Dataset Information

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

ABSTRACT: 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.

SUBMITTER: He Q

PROVIDER: S-EPMC5940794 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

He Qixin Q Pilosof Shai S Tiedje Kathryn E KE Ruybal-Pesántez Shazia S Artzy-Randrup Yael Y Baskerville Edward B EB Day Karen P KP Pascual Mercedes M

Nature communications 20180508 1

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 ...[more]

PMID: 29739937

Similar Datasets

Project description:Efforts to control malignant malaria caused by Plasmodium falciparum are hampered by the parasite's acquisition of resistance to antimalarial drugs, e.g., chloroquine. This necessitates evaluating the spread of chloroquine resistance in any malaria-endemic area. India displays highly variable malaria epidemiology and also shares porous international borders with malaria-endemic Southeast Asian countries having multi-drug resistant malaria. Malaria epidemiology in India is believed to be affected by two major factors: high genetic diversity and evolving drug resistance in P. falciparum. How transmission intensity of malaria can influence the genetic structure of chloroquine-resistant P. falciparum population in India is unknown. Here, genetic diversity within and among P. falciparum populations is analyzed with respect to their prevalence and chloroquine resistance observed in 13 different locations in India. Microsatellites developed for P. falciparum, including three putatively neutral and seven microsatellites thought to be under a hitchhiking effect due to chloroquine selection were used. Genetic hitchhiking is observed in five of seven microsatellites flanking the gene responsible for chloroquine resistance. Genetic admixture analysis and F-statistics detected genetically distinct groups in accordance with transmission intensity of different locations and the probable use of chloroquine. A large genetic break between the chloroquine-resistant parasite of the Northeast-East-Island group and Southwest group (FST=0.253, P<0.001) suggests a long period of isolation or a possibility of different origin between them. A pattern of significant isolation by distance was observed in low transmission areas (r=0.49, P=0.003, N=83, Mantel test). An unanticipated pattern of spread of hitchhiking suggests genetic structure for Indian P. falciparum population. Overall, the study suggests that transmission intensity can be an efficient driver for genetic differentiation at both neutral and adaptive loci across India.

Project description:At a time when effective tools for monitoring malaria control and eradication efforts are crucial, the increasing availability of molecular data motivates their application to epidemiology. The multiplicity of infection (MOI), defined as the number of genetically distinct parasite strains co-infecting a host, is one key epidemiological parameter for evaluating malaria interventions. Estimating MOI remains a challenge for high-transmission settings where individuals typically carry multiple co-occurring infections. Several quantitative approaches have been developed to estimate MOI, including two cost-effective ones relying on molecular data: i) THE REAL McCOIL method is based on putatively neutral single nucleotide polymorphism loci, and ii) the varcoding method is a fingerprinting approach that relies on the diversity and limited repertoire overlap of the var multigene family encoding the major Plasmodium falciparum blood-stage antigen PfEMP1 and is therefore under selection. In this study, we assess the robustness of the MOI estimates generated with these two approaches by simulating P. falciparum malaria dynamics under three transmission conditions using an extension of a previously developed stochastic agent-based model. We demonstrate that these approaches are complementary and best considered across distinct transmission intensities. While varcoding can underestimate MOI, it allows robust estimation, especially under high transmission where repertoire overlap is extremely limited from frequency-dependent selection. In contrast, THE REAL McCOIL often considerably overestimates MOI, but still provides reasonable estimates for low and moderate transmission. Regardless of transmission intensity, results for THE REAL McCOIL indicate that an inaccurate tail at high MOI values is generated, and that at high transmission, an apparently reasonable estimated MOI distribution can arise from some degree of compensation between overestimation and underestimation. As many countries pursue malaria elimination targets, defining the most suitable approach to estimate MOI based on sample size and local transmission intensity is highly recommended for monitoring the impact of intervention programs.

Project description: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.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets