Plasmodium vivax genomics to inform malaria control
Professor Taane Clark at LSHTM
Professor Susana Campino at LSHTM
Plasmodium vivax is the most prevalent human malaria parasite, causing most of the cases occurring outside of sub-Saharan Africa. Malaria control measures designed for more deadly P. falciparum parasites are widely known to be less effective at tackling P. vivax infections, but new molecular tools can be informed by the analysis of whole genome sequence data. This project will involve the generation of whole genome sequencing data using cutting-edge portable technologies. Advanced bioinformatic and population genomic analysis tools will be applied to understand the population structure of global P. vivax, characterise local transmission dynamics, reveal loci under selective pressure due to drug resistance, and provide insights into the genetic diversity of P. vivax invasion genes and vaccine candidates. The resulting insights will inform the design of much needed new diagnostics and launch laboratory functional work to validate molecular mechanisms (e.g., for drug resistance).
Project Key Words
Malaria, genomics, portable sequencing, bioinformatics, big data, machine learning
MRC LID Themes
- Global Health = Yes
- Health Data Science = No
- Infectious Disease = Yes
- Translational and Implementation Research = Yes
MRC Core Skills
- Quantitative skills = Yes
- Interdisciplinary skills = Yes
- Whole organism physiology = No
Skills we expect a student to develop/acquire whilst pursuing this project
Bioinformatics, pathogen and vector genomics, Plasmodium genetics, statistical and population genetics, drug resistance biology, molecular biology, epidemiology
Which route/s is this project available for?
- 1+4 = No
- +4 = Yes
Is this project available for full-time study? Yes
Is this project available for part-time study? Yes
Particular prior educational requirements for a student undertaking this project
- LSHTM’s standard institutional eligibility criteria for doctoral study.
Other useful information
- Potential CASE conversion? = No
PROJECT IN MORE DETAIL
Scientific description of this research project
More than 1/3 of the global population are at risk of Plasmodium vivax malaria, due to the wide geographical range of this parasite species. Complications associated with P. vivax infections can lead to severe, life-threatening syndromes. Malaria control is difficult due to dormant liver stage parasites leading to relapses, a poor understanding of biological and genetic susceptibility mechanisms including for frontline chloroquine drugs, and incomplete characterisation of genes associated parasite invasion of host erythrocytes and immune escape, due to their extreme genetic diversity.
Whole genome sequencing (WGS) technologies (e.g., Oxford Nanopore MinION) and advanced population genomic analysis methods can describe the population structure of global P. vivax parasites, characterise local transmission dynamics, reveal loci under selective pressure due to drug resistance, and provide insights into the genetic diversity of invasion genes and vaccine candidates. In this project, we will generate WGS data from P. vivax DNA sourced across Asia and South America (n>1000), using the in-house MinION platform, and combine it with the LSHTM P. vivax WGS database (n>2,000).
Using the combined WGS and meta data, the project objectives will be, to:
(1) understand the P. vivax global population structure, and use machine learning and population genomic methods to identify key molecular markers for barcoding sub-populations and transmission;
(2) identify genomic regions associated with recent positive selection driven by drug resistance, as well as find loci under balancing selection that are potential vaccine candidates;
(3) de novo assemble highly variable gene families (e.g., vir genes) and understand their genetic diversity across geography.
In this project, the PhD student has hands-on opportunities to generate sequencing data, design new diagnostics (e.g., amplicon-based), participate in laboratory functional work to validate findings (e.g., for drug resistance mutations and mechanisms using CRISPR gene editing of an established P. knowlesi in vitro model), develop informatic tools to interpret and visualise data, and contribute to capacity building and strengthening activities with collaborators.
There are no major risks associated with the project. Most P. vivax DNA is in the LSHTM and sequence data will be generated prior to the start of the project. Bioinformatic pipelines are in place for the initial processing of raw data and its quality control. Further, our group has a history of students submitting their theses by publication, thereby ensuring that the PhD student is in a strong position to secure further funding after completion.
(Relevant preprints and/or open access articles)
- doi: 10.1038/s41467-021-23422-3
- DOI: 10.1016/j.lana.2022.100420
Additional information from the supervisory team
- The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.