Geographic genetic profiling of human Plasmodium malaria

Malaria caused by Plasmodium falciparum kills about 600,000 people per year, and increased population mobility through international air travel carries further risks of re-introducing parasites to elimination areas and dispersing drug resistant parasites to new regions. A simple genetic marker that quickly and accurately identifies the geographic origin of infections would be a valuable tool for locating the source of outbreaks, and spotting the spread of drug resistant parasites from Asia into Africa. Genetic markers have proved extremely valuable in tracking and eradicating diseases, such as Polio. However, the previous candidates for malaria genetic barcodes have relied on identifying DNA markers found in the parasite nucleus, which shows too much genetic variation between individual parasites to be used accurately. Now, DNA sequences found outside the nucleus in organelles called the mitochondria and the apicoplast have been analysed. These are only inherited through maternal lines and therefore much more stable over generations than nuclear DNA sequences. The research outlined in this methodology proposal will create computational tools which will help to exploit use of mitochondria and the apicoplast sequences to create reliable genetic barcodes for tracking the geographical movement of malaria in an operational context.

Human malaria can be caused by one of 6 different Plasmodium species. We will develop genetic barcodes based on mitochondria and apicoplast sequences for each of the 6 species. We will develop new analytical approaches which can discriminate the different species even in mixed infections. We will also refine the exisiting barcoding methodology for discrimninating between infections originating from geographically distinct populations of the same species. Most crucially we will develop analytical software which can infer barcodes from complex mixed infections which are commonly found in malaria patients in many parts of the world.

We will create a publically available online resource to facilitate the widespread use of barcoding. It will be of practical use to malaria control agencies and research groups worldwide.

We propose to develop:
1. A library of apicoplast and mitochondrial genomic sequence variants across multiple human Plasmodium species P. falciparum, P. vivax, P. ovale curtisi, P. ovale wallikeri, P. malariae, and P. knowlesi using existing raw genomic sequence data generated by collaborating investigators with external funding.
2. A statistical algorithm to infer informative SNP haplotypes within and between species from complex mixed infections. The perfect linkage disequilibrium or "perfect phylogeny" across the co-inherited organelle SNPs leads to an opportunity to construct phylogenetic trees that represent the relationship between haplotypes. Crucially this allows modelling approaches to disaggregate complex mixed infections.
3. Prototype barcodes based on newly generated mt/apico sequences for Pv, Po, Pm, and Pk, in partnership with collaborators;
4. A proof of principle. In collaboration with overseas research colleagues who have raw genomic sequence data suspected to contain mixed species co-infection (e.g. P. falciparum + P. malariae in Kenya, P. falciparum+P. vivax in Thailand). Colleagues at the National Institute of Parasitic Diseases at the Chinese Center for Disease Control and Prevention in Shanghai, China are genotyping local and putative imported infections from archived bloodspot samples and we will reanalyse these using the published Pf barcoding methodology of 23 SNPs developed using a classification and regression tree (CART) algorithm (Preston et al Nature Communications in press).
5. An online resource, which summarises the library of mt/api genomic variants and barcode haplotypes, and facilitates the input of sequence data for the rapid identification of species and the potential geographic source of (imported) infections.

Malaria caused by Plasmodium falciparum kills about 600,000 people per year, and increased population mobility through international air travel carries further risks of re-introducing parasites to elimination areas and dispersing drug resistant parasites to new regions. A simple genetic marker that quickly and accurately identifies the geographic origin of infections would be a valuable tool for locating the source of outbreaks, and spotting the spread of drug resistant parasites from Asia into Africa. Genetic markers have proved extremely valuable in tracking and eradicating diseases, such as Polio. However, the previous candidates for malaria genetic barcodes have relied on identifying DNA markers found in the parasite nucleus, which shows too much genetic variation between individual parasites to be used accurately. DNA sequences found outside the nucleus in organelles called the mitochondria and the apicoplast are only inherited through maternal lines and therefore much more stable over generations than nuclear DNA sequences. The research outlined in this methodology proposal will create computational tools which will help to exploit use of mitochondria and the apicoplast sequences to create reliable genetic barcodes for tracking the geographical movement of malaria in an operational context. We aim to create an analytical framework which will support simple genetic barcoding for use by National Malaria Control Programmes who are engaged in malaria elimination. Other potential beneficiaries are all those engaged in malaria control and malaria treatment who's work will benefit from new knowledge about how malaria parasite populations are interconnected.