QUADRAT DTP: Biological control of mosquitoes: optimising the efficacy of native macroinvertebrate predators

Biological control of mosquitoes often fails and thus needs radical new approaches; here, we will harness variation in the predatory efficiencies of native invertebrate predators of mosquitoes. Behavioural, ecological and genetic techniques will be blended and the research operationalised locally and globally.

Mosquito borne diseases affect millions of humans and animals annually and may be exacerbated with climate change; hence, innovative new methods to reduce these impacts are imperative. The development of biocontrol using predators of mosquitoes to tackle disease transmission (eg malaria, West Nile virus) has typically used alien predators¹, often leading to deleterious impacts on non-target organisms/communities. Changing focus from vertebrate (eg fish) to invertebrate (eg 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 biocontrol². 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 predators³.

We will thus screen a range of native European and African invertebrates (eg beetles, shrimp, copepods) and proceed to test five core Hypotheses: 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). The deep RNA-Seq will guide gene expression-based quantitative trait locus (QTL) studies providing information on allele-specific expression (ASE) and RNA-isoform expression.

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, health professionals, farmers, vets, community groups) to disseminate ‘inoculation packs’ of native biocontrol agents; plus provide education packs of universally-interpretable (ie pictures and flow charts) information on use of control agents. Training and supervision in functional response experiments will be provided by Prof Dick (QUB) and Dr Cuthbert (QUB) 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.

Candidate Background: The successful candidate will have basic laboratory skills in the areas of ecology, behaviour and genetics. Experience of mosquito species in laboratory and field situations as well as training in bioinformatics would be desirable, but not essential.

More project details are available here: https://www.quadrat.ac.uk/quadrat-projects/

How to apply: https://www.quadrat.ac.uk/how-to-apply/