title: Contrasting population structures of the genes encoding ten leading vaccine-candidate antigens of the human malaria parasite, Plasmodium falciparum.
abstract: The extensive diversity of Plasmodium falciparum antigens is a major obstacle to a broadly effective malaria vaccine but population genetics has rarely been used to guide vaccine design. We have completed a meta-population genetic analysis of the genes encoding ten leading P. falciparum vaccine antigens, including the pre-erythrocytic antigens csp, trap, lsa1 and glurp; the merozoite antigens eba175, ama1, msp's 1, 3 and 4, and the gametocyte antigen pfs48/45. A total of 4553 antigen sequences were assembled from published data and we estimated the range and distribution of diversity worldwide using traditional population genetics, Bayesian clustering and network analysis. Although a large number of distinct haplotypes were identified for each antigen, they were organized into a limited number of discrete subgroups. While the non-merozoite antigens showed geographically variable levels of diversity and geographic restriction of specific subgroups, the merozoite antigens had high levels of diversity globally, and a worldwide distribution of each subgroup. This shows that the diversity of the non-merozoite antigens is organized by physical or other location-specific barriers to gene flow and that of merozoite antigens by features intrinsic to all populations, one important possibility being the immune response of the human host. We also show that current malaria vaccine formulations are based upon low prevalence haplotypes from a single subgroup and thus may represent only a small proportion of the global parasite population. This study demonstrates significant contrasts in the population structure of P. falciparum vaccine candidates that are consistent with the merozoite antigens being under stronger balancing selection than non-merozoite antigens and suggesting that unique approaches to vaccine design will be required. The results of this study also provide a realistic framework for the diversity of these antigens to be incorporated into the design of next-generation malaria vaccines.
authors.affiliation: Centre for Population Health, Burnet Institute, Melbourne, Australia. alyssa.barry@burnet.edu.au
authors.forename: Alyssa E
authors.initials: AE
authors.lastname: Barry
authors.forename: Lee
authors.initials: L
authors.lastname: Schultz
authors.forename: Caroline O
authors.initials: CO
authors.lastname: Buckee
authors.forename: John C
authors.initials: JC
authors.lastname: Reeder
mesh_terms: D000818:Animals; D000953:Antigens, Protozoan / Q000235:genetics*; D001499:Bayes Theorem; D016000:Cluster Analysis; D051456:Gene Flow / Q000235:genetics; D017125:Genes, Protozoan / Q000235:genetics; D005828:Genetics, Population; D006239:Haplotypes; D006801:Humans; D017780:Malaria Vaccines / Q000235:genetics*; D016778:Malaria, Falciparum / Q000235:genetics / Q000469:parasitology*; D010271:Parasites / Q000235:genetics* / Q000276:immunology*; D010963:Plasmodium falciparum / Q000235:genetics* / Q000276:immunology*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011157:Population Dynamics; D015995:Prevalence
chemical_list: D000953:Antigens, Protozoan; D017780:Malaria Vaccines