Forgebee, LLC — Department of Agriculture SBIR Phase I: 8.13

Description

Project SummaryTitle: An automated system for honey bee husbandry that enables high-throughput biologicalassaysPD/PI: Dr. Adam Hamiton; ForgeBeeSubaward PD/PI: Dr. Gene Robinson; University of Illinois at Urbana ChampaignHoney bees are crucial for agriculture and serve as a model system for insect pollinatorecotoxicology. At the heart of a honey bee colony's health and productivity is a set of complexinteractions among the workers and the queen determining egg production and the health of thequeen's offspring. The bee health crisis demands that researchers be able to study these interactionsand how they are influenced by nutrition pathogens parasites and pesticides. However progressin these areas has been stymied by the expensive time-consuming and seasonal nature oftraditional apiculture and experimental techniques. Similar limitations also impact the screeningof pesticides and other bioactive compounds on honey bee development creating a severebottleneck for agrochemical businesses seeking to create pollinator safe pesticides.We have developed the Queen Monitoring Cage (QMC) a published and patent- pending system for maintaining and monitoring queen honey bees in the lab. This systemallows for dozens or even hundreds of queens (each with a small retinue of 50-200 workers) to behoused in a single incubator or similar enclosure and easily observed for health and egg layingbehavior. Eggs can be assayed via a removable plate system permitting researchers to quantifythe impact of environmental factors on queen egg laying a process that would normally requirethe use of dozens of field colonies. QMCs also allow for eggs to be harvested year-round from ahighly controlled environment for downstream applications such as studies on honey beedevelopment or larval toxicology screening. The system thus has promise to facilitate basic andapplied research in the academic government and industrial sectors.In Phase 1 we will 1) create a machine vision algorithm for the automated identificationand assessment of eggs in egg laying plates 2) adapt the QMC system to existing techniques forthe automated tracking of behaviors (including the exchange of food with the queen) and 3) createa semi-autonomous QMC thereby drastically decreasing maintenance time. These advances willdrastically increase the throughput and scalability of the QMC system while enabling researchersto track mortality and egg laying linked to the flow of nutrients pathogens and otherenvironmental factors through the worker bees and to the queen. We will optimize and rigorouslytest each component of this system to ensure it is robust reliable and highly effective.Once commercialized the QMC system will provide end-users with a series of cost- effective and high throughput solutions to increase the scale of queen and larval research byorders of magnitude while enabling entirely novel experimental paradigms. The availability of thistechnology will therefore have dramatic ramifications for the long-term health of honey bees andother insect pollinators. By facilitating research into how nutrition pathogens parasitespesticides and other factors impact queen honey bee health and fecundity and larval survivaland development this system will help address priorities Strategic Goals 2 and 4 of theUSDA's 2022-2026 Strategic Plan as well as goals in all of the five subject areas of the 2022USDA Annual Strategic Pollinator Priorities and Goals Report.