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)..

The following data sets were generated

Article and author information

Author details

  1. Andrew McKay

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9179-5018
  2. Emma K Costa

    Department of Neurology and Neurological Sciences, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jingxun Chen

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Chi-Kuo Hu

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Xiaoshan Chen

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Claire Nicole Bedbrook

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Rishad C Khondker

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Mike Thielvoldt

    Thielvoldt Engineering, Albany, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Param Priya Singh

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Tony Wyss-Coray

    Department of Neurology and Neurological Sciences, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5893-0831
  11. Anne Brunet

    Department of Genetics, Stanford University, Stanford, United States
    For correspondence
    abrunet1@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4608-6845

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.

Metrics

  • 2,457
    views

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Andrew McKay
  2. Emma K Costa
  3. Jingxun Chen
  4. Chi-Kuo Hu
  5. Xiaoshan Chen
  6. Claire Nicole Bedbrook
  7. Rishad C Khondker
  8. Mike Thielvoldt
  9. Param Priya Singh
  10. Tony Wyss-Coray
  11. Anne Brunet
(2022)
An automated feeding system for the African killifish reveals effects of dietary restriction on lifespan and allows scalable assessment of associative learning
eLife 11:e69008.
https://doi.org/10.7554/eLife.69008

Share this article

https://doi.org/10.7554/eLife.69008

Further reading

    1. Genetics and Genomics
    Yi Li, Long Gong ... Shangbang Gao
    Research Article

    Resistance to anthelmintics, particularly the macrocyclic lactone ivermectin (IVM), presents a substantial global challenge for parasite control. We found that the functional loss of an evolutionarily conserved E3 ubiquitin ligase, UBR-1, leads to IVM resistance in Caenorhabditis elegans. Multiple IVM-inhibiting activities, including viability, body size, pharyngeal pumping, and locomotion, were significantly ameliorated in various ubr-1 mutants. Interestingly, exogenous application of glutamate induces IVM resistance in wild-type animals. The sensitivity of all IVM-affected phenotypes of ubr-1 is restored by eliminating proteins associated with glutamate metabolism or signaling: GOT-1, a transaminase that converts aspartate to glutamate, and EAT-4, a vesicular glutamate transporter. We demonstrated that IVM-targeted GluCls (glutamate-gated chloride channels) are downregulated and that the IVM-mediated inhibition of serotonin-activated pharynx Ca2+ activity is diminished in ubr-1. Additionally, enhancing glutamate uptake in ubr-1 mutants through ceftriaxone completely restored their IVM sensitivity. Therefore, UBR-1 deficiency-mediated aberrant glutamate signaling leads to ivermectin resistance in C. elegans.

    1. Genetics and Genomics
    Minsoo Noh, Xiangguo Che ... Sihoon Lee
    Research Article

    Osteoporosis, characterized by reduced bone density and strength, increases fracture risk, pain, and limits mobility. Established therapies of parathyroid hormone (PTH) analogs effectively promote bone formation and reduce fractures in severe osteoporosis, but their use is limited by potential adverse effects. In the pursuit of safer osteoporosis treatments, we investigated R25CPTH, a PTH variant wherein the native arginine at position 25 is substituted by cysteine. These studies were prompted by our finding of high bone mineral density in a hypoparathyroidism patient with the R25C homozygous mutation, and we explored its effects on PTH type-1 receptor (PTH1R) signaling in cells and bone metabolism in mice. Our findings indicate that R25CPTH(1–84) forms dimers both intracellularly and extracellularly, and the synthetic dimeric peptide, R25CPTH(1–34), exhibits altered activity in PTH1R-mediated cyclic AMP (cAMP) response. Upon a single injection in mice, dimeric R25CPTH(1–34) induced acute calcemic and phosphaturic responses comparable to PTH(1–34). Furthermore, repeated daily injections increased calvarial bone thickness in intact mice and improved trabecular and cortical bone parameters in ovariectomized (OVX) mice, akin to PTH(1–34). The overall results reveal a capacity of a dimeric PTH peptide ligand to activate the PTH1R in vitro and in vivo as PTH, suggesting a potential path of therapeutic PTH analog development.