Last Updated: 20/02/2023
Defining the antigenic diversity of Plasmodium vivax apical membrane antigen to inform vaccine development
Objectives
To create a robust design for a potent vaccine against vivax malaria. This project will focus on a specific protein that is promising vaccine candidate for vivax malaria by defining the diversity of this candidate over numerous countries using sequence-based and immunological analyses, then categorise these different variants into major groups.
The World Health Organization (WHO) has recommended an increased focus on P. vivax in areas of high burden, such as the Greater Mekong Subregion. This project will contribute to the treatment and prevention of this burden via a rigorous vaccine-design strategy, based on immunisation with multiple alleles of PvAMA1, carefully selected to cover diversity. In order to ensure thorough coverage of the immunological diversity of PvAMA1, this project will firstly focus on understanding the current antigenic landscape and sequence diversity, in order to determine which alleles and serotypes are represented. The project will then determine how these different variants can be grouped into antigenically-related groups using samples from high-burden regions, informing the development of a robust vaccine.
Aim 1: Using available databases from the Malaria Atlas Project (MAP), MalariaGEN, and the Broad Institute, we will investigate the genomic diversity of PvAMA1 in countries with a high burden of P. vivax. Our team members have previously developed MAP as a comprehensive resource to identify trends in malaria endemicity in geographic locations. Our detailed data will allow us to dissect geographic P. vivax trends over time, allowing identification of specific countries of interest, matched with analysis of common circulating alleles. We recently defined the diversity of genes encoding leading vaccine candidates in P. falciparum. We have begun applying a similar methodology to P. vivax antigens, and this project will shift the focus to PvAMA1 specifically as a model vaccine antigen. We will identify key alleles, connecting them to population diversity and structure, and map genetic variation and immune selection (Tajima’s D) on residues surface-exposed on the protein structure. We are currently sequencing samples from paired asymptomatic and clinical infections from two PNG longitudinal cohorts, and will measure allelic turnover to generate a model of major PvAMA1 serotype groups.
Aim 2: We will utilise these predicted major serotype groups to test antigenic diversity using invitro immunologic assays. Our previous results suggest that antigenic diversity can be more limited than expected from in-silico sequence analysis . Based on Aim 1, we will select alleles within the same and different putative serotype groups, and test these for serological coverage using competition ELISA. We will design and express recombinant PvAMA1 alleles using a reliable platform that we have recently established. We will then assay for reactivity against a panel of serum samples including those from PNG, Myanmar, Laos, Cambodia, and Thailand. This will allow us to measure confidence in our predictions from Aim 1, as well as how well the data from each country predicts interactions in a broader international context. These correlations will be fed back into the models from Aim 1, to increase the accuracy of our computational predictors.
Aim 3: Using data from Aim 1 and 2, we will model vaccine designs that will give coverage of predominant serotypes to provide maximum impact. We will assess each permutation, and determine which combination is most effective, while attempting to minimise the number of alleles required for vaccination. This will lead to an efficient and economic multivalent vaccine that will have effective coverage in high-burden countries. In the future, we will utilise data from MAP to inform effective vaccine optimisation and deployment. Further funding in the future will allow us to estimate the potential impact of P. vivax vaccines in populations with the highest vivax burden, by creating models based on different levels of vaccine efficacy. This will help elucidate the target vaccine efficacy level, to inform robust vaccine development.
Jun 2022 — Oct 2023
$15,000
