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Spatial epidemiology in sub-Saharan African wildlife: schistosomes of Cape Buffalo


Project Description

Animal distributions, including disease vectors and parasites, are influenced by environmental features, which can either facilitate or restrict their movement across the landscape. Local adaptation, dispersal behaviour and successful reproduction leaves a genomic footprint, allowing organisms to be tracked through space and time. Such data allow us to determine the drivers of disease emergence and spread, which can translate into more effective preventative and/or control measures to mitigate outbreaks. Schistosomiasis is neglected tropical disease of great medical and veterinary importance caused by a parasitic trematode. The parasites have a complex transmission cycle involving specific aquatic freshwater snails and a mammalian host Focusing on the Cape buffalo (Syncerus caffer caffer), a keystone species critical to the health of savannah grassland ecosystems, this studentship will involve fieldwork, species identification (snail and parasites) and landscape genomics to identify the drivers of schistosomiasis dynamics in the iconic Kruger National Park (KNP), South Africa.
This student will WP1) collect, identify and determine the distribution of Buffalo schistosome parasites within the Kruger National Park; WP2) identify and assess diversity of Bulinus snail intermediate hosts; WP3) assess the “genetic health and population structure of Cape buffalos and; WP4) correlate landscape variables with genetic diversity. To achieve these aims, WP1-2 will involve morphological identification and molecular metabarcoding. For WP3, the student will apply double-digest restriction-site associated DNA sequencing to obtain genome-wide SNP loci to resolve fine scale population structure in buffalo. WP4 will deploy a landscape genomics approach incorporating GIS resistance maps for each environmental variable. Using R statistical packages, resistance distance will be correlated with buffalo genetic distance in order to identify variables that are either positivity or negatively correlated with gene flow. Lastly, current maps will be generated in CIRCUITSCAPE to identify areas within the landscape of high and low connectivity that can inform disease spread and predictions of outbreaks. This project will provide a model for future landscape genomics of zoonotic disease vectors making a significant contribution to the field of molecular epidemiology.

References

Beechler BR et al. 2017. Host immunity, nutrition and coinfection alter longitudinal infection patterns of schistosomes in a free ranging African buffalo population. PLoS Neglected Tropical Diseases 11(12): e0006122. Biek R & Real LA. 2010. The landscape genetic of infectious disease emergence and spread. Molecular Ecology 19, 3515-3531. Caron A et al. 2016. African buffalo movement and zoonotic disease risk across transfrontier conservation areas, southern Africa. Emerging Infectious Diseases 22, 277-280. Hemming-Schroeder E et al. 2018. Landscape Genetics: a toolbox for studying vector-borne diseases. Frontiers in Ecology and Evolution 6:21. Hughes G et al. 2017. Modeling the spatial distribution of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa. PLoS ONE 12(9): e0182903. Ma T et al. 2018. Walking in a heterogeneous landscape: dispersal, gene-flow and conservation implications for the giant panda in the Qinling Mountains. Evolutionary Applications 00:1-14. Russo IM et al. 2016. Landscape determinants of fine-scale genetic structure of a small rodent in a heterogeneous landscape (Hluhluwe-iMfolozi Park, South Africa). Scientific Reports 6: 29168. Schwabl P et al. 2018. Prediction and prevention of parasitic diseases using a landscape genomics framework. Trends in Parasitology 33, 264-274.

How good is research at Cardiff University in Biological Sciences?

FTE Category A staff submitted: 54.70

Research output data provided by the Research Excellence Framework (REF)

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