HeALTH: An Automated Platform for Long-term Longitudinal Studies of Whole Organisms under Precise Environmental Control
| Autor: | Mei Zhan, Jason Wan, Kim N. Le, Dhaval S. Patel, Yongmin Cho, Hang Lu |
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| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
Computer science Process (engineering) ved/biology media_common.quotation_subject Control (management) ved/biology.organism_classification_rank.species Longevity Term (time) Variety (cybernetics) 03 medical and health sciences 0302 clinical medicine Risk analysis (engineering) Model organism 030217 neurology & neurosurgery 030304 developmental biology media_common |
| DOI: | 10.1101/863985 |
| Popis: | 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 organismCaenorhabditis 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 this constraint, we developed the Health and Lifespan Testing Hub (HeALTH), an automated, microfluidic-based system for robust, long-term, longitudinal behavioral monitoring. Our system provides spatiotemporal environmental control. We demonstrate health 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 forC. elegans, particularly for short- or long-term behavioral assays, and is also possible to be adapted for other model systems. |
| Databáze: | OpenAIRE |
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