Optogenetics, a revolutionary technique that utilizes light-sensitive proteins called opsins to control neuronal activity, has transformed the field of neuroscience by providing unprecedented precision in the study of neural circuits and behavior. This thesis focuses on the application of optogenetics in Drosophila melanogaster research, aiming to advance our understanding of neural circuits and behavior through the development of adaptive light sources, and a set of homemade tools to simplify the design of optogenetic experiments, combining biology, engineering and computer science approaches.
The first goal of this research was to find new, low-cost, and versatile ways to perform optogenetic experiments. This led us to the exploration and characterization of smartphone displays as light sources for optogenetic stimulation. By utilizing smartphone displays, the activation and inhibition of various cell types, including motoneurons, muscles, sensory neurons, and multidendritic neurons, were achieved in Drosophila larvae and flies. This approach expands the possibilities of optogenetic research, making it accessible for students and researchers to easily perform experiments with small animals, at high temporal and spatial resolution, or even the light and spectral requirements of novel light-sensitive proteins.
To facilitate optogenetic experiments, software tools were developed to accurately quantify light spatial distribution and analyze larval behavior. Spatial light distribution simulations provided insights into the emitted light from displays aiding us in the planning and understanding of the experimental results, tailored for light emitted by displays, and based on physical measurements rather than on simple assumptions on light spreading. Furthermore, an automatic feature extraction tool enhanced the understanding of larval responses to light stimuli, capturing key behavioral events such as stops, sweeps, turns, and runs. This aids us in extracting a high number of behavioral characteristics, automatically, accurately and in less time compared to manual behavioral feature definition.
The manipulation of complex light patterns using smartphone displays allowed us to design experiments for guiding larval movement. By integrating smartphone optogenetics, spatial light distribution simulations, and behavior feature extraction techniques, responses of larvae to different light profiles were elucidated, contributing to the understanding of larval behavior and its underlying mechanisms, particularly investigating the nociceptive adaptation of larvae in different gradients of light, showing similar adaptability in Drosophila larvae as in humans.
Additionally, investigations into the control of larval feeding behavior using optogenetics shed light on the influence of non-neuronal cells, specifically the salivary glands, on feeding regulation. Manipulating these glands through optogenetic techniques resulted in significant changes in larval feeding behavior, emphasizing the need to consider the contribution of other organs alongside neural control when studying animal behavior, and demonstrating for the first time optogenetically driven cannibalism in larvae.
Moreover, the integration of bicolored Organic LEDs (OLEDs) with bidirectional optogenetics opens new avenues for studying neural circuits and developing therapeutic interventions for neurological disorders. The precise control of larval motoneurons and locomotor systems using these AC/DC OLEDs holds promise for investigating the role of single neurons in complex behaviors and potentially restoring locomotion in patients with spinal cord injuries.
This thesis contributes to the field of optogenetics by advancing the understanding of larval behavior and its modulation through light stimulation. The novel adaptive light sources, tools for analysis, and insights gained from the experiments provide a framework for further exploration of neural circuits and behavior in Drosophila melanogaster and other small animal models.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:93393 |
| Date | 28 August 2024 |
| Creators | Meloni, Ilenia |
| Contributors | Czarske, Jürgen W., Gather, Malte C., Murawski, Caroline, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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