Chemical nociception in Wild-type and dYPEL3 Drosophila larva mutants
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Authors
Zito, Nicholas
Issue Date
2019
Type
Poster
Language
Keywords
Nociceptive behavior , machine learning , nociceptive circuit
Alternative Title
Abstract
Drosophila larval nociception is widely used for studying various basic circuit mechanisms. Traditionally, the behavioral assay for Drosophila nociception relied on either optogenetic or physical stimulation. The behavioral response upon chemical stimulation has not been widely used due to high levels of variability. We found that larva require co-stimulation with blue light to exhibit consistent nociceptive behavior upon a noxious chemical stimulation using allyl isothiocyanate (AITC). Introducing constant blue light illumination during AITC treatment greatly increased the consistency of behavioral output. dYPEL3 mutations have been identified in a number of neurological symptoms in human patients. We used our refined AITC-induced larval nociceptive behavior and found a reduction in nociceptive behavior in dYPEL3 mutants. Currently, larval nociceptive behavior is quantified by manual scoring. We are working to develop automatic quantitation of nocicieptive behavior using machine-learning techniques from software such as DeepLabCut (DLC). Going forward, we plan on using these machine-learning techniques such as DLC to automatically quantify nociceptive behavior to further study the effects of dYPEL3 mutations on nociceptive circuit development.
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In Copyright