Automated microfluidic platforms for high-throughput in vivo functional imaging and individualized long-term health and longevity tracking of C. elegans

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Cho, YongMin
Lu, Hang
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One of big questions in neuroscience is how animals modulate behavior in response to external stimuli and environmental cues, and how this changes with age. Over the last few decades, many molecules and signaling pathways involved in sensory transduction in the nervous system, as well as a diverse array of genetic and environmental modulators of the aging process have been found to be conserved between humans and many model organisms. Due to its relative simple nervous system and short lifespan, Caenorhabditis elegans is an important model organism for the study of sensory perception and aging. This thesis explores the use of microfluidic techniques in conjunction with automation technology, and its application to the functional neural imaging and longitudinal imaging of C. elegans. Mechanosensation is an important sensory modality, relevant to hearing, touch, and balance in human and other animals. However, an extensive understanding of how animals encode mechanical stimuli through their nervous system is still lacking. In the first and second aims, I developed a series of automated microfluidic systems for high-throughput in vivo functional imaging of C. elegans from larvae to adults for the study of mechanotrandsuction. Compared to previously described assay systems, these microsystems greatly improve experimental throughput and operational robustness. As a result of these technological advances, I tested a variety of neuronal responses in mechanosensory circuits to highly-controlled mechanical stimuli across stages of development and various physiological stages, including sleep-like states. I also demonstrated the ability to perform a drug screen based on neuronal activity and examined sensory integration in interneurons in response to multimodal sensory input. In the third aim, I developed an automated microfluidic platform for individualized long-term health and longevity tracking and investigation of genetic and environmental effects on aging under highly controlled environmental conditions. With this platform, I monitored both individual longevity and behavior information of C. elegans with sub-hourly experimental time resolution in a variety of temperature and food levels. Moreover, I developed an automatic behavior analysis algorithm and statistical methods to assess behavior-based healthspan metrics and the relation between environmental, and stochastic factors and health and lifespan. Together, the newly developed microsystems for high-throughput functional imaging and the long-term imaging platform permit the investigation of sensory integration in the nervous system and the large-scale investigation of long-term behavioral and health metrics during the aging process of C. elegans.
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