EASTBIO Finding water in a dry world: hygrosensation in the flour beetle Tribolium

Flour beetles (Tribolium spp.) are devastating agricultural pests of dry store grain products. They cause up to 19% loss of these commodities, mainly in the global south. From a neuroethological perspective, these animals are fascinating as they have evolved adaptations to live in extremely arid stored grain. Beetle larvae navigate through dry substrates where fine discrimination of humidity can mean the difference between life and death. Surprisingly, we know relatively little about how hygrosensation works in these animals. This project will address this gap. First we will deploy deep-learning based tools for tracking animal movements to develop behavioural assays for assessing hygrosensation abilities in larval Tribolium. Next we will use RNAi knockdown experiments and surgical manipulations to determine the roles(s) that external and internal organs and gene products play in sculpting navigation along humidity gradients. Finally we will use a combination of electrophysiology and calcium imaging, and potentially optogenetics to explore the how sensory information is translated into adaptive movement in the context of navigation through an arid world.
Overall, this work will address a critical gap in knowledge about neuroethology of an animal that directly impacts food security. The supervisor has extensive experience studying genetics, integrative physiology, and neuroethology in insects. The PhD student will take an integrative approach to studying the hygrosensation in Tribolium and will have an opportunity to train and work at both St Andrews and Edinburgh.
This CASE studentship will be supported by Cairn Research Ltd, a manufacturer of imaging equipment and creator of open-source hardware and software. Working with Cairn will enable us to develop inexpensive imaging and microscopy methods for studying Tribolium that can be deployed to the developing world where the impacts of grain pests are acute and particularly devastating