Exploring the global genetic diversity of P. falciparum Pf113 malaria vaccine candidate gene

Abstract

The malaria disease burden is still of great concern especially in sub-Saharan Africa among children below the age of 5 years. Evolution of the P. falciparum parasite in response to intervention measures as well as the high levels of polymorphism portrayed by target vaccine antigens has resulted in drug resistance and vaccine-variant specific immunity respectively. This points to a need for more effective intervention method. Research involving a more detailed understanding of the polymorphisms portrayed by potential vaccine candidates would be a great foundational step in the development of an effective malaria vaccine. Following a recent large epidemiological study involving over 10,000 samples from multiple regions of Africa a list of 10 top antigens that elicit protective antibodies against clinical malaria in the host, showed Pf113 among the top vaccine candidate antigens. We sought to perform diversity analysis on a highly immunogenic P. falciparum antigen, Pf113 which would help inform its potential use in malaria vaccine development. We performed SNP and haplotype calling on the Pf113 protein-coding gene PF3D7_1420700, intra and inter-population diversity analysis of parasite isolates from different malaria endemic countries as well as region-specific and global variant distribution patterns across the malaria endemic regions and countries respectively were determined. This study leveraged on data from the malariaGEN consortium which comprises of complete genome sequences from over 7000 P falciparum clinical isolates from 28 malaria-endemic countries. The vcf file was filtered for SNPs for the Pf3D7_1420700 gene based on its coordinates in the 3D7 genome. The R package vcfR was used to filter for SNPs based on depth and quality at defined thresholds and haplotype calling was performed using Beagle. Principal Component analysis was used to perform cluster diversity and phylogenetic analysis of the haplotypes and SNPs was performed using IQ-TREE. FST values were calculated to estimate population differentiation due to the genetic structure of the population. Tajima’s D was also calculated to evaluate region-specific and overall selection pressure in each parasite population. Inference of the haplotype networks and distribution by country was carried out using PopART which is a network analysis-based method. Majority of the alleles identified were minor alleles with most having allele frequencies below 0.5%. Phylogenetic analysis revealed both mixed and region-specific clades showing high levels of similarity between the Pf113 gene sequences from the different malaria endemic regions. Principal component analysis showed four major clusters with each containing SNPs from a mixture of regions. There were no distinct variations in the P.falciparum Pf113 gene across the different malaria endemic regions with some regions of the Pf113 gene having negative Tajima’s D values. There was no distinct region specific diversity detected in the P.falciparum Pf113 gene. This study further agreed with previous literature that there is low polymorphism within the Pf113 gene antigen making it a potentially strong candidate for malaria vaccine development.