This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply.
| Abstract | Arboviruses, such as dengue, Zika, yellow fever, and chikungunya currently pose a public health risk to ~3.9 billion people, with this number increasing due to environmental (climate) and economic (urbanisation) changes. Outbreaks of these arthropod-borne viruses have recently intensified around the World, with a striking increase in large and growing cities. Africa has been hit particularly hard by this surge in arbovirus infections, between 2013 and 2023, approximately 200,000 suspected cases, 90,000 confirmed cases, and 900 deaths from dengue alone were reported, primarily (80%) in West Africa. The increase in arbovirus transmission has created a major public health challenge in low and middle income countries that must be addressed. In 2022, the World Health Organisation launched the Global Arbovirus Initiative, defining six pillars to improve public health response, including strengthening vector control, monitoring risk and enhancing innovation. However, there are currently critical technology, data, and knowledge gaps severely limiting the progress in these areas. Our project addresses one of the critical gaps by building the world’s first arbovirus vector genomic data platform with an open, community driven, accessible, scalable and expandable resource of vector variation and associated detailed metadata. The Arbovirus Vector Genomics Surveillance Platform will enable comprehensive surveillance of arbovirus vector surveillance globally for the first time, elucidating factors affecting virus transmission. Beginning with the African of the primary dengue vector, Aedes aegypti, the resource will be built with the capability of expanding into other arbovirus vectors, ancestral forms and introduced species, wherever they are found. This will build upon analytical methods, tools and approaches for Anopheles previously developed by Dr Clarkson’s group in the Malaria Vector Genome Observatory (https://www.malariagen.net/vobs/). The first step in the project will be to build a baseline of tools to work with these large genome vector mosquito species (e.g. Aedes and Sabethes) at a scale required to meaningfully inform interventions, while also lowering the financial and technical entry barrier to work with the most comprehensive data set of arbovirus vector whole genome variation data from around the globe. By first integrating the 1,200 genomes sequenced as part of the 1,200 Aedes aegypti project, the project will create a foundational resource, designed in a modular fashion, such that it can scale to incorporate tens of thousands of additional Ae. aegypti mosquitoes, as well as adding other important arbovirus vector species (e.g. Sabethes, Culex). This integration will allow global analyses across disease-specific transmission vectors including dengue, zika, yellow fever, and chikungunya, key to providing the comprehensive perspective required to understand the drivers affecting arbovirus transmission. The PhD student will learn how to call various kinds of genetic variation from colony populations of Aedes mosquitoes, SNP, CNV, haplotypes, etc., that have been whole genome sequenced using different short-read technologies, then use these data to determine the most appropriate WGS platform for surveillance. They will design and implement “big data” bioinformatic pipelines to produce high-quality analysis-ready variation data from thousands of wild caught samples. The student will design and build cloud-native population genomic analysis software tools, and use these tools to gain new insights into the evolution of these important vectors, which will be communicated through publication and conferences. Laboratory work will involve the development of a gold standard arbovirus detection assay using ddPCR, followed by building the functionality to host and analyse data generated by the assay with wild caught samples on the cloud platform. |
| Where does this project lie in the translational pathway? | T1 - Basic Research |
| Methodological Aspects | Methodological aspects will include training in genomic data analysis, population genetics, cloud computing, programming (Python), statistical analysis, software development, evolutionary genetics of insecticide resistance. Also, laboratory techniques including DNA extraction and digital droplet qPCR. |
| Expected Outputs | The student will establish understanding and technical platforms required for public health Aedes genomic surveillance. They will co-create the world’s first arbovirus vector genomics platform, enabling discovery science and public health stakeholders to access and analyse whole genome data across 1000s of samples in the cloud, with just a laptop and internet connection. Owing to the novelty and topicality of the subject we expect that the student will generate high impact publications as well as producing actionable data for control of arbovirus-borne illness (e.g. dengue, Zika, yellow fever, chikungunya) worldwide, and talks at international conferences. |
| Training Opportunities | Additionally there would be an opportunity for an in-country placement with El Hadji Amadou Niang in Senegal, and the PhD student would be involved in design and delivery of outreach, partner support, and training materials. |
| Skills Required | Good command of written and spoken English. Highly numerate though other skills can be gained through the MRes year and during PhD. Programming and bioinformatics experience is required. Experience of working with stakeholders in low or middle income countries would be an advantage. |
| Subject Areas | Malaria & other Vector Borne Diseases |
| Key Publications associated with this project |
doi: 10.1038/nature24995 doi: 10.1101/gr.262790.120 doi: 10.1126/science.ads3732 doi: 10.1111/mec.15845 doi: 10.7554/eLife.83524 |