Characterization of a novel Plasmodium falciparum merozoite surface antigen and potential vaccine target

Introduction Detailed analyses of genetic diversity, antigenic variability, protein localization and immunological responses are vital for the prioritization of novel malaria vaccine candidates. Comprehensive approaches to determine the most appropriate antigen variants needed to provide broad protection are challenging and consequently rarely undertaken. Methods Here, we characterized PF3D7_1136200, which we named Asparagine-Rich Merozoite Antigen (ARMA) based on the analysis of its sequence, localization and immunogenicity. We analyzed IgG and IgM responses against the common variants of ARMA in independent prospective cohort studies in Burkina Faso (N = 228), Kenya (N = 252) and Mali (N = 195) using a custom microarray, Div-KILCHIP. Results We found a marked population structure between parasites from Africa and Asia. African isolates shared 34 common haplotypes, including a dominant pair although the overall selection pressure was directional (Tajima’s D = -2.57; Fu and Li’s F = -9.69; P < 0.02). ARMA was localized to the merozoite surface, IgG antibodies induced Fc-mediated degranulation of natural killer cells and strongly inhibited parasite growth in vitro. We found profound serological diversity, but IgG and IgM responses were highly correlated and a hierarchical clustering analysis identified only three major serogroups. Protective IgG and IgM antibodies appeared to target both cross-reactive and distinct epitopes across variants. However, combinations of IgG and IgM antibodies against selected variants were associated with complete protection against clinical episodes of malaria. Discussion Our systematic strategy exploits genomic data to deduce the handful of antigen variants with the strongest potential to induce broad protection and may be broadly applicable to other complex pathogens for which effective vaccines remain elusive.

37°C. After wash, the plate was incubated with diluted goat HRP-conjugated anti-rabbit IgG (1:2500, 50 μL/well) for 1 hour at 37°C. The rest of the experiment was performed as described above in antigen ELISA (Materials and Methods section).

Rabbit immunization
We generated recombinant proteins (V1, V2 and CD4) at Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme in Kilifi, Kenya and sent them to BioGenes GmbH company based in Berlin, Germany, to raise antibodies in rabbits using a custom 35-day immunization protocol. Two Zimmermann rabbits were immunized per protein. Rabbits were first bled on day 0 to obtain pre-immune sera before the first injection with 0.5 mg of protein.
On day 21, they received a boost with 0.25 mg of protein and were kept for two more weeks.
The final bleeding was performed on day 35 and the total IgG antibodies were isolated using protein A column.
Following an incubation at room temperature for 1 hour, the reactions were developed as described above in antigen ELISA.

Antibody-dependent respiratory burst assay
To isolate neutrophils, fresh blood (~60 mL) was mixed with Hanks buffered salt solution (HBSS, 1:1) and gently layered on top of Histopaque-1077 (Sigma-Aldrich) before centrifugation at 600 x g for 15 minutes. The peripheral blood mononuclear cells and plasma were removed and the cell pellets were resuspended in 5 mL of HBSS. The suspension was mixed with 3 % dextran in PBS (1:2) and incubated at room temperature for 1 hour. Thereafter, the supernatant was collected after decantation and centrifuged at 500 x g for 7 min at 4°C. The supernatant was discarded and the residual red blood cells in the pellet were lysed by adding cold 0.2 % NaCl for 30 seconds followed by neutralization with an equal volume of cold 1.6 % NaCl. The neutrophils that remained were resuspended in sterile 0.1 % BSA, 1 % D-glucose in HBSS to obtain to 1 x 10 17 /mL.

Quality control of protein microarray data
Although the normalization helps to correct for systematic variations in protein microarrays, producing quality raw data is key. To minimize technical and systematic errors, we took different quality control actions during the microarray design and processing including: i) the use of various types of control antibodies and sera, ii) the reduction of the number of sample batches, iii) random selection of samples from different sites to be used onto the same chips and, iv) limitation of the number of persons involved in sample processing and data extraction.  Figure 14). As expected, the test samples that included seronegative subjects, low and high responders spread out into both PHIS and naive control clusters. Altogether, the data structure denoted minimal technical variations in general. Only variations in antibody reactivities among high responders were systematically higher compared to low responders (Supplementary Figure   15). To deal with these common systematic variations in protein microarrays and batch effects while preserving biological differences between samples before statistical analyses, we normalized the data using combined ComBat and variance stabilizing normalization (vsn) methods (1-3). These normalization approaches could correct effectively for the systematic high variations in high responders (Supplementary Figure 16). Overall, the quality of the IgG and IgM responses was highly comparable.

Supplementary Figure 1. Selection pressure along the Pf3D7_1136200 gene in West and
Central Africa (N = 1,333) and South-East Asia (n = 984). Pi is the nucleotide diversity (π).
Tajima's D and Fu and Li's F are neutrality tests.