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Krug, J.

Publications and source records attributed to Krug, J..

At least 19 recordsLinked to original sources

Mutation-biased adaptation: The Yampolsky-Stoltzfus model revisited

The Yampolsky-Stoltzfus (YS) model provided the first formal demonstration that a bias in the introduction of new mutations can shape the direction of adaptive evolution, even when mutation rates are small relative to selection coefficients. Despite its foundational role, the model has been characterized almost entirely by simulation and closed-form solutions for its central quantity, the probability PA that a mutationally favored but less-fit genotype fixes ahead of a rarer, fitter alternative, have been available only in the limiting regimes of vanishing mutation supply and infinite population size. Here we derive closed-form approximations for PA across the intermediate regime of finite population size and appreciable mutation supply that lies between these two limits. Under strong selection between the competing mutants, we combine an establishment-probability argument with clonal interference theory to obtain an explicit expression for PA that accounts for both the ongoing input of the mutationally favored mutation and the frequency-dependent establishment probability of its competitor. Under weak selection between competing mutants, we derive a complementary expression based on the fixation of a mixed population under Kimura's classical formula. Both expressions agree closely with direct simulation of the underlying Wright-Fisher process, recover the known limiting cases, and remain consistent with one another over a substantial intermediate range of parameters. These results are expected to provide a basis for assessing how the strength of mutation bias affects adaptation in empirical data.

evolutionary biology↗

Experimental evolution of collective β-lactam resistance in Escherichia coli via activation of a dormant outermembrane porin

Understanding the mechanisms that drive antibiotic resistance is relevant for both evolutionary theory and the design of effective drug therapies. A specific challenge are collective resistance mechanisms, where bacterial populations survive drug concentrations that kill individual bacteria. Here, we explore the evolvability of collective resistance mechanisms in bacterial strains expressing antibiotic-degrading {beta}-lactamases with different levels of privatization. Four strains of Escherichia coli, with or without outermembrane porin OmpF to affect drug permeability and expressing either a low or high-activity periplasmic {beta}-lactamase, were subjected to lineage selection in a gradient of the drug cefotaxime. Strains with a low-activity enzyme increased cell-level resistance, while strains with low permeability, and hence a more private {beta}-lactamase function, increased collective resistance. Remarkably, increased collective resistance in the strain with a private high-activity {beta}-lactamase came with decreased cell-level resistance. This tradeoff was primarily caused by the activation of a dormant outermembrane porin, NmpC, via the excision of an insertion sequence. Increased drug permeability through NmpC explained both its lower cell-level resistance and its greater collective resistance through faster drug removal and growth recovery via enhanced filamentation at high cell density. The recovery advantage of the NmpC mutant also explained its initial invasion within the ancestral population, suggesting that drug permeability is a readily evolvable collective-resistance mechanism in bacteria with high-activity {beta}-lactamases. Our findings highlight the role of filamentation and drug permeability in {beta}-lactamase-mediated collective resistance to these widely used drugs.

evolutionary biology↗

Random Fitness Landscapes are Highly Navigable

With the increasing availability of large scale empirical fitness landscape data, there is a need for simple yet informative null models that can be used to interpret metrics of landscape ruggedness and navigability. A natural choice of a null model that maximizes ruggedness in a statistical sense assigns independent and identically distributed fitness values to the genotypes, a setting often referred to as the House-of-Cards (HoC) or mutational landscape model. In this work we examine the navigability of these landscapes, as quantified by the mean size of the adaptive basins of local fitness peaks. The adaptive basin is the set of genotypes from which a peak can be reached via selectively accessible, i.e., strictly fitnessincreasing mutational paths. Building on recent rigorous results on the statistics of accessible paths, we show that the adaptive basins in the HoC landscape encompass a positive fraction of all genotypes that is an analytically computable, increasing function of the number of alleles per site. For the four letter nucleotide alphabet, an average peak basin contains 52.8 % of all genotypes. When conditioned on peak fitness, the expected basin size increases linearly with fitness rank. The exact results on adaptive basins are complemented by an approximate analysis of gradient basins formed by greedy adaptive paths which maximize the fitness increase in each step. We argue that recent reports of large adaptive basins in empirical fitness landscapes should be reinterpreted in the light of our findings.

evolutionary biology↗

Adaptive Dynamics of Quantitative Traits in a SteadilyChanging Environment

Understanding the adaptation of quantitative traits to changing environments is a central challenge in evolutionary biology. However, the precise roles of the speed of environmental change and trait architecture in adaptive dynamics remain unclear. Here, we investigate their roles through an adaptive walk model and individual-based polygenic simulations within a moving-soptimum framework. We introduce a dimensionless parameter, the effective selection strength, to characterize quantitative traits in both models. We show that adapting populations attain a stationary state below a critical speed of environmental change. Properties of the stationary state are compared between the two approaches, and it is shown that the adaptive walk model provides a good approximation for long-term polygenic adaptation. Additionally, in the adaptive walk model, we derive an explicit formula for the logarithmic divergence of the stationary phenotypic gap upon approaching the critical speed. To elucidate population extinction in biologically realistic terms, we define a fitness-threshold-based critical speed and reveal its power-law dependence on the effective selection strength in both models. Finally, results of our polygenic simulations show how the genetic architecture in the stationary regime is shaped by a dynamic equilibrium between the influx of de novo mutations and their loss through fixation and extinction constrained by the rate of phenotypic change enforced by the optimum speed. Taken together, our study advances the understanding of polygenic adaptation and provides insights to simplify analytical work and computational simulations for future studies.

evolutionary biology↗

Population structure amplifies mutation load

The interplay of mutation and natural selection is key to evolution: Mutations introduce genetic variation, whereas selection favours higher-fitness individuals. The balance between the two is quantified by the mutation load--the reduction in mean population fitness due to deleterious mutations. In large well-mixed populations, selection dominates, and the mutation load is proportional to the mutation probability per reproduction event. However, the role of spatial structure in shaping mutation-selection dynamics is poorly understood. Here, we use evolutionary graph theory to show that heterogeneous spatial structures generically amplify the effect of mutation relative to selection. In contrast to well-mixed populations, the mutation load in heterogeneous structures can remain substantial even when the mutation rate is very small, signaling a breakdown of selection. For example, in star-shaped populations the mutation rate is effectively amplified by a factor proportional to the population size. When mutation is coupled to reproduction, this leads to the proliferation of less-fit types over fitter ones, a scenario of "survival of the weakest". The reduction of natural selection may help explain, for example, tumour heterogeneity in spatially structured tissues. It also suggests that heterogeneous social networks can promote the persistence of unpopular opinions, thereby fostering diversity. By showing how spatial structure modulates the effect of selection, our work points to potentially new ways of steering evolution toward desired outcomes.

evolutionary biology↗

Corticotropin-releasing hormone in melanoma and non-melanoma skin cancer.

BackgroundCorticotropin-releasing hormone (CRH) is involved in the regulation of immunological and cellular processes. Recently, CRH has been found to be expressed in skin cancers, where its expression appears to correlate with the degree of malignancy. ObjectiveThis study correlates CRH expression in melanoma metastases with patient survival and compares the intensity of CRH expression in melanoma to that in less aggressive skin cancer entities. MethodsTissue microarrays with cores from 94 melanomas and 40 melanocytic nevi and 51 slides from 41 basal cell carcinomas (BCC) and 10 squamous cell carcinomas (SCC) were immunohistochemically stained for CRH. The intensity of CRH expression in melanoma metastases was stratified by sex and correlated with patient survival. Furthermore, proliferation and apoptosis were assessed in CRH-stimulated A431 cells using enzyme-linked immunosorbent assays and an apoptosis detection kit. ResultsThe intensity of CRH expression was higher in primary melanomas than in melanocytic nevi. Higher CRH expression was also found in melanoma metastases from women compared to men. However, higher CRH expression was correlated with reduced overall survival only in men. Compared to melanoma, BCCs and SCCs showed weaker CRH expression, which was in line with the finding that in vitro, CRH stimulation of the A431 cells reduced their proliferative activity. ConclusionCRH does not necessarily correlate with the degree of malignancy, as semi-malignant cancers such as BCC show higher levels of CRH expression than SCCs. In melanoma, CRH expression in metastases may be an important prognostic factor for overall survival in men, which needs further evaluation. Statement of contributionMarcel Mueller and Susanne Melchers performed all experiments and wrote the first draft of the manuscript. Iris Mueller helped with the experiments and reviewed the manuscript, Jochen Utikal assembled the tissue microarrays and reviewed the manuscript, Julia Krug helped with the figures and reviewed the manuscript, and Astrid Schmieder designed and supervised the project and corrected the manuscript.

cancer biology↗

Biphasic adaptive evolution of antimicrobial resistance

The evolutionary adaptation of an organism to a stressful environment often comes at the cost of reduced fitness. For example, resistance to antimicrobial drugs frequently reduces growth rate in the drug-free environment. This cost can be compensated without loss in resistance by mutations at secondary sites when the organism evolves again in the stress-free environment. Here we analytically and numerically study evolution on a simple model fitness landscape to show that compensatory evolution can occur even in the presence of the stress and without the need for mutations at secondary sites. Fitness in the model depends on two phenotypes - the null-fitness defined as the fitness in the absence of stress, and the resistance level to the stress. Mutations universally exhibit antagonistic pleiotropy between the two phenotypes, that is they increase resistance while decreasing the null-fitness. Initial adaptation in this model occurs in a smooth region of the landscape with a rapid accumulation of stress resistance mutations and a concurrent decrease in the null-fitness. This is followed by a second, slower phase exhibiting partial recovery of the null-fitness. The second phase occurs on the rugged part of the landscape and involves the exchange of high-cost resistance mutations for low-cost ones. This process, which we call exchange compensation, is the result of changing epistatic interactions in the genotype as evolution progresses. The model provides general lessons about the tempo and mode of evolution under universal antagonistic pleiotropy with specific implications for drug resistance evolution.

evolutionary biology↗

Collective β-lactam resistance in Escherichia coli due to β-lactamase release upon cell death

Collective antibiotic resistance occurs when populations of bacteria survive antibiotic treatments that are lethal to individual bacteria, which affects the efficacy of drug therapies. An important mechanism of collective resistance against widely used {beta}-lactams is the production of drug-degrading {beta}-lactamases. Here, we integrate experiments with mathematical modeling to understand the collective survival of Escherichia coli challenged with cefotaxime. At near-lethal cefotaxime concentrations, we observe complex dynamics, involving initial biomass growth due to filamentation, followed by death, and subsequently growth recovery. We show that production of AmpC, a chromosomal {beta}-lactamase, is responsible for cefotaxime degradation, allowing the resumption of cell division in surviving filaments. The detoxification of the environment proceeds through CTX hydrolysis by AmpC in the periplasm of intact cells, as well as extracellularly after cell lysis. Our model predicts the recovery time from molecular parameters, and quantifies the relative roles of periplasmic and extracellular degradation for two strains of E. coli that differ in the degree of privatization of AmpC hydrolysis. Our findings suggest that {beta}-lactam survival of bacterial infections depends on a combination of intra- and extracellular {beta}-lactamase activity, which will likely vary among isolates.

microbiology↗

Graph-structured populations elucidate the role of deleterious mutations in long-term evolution

Birth-death models have long been employed to understand the interplay of genetic drift and natural selection. While well-mixed populations remain unaffected by the choice of replacement rules, the evolutionary outcomes in spatially structured populations are strongly impacted by this choice. Moving parent individuals to vacant sites gives rise to new update rules, leading to new fixation categories for spatial graphs. We discover a new category of graphs, amplifiers of fixation, where a structure has a higher probability of fixation for mutants than the well-mixed population, regardless of their fitness value. Under death-Birth updating with parents moving to vacant sites, the star graph is an amplifier of fixation. For very large population sizes, the probability to fix deleterious mutants on the star graph converges to a non-zero value, in contrast to the result from well-mixed populations where the probability goes to zero. Additionally, most random graphs are amplifiers of fixation for death-Birth updating, with parent individuals replacing dead individuals. Conversely, most random graphs are suppressors of fixation- graphs with lower fixation probability for mutants regardless of their fitnesses- for Birth-death updating with offspring replacing dead individuals. When subjected to long-term evolution, amplifiers of fixation, despite being more efficient at fixing beneficial mutants, attain lower fitness than the well-mixed population, whereas suppressors attain higher fitness despite their inferior ability to fix beneficial mutants. These surprising findings can be explained by their deleterious mutant regime. Therefore, the deleterious mutant regime can be as crucial as the beneficial mutant regime for adaptive evolution.

evolutionary biology↗

Generation of a transparent killifish line through multiplex CRISPR/Cas9-mediated gene inactivation

Body pigmentation is a major limitation for in vivo imaging and thus for the performance of longitudinal studies in biomedicine. A possibility to circumvent this obstacle is the employment of pigmentation mutants, which are used in fish species like zebrafish and medaka. To address the molecular basis of aging, the short-lived African killifish Nothobranchius furzeri has recently been established as a model organism. Despite its short lifespan, N. furzeri shows typical signs of mammalian aging including telomere shortening, accumulation of senescent cells and loss of regenerative capacity. Here, we report the generation of a transparent N. furzeri line by simultaneous inactivation of three key loci responsible for pigmentation. We demonstrate that this stable line, named klara, can serve as a tool for different in vivo applications including behavioral experiments addressing mate choice and the establishment of a senescence reporter by homology-directed repair-mediated integration of a fluorophore into the cdkn1a (p21) locus.

developmental biology↗

Unpredictable repeatability in molecular evolution

The extent of parallel evolution at the genotypic level is quantitatively linked to the distribution of beneficial fitness effects (DBFE) of mutations. The standard view, based on light-tailed distributions (i.e. distributions with finite moments), is that the probability of parallel evolution in duplicate populations is inversely proportional to the number of available mutations, and moreover that the DBFE is sufficient to determine the probability when the number of available mutations is large. Here we show that when the DBFE is heavy-tailed, as found in several recent experiments, these expectations are defied. The probability of parallel evolution decays anomalously slowly in the number of mutations or even becomes independent of it, implying higher repeatability of evolution. At the same time, the probability of parallel evolution is non-self-averaging, that is, it does not converge to its mean value even when a large number of mutations are involved. This behavior arises because the evolutionary process is dominated by only a few mutations of high weight. Consequently, the probability varies widely across systems with the same DBFE. Contrary to the standard view, the DBFE is no longer sufficient to determine the extent of parallel evolution, making it much less predictable. We illustrate these ideas theoretically and through analysis of empirical data on antibiotic resistance evolution.

evolutionary biology↗

Effects of recombination on the evolvability, genetic diversity and mutational robustness of neutrally evolving populations

Understanding the benefits and costs of recombination under different scenarios of evolutionary adaptation remains an open problem for theoretical and experimental research. In this study, we focus on finite populations evolving on neutral networks comprising viable and unfit genotypes. We provide a comprehensive overview of the effects of recombination by jointly considering different measures of evolvability and mutational robustness over a broad parameter range, such that many evolutionary regimes are covered. We find that several of these measures vary non-monotonically with the rates of mutation and recombination. Moreover, the presence of unfit genotypes that introduce inhomogeneities in the network of viable states qualitatively alters the effects of recombination. We conclude that conflicting trends induced by recombination can be explained by an emerging trade-off between evolvability on the one hand, and mutational robustness on the other. Finally, we discuss how different implementations of the recombination scheme in theoretical models can affect the observed dependence on recombination rate through a coupling between recombination and genetic drift. Author summaryMany genetic mechanisms have been invoked to explain the advantage of sex, but a coherent picture is still to emerge. Here we present a systematic theoretical and computational investigation of the effects of recombination in populations evolving on neutral fitness landscapes with unfit genotypes. We focus on populations that are large enough to be polymorphic, but nevertheless strongly affected by drift, which causes them to diffuse across the neutral network of viable genotypes. We identify a novel trade-off between evolvability, robustness and fitness that can lead to a dramatic reduction of the genetic diversity at large recombination rates. This disproves the common notion (often referred to as Weismanns hypothesis) that recombination generally increases diversity and evolvability, and instead highlights the interplay of recombination and mutational robustness.

evolutionary biology↗

A Driven Disordered Systems Approach to Biological Evolution in Changing Environments

Biological evolution of a population is governed by the fitness landscape, which is a map from genotype to fitness. However, a fitness landscape depends on the organisms environment, and evolution in changing environments is still poorly understood. We study a particular model of antibiotic resistance evolution in bacteria where the antibiotic concentration is an environmental parameter and the fitness landscapes incorporate tradeoffs between adaptation to low and high antibiotic concentration. With evolutionary dynamics that follow fitness gradients, the evolution of the system under slowly changing antibiotic concentration resembles the athermal dynamics of disordered physical systems under quasistatic external drives. Specifically, our model can be described as a system with interacting hysteretic elements, and it exhibits effects such as hysteresis loops and memory formation under antibiotic concentration cycling. Using methods familiar from studies in this field, we derive a number of analytical and numerical results. Our approach provides a general framework for studying motifs of evolutionary dynamics in biological systems in a changing environment.

evolutionary biology↗

Antibiotic breakdown by susceptible bacteria enhances the establishment of β-lactam resistant mutants

For a better understanding of the evolution of antibiotic resistance, it is imperative to study the factors that determine the initial establishment of mutant resistance alleles. In addition to the antibiotic concentration, the establishment of resistance alleles may be affected by interactions with the surrounding susceptible cells from which they derive, for instance via the release of nutrients or removal of the antibiotic. Here, we investigate the effects of social interactions with surrounding susceptible cells on the establishment of Escherichia coli mutants with increasing {beta}-lactamase activity (i.e. the capacity to hydrolyze {beta}-lactam antibiotics) from single cells under the exposure of the antibiotic cefotaxime on agar plates. We find that mutant establishment probability is increased in the presence of susceptible cells due to the active breakdown of the antibiotic, but the rate of breakdown by the susceptible strain is much higher than expected based on its low enzymatic activity. A detailed theoretical model suggests that this observation can be explained by cell filamentation causing delayed lysis. While susceptible cells may hamper the spread of higher-resistant {beta}-lactamase mutants at relatively high frequencies, our findings show that they could promote establishment during their emergence.

evolutionary biology↗

Stochastic effects on the establishment of mutants resistant to β-lactam antibiotics

For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing {beta}-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability. Lastly, we use the single-cell establishment probability to predict each strains MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays.

evolutionary biology↗

Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution

Both mutations with large benefits and mutations occurring at high rates may cause parallel evolution, but their contribution is expected to depend on population size. We show that small and large bacterial populations adapt to a novel antibiotic using similar numbers, but different types of mutations. Small populations repeatedly substitute similar high-rate structural variants, including the deletion of a nonfunctional {beta}-lactamase, and evolve modest resistance levels. Hundred-fold larger populations more frequently use the same low-rate, large-benefit point mutations, including those activating the {beta}-lactamase, and reach 50-fold higher resistance levels. Our results demonstrate a key role of clonal interference in mediating the contribution of high-rate and large-benefit mutations in populations of different size, facilitated by a tradeoff between rates and fitness effects of different mutation classes.

evolutionary biology↗

The fitness landscapes of translation

Motivated by recent experiments on an antibiotic resistance gene, we investigate genetic interactions between synonymous mutations in the framework of exclusion models of translation. We show that the range of possible interactions is markedly different depending on whether translation efficiency is assumed to be proportional to ribosome current or ribosome speed. In the first case every mutational effect has a definite sign that is independent of genetic background, whereas in the second case the effect-sign can vary depending on the presence of other mutations. The latter result is demonstrated using configurations of multiple translational bottlenecks induced by slow codons.

evolutionary biology↗

Predictable Properties of Fitness Landscapes Induced by Adaptational Tradeoffs

Fitness effects of mutations depend on environmental parameters. For example, mutations that increase fitness of bacteria at high antibiotic concentration often decrease fitness in the absence of antibiotic, exemplifying a tradeoff between adaptation to environmental extremes. We develop a mathematical model for fitness landscapes generated by such tradeoffs, based on experiments that determine the antibiotic dose-response curves of Escherichia coli strains, and previous observations on antibiotic resistance mutations. Our model generates a succession of landscapes with predictable properties as antibiotic concentration is varied. The landscape is nearly smooth at low and high concentrations, but the tradeoff induces a high ruggedness at intermediate antibiotic concentrations. Despite this high ruggedness, however, all the fitness maxima in the landscapes are evolutionarily accessible from the wild type. This implies that selection for antibiotic resistance in multiple mutational steps is relatively facile despite the complexity of the underlying landscape.

evolutionary biology↗