A high throughput imaging and classification system for fruit flies

PROJECT SUMMARY ABSTRACT In this Phase I SBIR application FlySorter proposes to development a high throughput imaging and classification system to aid research with fruit flies a widely used model organism relevant to both basic science as well as studies in human health The use of animal model systems is essential for research in almost all aspects of biology genetics development neuroscience disease physiology and beyond The fruit fly Drosophila melanogaster is small and easy to care for but is complex enough an organism to provide a wealth of information that directly relates to human biology and health Over of human diseases with a genetic basis including depression alcoholism certain forms of cancer and many more are either present or have an analog in Drosophila Modern genetic tools such as CRISPR cas allow the creation of transgenic flies that provide the opportunity to study diseases pathways and systems that don t exist naturally in Drosophila With these advances fruit flies are becoming more frequently subjects for drugs screens For all the advances in the biological tools and techniques applicable to flies however the limiting factor in many experiments is the manual labor involved in a few common tasks moving flies from vial to vial or other lab equipment classifying and sorting flies by sex eye color and other phenotypes and collecting virgin female flies before they mate so that they can be used in controlled crosses etc FlySorter s patent pending fly dispensing mechanism can reliably deliver a single organism from a vial containing hundreds of awake flies and our novel FlyPlate system allows storage of individual flies in custom well plates FlySorter s robotic fly handling system co developed with the de Bivort Lab at Harvard is capable of manipulating and transporting those individual flies between vial well plate and experimental apparatus The next piece of the automation puzzle to solve is high throughput imaging and classification To accomplish this goal FlySorter will complete a prototype automated image capture hardware system adapt state of the art computer vision and machine learning algorithms for use on Drosophila and build a module that can physically sort the classified flies into different vials Once integrated into the existing FlySorter product ecosystem this imaging and classification module will greatly expand the kinds of experiments and screens that can be automated allowing for the study of larger populations or a wider variety of flies reducing the impact of human error and freeing up valuable time for researchers PROJECT NARRATIVE Fruit flies Drosophila melanogaster are one of the most widely used model organisms in biology for research in genetics development neuroscience disease and much more One of the most common tasks in Drosophila labs is sorting flies by various markers and phenotypes using a microscope and paintbrush FlySorter aims to build an automated system for sorting flies using high resolution digital cameras and modern computer vision algorithms which will obviate the need for such tedious manual labor