Exploring pheromone recognition in ants: decoding odorant receptors and building an open-source tool for monitoring behavior

Communication between members of the same colony is critical for the success of any eusocial organism. Eusocial insects rely heavily on their olfactory systems to recognize nestmates, communicate reproductive status, and find food, among other behaviors. Specifically, cuticular hydrocarbons (CHC), which function as both a desiccation barrier and pheromone, play a key role in ant nest-mate communication. In the eusocial ponerine ant Harpegnathos saltator, odorant receptors (HsOrs) are divided between 23 subfamilies, each descended from a single protein in the most recent ancestor of all hymenoptera. Previous studies have characterized HsOrs in both the highly expanded 9-exon subfamily and across the other, less expanded, subfamilies, and found CHC sensitivity is present throughout the HsOr repertoire. Here, we present the functional characterization of 14 more HsOrs from less expanded subfamilies, which primarily showed sensitivity to a broad range of the hydrocarbon odorants tested. Several HsOrs were also sensitive to a CHC that plays a role in the H. saltator fertility signal, which only elicited a response in three previously characterized HsOrs. Together with previous HsOr characterization studies, this makes H. saltator the organism with the highest total number of characterized olfactory receptors, giving an in-depth understanding of the H. saltator olfactory system and insights into the evolution of chemical communication and social behavior in insects.

To follow up this work, observational studies will be performed investigate the behavioral implications of CHC recognition in H. saltator. However, direct observation can be time consuming and influence the organism through unintentional stimuli. Additionally, video capturing equipment can often be prohibitively expensive, difficult to modify to one's specific needs, and may come with unnecessary features. Rather than use suboptimal equipment, we developed PiSpy, a low-cost, automated video acquisition platform that uses a Raspberry Pi computer and camera to record video or images at specified time intervals or when externally triggered. All settings and controls, such as programmable light cycling, are accessible to users with no programming experience through an easy-to-use graphical user interface. Importantly, the entire PiSpy system can be assembled for less than $100 using laser-cut and 3D-printed components. We demonstrate the broad applications and flexibility of PiSpy across a range of model and non-model organisms. Designs, instructions, and code can be accessed through an online repository, where a global community of PiSpy users can also contribute their own unique customizations and help grow the community of open-source research solutions.