Population genetic strategies that leverage association, selection, and linkage have identified drug-resistant loci. However, challenges and limitations persist in identifying drug-resistance loci in malaria. In this review we discuss the genetic basis of drug resistance and the use of genome-wide association studies, complemented by selection and linkage studies, to identify and understand mechanisms of drug resistance and response. We also discuss the implications of nongenetic mechanisms of drug resistance recently reported in the literature, and present models of the interplay between nongenetic and genetic processes that contribute to the emergence of drug resistance. Throughout, we examine artemisinin resistance as an example to emphasize challenges in identifying phenotypes suitable for population genetic studies as well as complications due to multiple-factor drug resistance.
As public health interventions drive parasite populations to elimination, genetic epidemiology models that incorporate population genomics can be powerful tools for evaluating the effectiveness of continued intervention. However, current genetic epidemiology models may not accurately simulate the population genetic profile of parasite populations, particularly with regard to polygenomic (multi-strain) infections. Current epidemiology models simulate polygenomic infections via superinfection (multiple mosquito bites), despite growing evidence that cotransmission (a single mosquito bite) may contribute to polygenomic infections.
Background: The study of reverse evolution from resistant to susceptible phenotypes can reveal constraints on biological evolution, a topic for which evolutionary theory has relatively few general principles. The public health catastrophe of antimicrobial resistance in malaria has brought these constraints on evolution into a practical realm, with one proposed solution: withdrawing anti-malarial medication use in high resistance settings, built on the assumption that reverse evolution occurs readily enough that populations of pathogens may revert to their susceptible states. While past studies have suggested limits to reverse evolution, there have been few attempts to properly dissect its mechanistic constraints. Methods: Growth rates were determined from empirical data on the growth and resistance from a set of combinatorially complete set of mutants of a resistance protein (dihydrofolate reductase) in Plasmodium vivax, to construct reverse evolution trajectories. The fitness effects of individual mutations were calculated as a function of drug environment, revealing the magnitude of epistatic interactions between mutations and genetic backgrounds. Evolution across the landscape was simulated in two settings: starting from the population fixed for the quadruple mutant, and from a polymorphic population evenly distributed between double mutants. Results: A single mutation of large effect (S117N) serves as a pivot point for evolution to high resistance regions of the landscape. Through epistatic interactions with other mutations, this pivot creates an epistatic ratchet against reverse evolution towards the wild type ancestor, even in environments where the wild type is the most fit of all genotypes. This pivot mutation underlies the directional bias in evolution across the landscape, where evolution towards the ancestor is precluded across all examined drug concentrations from various starting points in the landscape. Conclusions: The presence of pivot mutations can dictate dynamics of evolution across adaptive landscape through epistatic interactions within a protein, leaving a population trapped on local fitness peaks in an adaptive landscape, unable to locate ancestral genotypes. This irreversibility suggests that the structure of an adaptive landscape for a resistance protein should be understood before considering resistance management strategies. This proposed mechanism for constraints on reverse evolution corroborates evidence from the field indicating that phenotypic reversal often occurs via compensatory mutation at sites independent of those associated with the forward evolution of resistance. Because of this, molecular methods that identify resistance patterns via single SNPs in resistance-associated markers might be missing signals for resistance and compensatory mutation throughout the genome. In these settings, whole genome sequencing efforts should be used to identify resistance patterns, and will likely reveal a more complicated genomic signature for resistance and susceptibility, especially in settings where anti-malarial medications have been used intermittently. Lastly, the findings suggest that, given their role in dictating the dynamics of evolution across the landscape, pivot mutations might serve as future targets for therapy. Electronic supplementary material The online version of this article (doi:10.1186/s12936-016-1090-3) contains supplementary material, which is available to authorized users.
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.
Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi. We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype–phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.
Crosses between closely related animal species often result in male hybrids that are sterile, and the molecular and functional basis of genetic factors for hybrid male sterility is of great interest. Here, we report a molecular and functional analysis of HMS1, a region of 9.2 kb in chromosome 3 of Drosophila mauritiana, which results in virtually complete hybrid male sterility when homozygous in the genetic background of sibling species Drosophila simulans. The HMS1 region contains two strong candidate genes for the genetic incompatibility, agt and Taf1. Both encode unrelated DNA-binding proteins, agt for an alkyl-cysteine-S-alkyltransferase and Taf1 for a subunit of transcription factor TFIID that serves as a multifunctional transcriptional regulator. The contribution of each gene to hybrid male sterility was assessed by means of germ-line transformation, with constructs containing complete agt and Taf1 genomic sequences as well as various chimeric constructs. Both agt and Taf1 contribute about equally to HMS1 hybrid male sterility. Transgenes containing either locus rescue sterility in about one-half of the males, and among fertile males the number of offspring is in the normal range. This finding suggests compensatory proliferation of the rescued, nondysfunctional germ cells. Results with chimeric transgenes imply that the hybrid incompatibilities result from interactions among nucleotide differences residing along both agt and Taf1. Our results challenge a number of preliminary generalizations about the molecular and functional basis of hybrid male sterility, and strongly reinforce the role of DNA-binding proteins as a class of genes contributing to the maintenance of postzygotic reproductive isolation.
Genes encode components of coevolved and interconnected networks. The effect of genotype on phenotype therefore depends on genotypic context through gene interactions known as epistasis. Epistasis is important in predicting phenotype from genotype for an individual. It is also examined in population studies to identify genetic risk factors in complex traits and to predict evolution under selection. Paradoxically, the effects of genotypic context in individuals and populations are distinct and sometimes contradictory. We argue that predicting genotype from phenotype for individuals based on population studies is difficult and, especially in human genetics, likely to result in underestimating the effects of genotypic context.
Plasmodium falciparum malaria remains a devastating public health problem. Recent discoveries have shed light on the origin and evolution of Plasmodium parasites and their interactions with their vertebrate and mosquito hosts. P. falciparum malaria originated in Africa from a single horizontal transfer between an infected gorilla and a human, and became global as the result of human migration. Today, P. falciparum malaria is transmitted worldwide by more than 70 different anopheline mosquito species. Recent studies indicate that the mosquito immune system can be a barrier to malaria transmission and that the P. falciparum Pfs47 gene allows the parasite to evade mosquito immune detection. Here, we review the origin and globalization of P. falciparum and integrate this history with analysis of the biology, evolution, and dispersal of the main mosquito vectors. This new perspective broadens our understanding of P. falciparum population structure and the dispersal of important parasite genetic traits.
Background: Encouraging advances in the control of Plasmodium falciparum malaria have been observed across much of Africa in the past decade. However, regions of high relative prevalence and transmission that remain unaddressed or unrecognized provide a threat to this progress. Difficulties in identifying such localized hotspots include inadequate surveillance, especially in remote regions, and the cost and labor needed to produce direct estimates of transmission. Genetic data can provide a much-needed alternative to such empirical estimates, as the pattern of genetic variation within malaria parasite populations is indicative of the level of local transmission. Here, genetic data were used to provide the first empirical estimates of P. falciparum malaria prevalence and transmission dynamics for the rural, remote Makira region of northeastern Madagascar. Methods: Longitudinal surveys of a cohort of 698 total individuals (both sexes, 0–74 years of age) were performed in two communities bordering the Makira Natural Park protected area. Rapid diagnostic tests, with confirmation by molecular methods, were used to estimate P. falciparum prevalence at three seasonal time points separated by 4-month intervals. Genomic loci in a panel of polymorphic, putatively neutral markers were genotyped for 94 P. falciparum infections and used to characterize genetic parameters known to correlate with transmission levels. Results: Overall, 27.8% of individuals tested positive for P. falciparum over the 10-month course of the study, a rate approximately sevenfold higher than the countrywide average for Madagascar. Among those P. falciparum infections, a high level of genotypic diversity and a high frequency of polygenomic infections (68.1%) were observed, providing a pattern consistent with high and stable transmission. Conclusions: Prevalence and genetic diversity data indicate that the Makira region is a hotspot of P. falciparum transmission in Madagascar. This suggests that the area should be highlighted for future interventions and that additional areas of high transmission may be present in ecologically similar regions nearby. Electronic supplementary material The online version of this article (doi:10.1186/s12936-016-1644-4) contains supplementary material, which is available to authorized users.
Genetic polymorphisms identified from genomic sequencing can be used to track changes in parasite populations through time. Such tracking is particularly informative when applying control strategies and evaluating their effectiveness. Using genomic approaches may also enable improved ability to categorise populations and to stratify them according to the likely effectiveness of intervention. Clinical applications of genomic approaches also allow relapses to be classified according to reinfection or recrudescence. These tools can be used not only to assess the effectiveness of malaria interventions but also to appraise the strategies for malaria elimination.
Quantitative genetics has primarily focused on describing genetic effects on trait means and largely ignored the effect of alternative alleles on trait variability, potentially missing an important axis of genetic variation contributing to phenotypic differences among individuals. To study the genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used Drosophila inbred lines and measured the spontaneous locomotor behavior of flies walking individually in Y-shaped mazes, focusing on variability in locomotor handedness, an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals, whereas lines with low variability behaved as although they tossed a coin at each left/right turn decision. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a, implicates a neuropil in the central complex of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination. We validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. Our study reveals the constellation of phenotypes that can arise from a single genotype and shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variabililty. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.
Despite decades of eradication efforts, malaria remains a global burden. Recent renewed interest in regional elimination and global eradication has been accompanied by increased genomic information about Plasmodium parasite species responsible for malaria, including characteristics of geographical populations as well as variations associated with reduced susceptibility to anti-malarial drugs. One common genetic variation, single-nucleotide polymorphisms (SNPs), offers attractive targets for parasite genotyping. These markers are useful not only for tracking drug resistance markers but also for tracking parasite populations using markers not under drug or other selective pressures. SNP genotyping methods offer the ability to track drug resistance as well as to fingerprint individual parasites for population surveillance, particularly in response to malaria control efforts in regions nearing elimination status. While informative SNPs have been identified that are agnostic to specific genotyping technologies, high-resolution melting (HRM) analysis is particularly suited to field-based studies. Compared to standard fluorescent-probe based methods that require individual SNPs in a single labeled probe and offer at best 10% sensitivity to detect SNPs in samples that contain multiple genomes (polygenomic), HRM offers 2-5% sensitivity. Modifications to HRM, such as blocked probes and asymmetric primer concentrations as well as optimization of amplification annealing temperatures to bias PCR towards amplification of the minor allele, further increase the sensitivity of HRM. While the sensitivity improvement depends on the specific assay, we have increased detection sensitivities to less than 1% of the minor allele. In regions approaching malaria eradication, early detection of emerging or imported drug resistance is essential for prompt response. Similarly, the ability to detect polygenomic infections and differentiate imported parasite types from cryptic local reservoirs can inform control programs. This manuscript describes modifications to high resolution melting technology that further increase its sensitivity to identify polygenomic infections in patient samples.
Understanding the molecular basis of species formation is an important goal in evolutionary genetics, and Dobzhansky-Muller incompatibilities are thought to be a common source of postzygotic reproductive isolation between closely related lineages. However, the evolutionary forces that lead to the accumulation of such incompatibilities between diverging taxa are poorly understood. Segregation distorters are believed to be an important source of Dobzhansky-Muller incompatibilities between hybridizing species of Drosophila as well as hybridizing crop plants, but it remains unclear if these selfish genetic elements contribute to reproductive isolation in other taxa. Here, we collected viable sperm from first-generation hybrid male progeny of Mus musculus castaneus and M. m. domesticus, two subspecies of rodent in the earliest stages of speciation. We then genotyped millions of single nucleotide polymorphisms in these gamete pools and tested for a skew in the frequency of parental alleles across the genome. We show that segregation distorters are not measurable contributors to observed infertility in these hybrid males, despite sufficient statistical power to detect even weak segregation distortion with our novel method. Thus, reduced hybrid male fertility in crosses between these nascent species is attributable to other evolutionary forces.
BACKGROUND: Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. METHODS: COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. RESULTS: COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. CONCLUSIONS: The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.
SUMMARY Detecting signals of selection in the genome of malaria parasites is a key to identify targets for drug and vaccine development. Malaria parasites have a unique life cycle alternating between vector and host organism with a population bottleneck at each transition. These recurrent bottlenecks could influence the patterns of genetic diversity and the power of existing population genetic tools to identify sites under positive selection. We therefore simulated the site-frequency spectrum of a beneficial mutant allele through time under the malaria life cycle. We investigated the power of current population genetic methods to detect positive selection based on the site-frequency spectrum as well as temporal changes in allele frequency. We found that a within-host selective advantage is difficult to detect using these methods. Although a between-host transmission advantage could be detected, the power is decreased when compared with the classical Wright-Fisher (WF) population model. Using an adjusted null site-frequency spectrum that takes the malaria life cycle into account, the power of tests based on the site-frequency spectrum to detect positive selection is greatly improved. Our study demonstrates the importance of considering the life cycle in genetic analysis, especially in parasites with complex life cycles.
Identifying the source of resurgent parasites is paramount to a strategic, successful intervention for malaria elimination. Although the malaria incidence in Panama is low, a recent outbreak resulted in a 6-fold increase in reported cases. We hypothesized that parasites sampled from this epidemic might be related and exhibit a clonal population structure. We tested the genetic relatedness of parasites, using informative single-nucleotide polymorphisms and drug resistance loci. We found that parasites were clustered into 3 clonal subpopulations and were related to parasites from Colombia. Two clusters of Panamanian parasites shared identical drug resistance haplotypes, and all clusters shared a chloroquine-resistance genotype matching the pfcrt haplotype of Colombian origin. Our findings suggest these resurgent parasite populations are highly clonal and that the high clonality likely resulted from epidemic expansion of imported or vestigial cases. Malaria outbreak investigations that use genetic tools can illuminate potential sources of epidemic malaria and guide strategies to prevent further resurgence in areas where malaria has been eliminated.
Imprinting is well-documented in both plant and animal species. In Drosophila, the Y chromosome is differently modified when transmitted through the male and female germlines. Here, we report genome-wide gene expression effects resulting from reversed parent-of-origin of the X and Y chromosomes. We found that hundreds of genes are differentially expressed between adult male Drosophila melanogaster that differ in the maternal and paternal origin of the sex chromosomes. Many of the differentially regulated genes are expressed specifically in testis and midgut cells, suggesting that sex chromosome imprinting might globally impact gene expression in these tissues. In contrast, we observed much fewer Y-linked parent-of-origin effects on genome-wide gene expression in females carrying a Y chromosome, indicating that gene expression in females is less sensitive to sex chromosome parent-of-origin. Genes whose expression differs between females inheriting a maternal or paternal Y chromosome also show sex chromosome parent-of-origin effects in males, but the direction of the effects on gene expression (overexpression or underexpression) differ between the sexes. We suggest that passage of sex chromosome chromatin through male meiosis may be required for wild-type function in F1 progeny, whereas disruption of Y-chromosome function through passage in the female germline likely arises because the chromosome is not adapted to the female germline environment.
Drug resistance emerges in an ecological context where fitness costs restrict the diversity of escape pathways. These pathways are targets for drug discovery, and here we demonstrate that we can identify small-molecule inhibitors that differentially target resistant parasites. Combining wild-type and mutant-type inhibitors may prevent the emergence of competitively viable resistance. We tested this hypothesis with a clinically derived chloroquine-resistant (CQ(r)) malaria parasite and with parasites derived by in vitro selection with Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors. We screened a chemical library against CQ(s) and CQ(r) lines and discovered a drug-like compound (IDI-3783) that was potent only in the CQ(r) line. Surprisingly, in vitro selection of Plasmodium falciparum resistant to IDI-3783 restored CQ sensitivity, thereby indicating that CQ might once again be useful as a malaria therapy. In parallel experiments, we selected P. falciparum lines resistant to structurally unrelated PfDHODH inhibitors (Genz-666136 and DSM74). Both selections yielded resistant lines with the same point mutation in PfDHODH:E182D. We discovered a compound (IDI-6273) more potent against E182D than wild-type parasites. Selection of the E182D mutant with IDI-6273 yielded a reversion to the wild-type protein sequence and phenotype although the nucleotide sequence was different. Importantly, selection with a combination of Genz-669178, a wild-type PfDHODH inhibitor, and IDI-6273, a mutant-selective PfDHODH inhibitor, did not yield resistant parasites. These two examples demonstrate that the compromise between resistance and evolutionary fitness can be exploited to design therapies that prevent the emergence and spread of resistant organisms.
Genes linked to X or Z chromosomes, which are hemizygous in the heterogametic sex, are predicted to evolve at different rates than those on autosomes. This "faster-X effect" can arise either as a consequence of hemizygosity, which leads to more efficient selection for recessive beneficial mutations in the heterogametic sex, or as a consequence of reduced effective population size of the hemizygous chromosome, which leads to increased fixation of weakly deleterious mutations due to genetic drift. Empirical results to date suggest that, while the overall pattern across taxa is complicated, systems with male heterogamy show a faster-X effect attributable to more efficient selection, whereas the faster-Z effect in female-heterogametic taxa is attributable to increased drift. To test the generality of the faster-Z pattern seen in birds and snakes, we sequenced the genome of the lepidopteran silkmoth Bombyx huttoni. We show that silkmoths experience faster-Z evolution, but unlike in birds and snakes, the faster-Z effect appears to be attributable to more efficient positive selection. These results suggest that female heterogamy alone is unlikely to explain the reduced efficacy of selection on vertebrate Z chromosomes. It is likely that many factors, including differences in overall effective population size, influence Z chromosome evolution.