection, and mutation are integral evolutionary factors. In this article, operator model is newly suggested to intuitively represent those evolutionary factors into mathematical operators, and to ultimately offer unconventional methodology for understanding evolutionary dynamics. To be specific, each of the drift, selection, and mutation was respectively interpreted as operator which in essence is a random matrix that acts upon the vector which contains population distribution information. The simulation results from the operator model coincided with the previous theoretical results for beneficial mutation accumulation rate in concurrent and successional regimes for asexually reproducing case. Furthermore, beneficial mutation accumulation in strong drift regime for asexually reproducing case was observed from the simulation while allowing the interactions of mutations with diverse selection coefficients. Lastly, methods to justify, reinforce, apply, and expand the operator model were discussed to scrutinize the implications of the model. With the operator model's unique characteristics, the model is expected to broaden perspective and to offer effective methodology for understanding the evolutionary process.

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population's mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn.

Changing fitness effects of mutations through long-term bacterial evolution

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.

A dynamical limit to evolutionary adaptation

Natural selection makes evolutionary adaptation possible even if the overwhelming majority of new mutations are deleterious. However, in rapidly evolving populations where numerous linked mutations occur and segregate simultaneously, clonal interference and genetic hitchhiking can limit the efficiency of selection, allowing deleterious mutations to accumulate over time. This can in principle overwhelm the fitness increases provided by beneficial mutations, leading to an overall fitness decline. Here, we analyze the conditions under which evolution will tend to drive populations to higher versus lower fitness. Our analysis focuses on quantifying the boundary between these two regimes, as a function of parameters such as population size, mutation rates, and selection pressures. This boundary represents a state in which adaptation is precisely balanced by Muller's ratchet, and we show that it can be characterized by rapid molecular evolution without any net fitness change. Finally, we consider the implications of global fitness-mediated epistasis and find that under some circumstances, this can drive populations toward the boundary state, which can thus represent a long-term evolutionary attractor.

Signification and Application of Mutator and Antimutator Phenotype-Induced Genetic Variations in Evolutionary Adaptation and Cancer Therapeutics

Mutations present a dichotomy in their implications for cellular processes. They primarily arise from DNA replication errors or damage repair processes induced by environmental challenges. Cumulative mutations underlie genetic variations and drive evolution, yet also contribute to degenerative diseases such as cancer and aging. The mutator phenotype elucidates the heightened mutation rates observed in malignant tumors. Evolutionary adaptation, analogous to bacterial and eukaryotic systems, manifests through mutator phenotypes during changing environmental conditions, highlighting the delicate balance between advantageous mutations and their potentially detrimental consequences. Leveraging the genetic tractability of Saccharomyces cerevisiae offers unique insights into mutator phenotypes and genome instability akin to human cancers. Innovative reporter assays in yeast model organisms enable the detection of diverse genome alterations, aiding a comprehensive analysis of mutator phenotypes. Despite significant advancements, our understanding of the intricate mechanisms governing spontaneous mutation rates and preserving genetic integrity remains incomplete. This review outlines various cellular pathways affecting mutation rates and explores the role of mutator genes and mutation-derived phenotypes, particularly prevalent in malignant tumor cells. An in-depth comprehension of mutator and antimutator activities in yeast and higher eukaryotes holds promise for effective cancer control strategies.

Metacommunity structure preserves genome diversity in the presence of gene-specific selective sweeps under moderate rates of horizontal gene transfer

The horizontal transfer of genes is fundamental for the eco-evolutionary dynamics of microbial communities, such as oceanic plankton, soil, and the human microbiome. In the case of an acquired beneficial gene, classic population genetics would predict a genome-wide selective sweep, whereby the genome spreads clonally within the community and together with the beneficial gene, removing genome diversity. Instead, several sources of metagenomic data show the existence of "gene-specific sweeps", whereby a beneficial gene spreads across a bacterial community, maintaining genome diversity. Several hypotheses have been proposed to explain this process, including the decreasing gene flow between ecologically distant populations, frequency-dependent selection from linked deleterious allelles, and very high rates of horizontal gene transfer. Here, we propose an additional possible scenario grounded in eco-evolutionary principles. Specifically, we show by a mathematical model and simulations that a metacommunity where species can occupy multiple patches, acting together with a realistic (moderate) HGT rate, helps maintain genome diversity. Assuming a scenario of patches dominated by single species, our model predicts that diversity only decreases moderately upon the arrival of a new beneficial gene, and that losses in diversity can be quickly restored. We explore the generic behaviour of diversity as a function of three key parameters, frequency of insertion of new beneficial genes, migration rates and horizontal transfer rates.Our results provides a testable explanation for how diversity can be maintained by gene-specific sweeps even in the absence of high horizontal gene transfer rates.

A Law of Redundancy Compounds the Problem of Cancer and Precision Medicine

Genetics and molecular biology research have progressed for over a century; however, no laws of biology resembling those of physics have been identified, despite the expectations of some physicists. It may be that it is not the properties of matter alone but evolved properties of matter in combination with atomic physics and chemistry that gave rise to the origin and complexity of life. It is proposed that any law of biology must also be a product of evolution that co-evolved with the origin and progression of life. It was suggested that molecular complexity and redundancy exponentially increase over time and have the following relationship: DNA sequence complexity (Cd) < molecular complexity (Cm) < phenotypic complexity (Cp). This study presents a law of redundancy, which together with the law of complexity, is proposed as an evolutionary law of biology. Molecular complexity and redundancy are inseparable aspects of biochemical pathways, and molecular redundancy provides the first line of defense against environmental challenges, including those of deleterious mutations. Redundancy can create problems for precision medicine because in addition to the issues arising from the involvement of multiple genes, redundancy arising from alternate pathways between genotypes and phenotypes can complicate gene detection for complex diseases and mental disorders. This study uses cancer as an example to show how cellular complexity, molecular redundancy, and hidden variation affect the ability of cancer cells to evolve and evade detection and elimination. Characterization of alternate biochemical pathways or "escape routes" can provide a step in the fight against cancer.

Evolutionary dynamics in non-Markovian models of microbial populations

In the past decade, great strides have been made to quantify the dynamics of single-cell growth and division in microbes. In order to make sense of the evolutionary history of these organisms, we must understand how features of single-cell growth and division influence evolutionary dynamics. This requires us to connect processes on the single-cell scale to population dynamics. Here, we consider a model of microbial growth in finite populations which explicitly incorporates the single-cell dynamics. We study the behavior of a mutant population in such a model and ask: can the evolutionary dynamics be coarse-grained so that the forces of natural selection and genetic drift can be expressed in terms of the long-term fitness? We show that it is in fact not possible, as there is no way to define a single fitness parameter (or reproductive rate) that defines the fate of an organism even in a constant environment. This is due to fluctuations in the population averaged division rate. As a result, various details of the single-cell dynamics affect the fate of a new mutant independently from how they affect the long-term growth rate of the mutant population. In particular, we show that in the case of neutral mutations, variability in generation times increases the rate of genetic drift, and in the case of beneficial mutations, variability decreases its fixation probability. Furthermore, we explain the source of the persistent division rate fluctuations and provide analytic solutions for the fixation probability as a multispecies generalization of the Euler-Lotka equation.

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

A dynamical limit to evolutionary adaptation

Natural selection makes evolutionary adaptation possible even if the overwhelming majority of new mutations are deleterious. However, in rapidly evolving populations where numerous linked mutations occur and segregate simultaneously, clonal interference and genetic hitchhiking can limit the efficiency of selection, allowing deleterious mutations to accumulate over time. This can in principle overwhelm the fitness increases provided by beneficial mutations, leading to an overall fitness decline. Here, we analyze the conditions under which evolution will tend to drive populations to higher versus lower fitness. Our analysis focuses on quantifying the boundary between these two regimes, as a function of parameters such as population size, mutation rates, and selection pressures. This boundary represents a state in which adaptation is precisely balanced by Muller's ratchet, and we show that it can be characterized by rapid molecular evolution without any net fitness change. Finally, we consider the implications of global fitness-mediated epistasis, and find that under some circumstances this can drive populations towards the boundary state, which can thus represent a long-term evolutionary attractor.

Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein

Can evolvability-the ability to produce adaptive heritable variation-itself evolve through adaptive Darwinian evolution? If so, then Darwinian evolution may help create the conditions that enable Darwinian evolution. Here I propose a framework that is suitable to address this question with available experimental data on adaptive landscapes. I introduce the notion of an evolvability-enhancing mutation, which increases the likelihood that subsequent mutations in an evolving organism, protein, or RNA molecule are adaptive. I search for such mutations in the experimentally characterized and combinatorially complete fitness landscapes of a protein and an RNA molecule. I find that such evolvability-enhancing mutations indeed exist. They constitute a small fraction of all mutations, which shift the distribution of fitness effects of subsequent mutations towards less deleterious mutations, and increase the incidence of beneficial mutations. Evolving populations which experience such mutations can evolve significantly higher fitness. The study of evolvability-enhancing mutations opens many avenues of investigation into the evolution of evolvability.

A fitness trade-off explains the early fate of yeast aneuploids with chromosome gains

The early development of aneuploidy from an accidental chromosome missegregation shows contrasting effects. On the one hand, it is associated with significant cellular stress and decreased fitness. On the other hand, it often carries a beneficial effect and provides a quick (but typically transient) solution to external stress. These apparently controversial trends emerge in several experimental contexts, particularly in the presence of duplicated chromosomes. However, we lack a mathematical evolutionary modeling framework that comprehensively captures these trends from the mutational dynamics and the trade-offs involved in the early stages of aneuploidy. Here, focusing on chromosome gains, we address this point by introducing a fitness model where a fitness cost of chromosome duplications is contrasted by a fitness advantage from the dosage of specific genes. The model successfully captures the experimentally measured probability of emergence of extra chromosomes in a laboratory evolution setup. Additionally, using phenotypic data collected in rich media, we explored the fitness landscape, finding evidence supporting the existence of a per-gene cost of extra chromosomes. Finally, we show that the substitution dynamics of our model, evaluated in the empirical fitness landscape, explains the relative abundance of duplicated chromosomes observed in yeast population genomics data. These findings lay a firm framework for the understanding of the establishment of newly duplicated chromosomes, providing testable quantitative predictions for future observations.

Statistical genetics in and out of quasi-linkage equilibrium

This review is about statistical genetics, an interdisciplinary topic between statistical physics and population biology. The focus is on the phase ofquasi-linkage equilibrium(QLE). Our goals here are to clarify under which conditions the QLE phase can be expected to hold in population biology and how the stability of the QLE phase is lost. The QLE state, which has many similarities to a thermal equilibrium state in statistical mechanics, was discovered by M Kimura for a two-locus two-allele model, and was extended and generalized to the global genome scale byNeher&Shraiman (2011). What we will refer to as the Kimura-Neher-Shraiman theory describes a population evolving due to the mutations, recombination, natural selection and possibly genetic drift. A QLE phase exists at sufficiently high recombination rate (r) and/or mutation ratesµwith respect to selection strength. We show how in QLE it is possible to infer the epistatic parameters of the fitness function from the knowledge of the (dynamical) distribution of genotypes in a population. We further consider the breakdown of the QLE regime for high enough selection strength. We review recent results for the selection-mutation and selection-recombination dynamics. Finally, we identify and characterize a new phase which we call the non-random coexistence where variability persists in the population without either fixating or disappearing.

Quantifying the local adaptive landscape of a nascent bacterial community

The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes ("L" and "S") shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

Two modes of evolution shape bacterial strain diversity in the mammalian gut for thousands of generations

How and at what pace bacteria evolve when colonizing healthy hosts remains unclear. Here, by monitoring evolution for more than six thousand generations in the mouse gut, we show that the successful colonization of an invader Escherichia coli depends on the diversity of the existing microbiota and the presence of a closely related strain. Following colonization, two modes of evolution were observed: one in which diversifying selection leads to long-term coexistence of ecotypes and a second in which directional selection propels selective sweeps. These modes can be quantitatively distinguished by the statistics of mutation trajectories. In our experiments, diversifying selection was marked by the emergence of metabolic mutations, and directional selection by acquisition of prophages, which bring their own benefits and costs. In both modes, we observed parallel evolution, with mutation accumulation rates comparable to those typically observed in vitro on similar time scales. Our results show how rapid ecotype formation and phage domestication can be in the mammalian gut.

Here, the authors show that a colonizing bacterial strain evolves in the gut by either generating ecotypes or continuously fixing beneficial mutations. They associate the first mode to metabolic mutations and the second to domestication of bacteriophages that are incorporated into the bacterial genome.

Ecological effects of stress drive bacterial evolvability under sub-inhibitory antibiotic treatments

Stress is thought to increase mutation rate and thus to accelerate evolution. In the context of antibiotic resistance, sub-inhibitory treatments could then lead to enhanced evolvability, thereby fuelling the adaptation of pathogens. Combining wet-lab experiments, stochastic simulations and a meta-analysis of the literature, we found that the increase in mutation rates triggered by antibiotic treatments is often cancelled out by reduced population size, resulting in no overall increase in genetic diversity. A careful analysis of the effect of ecological factors on genetic diversity showed that the potential for regrowth during recovery phase after treatment plays a crucial role in evolvability, being the main factor associated with increased genetic diversity in experimental data.

Overdominant and partially dominant mutations drive clonal adaptation in diploid Saccharomyces cerevisiae

Identification of adaptive targets in experimental evolution typically relies on extensive replication and genetic reconstruction. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of evolved mutations. Here, we apply this method to six Saccharomyces cerevisiae clones isolated from four diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains 17-26 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of the evolved clones to a barcoded haploid version of the ancestor. We competed the resulting barcoded diploids en masse and quantified fitness in the experimental and alternative environments by barcode sequencing. We estimated average fitness effects of evolved mutations using barcode-based fitness assays and whole genome sequencing for a subset of segregants. In contrast to our previous work with haploid evolved clones, we find that diploids carry fewer beneficial mutations, with modest fitness effects (up to 5.4%) in the environment in which they arose. In agreement with theoretical expectations, reconstruction experiments show that all mutations with a detectable fitness effect manifest some degree of dominance over the ancestral allele, and most are overdominant. Genotypes with lower fitness effects in alternative environments allowed us to identify conditions that drive adaptation in our system.

Competition with abundance-dependent fitness and the dynamics of heterogeneous populations in fluctuating environment

Species competition takes place in a fluctuating environment, so the selective forces on different populations vary through time. In many realistic situations the mean fitness and the amplitude of its temporal variations are abundance-dependent. Here we present a theory of two-species competition with abundance-dependent stochastic fitness variations and solve for the chance of ultimate fixation, the time to absorption and the time to fixation. We then examine the ability of this two-species system to serve as an effective model for high-diversity assemblages and to account for the presence of an intra-specific differential response to environmental variations. The effective model is shown to capture the main features of competition between composite populations.

Evolutionary Dynamics of Asexual Hypermutators Adapting to a Novel Environment

How microbes adapt to a novel environment is a central question in evolutionary biology. Although adaptive evolution must be fueled by beneficial mutations, whether higher mutation rates facilitate the rate of adaptive evolution remains unclear. To address this question, we cultured Escherichia coli hypermutating populations, in which a defective methyl-directed mismatch repair pathway causes a 140-fold increase in single-nucleotide mutation rates. In parallel with wild-type E. coli, populations were cultured in tubes containing Luria-Bertani broth, a complex medium known to promote the evolution of subpopulation structure. After 900 days of evolution, in three transfer schemes with different population-size bottlenecks, hypermutators always exhibited similar levels of improved fitness as controls. Fluctuation tests revealed that the mutation rates of hypermutator lines converged evolutionarily on those of wild-type populations, which may have contributed to the absence of fitness differences. Further genome-sequence analysis revealed that, although hypermutator populations have higher rates of genomic evolution, this largely reflects strong genetic linkage. Despite these linkage effects, the evolved population exhibits parallelism in fixed mutations, including those potentially related to biofilm formation, transcription regulation, and mutation-rate evolution. Together, these results are generally inconsistent with a hypothesized positive relationship between the mutation rate and the adaptive speed of evolution, and provide insight into how clonal adaptation occurs in novel environments.

Molecular signatures of resource competition: Clonal interference favors ecological diversification and can lead to incipient speciation

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages - clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes

Currently, the population dynamics of preclonal cancer cells before clonal expansion of tumors has not been sufficiently addressed thus far. By focusing on preclonal cancer cell population as a Darwinian evolutionary system, we formulated and analyzed the observed mutation frequency among tumors (MFaT) as a proxy for the hypothesized sequence read frequency and beneficial fitness effect of a cancer driver mutation. Analogous to intestinal crypts, we assumed that sample donor patients are separate culture tanks where proliferating cells follow certain population dynamics described by extreme value theory (EVT). To validate this, we analyzed three large-scale cancer genome datasets, each harboring > 10000 tumor samples and in total involving > 177898 observed mutation sites. We clarified the necessary premises for the application of EVT in the strong selection and weak mutation (SSWM) regime in relation to cancer genome sequences at scale. We also confirmed that the stochastic distribution of MFaT is likely of the Fréchet type, which challenges the well-known Gumbel hypothesis of beneficial fitness effects. Based on statistical data analysis, we demonstrated the potential of EVT as a population genetics framework to understand and explain the stochastic behavior of driver-mutation frequency in cancer genomes as well as its applicability in real cancer genome sequence data.

Can gene-inactivating mutations lead to evolutionary novelty?

Evolutionary novelty is difficult to define. It typically involves shifts in organismal or biochemical phenotypes that can be seen as qualitative as well as quantitative changes. In laboratory-based experimental evolution of novel phenotypes and the human domestication of crops, the majority of the mutations that lead to adaptation are loss-of-function mutations that impair or eliminate the function of genes rather than gain-of-function mutations that increase or qualitatively alter the function of proteins. Here, I speculate that easier access to loss-of-function mutations has led them to play a major role in the adaptive radiations that occur when populations have access to many unoccupied ecological niches. I discuss five possible objections to this claim: that genes can only survive if they confer benefits to the organisms that bear them, antagonistic pleiotropy, the importance of pre-existing genetic variation in populations, the danger that adaptation by breaking genes will, over long times, cause organisms to run out of genes, and the recessive nature of most loss-of-function mutations.

Fast and strong amplifiers of natural selection

Selection and random drift determine the probability that novel mutations fixate in a population. Population structure is known to affect the dynamics of the evolutionary process. Amplifiers of selection are population structures that increase the fixation probability of beneficial mutants compared to well-mixed populations. Over the past 15 years, extensive research has produced remarkable structures called strong amplifiers which guarantee that every beneficial mutation fixates with high probability. But strong amplification has come at the cost of considerably delaying the fixation event, which can slow down the overall rate of evolution. However, the precise relationship between fixation probability and time has remained elusive. Here we characterize the slowdown effect of strong amplification. First, we prove that all strong amplifiers must delay the fixation event at least to some extent. Second, we construct strong amplifiers that delay the fixation event only marginally as compared to the well-mixed populations. Our results thus establish a tight relationship between fixation probability and time: Strong amplification always comes at a cost of a slowdown, but more than a marginal slowdown is not needed.

Intra-Population Competition during Adaptation to Increased Temperature in an RNA Bacteriophage

Evolution of RNA bacteriophages of the family Leviviridae is governed by the high error rates of their RNA-dependent RNA polymerases. This fact, together with their large population sizes, leads to the generation of highly heterogeneous populations that adapt rapidly to most changes in the environment. Throughout adaptation, the different mutants that make up a viral population compete with each other in a non-trivial process in which their selective values change over time due to the generation of new mutations. In this work we have characterised the intra-population dynamics of a well-studied levivirus, Qβ, when it is propagated at a higher-than-optimal temperature. Our results show that adapting populations experienced rapid changes that involved the ascent of particular genotypes and the loss of some beneficial mutations of early generation. Artificially reconstructed populations, containing a fraction of the diversity present in actual populations, fixed mutations more rapidly, illustrating how population bottlenecks may guide the adaptive pathways. The conclusion is that, when the availability of beneficial mutations under a particular selective condition is elevated, the final outcome of adaptation depends more on the occasional occurrence of population bottlenecks and how mutations combine in genomes than on the selective value of particular mutations.

Mitotic recombination between homologous chromosomes drives genomic diversity in diatoms

Diatoms, an evolutionarily successful group of microalgae, display high levels of intraspecific genetic variability in natural populations. However, the contribution of various mechanisms generating such diversity is unknown. Here we estimated the genetic micro-diversity within a natural diatom population and mapped the genomic changes arising within clonally propagated diatom cell cultures. Through quantification of haplotype diversity by next-generation sequencing and amplicon re-sequencing of selected loci, we documented a rapid accumulation of multiple haplotypes accompanied by the appearance of novel protein variants in cell cultures initiated from a single founder cell. Comparison of the genomic changes between mother and daughter cells revealed copy number variation and copy-neutral loss of heterozygosity leading to the fixation of alleles within individual daughter cells. The loss of heterozygosity can be accomplished by recombination between homologous chromosomes. To test this hypothesis, we established an endogenous readout system and estimated that the frequency of interhomolog mitotic recombination was under standard growth conditions 4.2 events per 100 cell divisions. This frequency is increased under environmental stress conditions, including treatment with hydrogen peroxide and cadmium. These data demonstrate that copy number variation and mitotic recombination between homologous chromosomes underlie clonal variability in diatom populations. We discuss the potential adaptive evolutionary benefits of the plastic response in the interhomolog mitotic recombination rate, and we propose that this may have contributed to the ecological success of diatoms.

Concerns about SARS-CoV-2 evolution should not hold back efforts to expand vaccination

When vaccines are in limited supply, expanding the number of people who receive some vaccine, such as by halving doses or increasing the interval between doses, can reduce disease and mortality compared with concentrating available vaccine doses in a subset of the population. A corollary of such dose-sparing strategies is that the vaccinated individuals may have less protective immunity. Concerns have been raised that expanding the fraction of the population with partial immunity to SARS-CoV-2 could increase selection for vaccine-escape variants, ultimately undermining vaccine effectiveness. We argue that, although this is possible, preliminary evidence instead suggests such strategies should slow the rate of viral escape from vaccine or naturally induced immunity. As long as vaccination provides some protection against escape variants, the corresponding reduction in prevalence and incidence should reduce the rate at which new variants are generated and the speed of adaptation. Because there is little evidence of efficient immune selection of SARS-CoV-2 during typical infections, these population-level effects are likely to dominate vaccine-induced evolution.

Lateral Gene Transfer Acts As an Evolutionary Shortcut to Efficient C4 Biochemistry

The adaptation of proteins for novel functions often requires changes in their kinetics via amino acid replacement. This process can require multiple mutations, and therefore extended periods of selection. The transfer of genes among distinct species might speed up the process, by providing proteins already adapted for the novel function. However, this hypothesis remains untested in multicellular eukaryotes. The grass Alloteropsis is an ideal system to test this hypothesis due to its diversity of genes encoding phosphoenolpyruvate carboxylase, an enzyme that catalyzes one of the key reactions in the C₄ pathway. Different accessions of Alloteropsis either use native isoforms relatively recently co-opted from other functions or isoforms that were laterally acquired from distantly related species that evolved the C₄ trait much earlier. By comparing the enzyme kinetics, we show that native isoforms with few amino acid replacements have substrate K_M values similar to the non-C₄ ancestral form, but exhibit marked increases in catalytic efficiency. The co-option of native isoforms was therefore followed by rapid catalytic improvements, which appear to rely on standing genetic variation observed within one species. Native C₄ isoforms with more amino acid replacements exhibit additional changes in affinities, suggesting that the initial catalytic improvements are followed by gradual modifications. Finally, laterally acquired genes show both strong increases in catalytic efficiency and important changes in substrate handling. We conclude that the transfer of genes among distant species sharing the same physiological novelty creates an evolutionary shortcut toward more efficient enzymes, effectively accelerating evolution.

An interplay of resource availability, population size and mutation rate potentiates the evolution of metabolic signaling

Background

Asexually reproducing populations of single cells evolve through mutation, natural selection, and genetic drift. Environmental conditions in which the evolution takes place define the emergent fitness landscapes. In this work, we used Avida—a digital evolution framework—to uncover a hitherto unexplored interaction between mutation rates, population size, and the relative abundance of metabolizable resources, and its effect on evolutionary outcomes in small populations of digital organisms.

Results

Over each simulation, the population evolved to one of several states, each associated with a single dominant phenotype with its associated fitness and genotype. For a low mutation rate, acquisition of fitness by organisms was accompanied with, and dependent on, an increase in rate of genomic replication. At an increased mutation rate, phenotypes with high fitness values were similarly achieved through enhanced genome replication rates. In addition, we also observed the frequent emergence of suboptimal fitness phenotype, wherein neighboring organisms signaled to each other information relevant to performing metabolic tasks. This metabolic signaling was vital to fitness acquisition and was correlated with greater genotypic and phenotypic heterogeneity in the population. The frequency of appearance of signaling populations increased with population size and with resource abundance.

Conclusions

Our results reveal a minimal set of environment–genotype interactions that lead to the emergence of metabolic signaling within evolving populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01782-0.

Mutability of demographic noise in microbial range expansions

Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.

Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance

During antibiotic treatment, the evolution of bacterial pathogens is fundamentally affected by bottlenecks and varying selection levels imposed by the drugs. Bottlenecks-that is, reductions in bacterial population size-lead to an increased influence of random effects (genetic drift) during bacterial evolution, and varying antibiotic concentrations during treatment may favour distinct resistance variants. Both aspects influence the process of bacterial evolution during antibiotic therapy and thereby treatment outcome. Surprisingly, the joint influence of these interconnected factors on the evolution of antibiotic resistance remains largely unexplored. Here we combine evolution experiments with genomic and genetic analyses to demonstrate that bottleneck size and antibiotic-induced selection reproducibly impact the evolutionary path to resistance in pathogenic Pseudomonas aeruginosa, one of the most problematic opportunistic human pathogens. Resistance is favoured-expectedly-under high antibiotic selection and weak bottlenecks, but-unexpectedly-also under low antibiotic selection and severe bottlenecks. The latter is likely to result from a reduced probability of losing favourable variants through drift under weak selection. Moreover, the absence of high resistance under low selection and weak bottlenecks is caused by the spread of low-resistance variants with high competitive fitness under these conditions. We conclude that bottlenecks, in combination with drug-induced selection, are currently neglected key determinants of pathogen evolution and outcome of antibiotic treatment.

Evolution in alternating environments with tunable interlandscape correlations

Natural populations are often exposed to temporally varying environments. Evolutionary dynamics in varying environments have been extensively studied, although understanding the effects of varying selection pressures remains challenging. Here, we investigate how cycling between a pair of statistically related fitness landscapes affects the evolved fitness of an asexually reproducing population. We construct pairs of fitness landscapes that share global fitness features but are correlated with one another in a tunable way, resulting in landscape pairs with specific correlations. We find that switching between these landscape pairs, depending on the ruggedness of the landscape and the interlandscape correlation, can either increase or decrease steady-state fitness relative to evolution in single environments. In addition, we show that switching between rugged landscapes often selects for increased fitness in both landscapes, even in situations where the landscapes themselves are anticorrelated. We demonstrate that positively correlated landscapes often possess a shared maximum in both landscapes that allows the population to step through sub-optimal local fitness maxima that often trap single landscape evolution trajectories. Finally, we demonstrate that switching between anticorrelated paired landscapes leads to ergodic-like dynamics where each genotype is populated with nonzero probability, dramatically lowering the steady-state fitness in comparison to single landscape evolution.

Taming the diffusion approximation through a controlling-factor WKB method

The diffusion approximation (DA) is widely used in the analysis of stochastic population dynamics, from population genetics to ecology and evolution. The DA is an uncontrolled approximation that assumes the smoothness of the calculated quantity over the relevant state space and fails when this property is not satisfied. This failure becomes severe in situations where the direction of selection switches sign. Here we employ the WKB (Wentzel-Kramers-Brillouin) large-deviations method, which requires only the logarithm of a given quantity to be smooth over its state space. Combining the WKB scheme with asymptotic matching techniques, we show how to derive the diffusion approximation in a controlled manner and how to produce better approximations, applicable for much wider regimes of parameters. We also introduce a scalable (independent of population size) WKB-based numerical technique. The method is applied to a central problem in population genetics and evolution, finding the chance of ultimate fixation in a zero-sum, two-types competition.

Reflections on the Predictability of Evolution: Toward a Conceptual Framework

Evolution is generally considered to be unpredictable because genetic variations are known to occur randomly. However, remarkable patterns of repeated convergent evolution are observed, for instance, loss of pigments by organisms living in caves. Analogous phenotypes appear in similar environments, sometimes in response to similar constraints. Alongside randomness, a certain evolutionary determinism also exists, for instance, the selection of particular phenotypes subjected to particular environmental constraints in the “evolutionary funnel.” We pursue the idea that eco-evolutionary specialization is in some way determinist. The conceptual framework of phenotypic changes entailing specialization presented in this essay explains how evolution can be predicted. We also discuss how the predictability of evolution could be tested using the case of metabolic specialization through gene losses. We also put forward that microorganisms could be key models to test and possibly make headway evolutionary predictions and knowledge about evolution.

Evolutionary Dynamics and Consequences of Parthenogenesis in Vertebrates

Parthenogenesis is asexual reproduction without any required participation from males and, as such, is a null model for sexual reproduction. In a comparative context, we can expand our understanding of the evolution and ecology of sex by investigating the consequences of parthenogenesis. In this review, we examine the theoretical predictions of and empirical results on the evolution of asexual reproduction in vertebrates, focusing on recent studies addressing the origins and geographic spread of parthenogenetic lineages and the genomic consequences of an asexual life history. With advances in computational methods and genome technologies, researchers are poised to make rapid and significant progress in studying the origin and evolution of parthenogenesis in vertebrates, thus providing an important perspective on understanding biodiversity patterns of both asexual and sexual populations.

Application of simultaneous selective pressures slows adaptation

Beneficial mutations that arise in an evolving asexual population may compete or interact in ways that alter the overall rate of adaptation through mechanisms such as clonal or functional interference. The application of multiple selective pressures simultaneously may allow for a greater number of adaptive mutations, increasing the opportunities for competition between selectively advantageous alterations, and thereby reducing the rate of adaptation. We evolved a strain of Saccharomyces cerevisiae that could not produce its own histidine or uracil for ~500 generations under one or three selective pressures: limitation of the concentration of glucose, histidine, and/or uracil in the media. The rate of adaptation was obtained by measuring evolved relative fitness using competition assays. Populations evolved under a single selective pressure showed a statistically significant increase in fitness on those pressures relative to the ancestral strain, but the populations evolved on all three pressures did not show a statistically significant increase in fitness over the ancestral strain on any single pressure. Simultaneously limiting three essential nutrients for a population of S. cerevisiae effectively slows the rate of evolution on any one of the three selective pressures applied, relative to the single selective pressure cases. We identify possible mechanisms for fitness changes seen between populations evolved on one or three limiting nutrient pressures by high-throughput sequencing. Adding multiple selective pressures to evolving disease like cancer and infectious diseases could reduce the rate of adaptation and thereby may slow disease progression, prolong drug efficacy and prevent deaths.

Phenotypic delay in the evolution of bacterial antibiotic resistance: Mechanistic models and their implications

Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.

Hypermutator Pseudomonas aeruginosa Exploits Multiple Genetic Pathways To Develop Multidrug Resistance during Long-Term Infections in the Airways of Cystic Fibrosis Patients

Pseudomonas aeruginosa exploits intrinsic and acquired resistance mechanisms to resist almost every antibiotic used in chemotherapy. Antimicrobial resistance in P. aeruginosa isolates recovered from cystic fibrosis (CF) patients is further enhanced by the occurrence of hypermutator strains, a hallmark of chronic infections in CF patients. However, the within-patient genetic diversity of P. aeruginosa populations related to antibiotic resistance remains unexplored. Here, we show the evolution of the mutational resistome profile of a P. aeruginosa hypermutator lineage by performing longitudinal and transversal analyses of isolates collected from a CF patient throughout 20 years of chronic infection. Our results show the accumulation of thousands of mutations, with an overall evolutionary history characterized by purifying selection. However, mutations in antibiotic resistance genes appear to have been positively selected, driven by antibiotic treatment. Antibiotic resistance increased as infection progressed toward the establishment of a population constituted by genotypically diversified coexisting sublineages, all of which converged to multidrug resistance. These sublineages emerged by parallel evolution through distinct evolutionary pathways, which affected genes of the same functional categories. Interestingly, ampC and ftsI, encoding the β-lactamase and penicillin-binding protein 3, respectively, were found to be among the most frequently mutated genes. In fact, both genes were targeted by multiple independent mutational events, which led to a wide diversity of coexisting alleles underlying β-lactam resistance. Our findings indicate that hypermutators, apart from boosting antibiotic resistance evolution by simultaneously targeting several genes, favor the emergence of adaptive innovative alleles by clustering beneficial/compensatory mutations in the same gene, hence expanding P. aeruginosa strategies for persistence.

The adaptive potential of circular DNA accumulation in ageing cells

Carefully maintained and precisely inherited chromosomal DNA provides long-term genetic stability, but eukaryotic cells facing environmental challenges can benefit from the accumulation of less stable DNA species. Circular DNA molecules lacking centromeres segregate randomly or asymmetrically during cell division, following non-Mendelian inheritance patterns that result in high copy number instability and massive heterogeneity across populations. Such circular DNA species, variously known as extrachromosomal circular DNA (eccDNA), microDNA, double minutes or extrachromosomal DNA (ecDNA), are becoming recognised as a major source of the genetic variation exploited by cancer cells and pathogenic eukaryotes to acquire drug resistance. In budding yeast, circular DNA molecules derived from the ribosomal DNA (ERCs) have been long known to accumulate with age, but it is now clear that aged yeast also accumulate other high-copy protein-coding circular DNAs acquired through both random and environmentally-stimulated recombination processes. Here, we argue that accumulation of circular DNA provides a reservoir of heterogeneous genetic material that can allow rapid adaptation of aged cells to environmental insults, but avoids the negative fitness impacts on normal growth of unsolicited gene amplification in the young population.

Larger bacterial populations evolve heavier fitness trade-offs and undergo greater ecological specialization

Evolutionary studies over the last several decades have invoked fitness trade-offs to explain why species prefer some environments to others. However, the effects of population size on trade-offs and ecological specialization remain largely unknown. To complicate matters, trade-offs themselves have been visualized in multiple ways in the literature. Thus, it is not clear how population size can affect the various aspects of trade-offs. To address these issues, we conducted experimental evolution with Escherichia coli populations of two different sizes in two nutritionally limited environments, and studied fitness trade-offs from three different perspectives. We found that larger populations evolved greater fitness trade-offs, regardless of how trade-offs are conceptualized. Moreover, although larger populations adapted more to their selection conditions, they also became more maladapted to other environments, ultimately paying heavier costs of adaptation. To enhance the generalizability of our results, we further investigated the evolution of ecological specialization across six different environmental pairs, and found that larger populations specialized more frequently and evolved consistently steeper reaction norms of fitness. This is the first study to demonstrate a relationship between population size and fitness trade-offs, and the results are important in understanding the population genetics of ecological specialization and vulnerability to environmental changes.

Evolutionary repair: Changes in multiple functional modules allow meiotic cohesin to support mitosis

The role of proteins often changes during evolution, but we do not know how cells adapt when a protein is asked to participate in a different biological function. We forced the budding yeast, Saccharomyces cerevisiae, to use the meiosis-specific kleisin, recombination 8 (Rec8), during the mitotic cell cycle, instead of its paralog, Scc1. This perturbation impairs sister chromosome linkage, advances the timing of genome replication, and reduces reproductive fitness by 45%. We evolved 15 parallel populations for 1,750 generations, substantially increasing their fitness, and analyzed the genotypes and phenotypes of the evolved cells. Only one population contained a mutation in Rec8, but many populations had mutations in the transcriptional mediator complex, cohesin-related genes, and cell cycle regulators that induce S phase. These mutations improve sister chromosome cohesion and delay genome replication in Rec8-expressing cells. We conclude that changes in known and novel partners allow cells to use an existing protein to participate in new biological functions.

Limits on amplifiers of natural selection under death-Birth updating

The fixation probability of a single mutant invading a population of residents is among the most widely-studied quantities in evolutionary dynamics. Amplifiers of natural selection are population structures that increase the fixation probability of advantageous mutants, compared to well-mixed populations. Extensive studies have shown that many amplifiers exist for the Birth-death Moran process, some of them substantially increasing the fixation probability or even guaranteeing fixation in the limit of large population size. On the other hand, no amplifiers are known for the death-Birth Moran process, and computer-assisted exhaustive searches have failed to discover amplification. In this work we resolve this disparity, by showing that any amplification under death-Birth updating is necessarily bounded and transient. Our boundedness result states that even if a population structure does amplify selection, the resulting fixation probability is close to that of the well-mixed population. Our transience result states that for any population structure there exists a threshold r^⋆ such that the population structure ceases to amplify selection if the mutant fitness advantage r is larger than r^⋆. Finally, we also extend the above results to δ-death-Birth updating, which is a combination of Birth-death and death-Birth updating. On the positive side, we identify population structures that maintain amplification for a wide range of values r and δ. These results demonstrate that amplification of natural selection depends on the specific mechanisms of the evolutionary process.

Extensive literature exists on amplifiers of natural selection for the Birth-death Moran process, but no amplifiers are known for the death-Birth Moran process. Here we show that if amplifiers exist under death-Birth updating, they must be bounded and transient. Boundedness implies weak amplification, and transience implies amplification for only a limited range of the mutant fitness advantage. These results demonstrate that amplification depends on the specific mechanisms of the evolutionary process.

Fail-safe genetic codes designed to intrinsically contain engineered organisms

One challenge in engineering organisms is taking responsibility for their behavior over many generations. Spontaneous mutations arising before or during use can impact heterologous genetic functions, disrupt system integration, or change organism phenotype. Here, we propose restructuring the genetic code itself such that point mutations in protein-coding sequences are selected against. Synthetic genetic systems so-encoded should fail more safely in response to most spontaneous mutations. We designed fail-safe codes and simulated their expected effects on the evolution of so-encoded proteins. We predict fail-safe codes supporting expression of 20 or 15 amino acids could slow protein evolution to ∼30% or 0% the rate of standard-encoded proteins, respectively. We also designed quadruplet-codon codes that should ensure all single point mutations in protein-coding sequences are selected against while maintaining expression of 20 or more amino acids. We demonstrate experimentally that a reduced set of 21 tRNAs is capable of expressing a protein encoded by only 20 sense codons, whereas a standard 64-codon encoding is not expressed. Our work suggests that biological systems using rationally depleted but otherwise natural translation systems should evolve more slowly and that such hypoevolvable organisms may be less likely to invade new niches or outcompete native populations.