An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning
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...
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-11-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/69008 |
| _version_ | 1797978474453925888 |
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| author | Andrew McKay Emma K Costa Jingxun Chen Chi-Kuo Hu Xiaoshan Chen Claire N Bedbrook Rishad C Khondker Mike Thielvoldt Param Priya Singh Tony Wyss-Coray Anne Brunet |
| author_facet | Andrew McKay Emma K Costa Jingxun Chen Chi-Kuo Hu Xiaoshan Chen Claire N Bedbrook Rishad C Khondker Mike Thielvoldt Param Priya Singh Tony Wyss-Coray Anne Brunet |
| author_sort | Andrew McKay |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T05:23:33Z |
| format | Article |
| id | doaj.art-21efc0fc55a84b2998c5672deb075de3 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T05:23:33Z |
| publishDate | 2022-11-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-21efc0fc55a84b2998c5672deb075de32022-12-23T12:47:59ZengeLife Sciences Publications LtdeLife2050-084X2022-11-011110.7554/eLife.69008An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learningAndrew McKay0https://orcid.org/0000-0002-9179-5018Emma K Costa1https://orcid.org/0000-0002-9431-6852Jingxun Chen2https://orcid.org/0000-0001-7320-8652Chi-Kuo Hu3Xiaoshan Chen4Claire N Bedbrook5Rishad C Khondker6Mike Thielvoldt7Param Priya Singh8Tony Wyss-Coray9https://orcid.org/0000-0001-5893-0831Anne Brunet10https://orcid.org/0000-0002-4608-6845Department of Genetics, Stanford University, Stanford, United States; Biology Graduate Program, Stanford University, Stanford, United StatesDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, United States; Neurosciences Interdepartmental Program, Stanford University School of Medicine, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United States; Department of Bioengineering, Stanford University, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United StatesThielvoldt Engineering, Albany, United StatesDepartment of Genetics, Stanford University, Stanford, United StatesDepartment of Neurology and Neurological Sciences, Stanford University, Stanford, United States; Glenn Laboratories for the Biology of Aging, Stanford University, Stanford, United States; Wu Tsai Neurosciences Institute, Stanford University, Stanford, United StatesDepartment of Genetics, Stanford University, Stanford, United States; Glenn Laboratories for the Biology of Aging, Stanford University, Stanford, United States; Wu Tsai Neurosciences Institute, Stanford University, Stanford, United StatesThe 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.https://elifesciences.org/articles/69008Nothobranchius furzeriAfrican killifishturquoise killifishN. furzeri |
| spellingShingle | Andrew McKay Emma K Costa Jingxun Chen Chi-Kuo Hu Xiaoshan Chen Claire N Bedbrook Rishad C Khondker Mike Thielvoldt Param Priya Singh Tony Wyss-Coray Anne Brunet An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning eLife Nothobranchius furzeri African killifish turquoise killifish N. furzeri |
| title | An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| title_full | An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| title_fullStr | An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| title_full_unstemmed | An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| title_short | An automated feeding system for the African killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| title_sort | automated feeding system for the african killifish reveals the impact of diet on lifespan and allows scalable assessment of associative learning |
| topic | Nothobranchius furzeri African killifish turquoise killifish N. furzeri |
| url | https://elifesciences.org/articles/69008 |
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