Evidence of strain structure in Plasmodium falciparum var gene repertoires in children from Gabon, West Africa

From multiplicity of infection to force of infection for sparsely sampled Plasmodium falciparum populations at high transmission

High multiplicity of infection or MOI, the number of genetically distinct parasite strains co-infecting a single human host, characterizes infectious diseases including falciparum malaria at high transmission. It accompanies high asymptomatic Plasmodium falciparum prevalence despite high exposure, creating a large transmission reservoir challenging intervention. High MOI and asymptomatic prevalence are enabled by immune evasion of the parasite achieved via vast antigenic diversity. Force of infection or FOI, the number of new infections acquired by an individual host over a given time interval, is the dynamic sister quantity of MOI, and a key epidemiological parameter for monitoring the impact of antimalarial interventions and assessing vaccine or drug efficacy in clinical trials. FOI remains difficult, expensive, and labor-intensive to accurately measure, especially in high-transmission regions, whether directly via cohort studies or indirectly via the fitting of epidemiological models to repeated cross-sectional surveys. We propose here the application of queuing theory to obtain FOI on the basis of MOI, in the form of either a two-moment approximation method or Little's law. We illustrate these methods with MOI estimates obtained under sparse sampling schemes with the recently proposed " v a r coding" method, based on sequences of the v a r multigene family encoding for the major variant surface antigen of the blood stage of malaria infection. The methods are evaluated with simulation output from a stochastic agent-based model, and are applied to an interrupted time-series study from Bongo District in northern Ghana before and immediately after a three-round transient indoor residual spraying (IRS) intervention. We incorporate into the sampling of the simulation output, limitations representative of those encountered in the collection of field data, including under-sampling of v a r genes, missing data, and usage of antimalarial drug treatment. We address these limitations in MOI estimates with a Bayesian framework and an imputation bootstrap approach. We demonstrate that both proposed methods give good and consistent FOI estimates across various simulated scenarios. Their application to the field surveys shows a pronounced reduction in annual FOI during intervention, of more than 70%. The proposed approach should be applicable to the many geographical locations where cohort or cross-sectional studies with regular and frequent sampling are lacking but single-time-point surveys under sparse sampling schemes are available, and for MOI estimates obtained in different ways. They should also be relevant to other pathogens of humans, wildlife and livestock whose immune evasion strategies are based on large antigenic variation resulting in high multiplicity of infection.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of antimalarial drug resistance

The establishment and spread of antimalarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Molecular markers for malaria genetic epidemiology: progress and pitfalls

Over recent years, progress in molecular markers for genotyping malaria parasites has enabled informative studies of epidemiology and transmission dynamics. Results have highlighted the value of these tools for surveillance to support malaria control and elimination strategies. There are many different types and panels of markers available for malaria parasite genotyping, and for end users, the nuances of these markers with respect to 'use case', resolution, and accuracy, are not well defined. This review clarifies issues surrounding different molecular markers and their application to malaria control and elimination. We describe available marker panels, use cases, implications for different transmission settings, limitations, access, cost, and data accuracy. The information provided can be used as a guide for molecular epidemiology and surveillance of malaria.

An immune memory-structured SIS epidemiological model for hyperdiverse pathogens

A hyperdiverse class of pathogens of humans and wildlife, including the malaria parasite Plasmodium falciparum, relies on multigene families to encode antigenic variation. As a result, high (asymptomatic) prevalence is observed despite high immunity in local populations under high-transmission settings. The vast diversity of "strains" and genes encoding this variation challenges the application of established models for the population dynamics of such infectious diseases. Agent-based models have been formulated to address theory on strain coexistence and structure, but their complexity can limit application to gain insights into population dynamics. Motivated by P. falciparum malaria, we develop an alternative formulation in the form of a structured susceptible-infected-susceptible population model in continuous time, where individuals are classified not only by age, as is standard, but also by the diversity of parasites they have been exposed to and retain in their specific immune memory. We analyze the population dynamics and bifurcation structure of this system of partial-differential equations, showing the existence of alternative steady states and an associated tipping point with transmission intensity. We attribute the critical transition to the positive feedback between parasite genetic diversity and force of infection. Basins of attraction show that intervention must drastically reduce diversity to prevent a rebound to high infection levels. Results emphasize the importance of explicitly considering pathogen diversity and associated specific immune memory in the population dynamics of hyperdiverse epidemiological systems. This statement is discussed in a more general context for ecological competition systems with hyperdiverse trait spaces.

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

Here we introduce a new endpoint "census population size" to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (M O I v a r ), based on the hyper-diversity of the v a r multigene family. We present a Bayesian approach to estimate M O I v a r from sequencing and counting the number of unique DBLα tags (or DBLα types) of v a r genes, and derive from it census population size by summation of M O I v a r in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in v a r diversity, M O I v a r , and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, v a r diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the v a r population genetic characteristics of a high-transmission system (high v a r diversity; low v a r repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Performance of SNP barcodes to determine genetic diversity and population structure of Plasmodium falciparum in Africa

Panels of informative biallelic single nucleotide polymorphisms (SNPs) have been proposed to be an economical method to fast-track the population genetic analysis of Plasmodium falciparum in malaria-endemic areas. Whilst used successfully in low-transmission areas where infections are monoclonal and highly related, we present the first study to evaluate the performance of these 24- and 96-SNP molecular barcodes in African countries, characterised by moderate-to-high transmission, where multiclonal infections are prevalent. For SNP barcodes it is generally recommended that the SNPs chosen i) are biallelic, ii) have a minor allele frequency greater than 0.10, and iii) are independently segregating, to minimise bias in the analysis of genetic diversity and population structure. Further, to be standardised and used in many population genetic studies, these barcodes should maintain characteristics i) to iii) across various iv) geographies and v) time points. Using haplotypes generated from the MalariaGEN P. falciparum Community Project version six database, we investigated the ability of these two barcodes to fulfil these criteria in moderate-to-high transmission African populations in 25 sites across 10 countries. Predominantly clinical infections were analysed, with 52.3% found to be multiclonal, generating high proportions of mixed-allele calls (MACs) per isolate thereby impeding haplotype construction. Of the 24- and 96-SNPs, loci were removed if they were not biallelic and had low minor allele frequencies in all study populations, resulting in 20- and 75-SNP barcodes respectively for downstream population genetics analysis. Both SNP barcodes had low expected heterozygosity estimates in these African settings and consequently biased analyses of similarity. Both minor and major allele frequencies were temporally unstable. These SNP barcodes were also shown to identify weak genetic differentiation across large geographic distances based on Mantel Test and DAPC. These results demonstrate that these SNP barcodes are vulnerable to ascertainment bias and as such cannot be used as a standardised approach for malaria surveillance in moderate-to-high transmission areas in Africa, where the greatest genomic diversity of P. falciparum exists at local, regional and country levels.

Comparison of molecular surveillance methods to assess changes in the population genetics of Plasmodium falciparum in high transmission

A major motivation for developing molecular methods for malaria surveillance is to measure the impact of control interventions on the population genetics of Plasmodium falciparum as a potential marker of progress towards elimination. Here we assess three established methods (i) single nucleotide polymorphism (SNP) barcoding (panel of 24-biallelic loci), (ii) microsatellite genotyping (panel of 12-multiallelic loci), and (iii) varcoding (fingerprinting var gene diversity, akin to microhaplotyping) to identify changes in parasite population genetics in response to a short-term indoor residual spraying (IRS) intervention. Typical of high seasonal transmission in Africa, multiclonal infections were found in 82.3% (median 3; range 1-18) and 57.8% (median 2; range 1-12) of asymptomatic individuals pre- and post-IRS, respectively, in Bongo District, Ghana. Since directly phasing multilocus haplotypes for population genetic analysis is not possible for biallelic SNPs and microsatellites, we chose ~200 low-complexity infections biased to single and double clone infections for analysis. Each genotyping method presented a different pattern of change in diversity and population structure as a consequence of variability in usable data and the relative polymorphism of the molecular markers (i.e., SNPs < microsatellites < var). Varcoding and microsatellite genotyping showed the overall failure of the IRS intervention to significantly change the population structure from pre-IRS characteristics (i.e., many diverse genomes of low genetic similarity). The 24-SNP barcode provided limited information for analysis, largely due to the biallelic nature of SNPs leading to a high proportion of double-allele calls and a view of more isolate relatedness compared to microsatellites and varcoding. Relative performance, suitability, and cost-effectiveness of the methods relevant to sample size and local malaria elimination in high-transmission endemic areas are discussed.

Molecular epidemiology of continued Plasmodium falciparum disease transmission after an outbreak in Ecuador

To better understand the factors underlying the continued incidence of clinical episodes of falciparum malaria in E-2025 countries targeting elimination, we characterized the molecular epidemiology of Plasmodium falciparum disease transmission after a clonal outbreak in Ecuador. Here we study disease transmission by documenting the diversity and population structure of the major variant surface antigen of the blood stages of P. falciparum encoded by the var multigene family. We used a high-resolution genotyping method, “varcoding”, involving targeted amplicon sequencing to fingerprint the DBLα encoding region of var genes to describe both antigenic var diversity and var repertoire similarity or relatedness in parasite isolates from clinical cases. We identified nine genetic varcodes in 58 P. falciparum isolates causing clinical disease in 2013-2015. Network analyses revealed that four of the varcodes were highly related to the outbreak varcode, with identification of possible diversification of the outbreak parasites by recombination as seen in three of those varcodes. The majority of clinical cases in Ecuador were associated with parasites with highly related or recombinant varcodes to the outbreak clone and due to local transmission rather than recent importation of parasites from other endemic countries. Sharing of types in Ecuadorian varcodes to those sampled in South American varcodes reflects historical parasite importation of some varcodes, especially from Colombia and Peru. Our findings highlight the translational application of varcoding for outbreak surveillance in epidemic/unstable malaria transmission, such as in E-2025 countries, and point to the need for surveillance of local reservoirs of infection in Ecuador to achieve the malaria elimination goal by 2025.

Unravelling var complexity: Relationship between DBLα types and var genes in Plasmodium falciparum

The enormous diversity and complexity of var genes that diversify rapidly by recombination has led to the exclusion of assembly of these genes from major genome initiatives (e.g., Pf6). A scalable solution in epidemiological surveillance of var genes is to use a small ‘tag’ region encoding the immunogenic DBLα domain as a marker to estimate var diversity. As var genes diversify by recombination, it is not clear the extent to which the same tag can appear in multiple var genes. This relationship between marker and gene has not been investigated in natural populations. Analyses of in vitro recombination within and between var genes have suggested that this relationship would not be exclusive. Using a dataset of publicly-available assembled var sequences, we test this hypothesis by studying DBLα-var relationships for four study sites in four countries: Pursat (Cambodia) and Mae Sot (Thailand), representing low malaria transmission, and Navrongo (Ghana) and Chikwawa (Malawi), representing high malaria transmission. In all study sites, DBLα-var relationships were shown to be predominantly 1-to-1, followed by a second largest proportion of 1-to-2 DBLα-var relationships. This finding indicates that DBLα tags can be used to estimate not just DBLα diversity but var gene diversity when applied in a local endemic area. Epidemiological applications of this result are discussed.

The mystery of persistent, asymptomatic Plasmodium falciparum infections

Plasmodium falciparum causes millions of malaria infections and hundreds of thousands of deaths annually. These parasites avoid the adaptive immune response by systematically cycling through a limited repertoire of variant surface antigens after which the number of circulating parasites drops to extremely low levels, coinciding with a loss of symptoms and eventual clearance of the infection. However, in regions with extended dry seasons or in individuals who no longer reside in endemic areas, asymptomatic infections have been observed to persist for many months or years, potentially serving as reservoirs for transmission. Recent work suggests the possibility that parasites can assume a state in which no variant surface antigens are expressed, thus rendering them virtually invisible to the immune system and enabling them to persist at low levels indefinitely.

Age-specific patterns of DBLα var diversity can explain why residents of high malaria transmission areas remain susceptible to Plasmodium falciparum blood stage infection throughout life

Immunity to Plasmodium falciparum is non-sterilising, thus individuals residing in malaria-endemic areas are at risk of infection throughout their lifetime. Here we seek to find a genomic epidemiological explanation for why residents of all ages harbour blood stage infections despite lifelong exposure to P. falciparum in areas of high transmission. We do this by exploring, for the first known time, the age-specific patterns of diversity of variant antigen encoding (var) genes in the reservoir of infection. Microscopic and submicroscopic P. falciparum infections were analysed at the end of the wet and dry seasons in 2012-2013 for a cohort of 1541 residents aged from 1 to 91 years in an area characterised by high seasonal malaria transmission in Ghana. By sequencing the near ubiquitous Duffy-binding-like alpha domain (DBLα) that encodes immunogenic domains, we defined var gene diversity in an estimated 1096 genomes detected in sequential wet and dry season sampling of this cohort. Unprecedented var (DBLα) diversity was observed in all ages with 42,399 unique var types detected. There was a high degree of maintenance of types between seasons (>40% seen more than once), with many of the same types, especially upsA, appearing multiple times in isolates from different individuals. Children and adolescents were found to be significant reservoirs of var DBLα diversity compared with adults. Var repertoires within individuals were highly variable, with children having more related var repertoires compared to adolescents and adults. Individuals of all ages harboured multiple genomes with var repertoires unrelated to those infecting other hosts. High turnover of parasites with diverse isolate var repertoires was also observed in all ages. These age-specific patterns are best explained by variant-specific immune selection. The observed level of var diversity for the population was then used to simulate the development of variant-specific immunity to the diverse var types under conservative assumptions. Simulations showed that the extent of observed var diversity with limited repertoire relatedness was sufficient to explain why adolescents and adults in this community remain susceptible to blood stage infection, even with multiple genomes.

An accurate method for identifying recent recombinants from unaligned sequences

Motivation

Recombination is a fundamental process in molecular evolution, and the identification of recombinant sequences is thus of major interest. However, current methods for detecting recombinants are primarily designed for aligned sequences. Thus they struggle with analyses of highly diverse genes, such as the var genes of the malaria parasite Plasmodium falciparum, which are known to diversify primarily through recombination.

Results

We introduce an algorithm to detect recent recombinant sequences from a dataset without a full multiple alignment. Our algorithm can handle thousands of gene-length sequences without the need for a reference panel. We demonstrate the accuracy of our algorithm through extensive numerical simulations; in particular, it maintains its effectiveness in the presence of insertions and deletions. We apply our algorithm to a dataset of 17,335 DBLα types in var genes from Ghana, observing that sequences belonging to the same ups group or domain subclass recombine amongst themselves more frequently, and that non-recombinant DBLα types are more conserved than recombinant ones.

Availability

Source code is freely available at https://github.com/qianfeng2/detREC_program.

Supplementary information

Supplementary data are available at Bioinformatics online.

A systematic review on genetic diversity of var gene DBL1α domain from different geographical regions in Plasmodium falciparum isolates

Background The major variant surface antigen (VSA) in Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) encoded by var gene family has an important role in cytoadhesion/sequestration and rosetting by adhesion of uninfected erythrocytes to infected erythrocytes leading to disease severity. DBL1α domain in the PfEMP-1, protein is crucial in the cytoadhesion phenomena in P. falciparum infections and this review aims to analyse the genetic diversity of DBL1α domain sequences in PfEMP-1 from different geographical regions globally. Methods All available DBL1α sequence data was reviewed by using the electronic database PubMed, ResearchGate, Google, Google scholar, MEDLINE with the following Keywords-Plasmodium falciparum", "var gene", "DBL1α", "field isolate", "diversity", "polymorphism", "Africa", "America", "Asia" and "Caribbean" from different geographical regions across the world. Results A total of 240 studies were identified initially but only 20 studies qualified for this systematic review. The overall ratio of distinct sequences DBL1α domain was 24.62/1167 the highest in African region (33.59/766 isolates) and lowest in South America (5.6/215 isolates). In the 18 included studies, the presence of distinct DBL1α sequences was the highest in Oceania 55.32% (1186/2144) followed by Africa (38.43%), Asia (22.45%) and South America (16.48%), though the sample size in Oceania was comparatively smaller to that of Africa and South America. Conclusion This review highlights the ratio and percentage of distinct sequences of DBL1α domain of var gene in different geographical regions giving an idea of the existing diversity prevalent in this potential vaccine target gene which may contribute to designing the preventive measures towards disease severity.

Frequency-Dependent Competition Between Strains Imparts Persistence to Perturbations in a Model of Plasmodium falciparum Malaria Transmission

In high-transmission endemic regions, local populations of Plasmodium falciparum exhibit vast diversity of the var genes encoding its major surface antigen, with each parasite comprising multiple copies from this diverse gene pool. This strategy to evade the immune system through large combinatorial antigenic diversity is common to other hyperdiverse pathogens. It underlies a series of fundamental epidemiological characteristics, including large reservoirs of transmission from high prevalence of asymptomatics and long-lasting infections. Previous theory has shown that negative frequency-dependent selection (NFDS) mediated by the acquisition of specific immunity by hosts structures the diversity of var gene repertoires, or strains, in a pattern of limiting similarity that is both non-random and non-neutral. A combination of stochastic agent-based models and network analyses has enabled the development and testing of theory in these complex adaptive systems, where assembly of local parasite diversity occurs under frequency-dependent selection and large pools of variation. We show here the application of these approaches to theory comparing the response of the malaria transmission system to intervention when strain diversity is assembled under (competition-based) selection vs. a form of neutrality, where immunity depends only on the number but not the genetic identity of previous infections. The transmission system is considerably more persistent under NFDS, exhibiting a lower extinction probability despite comparable prevalence during intervention. We explain this pattern on the basis of the structure of strain diversity, in particular the more pronounced fraction of highly dissimilar parasites. For simulations that survive intervention, prevalence under specific immunity is lower than under neutrality, because the recovery of diversity is considerably slower than that of prevalence and decreased var gene diversity reduces parasite transmission. A Principal Component Analysis of network features describing parasite similarity reveals that despite lower overall diversity, NFDS is quickly restored after intervention constraining strain structure and maintaining patterns of limiting similarity important to parasite persistence. Given the described enhanced persistence under perturbation, intervention efforts will likely require longer times than the usual practice to eliminate P. falciparum populations. We discuss implications of our findings and potential analogies for ecological communities with non-neutral assembly processes involving frequency-dependence.

Evolutionary analyses of the major variant surface antigen-encoding genes reveal population structure of Plasmodium falciparum within and between continents

Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.

An antigenic diversification threshold for falciparum malaria transmission at high endemicity

In malaria and several other important infectious diseases, high prevalence occurs concomitantly with incomplete immunity. This apparent paradox poses major challenges to malaria elimination in highly endemic regions, where asymptomatic Plasmodium falciparum infections are present across all age classes creating a large reservoir that maintains transmission. This reservoir is in turn enabled by extreme antigenic diversity of the parasite and turnover of new variants. We present here the concept of a threshold in local pathogen diversification that defines a sharp transition in transmission intensity below which new antigen-encoding genes generated by either recombination or migration cannot establish. Transmission still occurs below this threshold, but diversity of these genes can neither accumulate nor recover from interventions that further reduce it. An analytical expectation for this threshold is derived and compared to numerical results from a stochastic individual-based model of malaria transmission that incorporates the major antigen-encoding multigene family known as var. This threshold corresponds to an “innovation” number we call R_div; it is different from, and complementary to, the one defined by the classic basic reproductive number of infectious diseases, R₀, which does not readily is better apply under large and dynamic strain diversity. This new threshold concept can be exploited for effective malaria control and applied more broadly to other pathogens with large multilocus antigenic diversity.

The vast diversity of the falciparum malaria parasite, as seen by the immune system of hosts in high transmission regions, underlies both high prevalence of asymptomatic infections and partial protection to re-infection despite previous exposure. This large antigenic diversity of the parasite challenges control and elimination efforts. We propose a threshold quantity for antigenic innovation, we call R_div, measuring the potential of transmission to accumulate new antigenic variants over time. When R_div is pushed below one by reduced transmission intensity, new genes encoding this variation can no longer accumulate, resulting in a lower number of strains and facilitating further intervention. This innovation number can be applied to other infectious diseases with fast turnover of antigens, where large standing diversity similarly opposes successful intervention.

Host-Malaria Parasite Interactions and Impacts on Mutual Evolution

Malaria is the most deadly parasitic disease, affecting hundreds of millions of people worldwide. Malaria parasites have been associated with their hosts for millions of years. During the long history of host-parasite co-evolution, both parasites and hosts have applied pressure on each other through complex host-parasite molecular interactions. Whereas the hosts activate various immune mechanisms to remove parasites during an infection, the parasites attempt to evade host immunity by diversifying their genome and switching expression of targets of the host immune system. Human intervention to control the disease such as antimalarial drugs and vaccination can greatly alter parasite population dynamics and evolution, particularly the massive applications of antimalarial drugs in recent human history. Vaccination is likely the best method to prevent the disease; however, a partially protective vaccine may have unwanted consequences that require further investigation. Studies of host-parasite interactions and co-evolution will provide important information for designing safe and effective vaccines and for preventing drug resistance. In this essay, we will discuss some interesting molecules involved in host-parasite interactions, including important parasite antigens. We also discuss subjects relevant to drug and vaccine development and some approaches for studying host-parasite interactions.

Critical transitions in malaria transmission models are consistently generated by superinfection

The history of modelling vector-borne infections essentially begins with the papers by Ross on malaria. His models assume that the dynamics of malaria can most simply be characterized by two equations that describe the prevalence of malaria in the human and mosquito hosts. This structure has formed the central core of models for malaria and most other vector-borne diseases for the past century, with additions acknowledging important aetiological details. We partially add to this tradition by describing a malaria model that provides for vital dynamics in the vector and the possibility of super-infection in the human host: reinfection of asymptomatic hosts before they have cleared a prior infection. These key features of malaria aetiology create the potential for break points in the prevalence of infected hosts, sudden transitions that seem to characterize malaria's response to control in different locations. We show that this potential for critical transitions is a general and underappreciated feature of any model for vector-borne diseases with incomplete immunity, including the canonical Ross-McDonald model. Ignoring these details of the host's immune response to infection can potentially lead to serious misunderstanding in the interpretation of malaria distribution patterns and the design of control schemes for other vector-borne diseases. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Serologic responses to the PfEMP1 DBL-CIDR head structure may be a better indicator of malaria exposure than those to the DBL-α tag

BACKGROUND

Plasmodium falciparum erythrocyte membrane protein-1 (PfEMP1) antigens play a critical role in host immune evasion. Serologic responses to these antigens have been associated with protection from clinical malaria, suggesting that antibodies to PfEMP1 antigens may contribute to natural immunity. The first N-terminal constitutive domain in a PfEMP1 is the Duffy binding-like alpha (DBL-α) domain, which contains a 300 to 400 base pair region unique to each particular protein (the DBL-α "tag"). This DBL-α tag has been used as a marker of PfEMP1 diversity and serologic responses in malaria-exposed populations. In this study, using sera from a malaria-endemic region, responses to DBL-α tags were compared to responses to the corresponding entire DBL-α domain (or "parent" domain) coupled with the succeeding cysteine-rich interdomain region (CIDR).

METHODS

A protein microarray populated with DBL-α tags, the parent DBL-CIDR head structures, and downstream PfEMP1 protein fragments was probed with sera from Malian children (aged 1 to 6 years) and adults from the control arms of apical membrane antigen 1 (AMA1) vaccine clinical trials before and during a malaria transmission season. Serological responses to the DBL-α tag and the DBL-CIDR head structure were measured and compared in children and adults, and throughout the season.

RESULTS

Malian serologic responses to a PfEMP1's DBL-α tag region did not correlate with seasonal malaria exposure, or with responses to the parent DBL-CIDR head structure in either children or adults. Parent DBL-CIDR head structures were better indicators of malaria exposure.

CONCLUSIONS

Larger PfEMP1 domains may be better indicators of malaria exposure than short, variable PfEMP1 fragments such as DBL-α tags. PfEMP1 head structures that include conserved sequences appear particularly well suited for study as serologic predictors of malaria exposure.

Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum

In their competition for hosts, parasites with antigens that are novel to the host immune system will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For the causative agent of malaria, Plasmodium falciparum, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering in endemic regions. This undermines the definition of strains as specific, temporally persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within than between the modules and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is, in turn, associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.

A combination of computational modeling and empirical data reveals persistent strain structure despite vast antigenic diversity in the human malaria parasite Plasmodium falciparum, with potential consequences for the acquisition of immunity.

Bayes-optimal estimation of overlap between populations of fixed size

Measuring the overlap between two populations is, in principle, straightforward. Upon fully sampling both populations, the number of shared objects—species, taxonomical units, or gene variants, depending on the context—can be directly counted. In practice, however, only a fraction of each population’s objects are likely to be sampled due to stochastic data collection or sequencing techniques. Although methods exists for quantifying population overlap under subsampled conditions, their bias is well documented and the uncertainty of their estimates cannot be quantified. Here we derive and validate a method to rigorously estimate the population overlap from incomplete samples when the total number of objects, species, or genes in each population is known, a special case of the more general β-diversity problem that is particularly relevant in the ecology and genomic epidemiology of malaria. By solving a Bayesian inference problem, this method takes into account the rates of subsampling and produces unbiased and Bayes-optimal estimates of overlap. In addition, it provides a natural framework for computing the uncertainty of its estimates, and can be used prospectively in study planning by quantifying the tradeoff between sampling effort and uncertainty.

Understanding when two populations are composed of similar species is important for ecologists, epidemiologists, and population geneticists, and in principle it is easy: just sample the two populations, compare the sets of species identified in each, and count how many appear in both populations. In practice, however, this is difficult because sampling methods typically produce only a random subset of the total population, leaving current population overlap estimates biased. Knowing only the number of shared members between two of these partial population samples, this paper shows how we can nevertheless estimate the true overlap between the full populations, when those full populations’ sizes are known. Using Bayesian statistics, we can also compute credible intervals to produce error bars. We show that using this unbiased approach has a dramatic impact on the conclusions one might draw from previously published studies in the malaria literature, which used simple but biased methods. Because the method in this paper quantifies the tradeoff between sampling effort and uncertainty, we also show how to compute the number of samples required to ensure high-confidence results, which may be useful for planning future studies or budgeting lab reagents and time.

Identifying functional groups among the diverse, recombining antigenic var genes of the malaria parasite Plasmodium falciparum from a local community in Ghana

A challenge in studying diverse multi-copy gene families is deciphering distinct functional types within immense sequence variation. Functional changes can in some cases be tracked through the evolutionary history of a gene family; however phylogenetic approaches are not possible in cases where gene families diversify primarily by recombination. We take a network theoretical approach to functionally classify the highly recombining var antigenic gene family of the malaria parasite Plasmodium falciparum. We sample var DBLα sequence types from a local population in Ghana, and classify 9,276 of these variants into just 48 functional types. Our approach is to first decompose each sequence type into its constituent, recombining parts; we then use a stochastic block model to identify functional groups among the parts; finally, we classify the sequence types based on which functional groups they contain. This method for functional classification does not rely on an inferred phylogenetic history, nor does it rely on inferring function based on conserved sequence features. Instead, it infers functional similarity among recombining parts based on the sharing of similar co-occurrence interactions with other parts. This method can therefore group sequences that have undetectable sequence homology or even distinct origination. Describing these 48 var functional types allows us to simplify the antigenic diversity within our dataset by over two orders of magnitude. We consider how the var functional types are distributed in isolates, and find a nonrandom pattern reflecting that common var functional types are non-randomly distinct from one another in terms of their functional composition. The coarse-graining of var gene diversity into biologically meaningful functional groups has important implications for understanding the disease ecology and evolution of this system, as well as for designing effective epidemiological monitoring and intervention.

Networks of genetic similarity reveal non-neutral processes shape strain structure in Plasmodium falciparum

Pathogens compete for hosts through patterns of cross-protection conferred by immune responses to antigens. In Plasmodium falciparum malaria, the var multigene family encoding for the major blood-stage antigen PfEMP1 has evolved enormous genetic diversity through ectopic recombination and mutation. With 50-60 var genes per genome, it is unclear whether immune selection can act as a dominant force in structuring var repertoires of local populations. The combinatorial complexity of the var system remains beyond the reach of existing strain theory and previous evidence for non-random structure cannot demonstrate immune selection without comparison with neutral models. We develop two neutral models that encompass malaria epidemiology but exclude competitive interactions between parasites. These models, combined with networks of genetic similarity, reveal non-neutral strain structure in both simulated systems and an extensively sampled population in Ghana. The unique population structure we identify underlies the large transmission reservoir characteristic of highly endemic regions in Africa.

The Plasmodium falciparum transcriptome in severe malaria reveals altered expression of genes involved in important processes including surface antigen-encoding var genes

Within the human host, the malaria parasite Plasmodium falciparum is exposed to multiple selection pressures. The host environment changes dramatically in severe malaria, but the extent to which the parasite responds to-or is selected by-this environment remains unclear. From previous studies, the parasites that cause severe malaria appear to increase expression of a restricted but poorly defined subset of the PfEMP1 variant, surface antigens. PfEMP1s are major targets of protective immunity. Here, we used RNA sequencing (RNAseq) to analyse gene expression in 44 parasite isolates that caused severe and uncomplicated malaria in Papuan patients. The transcriptomes of 19 parasite isolates associated with severe malaria indicated that these parasites had decreased glycolysis without activation of compensatory pathways; altered chromatin structure and probably transcriptional regulation through decreased histone methylation; reduced surface expression of PfEMP1; and down-regulated expression of multiple chaperone proteins. Our RNAseq also identified novel associations between disease severity and PfEMP1 transcripts, domains, and smaller sequence segments and also confirmed all previously reported associations between expressed PfEMP1 sequences and severe disease. These findings will inform efforts to identify vaccine targets for severe malaria and also indicate how parasites adapt to-or are selected by-the host environment in severe malaria.

Signatures of competition and strain structure within the major blood-stage antigen of Plasmodium falciparum in a local community in Ghana

The concept of niche partitioning has received considerable theoretical attention at the interface of ecology and evolution of infectious diseases. Strain theory postulates that pathogen populations can be structured into distinct nonoverlapping strains by frequency-dependent selection in response to intraspecific competition for host immune space. The malaria parasite Plasmodium falciparum presents an opportunity to investigate this phenomenon in nature, under conditions of high recombination rate and extensive antigenic diversity. The parasite's major blood-stage antigen, Pf EMP1, is encoded by the hyperdiverse var genes. With a dataset that includes thousands of var DBLα sequence types sampled from asymptomatic cases within an area of high endemicity in Ghana, we address how var diversity is distributed within isolates and compare this to the distribution of microsatellite allelic diversity within isolates to test whether antigenic and neutral regions of the genome are structured differently. With respect to var DBLα sequence types, we find that on average isolates exhibit significantly lower overlap than expected randomly, but that there also exists frequent pairs of isolates that are highly related. Furthermore, the linkage network of var DBLα sequence types reveals a pattern of nonrandom modularity unique to these antigenic genes, and we find that modules of highly linked DBLα types are not explainable by neutral forces related to var recombination constraints, microsatellite diversity, sampling location, host age, or multiplicity of infection. These findings of reduced overlap and modularity among the var antigenic genes are consistent with a role for immune selection as proposed by strain theory. Identifying the evolutionary and ecological dynamics that are responsible for the nonrandom structure in P. falciparum antigenic diversity is important for designing effective intervention in endemic areas.

Cryptic Microheteroresistance Explains Mycobacterium tuberculosis Phenotypic Resistance

RATIONALE

Minority drug-resistant Mycobacterium tuberculosis subpopulations can be associated with phenotypic resistance but are poorly detected by Sanger sequencing or commercial molecular diagnostic assays.

OBJECTIVES

To determine the role of targeted next-generation sequencing in resolving these minor variant subpopulations.

METHODS

We used single molecule overlapping reads (SMOR), a targeted next-generation sequencing approach that dramatically reduces sequencing error, to analyze primary cultured isolates phenotypically resistant to rifampin, fluoroquinolones, or aminoglycosides, but for which Sanger sequencing found no resistance-associated variants (RAVs) within respective resistance-determining regions (study group). Isolates also underwent single-colony selection on antibiotic-containing agar, blinded to sequencing results. As a positive control, isolates with multiple colocalizing chromatogram peaks were also analyzed (control group).

MEASUREMENTS AND MAIN RESULTS

Among 61 primary culture isolates (25 study group and 36 control group), SMOR described 66 (49%) and 45 (33%) of 135 total heteroresistant RAVs at frequencies less than 5% and less than 1% of the total mycobacterial population, respectively. In the study group, SMOR detected minor resistant variant subpopulations in 80% (n = 20/25) of isolates with no Sanger-identified RAVs (median subpopulation size, 1.0%; interquartile range, 0.2-3.9%). Single-colony selection on drug-containing media corroborated SMOR results for 90% (n = 18/20) of RAV-containing specimens, and the absence of RAVs in 60% (n = 3/5) of isolates. Overall, Sanger sequencing was concordant with SMOR for 77% (n = 53/69) of macroheteroresistant (5-95% total population), but only 5% of microheteroresistant (<5%) subpopulations (n = 3/66) across both groups.

CONCLUSIONS

Cryptic minor variant mycobacterial subpopulations exist below the resolving capability of current drug susceptibility testing methodologies, and may explain an important proportion of false-negative resistance determinations.

Evolutionary structure of Plasmodium falciparum major variant surface antigen genes in South America: Implications for epidemic transmission and surveillance

Strong founder effects resulting from human migration out of Africa have led to geographic variation in single nucleotide polymorphisms (SNPs) and microsatellites (MS) of the malaria parasite, Plasmodium falciparum. This is particularly striking in South America where two major founder populations of P. falciparum have been identified that are presumed to have arisen from the transatlantic slave trade. Given the importance of the major variant surface antigen of the blood stages of P. falciparum as both a virulence factor and target of immunity, we decided to investigate the population genetics of the genes encoding “Plasmodium falciparum Erythrocyte Membrane Protein 1” (PfEMP1) among several countries in South America, in order to evaluate the transmission patterns of malaria in this continent. Deep sequencing of the DBLα domain of var genes from 128 P. falciparum isolates from five locations in South America was completed using a 454 high throughput sequencing protocol. Striking geographic variation in var DBLα sequences, similar to that seen for SNPs and MS markers, was observed. Colombia and French Guiana had distinct var DBLα sequences, whereas Peru and Venezuela showed an admixture. The importance of such geographic variation to herd immunity and malaria vaccination is discussed.

Population genomics of virulence genes of Plasmodium falciparum in clinical isolates from Uganda

Plasmodium falciparum causes a spectrum of malarial disease from asymptomatic to uncomplicated through to severe. Investigations of parasite virulence have associated the expression of distinct variants of the major surface antigen of the blood stages known as Pf EMP1 encoded by up to 60 var genes per genome. Looking at the population genomics of var genes in cases of uncomplicated malaria, we set out to determine if there was any evidence of a selective sweep of specific var genes or clonal epidemic structure related to the incidence of uncomplicated disease in children. By sequencing the conserved DBLα domain of var genes from six sentinel sites in Uganda we found that the parasites causing uncomplicated P. falciparum disease in children were highly diverse and that every child had a unique var DBLα repertoire. Despite extensive var DBLα diversity and minimal overlap between repertoires, specific DBLα types and groups were conserved at the population level across Uganda. This pattern was the same regardless of the geographic distance or malaria transmission intensity. These data lead us to propose that any parasite can cause uncomplicated malarial disease and that these diverse parasite repertoires are composed of both upsA and non-upsA var gene groups.