An automated platform to monitor long-term behavior and healthspan in Caenorhabditis elegans under precise environmental control

• Type of Material: Article
• Authors: Kim N Le, Emory University; Mei Zhan, Emory University; Yongmin Cho, Georgia Institute of Technology; Jason Wan, Georgia Institute of Technology; Dhaval S Patel, Georgia Institute of Technology; Hang Lu, Georgia Institute of Technology
• Language: English
• Date: 2020-12-01
• Publisher: Emory University Libraries
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2020
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1038/s42003-020-1013-2
• Title of Journal or Parent Work: Communications Biology
• Volume: 3
• Issue: 1
• Start Page: 297
• End Page: 297
• Grant/Funding Information: This work was supported by NIH R01AG056436, NIH R01GM088333, R01AG035317, and NSF DGE-1650044.
• Keywords: Mutation; Animals; Behavior, Animal; Environmental Exposure; Aging; Automation; Microfluidics; Longevity; Models, Biological; Caenorhabditis elegans
• Research Categories: Engineering, Biomedical

Abstract

Health and longevity in all organisms are strongly influenced by the environment. To fully understand how environmental factors interact with genetic and stochastic factors to modulate the aging process, it is crucial to precisely control environmental conditions for long-term studies. In the commonly used model organism Caenorhabditis elegans, existing assays for healthspan and lifespan have inherent limitations, making it difficult to perform large-scale longitudinal aging studies under precise environmental control. To address these constraints, we developed the Health and Lifespan Testing Hub (HeALTH), an automated, microfluidic-based system for robust longitudinal behavioral monitoring. Our system provides long-term (i.e. entire lifespan) spatiotemporal environmental control. We demonstrate healthspan and lifespan studies under a variety of genetic and environmental perturbations while observing how individuality plays a role in the aging process. This system is generalizable beyond aging research, particularly for short- or long-term behavioral assays, and could be adapted for other model systems.