About the Project
The development of biocontrol using predators of mosquitoes to tackle disease transmission (e.g. malaria, West Nile virus) has typically used alien predators(1), often leading to deleterious impacts on non-target organisms/communities. Changing focus from vertebrate (e.g. fish) to invertebrate (e.g. copepod) control agents brings advantages, as invertebrates are more abundant and tolerant of environmental extremes, and have greater reproduction and dispersal. Thus, small invertebrate predators have great potential for cheap, easy to manage and effective mosquito biocontrol(2). Specifically, we will harness variation in the predatory efficiency among individuals within populations of native predators, evidenced by variation in per capita feeding rates or ‘functional responses’ of such predators(3). We will thus screen a range of native European and African invertebrates (e.g. beetles, shrimp, copepods) and proceed to test five core hypotheses: Hypothesis 1 (H1): There is significant variation in predatory efficiency among otherwise morphologically identical individual predators within species/populations; Hypothesis 2 (H2): Highly efficient predators within populations maintain this high predatory efficiency over time; Hypothesis 3 (H3): Individuals showing high predatory efficiency produce offspring with the same predatory characteristics; Hypothesis 4 (H4): Individuals showing high predatory efficiency exhibit altered transcriptomic profiles and perturbation of key biological pathways; Hypothesis 5 (H5): Individuals with high predatory efficiency will have altered genomic loci that contribute to variation in expression levels of mRNA and modified proteins. With functional response analyses, we will quantify individual mosquito predator efficiencies (H1), test individual predator consistency over time (H2) and identify heritability of such traits in subsequent generations (H3). Transcriptomic differences will be assessed using RNAseq (H4) and correlation/deep machine learning approaches, for example, Logic Forest will investigate the relationship between the gene expression signatures and phenotypic measures linked to increased predator efficiency. The genomic impact will be assessed via high throughput RNA sequencing (H5). This methodology will allow us to exploit variation among individuals within populations, and identify those native species with the highest, and most consistently heritable, biocontrol potential. We will engage with local and global stakeholders (eg PHA, DAERA, AFBI, NGOs, CABI Kenya, health professionals, farmers, vets, community groups) to disseminate ‘inoculation packs’ of native biocontrol agents for use in drinking and other small anthropogenic water sources; plus provide education packs of universally-interpretable (i.e. pictures and flow charts) information on use of control agents in the locality.
Training and supervision in functional response experiments will be provided by Prof Dick (QUB) at Queen’s Marine Laboratory (QML) and computational biology and genomics by Prof Hardiman (QUB); Dr Bodey will train the student in measuring trait variation in species. The student will engage with European/Southern African partners and collaborate with Dr Archie Murchie (AFBI NI) and join existing QUADRAT students.
This research will be conducted in the UK and hopefully abroad when COVID restrictions allow.
More project details are available here: https://www.quadrat.ac.uk/projects/biological-control-of-mosquitoes-optimising-the-efficacy-of-native-macroinvertebrate-predators/
How to apply: https://www.quadrat.ac.uk/how-to-apply/
Note that applications should NOT be submitted directly to Queen’s.
Before applying please check full funding and eligibility information: View Website
2. Cuthbert, R.N., Callaghan, A., Sentis, A., Dalal, A. & Dick, J.T.A. (2020). Additive multiple predator effects can reduce mosquito populations. Ecological Entomology, 45: 243-250.
3. Alexander, M.E., Dick, J.T.A. & O'Connor, N.E. (2015). Predation in the marine intertidal amphipod Echinogammarus marinus Leach: implications of inter- and intra-individual variation. Journal of Experimental Marine Biology and Ecology, 462: 50-54.
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