An automated feeding system for the African killifish reveals effects of dietary restriction on lifespan and allows scalable assessment of associative learning

Abstract

AbstractThe African turquoise killifish is an exciting new vertebrate model for aging studies. A significant challenge for any model organism is control over its diet in space and time. To address this challenge, we created an automated and networked fish feeding system. Our automated feeder is designed to be open-source, easily transferable, and built from widely available components. Compared to manual feeding, our automated system is highly precise and flexible. As a proof-of-concept for the feeding schedule flexibility of these automated feeders, we define a favorable regimen for growth and fertility for the African killifish and a dietary restriction regimen where both feeding time and quantity are reduced. We show that this dietary restriction regimen extends lifespan in males. Moreover, combining our automated feeding system with a video camera, we establish an associative learning assay for the killifish. This learning assay provides an integrative measure of cognitive decline during aging. The ability to precisely control food delivery in the killifish opens new areas to assess lifespan and cognitive behavior dynamics and to screen for dietary interventions and drugs in a high-throughput manner previously impossible with traditional vertebrate model organisms.