Selection history and epistatic interactions impact dynamics of adaptation to novel environmental stresses

Diverse mutant selection windows shape spatial heterogeneity in evolving populations

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes in both cancer and infectious diseases. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N * 2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more fully reflect the selection of drug resistant genotypes. Furthermore, using synthetic data and empirical dose-response data in cancer, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. By simulating a tumor treated with cyclic drug therapy, we find that mutant selection windows introduced by drug diffusion promote the proliferation of drug resistant cells. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

Diverse mutant selection windows shape spatial heterogeneity in evolving populations

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N*2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more accurately reflect the selection fo drug resistant genotypes. Furthermore, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

Pervasive genotype-by-environment interactions shape the fitness effects of antibiotic resistance mutations

The fitness effects of antibiotic resistance mutations are a major driver of resistance evolution. While the nutrient environment affects bacterial fitness, experimental studies of resistance typically measure fitness of mutants in a single environment only. We explored how the nutrient environment affected the fitness effects of rifampicin-resistant rpoB mutations in Escherichia coli under several conditions critical for the emergence and spread of resistance-the presence of primary or secondary antibiotic, or the absence of any antibiotic. Pervasive genotype-by-environment (GxE) interactions determined fitness in all experimental conditions, with rank order of fitness in the presence and absence of antibiotics being strongly dependent on the nutrient environment. GxE interactions also affected the magnitude and direction of collateral effects of secondary antibiotics, in some cases so drastically that a mutant that was highly sensitive in one nutrient environment exhibited cross-resistance to the same antibiotic in another. It is likely that the mutant-specific impact of rpoB mutations on the global transcriptome underpins the observed GxE interactions. The pervasive, mutant-specific GxE interactions highlight the importance of doing what is rarely done when studying the evolution and spread of resistance in experimental and clinical work: assessing fitness of antibiotic-resistant mutants across a range of relevant environments.

Dissecting weed adaptation: Fitness and trait correlations in herbicide-resistant Alopecurus myosuroides

BACKGROUND

Unravelling the genetic architecture of non-target-site resistance (NTSR) traits in weed populations can inform questions about the inheritance, trade-offs and fitness costs associated with these traits. Classical quantitative genetics approaches allow study of the genetic architecture of polygenic traits even where the genetic basis of adaptation remains unknown. These approaches have the potential to overcome some of the limitations of previous studies into the genetics and fitness of NTSR.

RESULTS

Using a quantitative genetic analysis of 400 pedigreed Alopecurus myosuroides seed families from nine field-collected populations, we found strong heritability for resistance to the acetolactate synthase and acetyl CoA carboxylase inhibitors (h²  = 0.731 and 0.938, respectively), and evidence for shared additive genetic variance for resistance to these two different herbicide modes of action, r_g  = 0.34 (survival), 0.38 (biomass). We find no evidence for genetic correlations between life-history traits and herbicide resistance, indicating that resistance to these two modes of action is not associated with large fitness costs in blackgrass. We do, however, demonstrate that phenotypic variation in plant flowering characteristics is heritable, h²  = 0.213 (flower height), 0.529 (flower head number), 0.449 (time to flowering) and 0.372 (time to seed shed), demonstrating the potential for adaptation to other nonchemical management practices (e.g. mowing of flowering heads) now being adopted for blackgrass control.

CONCLUSION

These results highlight that quantitative genetics can provide important insight into the inheritance and genetic architecture of NTSR, and can be used alongside emerging molecular techniques to better understand the evolutionary and fitness landscape of herbicide resistance. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Multiple Stress Reduces the Advantage of Pesticide Adaptation

Under global change scenarios, multistress conditions may occur regularly and require adaptation. However, the adaptation to one stressor might be associated with the increased sensitivity to another stressor. Here, we investigated the ecological consequences of such trade-off under multiple stress. We compared the pesticide tolerance of the crustacean Gammarus pulex from agricultural streams with populations from reference streams. Under optimum temperature, G. pulex from agricultural streams were considerably more tolerant to pesticides as compared to the reference populations. Here, we assume that the increased tolerance in agricultural populations is the combination of acclimation, epigenetic effect, and genetic evolution. After experimental pre-exposure to very low concentration (LC₅₀/1000), reference populations showed increased pesticide tolerance. In contrast, pre-exposure did not further increase the tolerance of agricultural populations. Moreover, these populations were more sensitive to elevated temperature alone due to the hypothesized fitness cost of genetic adaptation to pesticides. However, both reference and agricultural populations showed a similar tolerance to the combined stress of pesticides and warming due to stronger synergistic effects in adapted populations. As a result, pesticide adaptation loses its advantage. The combined effect was predicted well using the stress addition model, developed for predicting the synergistic interaction of independent stressors. We conclude that under multistress conditions, adaptation to pesticides reduces the general stress capacity of individuals and trade-off processes increase the sensitivity to additional stressors. This causes strong synergistic effects of additional stressors on pesticide-adapted individuals.

Genomic rearrangements uncovered by genome-wide co-evolution analysis of a major nosocomial pathogen, Enterococcus faecium

Enterococcus faecium is a gut commensal of the gastro-digestive tract, but also known as nosocomial pathogen among hospitalized patients. Population genetics based on whole-genome sequencing has revealed that E. faecium strains from hospitalized patients form a distinct clade, designated clade A1, and that plasmids are major contributors to the emergence of nosocomial E. faecium. Here we further explored the adaptive evolution of E. faecium using a genome-wide co-evolution study (GWES) to identify co-evolving single-nucleotide polymorphisms (SNPs). We identified three genomic regions harbouring large numbers of SNPs in tight linkage that are not proximal to each other based on the completely assembled chromosome of the clade A1 reference hospital isolate AUS0004. Close examination of these regions revealed that they are located at the borders of four different types of large-scale genomic rearrangements, insertion sites of two different genomic islands and an IS30-like transposon. In non-clade A1 isolates, these regions are adjacent to each other and they lack the insertions of the genomic islands and IS30-like transposon. Additionally, among the clade A1 isolates there is one group of pet isolates lacking the genomic rearrangement and insertion of the genomic islands, suggesting a distinct evolutionary trajectory. In silico analysis of the biological functions of the genes encoded in three regions revealed a common link to a stress response. This suggests that these rearrangements may reflect adaptation to the stringent conditions in the hospital environment, such as antibiotics and detergents, to which bacteria are exposed. In conclusion, to our knowledge, this is the first study using GWES to identify genomic rearrangements, suggesting that there is considerable untapped potential to unravel hidden evolutionary signals from population genomic data.

Evolutionary and ecological insights from herbicide-resistant weeds: what have we learned about plant adaptation, and what is left to uncover?

The evolution of herbicide resistance in crop weeds presents one of the greatest challenges to agriculture and the production of food. Herbicide resistance has been studied for more than 60 yr, in the large part by researchers seeking to design effective weed control programs. As an outcome of this work, various unique questions in plant adaptation have been addressed. Here, I collate recent research on the herbicide-resistant problem in light of key questions and themes in evolution and ecology. I highlight discoveries made on herbicide-resistant weeds in three broad areas - the genetic basis of adaptation, evolutionary constraints, experimental evolution - and similarly discuss questions left to be answered. I then develop how one would use herbicide-resistance evolution as a model for studying eco-evolutionary dynamics within a community context. My overall goals are to highlight important findings in the weed science literature that are relevant to themes in plant adaptation and to stimulate the use of herbicide-resistant plants as models for addressing key questions within ecology and evolution.

The evolutionary origins of pesticide resistance

Durable crop protection is an essential component of current and future food security. However, the effectiveness of pesticides is threatened by the evolution of resistant pathogens, weeds and insect pests. Pesticides are mostly novel synthetic compounds, and yet target species are often able to evolve resistance soon after a new compound is introduced. Therefore, pesticide resistance provides an interesting case of rapid evolution under strong selective pressures, which can be used to address fundamental questions concerning the evolutionary origins of adaptations to novel conditions. We ask: (i) whether this adaptive potential originates mainly from de novo mutations or from standing variation; (ii) which pre-existing traits could form the basis of resistance adaptations; and (iii) whether recurrence of resistance mechanisms among species results from interbreeding and horizontal gene transfer or from independent parallel evolution. We compare and contrast the three major pesticide groups: insecticides, herbicides and fungicides. Whilst resistance to these three agrochemical classes is to some extent united by the common evolutionary forces at play, there are also important differences. Fungicide resistance appears to evolve, in most cases, by de novo point mutations in the target-site encoding genes; herbicide resistance often evolves through selection of polygenic metabolic resistance from standing variation; and insecticide resistance evolves through a combination of standing variation and de novo mutations in the target site or major metabolic resistance genes. This has practical implications for resistance risk assessment and management, and lessons learnt from pesticide resistance should be applied in the deployment of novel, non-chemical pest-control methods.

Nitrate: An Environmental Endocrine Disruptor? A Review of Evidence and Research Needs

Nitrate is heavily used as an agricultural fertilizer and is today a ubiquitous environmental pollutant. Environmental endocrine effects caused by nitrate have received increasing attention over the last 15 years. Nitrate is hypothesized to interfere with thyroid and steroid hormone homeostasis and developmental and reproductive end points. The current review focuses on aquatic ecotoxicology with emphasis on field and laboratory controlled in vitro and in vivo studies. Furthermore, nitrate is just one of several forms of nitrogen that is present in the environment and many of these are quickly interconvertible. Therefore, the focus is additionally confined to the oxidized nitrogen species (nitrate, nitrite and nitric oxide). We reviewed 26 environmental toxicology studies and our main findings are (1) nitrate has endocrine disrupting properties and hypotheses for mechanisms exist, which warrants for further investigations; (2) there are issues determining actual nitrate-speciation and abundance is not quantified in a number of studies, making links to speciation-specific effects difficult; and (3) more advanced analytical chemistry methodologies are needed both for exposure assessment and in the determination of endocrine biomarkers.

History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment

Antibiotic regimens often include the sequential changing of drugs to limit the development and evolution of resistance of bacterial pathogens. It remains unclear how history of adaptation to one antibiotic can influence the resistance profiles when bacteria subsequently adapt to a different antibiotic. Here, we experimentally evolved Pseudomonas aeruginosa to six 2-drug sequences. We observed drug order-specific effects, whereby adaptation to the first drug can limit the rate of subsequent adaptation to the second drug, adaptation to the second drug can restore susceptibility to the first drug, or final resistance levels depend on the order of the 2-drug sequence. These findings demonstrate how resistance not only depends on the current drug regimen but also the history of past regimens. These order-specific effects may allow for rational forecasting of the evolutionary dynamics of bacteria given knowledge of past adaptations and provide support for the need to consider the history of past drug exposure when designing strategies to mitigate resistance and combat bacterial infections.

The effect of selection history on extinction risk during severe environmental change

Environments rarely remain the same over time, and populations are therefore frequently at risk of going extinct when changes are significant enough to reduce fitness. Although many studies have investigated what attributes of the new environments and of the populations experiencing these changes will affect their probability of going extinct, limited work has been directed towards determining the role of population history on the probability of going extinct during severe environmental change. Here, we compare the extinction risk of populations with a history of selection in a benign environment, to populations with a history of selection in one or two stressful environments. We exposed spores and lines of the green alga Chlamydomonas reinhardtii from these three different histories to a range of severe environmental changes. We found that the extinction risk was higher for populations with a history of selection in stressful environments compared to populations with a history of selection in a benign environment. This effect was not due to differences in initial population sizes. Finally, the rates of extinction were highly repeatable within histories, indicating strong historical contingency of extinction risk. Hence, information on the selection history of a population can be used to predict their probability of going extinct during environmental change.

Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein

Epistatic interactions between residues determine a protein’s adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient) condition that detects epistasis in most cases. We analyze the “fossils” of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing environment.

Evolution is often viewed as a process that occurs “mutation by mutation”, suggesting that the effect of each mutation is independent of that of others. However, in reality the effect of a mutation often depends on the context of other mutations, a dependence known as “epistasis”. Even though epistasis can constrain protein evolution, it is actually very common. Such interactions are particularly pervasive in proteins that evolve resistance to a drug via mutations that create defects, and that must be repaired with compensatory mutations. We study how epistasis between protein residues evolves over time in a new and changing environment, and compare these findings to protein evolution in a constant environment. We analyze the sequences of the human immunodeficiency virus type 1 (HIV-1) protease enzyme collected over a period of 9 years from patients treated with anti-viral drugs (as well as from patients that went untreated), and find that epistasis between residues continues to increase as more potent anti-viral drugs enter the market, while epistasis is unchanging in the proteins exposed to a constant environment. Yet, the proteins adapting to the changing landscape do not appear to be constrained by the epistatic interactions and continue to manage to evade new drugs.

Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary "forks in the road" that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance.

Tebuconazole disrupts steroidogenesis in Xenopus laevis

A 27-day controlled exposure study of adult male African clawed frogs (Xenopus laevis) was conducted to examine the mechanism by which tebuconazole may disrupt steroidogenesis. The fungicide was measured by LC-MS/MS in tank water and in target tissues (adipose, kidney, liver, and brain), and we observed tissue-specific bioconcentration with BCF up to 238. Up to 10 different steroid hormones were quantified in gonads using LC-MS/MS and in plasma using GC-MS/MS and a radioimmunoassay was performed for further measurement of androgens. In order to assess whether effects increased with exposure or animals adapted to the xenobiotic, blood samples were collected 12 days into the study and at termination (day 27). After 12 days of exposure to 100 and 500μgL(-1) tebuconazole, plasma levels of testosterone (T) and dihydrotestosterone (DHT) were increased, while plasma 17β-estradiol (E2) concentrations were greatly reduced. Exposure to 0.1μgL(-1), on the other hand, resulted in decreased levels of T and DHT, with no effects observed for E2. After 27 days of exposure, effects were no longer observed in circulating androgen levels while the suppressive effect on E2 persisted in the two high-exposure groups (100 and 500μgL(-1)). Furthermore, tebuconazole increased gonadal concentrations of T and DHT as well as expression of the enzyme CYP17 (500μgL(-1), 27 days). These results suggest that tebuconazole exposure may supress the action of CYP17 at the lowest exposure (0.1μgL(-1)), while CYP19 suppression dominates at higher exposure concentrations (increased androgens and decreased E2). Increased androgen levels in plasma half-way into the study and in gonads at termination may thus be explained by compensatory mechanisms, mediated through increased enzymatic expression, as prolonged exposure had no effect on circulating androgen levels.

Eco-evo-devo of the lemur syndrome: did adaptive behavioral plasticity get canalized in a large primate radiation?

BACKGROUND

Comprehensive explanations of behavioral adaptations rarely invoke all levels famously admonished by Niko Tinbergen. The role of developmental processes and plasticity, in particular, has often been neglected. In this paper, we combine ecological, physiological and developmental perspectives in developing a hypothesis to account for the evolution of 'the lemur syndrome', a combination of reduced sexual dimorphism, even adult sex ratios, female dominance and mild genital masculinization characterizing group-living species in two families of Malagasy primates.

RESULTS

We review the different components of the lemur syndrome and compare it with similar adaptations reported for other mammals. We find support for the assertion that the lemur syndrome represents a unique set of integrated behavioral, demographic and morphological traits. We combine existing hypotheses about underlying adaptive function and proximate causation by adding a potential developmental mechanism linking maternal stress and filial masculinization, and outline an evolutionary scenario for its canalization.

CONCLUSIONS

We propose a new hypothesis linking ecological, physiological, developmental and evolutionary processes to adumbrate a comprehensive explanation for the evolution of the lemur syndrome, whose assumptions and predictions can guide diverse future research on lemurs. This hypothesis should also encourage students of other behavioral phenomena to consider the potential role of developmental plasticity in evolutionary innovation.