Biology subjects

Day, K. P.

Publications and source records attributed to Day, K. P..

3 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↗

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↗