Biology subjects

Tiedje, K. E.

Publications and source records attributed to Tiedje, K. E..

6 recordsLinked to original sources

bioRxiv2023

A paradoxical population structure of var DBLα types in Africa

The var multigene family encodes the P. falciparum erythrocyte membrane protein 1 (PfEMP1), which is important in host-parasite interaction as a virulence factor and major surface antigen of the blood stages of the parasite, responsible for maintaining chronic infection. Whilst important in the biology of P. falciparum, these genes (50 to 60 genes per parasite genome) are routinely excluded from whole genome analyses due to their hyper-diversity, achieved primarily through recombination. The PfEMP1 head structure almost always consists of a DBL-CIDR tandem. Categorised into different groups (upsA, upsB, upsC), different head structures have been associated with different ligand-binding affinities and disease severities. We study how conserved individual DBL types are at the country, regional, and local scales in Sub-Saharan Africa. Using publicly-available sequence datasets and a novel ups classification algorithm, cUps, we performed an in silico exploration of DBL conservation through time and space in Africa. In all three ups groups, the population structure of DBL types in Africa consists of variants occurring at rare, low, moderate, and high frequencies. Non-rare variants were found to be temporally stable in a local area in endemic Ghana. When inspected across different geographical scales, we report different levels of conservation; while some DBL types were consistently found in high frequencies in multiple African countries, others were conserved only locally, signifying local preservation of specific types. Underlying this population pattern is the composition of DBL types within each isolate DBL repertoire, revealed to also consist of a mix of types found at rare, low, moderate, and high frequencies in the population. We further discuss the adaptive forces and balancing selection, including host genetic factors, potentially shaping the evolution and diversity of DBL types in Africa.

genetics↗

bioRxiv2022

Neutral vs. non-neutral genetic footprints of Plasmodium falciparum multiclonal infections

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. 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. Author SummaryDespite control and elimination efforts, malaria continues to be a serious public health threat especially in high-transmission regions. Molecular tools for evaluating these efforts include those seeking to estimate multiplicity (or complexity) of infection (MOI), the number of genetically distinct parasite strains co-infecting a host, a key epidemiological parameter. MOI estimation remains challenging in high-transmission regions where hosts typically carry multiple co-infections by Plasmodium falciparum. THE REAL McCOIL and the varcoding are two cost-effective methods relying on distinct parts of the parasite genome, those respectively under neutrality and selection. The more recent varcoding approach relies on the var multigene family encoding for the major blood-stage antigen and contributing to a complex immune evasion strategy of the parasite. We compare the performance of the two methods by simulating disease dynamics under different transmission intensities with a stochastic agent-based model tracking infection by different parasite genomes and immune memory in individual hosts, then sampling resulting infections to estimate MOI. Although THE REAL McCOIL provides reasonable estimates for low- and moderate-transmission, varcoding allows more robust estimates especially under high-transmission. Defining the most suitable approach to estimate MOI based on local transmission intensity is highly recommended for hyper-diverse pathogens such as malaria.

evolutionary biology↗

bioRxiv2020

Frequency-dependent competition between strains imparts resilience 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 (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 resilience 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 resilient 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 resulting resilience to perturbations, 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.

ecology↗

bioRxiv2018

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 host immunity will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For Plasmodium falciparum-the causative agent of malaria-in endemic regions, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering; 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.\n\nSignificanceMany pathogens, including the causative agent of malaria Plasmodium falciparum, use antigenic variation, obtained via recombination, as a strategy to evade the human immune system. The vast diversity and multiplicity of genes encoding antigenic variation in high transmission regions challenge the notion of the existence of distinct strains: temporally-persistent and specific combinations of genes relevant to epidemiology. We examine the role of human immune selection in generating such genetic population structure in the major blood-stage antigen of Plasmodium falciparum. We show, using simulated and empirical data, that immune selection generates and maintains modules of genomes with higher genetic similarity within, than between, these groups. Selection further promotes the persistence of these modules for much longer times than those of their constituent genomes. Simulations show that the temporal modular structure reduces the speed at which hosts acquire immunity to the parasite. We argue that in P. falciparum modules can be viewed as dynamic strains occupying different niches in human immune space; they are thus relevant to formulating transmission models that encompass the antigenic diversity of the parasite. Our analyses may prove useful to understand the interplay between temporal genetic structure and epidemiology in other pathogens of human and wildlife importance.

ecology↗

bioRxiv2017

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 to 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.

ecology↗

bioRxiv2017

Conservation of single amino-acid polymorphisms in Plasmodium falciparum erythrocyte membrane protein 1 and association with severe pathophysiology

Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) is a parasite protein encoded by a multigene family known as var. Expressed on the surface of infected red blood cells, PfEMP1 plays a central role in parasite virulence. The DBL domain of PfEMP1 contains short sequence motifs termed homology blocks. Variation within homology blocks, at the level of single amino-acid modifications, has not been considered before in association with severe disease. Here we identify a total of 2701 amino-acid polymorphisms within DBL homology blocks, the majority of which are shared between two geographically distant study populations in existing transcription data from Kenya and in a new genomic dataset sampled in Ghana. Parasitemia levels and the transcription levels of specific polymorphisms are as predictive of severe disease (AUC=0.83) and of the degree of rosetting (forecast skill SS=0.45) as the transcription of classic var groups. 11 newly categorized polymorphisms were strongly correlated with grpA var gene expression (SS=0.93) and a different set of 16 polymorphisms was associated with the H3 subset (SS=0.20). These associations provide the basis for a novel method of relating pathophysiology to parasite gene expression levels--one that, being site-specific, has more molecular detail than previous models based on var groups or homology blocks. This newly described variation influences disease outcome, and can help develop anti-malarial intervention strategies such as vaccines that target severe disease. Further replication of this analysis in geographically disparate populations and for larger sample sizes can help improve the identification of the molecular causes of severe disease.

genomics↗