A population genetic model for the initial spread of partially resistant malaria parasites under anti-malarial combination therapy and weak intrahost competition

Evolutionary genetics of malaria

Many standard-textbook population-genetic results apply to a wide range of species. Sometimes, however, population-genetic models and principles need to be tailored to a particular species. This is particularly true for malaria, which next to tuberculosis and HIV/AIDS ranks among the economically most relevant infectious diseases. Importantly, malaria is not one disease—five human-pathogenic species of Plasmodium exist. P. falciparum is not only the most severe form of human malaria, but it also causes the majority of infections. The second most relevant species, P. vivax, is already considered a neglected disease in several endemic areas. All human-pathogenic species have distinct characteristics that are not only crucial for control and eradication efforts, but also for the population-genetics of the disease. This is particularly true in the context of selection. Namely, fitness is determined by so-called fitness components, which are determined by the parasites live-history, which differs between malaria species. The presence of hypnozoites, i.e., dormant liver-stage parasites, which can cause disease relapses, is a distinct feature of P. vivax and P. ovale sp. In P. malariae inactivated blood-stage parasites can cause a recrudescence years after the infection was clinically cured. To properly describe population-genetic processes, such as the spread of anti-malarial drug resistance, these features must be accounted for appropriately. Here, we introduce and extend a population-genetic framework for the evolutionary dynamics of malaria, which applies to all human-pathogenic malaria species. The model focuses on, but is not limited to, the spread of drug resistance. The framework elucidates how the presence of dormant liver stage or inactivated blood stage parasites that act like seed banks delay evolutionary processes. It is shown that, contrary to standard population-genetic theory, the process of selection and recombination cannot be decoupled in malaria. Furthermore, we discuss the connection between haplotype frequencies, haplotype prevalence, transmission dynamics, and relapses or recrudescence in malaria.

Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

Although drug resistance in Plasmodium falciparum typically evolves in regions of low transmission, resistance spreads readily following introduction to regions with a heavier disease burden. This suggests that the origin and the spread of resistance are governed by different processes, and that high transmission intensity specifically impedes the origin. Factors associated with high transmission, such as highly immune hosts and competition within genetically diverse infections, are associated with suppression of resistant lineages within hosts. However, interactions between these factors have rarely been investigated and the specific relationship between adaptive immunity and selection for resistance has not been explored. Here, we developed a multiscale, agent-based model of Plasmodium parasites, hosts, and vectors to examine how host and parasite dynamics shape the evolution of resistance in populations with different transmission intensities. We found that selection for antigenic novelty (“immune selection”) suppressed the evolution of resistance in high transmission settings. We show that high levels of population immunity increased the strength of immune selection relative to selection for resistance. As a result, immune selection delayed the evolution of resistance in high transmission populations by allowing novel, sensitive lineages to remain in circulation at the expense of the spread of a resistant lineage.

In contrast, in low transmission settings, we observed that resistant strains were able to sweep to high population prevalence without interference. Additionally, we found that the relationship between immune selection and resistance changed when resistance was widespread. Once resistance was common enough to be found on many antigenic backgrounds, immune selection stably maintained resistant parasites in the population by allowing them to proliferate, even in untreated hosts, when resistance was linked to a novel epitope. Our results suggest that immune selection plays a role in the global pattern of resistance evolution.

Drug resistance in the malaria parasite, Plasmodium falciparum, presents an ongoing public health challenge, but aspects of its evolution are poorly understood. Although antimalarial resistance is common worldwide, it can typically be traced to just a handful of evolutionary origins. Counterintuitively, although Sub Saharan Africa bears 90% of the global malaria burden, resistance typically originates in regions where transmission intensity is low. In high transmission regions, infections are genetically diverse, and hosts have significant standing adaptive immunity, both of which are known to suppress the frequency of resistance within infections. However, interactions between immune-driven selection, transmission intensity, and resistance have not been investigated. Using a multiscale, agent-based model, we found that high transmission intensity slowed the evolution of resistance via its effect on host population immunity. High host immunity strengthened selection for antigenic novelty, interfering with selection for resistance and allowing sensitive lineages to suppress resistant lineages in untreated hosts. However, once resistance was common in the circulating parasite population, immune selection maintained it in the population at a high prevalence. Our findings provide a novel explanation for observations about the origin of resistance and suggest that adaptive immunity is a critical component of selection.

Genetic Signatures of Evolutionary Rescue by a Selective Sweep

One of the most useful models in population genetics is that of a selective sweep and the consequent hitch-hiking of linked neutral alleles. While variations on this model typically assume constant population size, many instances of strong selection and rapid adaptation in nature may co-occur with complex demography. Here, we extend the hitch-hiking model to evolutionary rescue, where adaptation and demography not only co-occur but are intimately entwined. Our results show how this feedback between demography and evolution determines-and restricts-the genetic signatures of evolutionary rescue, and how these differ from the signatures of sweeps in populations of constant size. In particular, we find rescue to harden sweeps from standing variance or new mutation (but not from migration), reduce genetic diversity both at the selected site and genome-wide, and increase the range of observed Tajima's D values. For a given initial rate of population decline, the feedback between demography and evolution makes all of these differences more dramatic under weaker selection, where bottlenecks are prolonged. Nevertheless, it is likely difficult to infer the co-incident timing of the sweep and bottleneck from these simple signatures, never mind a feedback between them. Temporal samples spanning contemporary rescue events may offer one way forward.

Early transmission of sensitive strain slows down emergence of drug resistance in Plasmodium vivax

The spread of drug resistance of Plasmodium falciparum and Plasmodium vivax parasites is a challenge towards malaria elimination. P. falciparum has shown an early and severe drug resistance in comparison to P. vivax in various countries. In fact, P. vivax differs in its life cycle and treatment in various factors: development and duration of sexual parasite forms differ, symptoms severity are unequal, relapses present only in P. vivax cases and the Artemisinin-based combination therapy (ACT) is only mandatory in P. falciparum cases. We compared the spread of drug resistance for both species through two compartmental models using ordinary differential equations. The model structure describes how sensitive and resistant parasite strains infect a human population treated with antimalarials. We found that an early transmission,i.e., before treatment and low effectiveness of drug coverage, supports the prevalence of sensitive parasites delaying the emergence of resistant P. vivax. These results imply that earlier attention of both symptomatic cases and reservoirs of P. vivax are essential in controlling transmission but also accelerate the spread of drug resistance.

Evolution and Genetic Diversity of the k13 Gene Associated with Artemisinin Delayed Parasite Clearance in Plasmodium falciparum

Mutations in the Plasmodium falciparum k13 (Pfk13) gene are linked to delayed parasite clearance in response to artemisinin-based combination therapies (ACTs) in Southeast Asia. To explore the evolutionary rate and constraints acting on this gene, k13 orthologs from species sharing a recent common ancestor with P. falciparum and Plasmodium vivax were analyzed. These comparative studies were followed by genetic polymorphism analyses within P. falciparum using 982 complete Pfk13 sequences from public databases and new data obtained by next-generation sequencing from African and Haitian isolates. Although k13 orthologs evolve at heterogeneous rates, the gene was conserved across the genus, with only synonymous substitutions being found at residues where mutations linked to the delayed parasite clearance phenotype have been reported. This suggests that those residues were under constraint from undergoing nonsynonymous changes during evolution of the genus. No fixed nonsynonymous differences were found between Pfk13 and its orthologs in closely related species found in African apes. This indicates that all nonsynonymous substitutions currently found in Pfk13 are younger than the time of divergence between P. falciparum and its closely related species. At the population level, no mutations linked to delayed parasite clearance were found in our samples from Africa and Haiti. However, there is a high number of single Pfk13 mutations segregating in P. falciparum populations, and two predominant alleles are distributed worldwide. This pattern is discussed in terms of how changes in the efficacy of natural selection, affected by population expansion, may have allowed for the emergence of mutations tolerant to ACTs.

The Impact of Antimalarial Use on the Emergence and Transmission of Plasmodium falciparum Resistance: A Scoping Review of Mathematical Models

The emergence and transmission of resistance to antimalarial treatments continue to hamper malaria elimination efforts. A scoping review was undertaken regarding the impact of antimalarial treatment in the human population on the emergence and transmission of Plasmodium falciparum resistance, to (i) describe the use of mathematical models used to explore this relationship; (ii) discuss model findings; and (iii) identify factors influencing the emergence and transmission of resistance. Search strategies were developed and deployed in six major databases. Thirty-seven articles met the eligibility criteria and were included in the review: nine articles modeled the emergence of resistance, 19 modeled the transmission of resistance, and nine modeled both the emergence and transmission. The proportion of antimalarial use within the population and the presence of residual drug concentrations were identified to be the main predictors of the emergence and transmission of resistance. Influencing factors pertaining to the human, parasite and mosquito populations are discussed. To ensure the prolonged therapeutic usefulness of antimalarial treatments, the effect of antimalarial drug use on the emergence and transmission of resistance must be understood, and mathematical models are a useful tool for exploring these dynamics.

Spatial Effects on the Multiplicity of Plasmodium falciparum Infections

As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.

Variation in infection length and superinfection enhance selection efficiency in the human malaria parasite

The capacity for adaptation is central to the evolutionary success of the human malaria parasite Plasmodium falciparum. Malaria epidemiology is characterized by the circulation of multiple, genetically diverse parasite clones, frequent superinfection, and highly variable infection lengths, a large number of which are chronic and asymptomatic. The impact of these characteristics on the evolution of the parasite is largely unknown, however, hampering our understanding of the impact of interventions and the emergence of drug resistance. In particular, standard population genetic frameworks do not accommodate variation in infection length or superinfection. Here, we develop a population genetic model of malaria including these variations, and show that these aspects of malaria infection dynamics enhance both the probability and speed of fixation for beneficial alleles in complex and non-intuitive ways. We find that populations containing a mixture of short- and long-lived infections promote selection efficiency. Interestingly, this increase in selection efficiency occurs even when only a small fraction of the infections are chronic, suggesting that selection can occur efficiently in areas of low transmission intensity, providing a hypothesis for the repeated emergence of drug resistance in the low transmission setting of Southeast Asia.

Multiplicity of Infection and Disease Severity in Plasmodium vivax

Background

Multiplicity of infection (MOI) refers to the average number of distinct parasite genotypes concurrently infecting a patient. Although several studies have reported on MOI and the frequency of multiclonal infections in Plasmodium falciparum, there is limited data on Plasmodium vivax. Here, MOI and the frequency of multiclonal infections were studied in areas from South America where P. vivax and P. falciparum can be compared.

Methodology/Principal Findings

As part of a passive surveillance study, 1,328 positive malaria patients were recruited between 2011 and 2013 in low transmission areas from Colombia. Of those, there were only 38 P. vivax and 24 P. falciparum clinically complicated cases scattered throughout the time of the study. Samples from uncomplicated cases were matched in time and location with the complicated cases in order to compare the circulating genotypes for these two categories. A total of 92 P. vivax and 57 P. falciparum uncomplicated cases were randomly subsampled. All samples were genotyped by using neutral microsatellites. Plasmodium vivax showed more multiclonal infections (47.7%) than P. falciparum (14.8%). Population genetics and haplotype network analyses did not detect differences in the circulating genotypes between complicated and uncomplicated cases in each parasite. However, a Fisher exact test yielded a significant association between having multiclonal P. vivax infections and complicated malaria. No association was found for P. falciparum infections.

Conclusion

The association between multiclonal infections and disease severity in P. vivax is consistent with previous observations made in rodent malaria. The contrasting pattern between P. vivax and P. falciparum could be explained, at least in part, by the fact that P. vivax infections have lineages that were more distantly related among them than in the case of the P. falciparum multiclonal infections. Future research should address the possible role that acquired immunity and exposure may have on multiclonal infections and their association with disease severity.

Previous studies on rodent malarias and mathematical models have postulated a link between multiclonal infections and disease severity. This association has been tested in Plasmodium falciparum mostly in Africa with limited information on P. vivax. Furthermore, there is a paucity of information from areas with low transmission. Here, we used samples available from a passive surveillance carried out in Colombia, South America. We found an association between multiclonal infections and disease severity in P. vivax but not in P. falciparum. Although the number of complicated malaria cases is low, the contrasting pattern between these two species emphasizes their epidemiological differences. We discuss how this pattern could be the result of a higher divergence among the P. vivax lineages co-infecting a patient. We hypothesize that low levels of acquired immunity may play a role in the association between multiclonal infections and disease severity.

How competition governs whether moderate or aggressive treatment minimizes antibiotic resistance

Understanding how our use of antimicrobial drugs shapes future levels of drug resistance is crucial. Recently, there has been debate over whether an aggressive (i.e., high dose) or more moderate (i.e., lower dose) treatment of individuals will most limit the emergence and spread of resistant bacteria. In this study, we demonstrate how one can understand and resolve these apparently contradictory conclusions. We show that a key determinant of which treatment strategy will perform best at the individual level is the extent of effective competition between resistant and sensitive pathogens within a host. We extend our analysis to the community level, exploring the spectrum between strict inter-strain competition and strain independence. From this perspective as well, we find that the magnitude of effective competition between resistant and sensitive strains determines whether an aggressive approach or moderate approach minimizes the burden of resistance in the population.

DOI:http://dx.doi.org/10.7554/eLife.10559.001

Antibiotics are chemical compounds used to treat bacterial infections. The discovery of antibiotics, starting with penicillin in 1929, revolutionized medicine, making it possible to cure or prevent life-threatening infections such as tetanus and pneumonia. However, many bacteria have become resistant to one or more antibiotics and so can no longer be killed by these drugs.

The emergence of antibiotic resistance reflects an evolutionary process that occurs during antibiotic treatment. While the antibiotic will kill most bacteria, some bacteria may naturally have a feature or genetic mutation that allows them to survive in the presence of the antibiotic. These bacteria then reproduce and pass on their resistant traits, eventually leading to the emergence of a new antibiotic-resistant strain of bacteria. Once a resistant strain exists it may be able to spread from one person to another.

There is conflicting evidence about how best to prevent antibiotic-resistant bacteria from evolving and spreading. The results of some experiments suggest that treating bacteria with large doses of antibiotics early in an infection is the most effective way to optimize treatment and minimize the risk of an antibiotic-resistant strain developing. However, other studies suggest that exposing bacteria to high levels of antibiotics more efficiently selects for resistance; in this case a more moderate approach should be used when treating bacterial infections.

Here, Colijn and Cohen present a mathematical model that suggests that the natural competition between the antibiotic-resistant and antibiotic-sensitive strains of bacteria influence which treatment strategy should be taken. Strains were modeled both within individual hosts and spreading in a community of individuals. In the models, aggressive antibiotic treatment is most effective (in that it minimizes antibiotic resistance) when the antibiotic-resistant strain either does not experience strong competition from the non-resistant strains of bacteria or is not fit enough to be a good competitor. However, a more moderate treatment is appropriate when the two strains are competing and the antibiotic-resistant strain is a fit competitor. Competition may mean that moderate treatment is best to avoid resistance at the community level, even in situations when aggressive treatment is likely best for individuals.

Two important future challenges are to better understand the diversity of strains in bacterial infections, and to develop tools to measure to what extent strains are effectively competing with each other.

DOI:http://dx.doi.org/10.7554/eLife.10559.002

Malaria Molecular Epidemiology: Lessons from the International Centers of Excellence for Malaria Research Network

Molecular epidemiology leverages genetic information to study the risk factors that affect the frequency and distribution of malaria cases. This article describes molecular epidemiologic investigations currently being carried out by the International Centers of Excellence for Malaria Research (ICEMR) network in a variety of malaria-endemic settings. First, we discuss various novel approaches to understand malaria incidence and gametocytemia, focusing on Plasmodium falciparum and Plasmodium vivax. Second, we describe and compare different parasite genotyping methods commonly used in malaria epidemiology and population genetics. Finally, we discuss potential applications of molecular epidemiological tools and methods toward malaria control and elimination efforts.

Modelling the effects of mass drug administration on the molecular epidemiology of schistosomes

As national governments scale up mass drug administration (MDA) programs aimed to combat neglected tropical diseases (NTDs), novel selection pressures on these parasites increase. To understand how parasite populations are affected by MDA and how to maximize the success of control programmes, it is imperative for epidemiological, molecular and mathematical modelling approaches to be combined. Modelling of parasite population genetic and genomic structure, particularly of the NTDs, has been limited through the availability of only a few molecular markers to date. The landscape of infectious disease research is being dramatically reshaped by next-generation sequencing technologies and our understanding of how repeated selective pressures are shaping parasite populations is radically altering. Genomics can provide high-resolution data on parasite population structure, and identify how loci may contribute to key phenotypes such as virulence and/or drug resistance. We discuss the incorporation of genetic and genomic data, focussing on the recently sequenced Schistosoma spp., into novel mathematical transmission models to inform our understanding of the impact of MDA and other control methods. We summarize what is known to date, the models that exist and how population genetics has given us an understanding of the effects of MDA on the parasites. We consider how genetic and genomic data have the potential to shape future research, highlighting key areas where data are lacking, and how future molecular epidemiology knowledge can aid understanding of transmission dynamics and the effects of MDA, ultimately informing public health policy makers of the best interventions for NTDs.