Advancements in genetically based technologies have begun to allow us to better understand the relationships between underlying neural activity and the patterns of measurable behavior that can be reproducibly studied in the laboratory. As this field develops, there are key limitations to the currently available technologies hindering their full potential to deliver meaningful datasets. The limitations which are most critical to advancement of these technologies in behavioral neuroscience are: the temporal resolution at which physiological events can be windowed, the divergent molecular pathways in signal transduction that introduce ambiguity into the output of activity sensors, and the impractical size of the tool’s genetic material—requiring 3-4 separate AAV vectors to deliver a fully functional system into a cell. To address these limitations and help bring the potential of these types of technologies into better realization, we have engineered a nucleus localized light-sensitive Ca2+-dependent gene expression system based on AsLOV2 and the downstream responsive element antagonist modulator (DREAM). The design and engineering of each component was performed in such a way to: 1) preserve behaviorally relevant temporal dynamics, 2) preserve signal fidelity appropriate for studying experience-driven neural activity patterns and their relationship to specific animal responses, and 3) have full delivery of the system’s genetic material via a single AAV vector. The system was tested in vitro and subsequently in vivo with neural activity induced by Channelrhodopsin, and could be used in the future with behaviorally-driven neural activity. To our knowledge this is the first optogenetic tool for the practical use of linking activity-dependent gene activation in response to direct nuclear calcium transduction.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/41105 |
| Date | 28 May 2020 |
| Creators | Vogel, Adam Tyler |
| Contributors | Russek, Shelley J., Hasselmo, Michael |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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