Using whole genome sequence data to develop molecular barcodes to profile Plasmodium malaria parasites

Malaria is an important disease caused by parasites of the Plasmodium genus. Whilst the
incidence of malaria has decreased in recent years, the burden still remains significant,
with approximately 212 million new cases of malaria in 2015. Imported malaria can
jeopardise disease control and elimination, and its prevalence is likely to increase due to
greater travel. When assessing whether a country has successfully eliminated malaria,
there is a need to distinguish imported cases from the cases transmitted locally. A
molecular barcode has been developed for P. falciparum parasites to predict the
geographical region of parasite origin, to high (>90%) accuracy. The barcode was
developed by investigating the genetic variation within two parasite organelles, the
mitochondrion and the apicoplast. These organelles are present within all Plasmodium
parasite species, and both contain specific sequences of DNA. There is regional genetic
diversity within these genomes, and this diversity can be used within the barcode to
predict the origin of the parasite.
The barcode developed could prove to be an important tool for malaria control, but there
are limitations, which if overcome would improve its performance. P. falciparum parasites
are the main cause of malaria-related deaths worldwide, however there are many other
human-infective Plasmodium species, including P. vivax, P. malariae, P. knowlesi, P.
ovale wallikeri and P. ovale curtisi. I propose to broaden the scope of the barcode by
including additional genetic markers to profile multiple Plasmodium species. In addition,
the previous barcode was developed using parasite samples from West Africa, East
Africa, Southeast Asia and a limited set of countries in South America and Oceania.
Therefore, I will aim to broaden the geographical scope of the barcode by inputting data
from currently underrepresented regions. The barcode was also less efficient at predicting
samples from East Africa which were occasionally mistaken for parasites from West
Africa, this is thought to be due to the high levels of genetic diversity within East African
Plasmodium parasites. I will address this issue by using more samples from East Africa to
appreciate the high levels of genetic diversity within this region.
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A further complication in disease control is the emergence of drug resistance to
Artemisinin Combination Therapy (ACT), which is the current first line of treatment for
uncomplicated P. falciparum malaria. Specific genetic regions known to be associated with
ACT resistance may be incorporated into the barcode to allow for the detection of drug
resistant parasites. Combined with the geographical information within the barcode, this
allows for tracking the spread of drug resistant parasites, which may aid as a revolutionary
tool for malaria control in the near future.
During the process of this project, strong bioinformatics skills will be gained to analyse
large sets of genetic sequence data, this will develop my quantitative skills, fitting in with
the 'Quantitative Skills for Large Data Sets' MRC research theme. Many Plasmodium
samples will be investigated for genetic diversity using whole genome sequencing; this will
train me within the field of genomics, enhancing my skills on whole organism physiology.
Finally, the aim of the project is to develop a platform known as a molecular barcode,
which can track the movement and spread of Plasmodium parasites globally. I will aim to
incorporate the barcode into a diagnostic tool that can be used in the evaluation of
complex malaria interventions and control programmes.