Order within chaos: Harnessing Plasmodium falciparum var gene extreme polymorphism for malaria epidemiology

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.
Author summary Globalization has led to the spread of pathogens through increased human movement. Microbiologists track epidemics of these pathogens by cataloguing geographic diversity in the genes that encode for variant surface antigens (VSA). Here, we developed a computational approach to explore the evolution of specific DNA sequences of the major VSA gene of the human malaria parasite, Plasmodium falciparum. First, we tested the method by comparing DNA sequences of these genes from P. falciparum to those of Plasmodium species that infect chimpanzees and gorillas. We showed that it could distinguish DNA signatures specific to each species. Next, we asked whether our method could detect geographic signatures within these genes by analyzing a global collection of P. falciparum isolates from 23 locations in 10 countries. The important outcome of our work was the ability to identify geographic signatures specific to countries and continents that were consistent with the “out of Africa” origin of P. falciparum. We can now identify malaria parasites from countries within Africa, South America, and Asia/Oceania using a diverse region of VSA genes without having to sequence and assemble whole parasite genomes. This methodology has potential applications in malaria surveillance to track parasites as they move around the world.