A molecular epidemiological study of var gene diversity to characterize the reservoir of Plasmodium falciparum in humans in Africa

Abstract

Background: The reservoir of Plasmodium infection in humans has traditionally been defined by blood slide positivity. This study was designed to characterize the local reservoir of infection in relation to the diverse var genes that encode the major surface antigen of Plasmodium falciparum blood stages and underlie the parasite's ability to establish chronic infection and transmit from human to mosquito.

Methodology/principal findings: We investigated the molecular epidemiology of the var multigene family at local sites in Gabon, Senegal and Kenya which differ in parasite prevalence and transmission intensity. 1839 distinct var gene types were defined by sequencing DBLα domains in the three sites. Only 76 (4.1%) var types were found in more than one population indicating spatial heterogeneity in var types across the African continent. The majority of var types appeared only once in the population sample. Non-parametric statistical estimators predict in each population at minimum five to seven thousand distinct var types. Similar diversity of var types was seen in sites with different parasite prevalences.

Conclusions/significance: Var population genomics provides new insights into the epidemiology of P. falciparum in Africa where malaria has never been conquered. In particular, we have described the extensive reservoir of infection in local African sites and discovered a unique var population structure that can facilitate superinfection through minimal overlap in var repertoires among parasite genomes. Our findings show that var typing as a molecular surveillance system defines the extent of genetic complexity in the reservoir of infection to complement measures of malaria prevalence. The observed small scale spatial diversity of var genes suggests that var genetics could greatly inform current malaria mapping approaches and predict complex malaria population dynamics due to the import of var types to areas where no widespread pre-existing immunity in the population exists.

Figure 1. Clonal antigenic variation and parasite persistence.

Asexual P. falciparum parasitemia followed over time in a naturally infected Puerto Rican child. The parasitemia follows a pattern of recurrent peaks that decline in amplitude with time. The parasitemia in this child, believed to be a clone, lasted nearly 800 days. These successive peaks of parasitemia are consistent with antigenically distinct waves of parasitemia in P. falciparum infection believed to be mediated by PfEMP1 that allow for parasite persistence . The intra-host dynamics of parasitemia observed in semi-immune children and induced human infections are best explained by variant-specific immunity to PfEMP1 variants encoded by the var multigene family rather than by immunity to single-copy antigen genes. Figure composed using data from .

Figure 2. Diversity and sharing of var types among African and non-African populations.

A) Cumulative diversity curves for each of the five populations. These averaged curves plot the cumulative number of var types observed with successive sampling of var sequences. A well-sampled population will show a curve that levels off and approaches an asymptote, that would approximate the total number of types in the population. The curves from the three African populations (Bakoumba, Pikine, Kilifi) did not show evidence of leveling off, in contrast to the curves from Amele, Papua New Guinea or Porto Velho, Brazil . Sampling of the African populations has not yet begun to approach the limits of diversity. B) Sharing of var types among the three African population samples. Between 26 and 41 var types were shared among any two population samples; only 10 var types were found in all three populations. C) The majority of var types in each continent were not found in the other continents. Only 5 var types were found in all three continents. Samples from Bakoumba, Pikine, and Kilifi represent Africa, samples from Amele represent Asia-Pacific, and samples from Porto Velho represent the Americas.

Figure 3. Frequency distribution of var types in the five population samples. Bakoumba, Kilifi, Pikine, Amele, and Porto Velho.

In parenthesis next to each population is the number of isolates (n) sampled from the population. On the horizontal axis is the frequency class (in number of isolates) for each var type. The vertical axis depicts the number of var types found in each frequency class. For example, in the Kilifi dataset 622 var types were found in one isolate; 28 var types were each found in two isolates, etc. In the African populations, the overwhelming majority of var types were found in only one isolate. Differences in frequency distribution of var sequences were statistically significant by χ² analysis (p<0.0001) (Table S6).

Figure 4. Organization of var genes in Africa (Bakoumba, Kilifi, Pikine), PNG (Amele) and Brazil (Porto Velho).

Within each labeled population, columns represent individual parasite isolates, and the black boxes represent var genes found in that isolate. Black boxes at the top of Figure 4 represent rare var types (found only in one isolate). Black boxes in the lower portion of Figure 4 depict var types that were found in more than one isolate within a population. For var types found in more than one isolate, each row represents a distinct type within the population. The key at the bottom-left of Figure 4 depicts frequency (in number of isolates) with which a particular var type was found in the population sample. Var types found more frequently were placed towards the bottom of the figure. White space represents an unknown number of var types that were not sequenced. Note that the amount of whitespace is not associated with numbers of genes missing, but was necessary to demonstrate sharing among repertoires. There was greater sharing of var types among isolates in the non-African populations compared to the African populations. Among the African populations, there appears to be more var type sharing in the Bakoumba population.

Figure 5. Relationship between var richness estimates and malariometric indices.

For each population sampled, var richness estimated using the Chao1 equation is plotted against A) parasite prevalence and B) transmission as represented by entomological inoculation rate (EIR). We have used published parasite prevalence and EIR figures which are listed in Table 1. Where EIR has been reported as a range, we have plotted the midpoint of the range. The bars above and below each point represent the 95% confidence interval of the Chao1 estimate. Despite differences in transmission intensity and parasite prevalence, the local African populations all exhibited high estimates of var richness, roughly a log-order greater than the non-African populations.