Over the last two decades, aging studies have found that the evolutionarily conserved genes and signaling pathways could extend lifespans of many organisms. However, it is still unknown whether organisms are extending the healthy lifetime or simply prolonging a period of frailty with increased incidence of age-related diseases. The nematode Caenorhabditis elegans is an important model organism for the investigation of the aging process: first, the longevity of the worm population subject to different genetic or environmental regulations can be easily assessed over relatively short lifespans; second, C. elegans is capable of exhibiting complex behaviors that are relevant to functional metrics of human healthspan. The current experimental techniques for aging assays in the worm, however, have limitations, such as the inability to exert fine control over environmental conditions, longitudinal tracking of individuals, high experimental temporal resolution, and large-scale experimentation.
To address these limitations, we developed a scalable high-throughput automatic long-term individual tracking platform, integrated with microfluidics and hardware and software technologies; this platform offers the advantages of physical isolation of individual animals, high temporal resolution of behavior tracking, and highly controlled environmental conditions. This platform is composed of three major modules. The first module is the liquid worm culture system, which is comprised of both the microfluidic chip and the off-chip support system for food control and delivery. The second module is to control environmental temperature on chip. This platform can perform the simultaneous investigation of up to 32 independent microfluidic chips, each housing up to 60 worms. These chips can each be operated via independent food delivery paths that permit the investigation of different food conditions. Furthermore, up to 8 different temperature conditions can be used in this system. The third module enables automated experimental control by interfacing with the first two modules and automated data acquisition via camera control and state movement. We can automatically monitor both individual longevity and behavior information with sub-hourly experimental time resolution. Here, we show that this platform allows high-throughput high-content, long-term analysis of health outcomes in large number of animals, with individual resolution and extremely well controlled environmental conditions. We envision this tool to enable large-scale studies of how genes and environment affect aging and age-related diseases.