Fitness trade-offs in the evolution of dihydrofolate reductase and drug resistance in Plasmodium falciparum

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.

The problem of antimalarial resistance and its implications for drug discovery

INTRODUCTION

Malaria remains a devastating infectious disease with hundreds of thousands of casualties each year. Antimalarial drug resistance has been a threat to malaria control and elimination for many decades and is still of concern today. Despite the continued effectiveness of current first-line treatments, namely artemisinin-based combination therapies, the emergence of drug-resistant parasites in Southeast Asia and even more alarmingly the occurrence of resistance mutations in Africa is of great concern and requires immediate attention.

AREAS COVERED

A comprehensive overview of the mechanisms underlying the acquisition of drug resistance in Plasmodium falciparum is given. Understanding these processes provides valuable insights that can be harnessed for the development and selection of novel antimalarials with reduced resistance potential. Additionally, strategies to mitigate resistance to antimalarial compounds on the short term by using approved drugs are discussed.

EXPERT OPINION

While employing strategies that utilize already approved drugs may offer a prompt and cost-effective approach to counter antimalarial drug resistance, it is crucial to recognize that only continuous efforts into the development of novel antimalarial drugs can ensure the successful treatment of malaria in the future. Incorporating resistance propensity assessment during this developmental process will increase the likelihood of effective and enduring malaria treatments.

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.

Challenges and potential solutions for studying the genetic and phenotypic architecture of adaptation in microbes

All organisms are defined by the makeup of their DNA. Over billions of years, the structure and information contained in that DNA, often referred to as genetic architecture, have been honed by a multitude of evolutionary processes. Mutations that cause genetic elements to change in a way that results in beneficial phenotypic change are more likely to survive and propagate through the population in a process known as adaptation. Recent work reveals that the genetic targets of adaptation are varied and can change with genetic background. Further, seemingly similar adaptive mutations, even within the same gene, can have diverse and unpredictable effects on phenotype. These challenges represent major obstacles in predicting adaptation and evolution. In this review, we cover these concepts in detail and identify three emerging synergistic solutions: higher-throughput evolution experiments combined with updated genotype-phenotype mapping strategies and physiological models. Our review largely focuses on recent literature in yeast, and the field seems to be on the cusp of a new era with regard to studying the predictability of evolution.

Inferring a complete genotype-phenotype map from a small number of measured phenotypes

Understanding evolution requires detailed knowledge of genotype-phenotype maps; however, it can be a herculean task to measure every phenotype in a combinatorial map. We have developed a computational strategy to predict the missing phenotypes from an incomplete, combinatorial genotype-phenotype map. As a test case, we used an incomplete genotype-phenotype dataset previously generated for the malaria parasite’s ‘chloroquine resistance transporter’ (PfCRT). Wild-type PfCRT (PfCRT^3D7) lacks significant chloroquine (CQ) transport activity, but the introduction of the eight mutations present in the ‘Dd2’ isoform of PfCRT (PfCRT^Dd2) enables the protein to transport CQ away from its site of antimalarial action. This gain of a transport function imparts CQ resistance to the parasite. A combinatorial map between PfCRT^3D7 and PfCRT^Dd2 consists of 256 genotypes, of which only 52 have had their CQ transport activities measured through expression in the Xenopus laevis oocyte. We trained a statistical model with these 52 measurements to infer the CQ transport activity for the remaining 204 combinatorial genotypes between PfCRT^3D7 and PfCRT^Dd2. Our best-performing model incorporated a binary classifier, a nonlinear scale, and additive effects for each mutation. The addition of specific pairwise- and high-order-epistatic coefficients decreased the predictive power of the model. We evaluated our predictions by experimentally measuring the CQ transport activities of 24 additional PfCRT genotypes. The R² value between our predicted and newly-measured phenotypes was 0.90. We then used the model to probe the accessibility of evolutionary trajectories through the map. Approximately 1% of the possible trajectories between PfCRT^3D7 and PfCRT^Dd2 are accessible; however, none of the trajectories entailed eight successive increases in CQ transport activity. These results demonstrate that phenotypes can be inferred with known uncertainty from a partial genotype-phenotype dataset. We also validated our approach against a collection of previously published genotype-phenotype maps. The model therefore appears general and should be applicable to a large number of genotype-phenotype maps.

Biological macromolecules are built from chains of building blocks. The function of a macromolecule depends on the specific chemical properties of the building blocks that make it up. Macromolecules evolve through mutations that swap one building block for another. Understanding how biomolecules work and evolve therefore requires knowledge of the effects of mutations. The effects of mutations can be measured experimentally; however, because there are a vast number of possible combinations of mutations, it is often difficult to make enough measurements to understand biomolecular function and evolution. In this paper, we describe a simple method to predict the effects of mutations on biomolecules from a small number of measurements. This method works by appropriately averaging the effects of mutations seen in different contexts. We test the method by predicting the effects of mutations on a PfCRT—a macromolecule from the malarial parasite that confers drug resistance. We find that our method is fast and effective. Using a small number of measurements, we were able to gain insight into the evolutionary steps by which this macromolecule conferred drug resistance. To make this method accessible to other researchers, we have released it as an open-source software package: https://gpseer.readthedocs.io.

Characterization of Plasmodium knowlesi dihydrofolate reductase-thymidylate synthase and sensitivity to antifolates

Malaria caused by an infection of Plasmodium knowlesi can result in high parasitemia and deaths. Therefore, effective and prompt treatment is necessary to reduce morbidity and mortality. The study aims to characterize P. knowlesi dihydrofolate reductase-thymidylate synthase enzyme (PkDHFR-TS) and its sensitivity to antifolates. The putative Pkdhfr gene was PCR amplified from field isolates collected from the Southern Thailand. Molecular analysis showed 11 polymorphisms in the dhfr domain of the bifunctional dhfr-ts gene. Of these, 1 polymorphism was a non-synonymous substitution (R34L) that had previously been reported but not associated with antifolate resistance. The recombinant PkDHFR-TS enzyme was found to be sensitive to standard antifolates-pyrimethamine and cycloguanil-as well as P218, a registered candidate drug currently first in human clinical trial. Results suggest that antifolates class of compounds should be effective against P. knowlesi infection.

The Influence of Higher-Order Epistasis on Biological Fitness Landscape Topography

The effect of a mutation on the organism often depends on what other mutations are already present in its genome. Geneticists refer to such mutational interactions as epistasis. Pairwise epistatic effects have been recognized for over a century, and their evolutionary implications have received theoretical attention for nearly as long. However, pairwise epistatic interactions themselves can vary with genomic background. This is called higher-order epistasis, and its consequences for evolution are much less well understood. Here, we assess the influence that higher-order epistasis has on the topography of 16 published, biological fitness landscapes. We find that on average, their effects on fitness landscape declines with order, and suggest that notable exceptions to this trend may deserve experimental scrutiny. We conclude by highlighting opportunities for further theoretical and experimental work dissecting the influence that epistasis of all orders has on fitness landscape topography and on the efficiency of evolution by natural selection.

Competition along trajectories governs adaptation rates towards antimicrobial resistance

The increasing availability of genotype-phenotype maps for different combinations of mutations has empowered evolutionary biologists with the tools to interrogate the predictability of adaptive evolution, especially in the context of the evolution of antimicrobial resistance. Large microbial populations are known to generate competing beneficial mutations, but determining how these mutations contribute to the adaptive trajectories that are most likely to be followed remains a challenge. Despite a recognition that there may also be competition between successive alleles on the same trajectory, prior studies have not fully considered how this impacts adaptation rates along, or likelihood of following, individual trajectories. Here, we develop a metric that quantifies the competition between successive alleles along adaptive trajectories and show how this competition largely governs the rate of evolution in simulations on empirical fitness landscapes for proteins involved in drug resistance in two species of malaria (Plasmodium falciparum and P. vivax). Our findings reveal that a trajectory with a larger-than-average initial fitness increase may have smaller fitness increases in later steps, which slows adaptation. In some circumstances, these trajectories may be outcompeted by alleles on faster alternative trajectories that are being explored simultaneously. The ability to predict adaptation rates along accessible trajectories has implications for efforts to manage antimicrobial resistance in real-world settings and for the broader intellectual pursuit of predictive evolution in complex adaptive fitness landscapes for a variety of application domains.

A New Take on John Maynard Smith's Concept of Protein Space for Understanding Molecular Evolution

Much of the public lacks a proper understanding of Darwinian evolution, a problem that can be addressed with new learning and teaching approaches to be implemented both inside the classroom and in less formal settings. Few analogies have been as successful in communicating the basics of molecular evolution as John Maynard Smith’s protein space analogy (1970), in which he compared protein evolution to the transition between the terms WORD and GENE, changing one letter at a time to yield a different, meaningful word (in his example, the preferred path was WORD → WORE → GORE → GONE → GENE). Using freely available computer science tools (Google Books Ngram Viewer), we offer an update to Maynard Smith’s analogy and explain how it might be developed into an exploratory and pedagogical device for understanding the basics of molecular evolution and, more specifically, the adaptive landscape concept. We explain how the device works through several examples and provide resources that might facilitate its use in multiple settings, ranging from public engagement activities to formal instruction in evolution, population genetics, and computational biology.

Functional Trade-Offs in Promiscuous Enzymes Cannot Be Explained by Intrinsic Mutational Robustness of the Native Activity

The extent to which an emerging new function trades off with the original function is a key characteristic of the dynamics of enzyme evolution. Various cases of laboratory evolution have unveiled a characteristic trend; a large increase in a new, promiscuous activity is often accompanied by only a mild reduction of the native, original activity. A model that associates weak trade-offs with “evolvability” was put forward, which proposed that enzymes possess mutational robustness in the native activity and plasticity in promiscuous activities. This would enable the acquisition of a new function without compromising the original one, reducing the benefit of early gene duplication and therefore the selection pressure thereon. Yet, to date, no experimental study has examined this hypothesis directly. Here, we investigate the causes of weak trade-offs by systematically characterizing adaptive mutations that occurred in two cases of evolutionary transitions in enzyme function: (1) from phosphotriesterase to arylesterase, and (2) from atrazine chlorohydrolase to melamine deaminase. Mutational analyses in various genetic backgrounds revealed that, in contrast to the prevailing model, the native activity is less robust to mutations than the promiscuous activity. For example, in phosphotriesterase, the deleterious effect of individual mutations on the native phosphotriesterase activity is much larger than their positive effect on the promiscuous arylesterase activity. Our observations suggest a revision of the established model: weak trade-offs are not caused by an intrinsic robustness of the native activity and plasticity of the promiscuous activity. We propose that upon strong adaptive pressure for the new activity without selection against the original one, selected mutations will lead to the largest possible increases in the new function, but whether and to what extent they decrease the old function is irrelevant, creating a bias towards initially weak trade-offs and the emergence of generalist enzymes.

Understanding how enzymes evolve is a fundamental question that can help us decipher not only the mechanisms of evolution on a higher level, i.e., whole organisms, but also advances our knowledge of sequence-structure-function relationships as a guide to artificial evolution in the test tube. An important yet unexplained phenomenon occurs during the evolution of a new enzymatic function; it has been observed that new and ancestral functions often trade-off only weakly, meaning the original native activity is initially maintained at a high level despite drastic improvement of the new promiscuous activity. It has previously been proposed that weak trade-offs occur because the native activity is robust to mutations while the promiscuous activity is not. However, the present work contradicts this hypothesis, based on the detailed characterization of mutational effects on both activities in two examples of enzyme evolution. We propose an alternative explanation: the weak activity trade-off is consistent with being a by-product of strong selection for the new activity rather than an intrinsic property of the native activity.

Combinatorial Genetic Modeling of pfcrt-Mediated Drug Resistance Evolution in Plasmodium falciparum

The emergence of drug resistance continuously threatens global control of infectious diseases, including malaria caused by the protozoan parasite Plasmodium falciparum. A critical parasite determinant is the P. falciparum chloroquine resistance transporter (PfCRT), the primary mediator of chloroquine (CQ) resistance (CQR), and a pleiotropic modulator of susceptibility to several first-line artemisinin-based combination therapy partner drugs. Aside from the validated CQR molecular marker K76T, P. falciparum parasites have acquired at least three additional pfcrt mutations, whose contributions to resistance and fitness have been heretofore unclear. Focusing on the quadruple-mutant Ecuadorian PfCRT haplotype Ecu1110 (K76T/A220S/N326D/I356L), we genetically modified the pfcrt locus of isogenic, asexual blood stage P. falciparum parasites using zinc-finger nucleases, producing all possible combinations of intermediate pfcrt alleles. Our analysis included the related quintuple-mutant PfCRT haplotype 7G8 (Ecu1110 + C72S) that is widespread throughout South America and the Western Pacific. Drug susceptibilities and in vitro growth profiles of our combinatorial pfcrt-modified parasites were used to simulate the mutational trajectories accessible to parasites as they evolved CQR. Our results uncover unique contributions to parasite drug resistance and growth for mutations beyond K76T and predict critical roles for the CQ metabolite monodesethyl-CQ and the related quinoline-type drug amodiaquine in driving mutant pfcrt evolution. Modeling outputs further highlight the influence of parasite proliferation rates alongside gains in drug resistance in dictating successful trajectories. Our findings suggest that P. falciparum parasites have navigated constrained pfcrt adaptive landscapes by means of probabilistically rare mutational bursts that led to the infrequent emergence of pfcrt alleles in the field.

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.

Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes

Predicting evolutionary paths to antibiotic resistance is key for understanding and controlling drug resistance. When considering a single final resistant genotype, epistatic contingencies among mutations restrict evolution to a small number of adaptive paths. Less attention has been given to multi-peak landscapes, and while specific peaks can be favoured, it is unknown whether and how early a commitment to final fate is made. Here we characterize a multi-peaked adaptive landscape for trimethoprim resistance by constructing all combinatorial alleles of seven resistance-conferring mutations in dihydrofolate reductase. We observe that epistatic interactions increase rather than decrease the accessibility of each peak; while they restrict the number of direct paths, they generate more indirect paths, where mutations are adaptively gained and later adaptively lost or changed. This enhanced accessibility allows evolution to proceed through many adaptive steps while delaying commitment to genotypic fate, hindering our ability to predict or control evolutionary outcomes.

The molecular basis of antifolate resistance in Plasmodium falciparum: looking beyond point mutations

Drugs that target the folate-synthesis pathway have a long history of effectiveness against a variety of pathogens. As antimalarials, the antifolates were safe and well tolerated, but resistance emerged quickly and has persisted even with decreased drug pressure. The primary determinants of resistance in Plasmodium falciparum are well-described point mutations in the enzymes dihydropteroate synthase and dihydrofolate reductase targeted by the combination sulfadoxine-pyrimethamine. Recent work has highlighted the contributions of additional parasite adaptation to antifolate resistance. In fact, the evolution of antifolate-resistant parasites is multifaceted and complex. Gene amplification of the first enzyme in the parasite folate synthesis pathway, GTP-cyclohydrolase, is strongly associated with resistant parasites and potentially contributes to persistence of resistant parasites. Further understanding of how parasites adjust flux through the folate pathway is important to the further development of alternative agents targeting this crucial synthesis pathway.

What can we learn from fitness landscapes?

A combinatorially complete data set consists of studies of all possible combinations of a set of mutant sites in a gene or mutant alleles in a genome. Among the most robust conclusions from these studies is that epistasis between beneficial mutations often shows a pattern of diminishing returns, in which favorable mutations are less fit when combined than would be expected. Another robust inference is that the number of adaptive evolutionary paths is often limited to a relatively small fraction of the theoretical possibilities, owing largely to sign epistasis requiring evolutionary steps that would entail a decrease in fitness. Here we summarize these and other results while also examining issues that remain unresolved and future directions that seem promising.

Correlation of molecular markers, Pfmdr1-N86Y and Pfcrt-K76T, with in vitro chloroquine resistant Plasmodium falciparum, isolated in the malaria endemic states of Assam and Arunachal Pradesh, Northeast India

The mechanism of chloroquine (CQ) resistance in Plasmodium falciparum is not clearly understood. However, CQ resistance has been shown to be associated with point mutations in Pfcrt and Pfmdr1. These genes encode for digestive vacuole transmembrane proteins Pfcrt and Pgh1, respectively. The present study was carried out to analyze the association of Pfcrt-K76T and Pfmdr1-N86Y mutations with CQ resistance in Northeast Indian P. falciparum isolates. 115 P. falciparum isolates were subjected to in vitro CQ sensitivity testing and PCR-RFLP analysis for the Pfmdr1-N86Y and Pfcrt-K76T mutations. 100 isolates of P. falciparum were found to be resistant to CQ by the in vitro susceptibility test (geometric mean EC₅₀ 2.21 µM/L blood) while 15 were found to be CQ sensitive (geometric mean EC₅₀ 0.32 µM/L blood). All the CQ resistant isolates showed the presence of Pfmdr1 and Pfcrt mutations. CQ sensitive isolates were negative for these mutations. Strong linkage disequilibrium was observed between the alleles at these two loci (Pfmdr1-N86Y and Pfcrt-K76T). The results indicate that Pfmdr1-N86Y and Pfcrt-K76T mutations can be used as molecular markers to identify CQ resistance in P. falciparum. The result necessitates the evaluation of CQ in vivo therapeutic efficacy in endemic areas for more effective malaria control strategies.

Origin of robustness in generating drug-resistant malaria parasites

Biological robustness allows mutations to accumulate while maintaining functional phenotypes. Despite its crucial role in evolutionary processes, the mechanistic details of how robustness originates remain elusive. Using an evolutionary trajectory analysis approach, we demonstrate how robustness evolved in malaria parasites under selective pressure from an antimalarial drug inhibiting the folate synthesis pathway. A series of four nonsynonymous amino acid substitutions at the targeted enzyme, dihydrofolate reductase (DHFR), render the parasites highly resistant to the antifolate drug pyrimethamine. Nevertheless, the stepwise gain of these four dhfr mutations results in tradeoffs between pyrimethamine resistance and parasite fitness. Here, we report the epistatic interaction between dhfr mutations and amplification of the gene encoding the first upstream enzyme in the folate pathway, GTP cyclohydrolase I (GCH1). gch1 amplification confers low level pyrimethamine resistance and would thus be selected for by pyrimethamine treatment. Interestingly, the gch1 amplification can then be co-opted by the parasites because it reduces the cost of acquiring drug-resistant dhfr mutations downstream in the same metabolic pathway. The compensation of compromised fitness by extra GCH1 is an example of how robustness can evolve in a system and thus expand the accessibility of evolutionary trajectories leading toward highly resistant alleles. The evolution of robustness during the gain of drug-resistant mutations has broad implications for both the development of new drugs and molecular surveillance for resistance to existing drugs.

The reproducibility of adaptation in the light of experimental evolution with whole genome sequencing

A key question in evolutionary biology is the reproducibility of adaptation. This question can now be quantitatively analyzed using experimental evolution coupled to whole genome sequencing (WGS). With complete sequence data, one can assess convergence among replicate populations. In turn, convergence reflects the action of natural selection and also the breadth of the field of possible adaptive solutions. That is, it provides insight into how many genetic solutions or adaptive paths may lead to adaptation in a given environment. Convergence is both a property of an adaptive landscape and, reciprocally, a tool to study that landscape. In this chapter we present the links between convergence and the properties of adaptive landscapes with respect to two types of microbial experimental evolution. The first tries to reconstruct a full adaptive landscape using a handful of carefully identified mutations (the reductionist approach), while the second uses WGS of replicate experiments to infer properties of the adaptive landscape. Reductionist approaches have highlighted the importance of epistasis in shaping the adaptive landscape, but have also uncovered a wide diversity of landscape architectures. The WGS approach has uncovered a very high diversity of beneficial mutations that affect a limited set of genes or functions and also suggests some shortcomings of the reductionist approach. We conclude that convergence may be better defined at an integrated level, such as the genic level or even at a phenotypic level, and that integrated mechanistic models derived from systems biology may offer an interesting perspective for the analysis of convergence at all levels.

Should evolutionary geneticists worry about higher-order epistasis?

Natural selection drives evolving populations up the fitness landscape, the projection from nucleotide sequence space to organismal reproductive success. While it has long been appreciated that topographic complexities on fitness landscapes can arise only as a consequence of epistatic interactions between mutations, evolutionary genetics has mainly focused on epistasis between pairs of mutations. Here we propose a generalization to the classical population genetic treatment of pairwise epistasis that yields expressions for epistasis among arbitrary subsets of mutations of all orders (pairwise, three-way, etc.). Our approach reveals substantial higher-order epistasis in almost every published fitness landscape. Furthermore we demonstrate that higher-order epistasis is critically important in two systems we know best. We conclude that higher-order epistasis deserves empirical and theoretical attention from evolutionary geneticists.

Malaria life cycle intensifies both natural selection and random genetic drift

Analysis of genome sequences of 159 isolates of Plasmodium falciparum from Senegal yields an extraordinarily high proportion (26.85%) of protein-coding genes with the ratio of nonsynonymous to synonymous polymorphism greater than one. This proportion is much greater than observed in other organisms. Also unusual is that the site-frequency spectra of synonymous and nonsynonymous polymorphisms are virtually indistinguishable. We hypothesized that the complicated life cycle of malaria parasites might lead to qualitatively different population genetics from that predicted from the classical Wright-Fisher (WF) model, which assumes a single random-mating population with a finite and constant population size in an organism with nonoverlapping generations. This paper summarizes simulation studies of random genetic drift and selection in malaria parasites that take into account their unusual life history. Our results show that random genetic drift in the malaria life cycle is more pronounced than under the WF model. Paradoxically, the efficiency of purifying selection in the malaria life cycle is also greater than under WF, and the relative efficiency of positive selection varies according to conditions. Additionally, the site-frequency spectrum under neutrality is also more skewed toward low-frequency alleles than expected with WF. These results highlight the importance of considering the malaria life cycle when applying existing population genetic tools based on the WF model. The same caveat applies to other species with similarly complex life cycles.

Evolutionary biochemistry: revealing the historical and physical causes of protein properties

The repertoire of proteins and nucleic acids in the living world is determined by evolution; their properties are determined by the laws of physics and chemistry. Explanations of these two kinds of causality - the purviews of evolutionary biology and biochemistry, respectively - are typically pursued in isolation, but many fundamental questions fall squarely at the interface of fields. Here we articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution. We show how an integration of evolution with biochemistry moves us towards a more complete understanding of why biological molecules have the properties that they do.

Exact results for amplitude spectra of fitness landscapes

Starting from fitness correlation functions, we calculate exact expressions for the amplitude spectra of fitness landscapes as defined by Stadler [1996. Landscapes and their correlation functions. J. Math. Chem. 20, 1] for common landscape models, including Kauffman's NK-model, rough Mount Fuji landscapes and general linear superpositions of such landscapes. We further show that correlations decaying exponentially with the Hamming distance yield exponentially decaying spectra similar to those reported recently for a model of molecular signal transduction. Finally, we compare our results for the model systems to the spectra of various experimentally measured fitness landscapes. We claim that our analytical results should be helpful when trying to interpret empirical data and guide the search for improved fitness landscape models.

Long-term evolution is surprisingly predictable in lattice proteins

It has long been debated whether natural selection acts primarily upon individual organisms, or whether it also commonly acts upon higher-level entities such as lineages. Two arguments against the effectiveness of long-term selection on lineages have been (i) that long-term evolutionary outcomes will not be sufficiently predictable to support a meaningful long-term fitness and (ii) that short-term selection on organisms will almost always overpower long-term selection. Here, we use a computational model of protein folding and binding called 'lattice proteins'. We quantify the long-term evolutionary success of lineages with two metrics called the k-fitness and k-survivability. We show that long-term outcomes are surprisingly predictable in this model: only a small fraction of the possible outcomes are ever realized in multiple replicates. Furthermore, the long-term fitness of a lineage depends only partly on its short-term fitness; other factors are also important, including the 'evolvability' of a lineage-its capacity to produce adaptive variation. In a system with a distinct short-term and long-term fitness, evolution need not be 'short-sighted': lineages may be selected for their long-term properties, sometimes in opposition to short-term selection. Similar evolutionary basins of attraction have been observed in vivo, suggesting that natural biological lineages will also have a predictive long-term fitness.

Replaying the tape of life: quantification of the predictability of evolution

The question whether adaptation follows a deterministic route largely prescribed by the environment or can proceed along a large number of alternative trajectories has engaged extensive research over the recent years. Experimental evolution studies enabled by advances in high throughput techniques for genome sequencing and manipulation, along with increasingly detailed mathematical modeling of fitness landscapes, are beginning to allow quantitative exploration of the repeatability of evolutionary trajectories. It is becoming clear that evolutionary trajectories in static correlated fitness landscapes are substantially non-random but the relative contributions of determinism and stochasticity in the evolution of specific phenotypes strongly depend on the specific conditions, particularly the magnitude of the selective pressure and the number of available beneficial mutations.

Intramolecular epistasis and the evolution of a new enzymatic function

Atrazine chlorohydrolase (AtzA) and its close relative melamine deaminase (TriA) differ by just nine amino acid substitutions but have distinct catalytic activities. Together, they offer an informative model system to study the molecular processes that underpin the emergence of new enzymatic function. Here we have constructed the potential evolutionary trajectories between AtzA and TriA, and characterized the catalytic activities and biophysical properties of the intermediates along those trajectories. The order in which the nine amino acid substitutions that separate the enzymes could be introduced to either enzyme, while maintaining significant catalytic activity, was dictated by epistatic interactions, principally between three amino acids within the active site: namely, S331C, N328D and F84L. The mechanistic basis for the epistatic relationships is consistent with a model for the catalytic mechanisms in which protonation is required for hydrolysis of melamine, but not atrazine.

Combined spatial limitation around residues 16 and 108 of Plasmodium falciparum dihydrofolate reductase explains resistance to cycloguanil

Natural mutations of Plasmodium falciparum dihydrofolate reductase (PfDHFR) at A16V and S108T specifically confer resistance to cycloguanil (CYC) but not to pyrimethamine (PYR). In order to understand the nature of CYC resistance, the effects of various mutations at A16 on substrate and inhibitor binding were examined. Three series of mutations at A16 with or without the S108T/N mutation were generated. Only three mutants with small side chains at residue 16 (G, C, and S) were viable from bacterial complementation assay in the S108 series, whereas these three and an additional four mutants (T, V, M, and I) with slightly larger side chains were viable with simultaneous S108T mutation. Among these combinations, the A16V+S108T mutant was the most CYC resistant, and all of the S108T series ranged from being highly to moderately sensitive to PYR. In the S108N series, a strict requirement for alanine was observed at position 16. Crystal structure analyses reveal that in PfDHFR-TS variant T9/94 (A16V+S108T) complexed with CYC, the ligand has substantial steric conflicts with the side chains of both A16V and S108T, whereas in the complex with PYR, the ligand only showed mild conflict with S108T. CYC analogs designed to avoid such conflicts improved the binding affinity of the mutant enzymes. These results show that there is greater spatial limitation around the S108T/N residue when combined with the limitation imposed by A16V. The limitation of mutation of this series provides opportunities for drug design and development against antifolate-resistant malaria.

Source of drug resistant Plasmodium falciparum in a potential malaria elimination site in Saudi Arabia

A major challenge to the success of malaria control program in Saudi Arabia is the high influx of expatriates and holy visitors from malaria endemic countries. In the present study we examined whether drug resistant parasite genotypes reported in Jazan region, southwest of Saudi Arabia are imported or developed locally. We examined 178 Plasmodium falciparum isolates for alleles of dihydropteroate synthase (dhps) and dihydrofolate reductase (dhfr), associated with Sulfadoxine-Pyrimethamine (SP) resistance, and three microsatellites flanking each gene. In addition, we examined a neutral polymorphic gene (Pfg377). We compared the dhfr and dhps haplotypes in Jazan, using network analysis, to an existing similar data set of 94 P. falciparum isolates from eastern Sudan. In Jazan, double mutant dhfr allele (51I, 108N) occurred with a prevalence of 33%. The vast majority (99%) of dhps were wild-type alleles. The mean expected heterozygosity (H(e)) of microsatellites around mutant dhfr alleles (H(e)=0.312; n=60) was lower (P ≤ 0.05) than that around the wild-type allele (H(e)=0.834; n=116). Also, the mutant dhfr isolates showed high H(e) for dhps (H(e)=0.80) and the non-drug resistance locus Pfg377 (H(e)=0.63) indicative of selection for mutant dhfr only. The predominant double mutant dhfr haplotype in Jazan (73%), was prevalent among P. falciparum in east Africa. Network analysis suggests the mutant haplotype of dhfr gene was possibly introduced into Jazan from East Africa. The absence of mutations in dhps as well as triple mutant dhfr haplotype associated with SP failure support the current use of SP as a partner with artesunate as a first line therapy in Saudi Arabia. However, the close relationship between the major mutant dhfr haplotype in Sudan and Saudi Arabia, favour the hypothesis of recent migration as a source of the major resistant dhfr lineage. Thus, regular monitoring of the dhfr and dhps haplotypes is of high priority to guard possible importation of high level SP resistant lineages.

The evolutionary landscape of antifolate resistance in Plasmodium falciparum

Resistance to antifolates in Plasmodium falciparum is well described and has been observed in clinical settings for decades. At the molecular level, point mutations in the dhfr gene that lead to resistance have been identified, and the crystal structure of the wildtype and mutant dihydrofolate reductase enzymes have been solved in complex with native substrate and drugs. However, we are only beginning to understand the complexities of the evolutionary pressures that lead to the evolution of drug resistance in this system. Microbial systems that allow heterologous expression of malarial proteins provide a tractable way to investigate patterns of evolution that can inform our eventual understanding of the more complex factors that influence the evolution of drug resistance in clinical settings. In this paper we will review work in Escherichia coli and Saccharomyces cerevisiae expression systems that explore the fitness landscape of mutations implicated in drug resistance and show that (i) a limited number of evolutionary pathways to resistance are followed with high probability; (ii) fitness costs associated with the maintenance of high levels of resistance are modest; and (iii) different antifolates may exert opposing selective forces.