Abstract
In Caenorhabditis elegans, optogenetic stimulation has been widely used to assess neuronal function, control animal movement, or assay circuit responses to controlled stimuli. Most studies are performed on single animals and require high-end components such as lasers and shutters. We present an accessible platform that enables controlled optogenetic stimulation of C. elegans in two modes: single animal stimulation with locomotion tracking and entire population stimulation for neuronal exercise regimens. The system consists of accessible electronic components: a high-power light-emitting diode, Arduino board, and relay are integrated with MATLAB to enable programmable optogenetic stimulation regimens. This system provides flexibility in optogenetic stimulation in freely moving animals while providing quantitative information of optogenetic-driven locomotion responses. We show the applicability of this platform in single animals by stimulation of cholinergic motor neurons in C. elegans and quantitative assessment of contractile responses. In addition, we tested synaptic plasticity by coupling the entire-population stimulation mode with measurements of synaptic strength using an aldicarb assay, where clear changes in synaptic strength were observed after regimens of neuronal exercise. This platform is composed of inexpensive components, while providing the illumination strength of high-end systems, which require expensive lasers, shutters, or automated stages. This platform requires no moving parts but provides flexibility in stimulation regimens.
Highlights
Human life expectancy has significantly increased worldwide in the past century, and this trend is expected to continue (Lassonde et al, 2017)
The system consists of accessible electronic components: a high-power light-emitting diode, Arduino board, and relay are integrated with MATLAB to enable programmable optogenetic stimulation regimens
We present a platform for optogenetic-driven neuronal stimulation that includes the use of light-emitting diode (LED) lamps, MATLAB, and an Arduino controller to automate neuronal exercise
Summary
Human life expectancy has significantly increased worldwide in the past century, and this trend is expected to continue (Lassonde et al, 2017). Neurodegenerative diseases reduce cognitive function by impairing synaptic function and plasticity (Arancio and Chao, 2007; Gispen and Biessels, 2000; Shankar et al, 2008). We are far from understanding how neurodegenerative disease drives synapse loss and malfunction. Synaptic plasticity forms the basis of current models for memory, learning, and sensory adaptation (Fox and Stryker, 2017; Hebb, 1949). Behavioral training in Sprague Dawley rats and regulated neuronal activation in Tritonia diomedea, Xenopus tadpoles, and Caenorhabditis elegans (Abbott and Nelson, 2000; Foster and Dumas, 2001; Hoerndli et al, 2015; Katz et al, 1994) has been shown to improve synaptic plasticity. Studying neuronal exercise is vital for the understanding of the underlying mechanisms of synaptic plasticity, discovering features of learning and memory, and identifying the genes and pathways that play a role in age-associated synaptic plasticity decline
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