Serotonergic Circuits: Role in Sleep and Enhanced Genetic Tools for Access and Optical Recording

Citation

Altermatt, Michael (2021) Serotonergic Circuits: Role in Sleep and Enhanced Genetic Tools for Access and Optical Recording. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/gfe2-w578. https://resolver.caltech.edu/CaltechTHESIS:01202021-155015733

Abstract

Overall, this thesis encompasses three main directions: the study of neural circuits in sleep (Chapter 2), the development and testing of tools for measuring neuromodulator release (Chapter 3), and methods for in vivo characterization of gene delivery vehicles (Chapter 5).

The role of the neuromodulator serotonin in sleep has been debated for over 60 years. Until recently, the serotonergic system was widely thought to be part of the arousal system and promote wakefulness. In Chapter 2, we investigate the function of serotonin-producing neurons in murine and zebrafish sleep with tools featuring superior specificity and precision compared to previously employed techniques. Our results demonstrate that the serotonergic raphe are sleep-promoting and required for sleep homeostasis. Intriguingly, serotonergic neurons in mice can have opposing effects on sleep depending on the firing mode.

The release of serotonin from neurons can be regulated by the frequency of neuronal firing and can occur at classical synapses, varicosities, soma, and dendrites. Further examination of the complex signaling mechanism of serotonin would benefit from tools capable of measuring the release of serotonin in vivo with long-term stability and high spatiotemporal resolution. To this end, we developed and characterized iSeroSnFR, an intensity-based genetically encoded serotonin indicator. In Chapter 3, we demonstrate that iSeroSnFR can detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep-wake transitions.

Adeno-associated viruses (AAVs) have been extensively used as gene delivery vehicles in basic neuroscience and gene therapy. However, optimization of transduction efficiency and target specificity remain a key challenge to overcome. Several AAV vector engineering approaches have been devised for this purpose and yield large collections of candidates that require further in vivo characterization. However, conventional characterization methods fall short with regard to in-depth cell type tropism analysis and/or high-throughput capabilities. In Chapter 5, we address this shortcoming with single-cell RNA sequencing technologies based on the Drop-seq method. We established an experimental and computational pipeline that allows us to profile the viral tropism of multiple AAV variants in parallel across numerous complex cell types.

Thesis Files