An automated feeding system for the African killifish reveals effects of dietary restriction on lifespan and allows scalable assessment of associative learning
Abstract
The African turquoise killifish is an exciting new vertebrate model for aging studies. A significant challenge for any model organism is the 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 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 (but not in females) and impacts the transcriptomes of killifish livers in a sex-specific manner. Moreover, combining our automated feeding system with a video camera, we establish a quantitative associative learning assay to provide an integrative measure of cognitive performance for the killifish. 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 scalable manner previously impossible with traditional vertebrate model organisms.
Data availability
This study's data are included in the submitted manuscript and supporting files. Source data have been provided as a compressed directory of supporting tables that correspond to figures as indicated in figure legends. All the scripts for analyzing the RNA-seq datasets and the behavioral assay can be accessed on GitHub. RNA-seq data have been deposited in GEO (accession number: GSE216369)..
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An automated feeding system for the African killifish reveals effects of dietary restriction on lifespan and allows scalable assessment of associative learningGene Expression Omnibus (GEO), accession number: GSE216369.
Article and author information
Author details
Funding
Stanford Brain Rejuvenation Program
- Tony Wyss-Coray
- Anne Brunet
Stanford Graduate Fellowship
- Andrew McKay
Helen Hay Whitney Fellowship
- Claire Nicole Bedbrook
National Institutes of Health (RF1AG057334)
- Anne Brunet
National Institutes of Health (R01AG063418)
- Anne Brunet
Jane Coffin Childs Memorial Fund for Medical Research (61-1762)
- Jingxun Chen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animals were housed within the Stanford Research Animal Facility and treated in accordance with protocols approved by the Stanford Administrative Panel on Laboratory Animal Care (protocol # APLAC- 13645).
Copyright
© 2022, McKay et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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