Title: “Genetically Encoded Molecular Probes for Analyzing Neural Circuits”
Xue Han, PhD – BME (Advisor)
John White, PhD – BME (Chair)
Jerome Mertz, PhD – BME
John Ngo, PhD – BME
Hengye Man, PhD – Biology
Precise electrochemical signaling is essential for neural network computation. Over the past century, we have learned much about the links between behavior and the activity patterns of specific neurons. The development of optogenetic tools to control and monitor specific neurons in the living brain has enabled the causal analysis of neuron populations with unique genetic identity in brain computation. In this thesis, we developed a novel genetically encoded voltage indicator (GEVI), SomArchon, for optical voltage recording in behaving mice, and assembled a viral toolbox of genetically encoded synaptic tags. Overall, these novel genetically encoded tools will facilitate the study of synaptic wiring and neural activity in a wide variety of neuroscience applications.
Optical voltage imaging enables the monitoring of neural activity with millisecond temporal precision and cellular resolution. However, current state-of-the-art GEVIs only report spiking activity in 1-2 cells simultaneously in vivo. We developed a soma-localized GEVI, SomArchon, compatible with optogenetic control and capable of reporting subthreshold and spiking activity in populations of individual neurons in awake mice. We found that highly coherent subthreshold activity does not govern highly coherent spike outputs in neighboring neurons. Overall, SomArchon outperforms existing sensors and enables in vivo population voltage imaging suitable for a diversity of neuroscience experiments.
Synaptic labeling is important in understanding the wiring of neural circuits or the synaptic changes involved in development, plasticity, and disease. Fibronectin intrabodies generated with mRNA display (FingRs) are genetically encoded fluorescent synaptic labels that do not alter synaptic transmission. Here, we generated a set of adeno-associated virus (AAV) FingR variants for labeling of excitatory or inhibitory synapses in multiple brain regions, and in specific cell types in cre-transgenic mice. We optimized a red synaptic tag for inhibitory synapses that allowed for dual labeling of both excitatory and inhibitory synapses in the same cells. Finally, we generated FingR retroviruses and tracked synaptic development of adult born hippocampal granule cells. These AAV and retrovirus variants label excitatory or inhibitory synapses in specific cell types and provide a comprehensive viral toolbox for multi-color, cell type specific synaptic labeling for studying synaptic architecture, synapse development, and synaptic plasticity.