Title: Machine learning-guided rhodopsin engineering enables sensitive all-optical voltage imaging and optogenetics

Speaker:Miranda Dawson (Fan Lab)

Abstract:  Understanding how neural circuits change during learning and disease requires tools that can measure fast synaptic voltage signals with high spatial and temporal resolution. Genetically encoded voltage indicators (GEVIs) enable optical recording of membrane potential dynamics from genetically defined neurons, but current sensors lack the sensitivity and robustness needed to reliably resolve subthreshold synaptic events on single trials in vivo during behavior. We develop and apply next-generation rhodopsin-based GEVIs optimized for brightness, voltage sensitivity, and kinetics. Using a machine learning-guided protein engineering framework, candidate indicators are computationally prioritized across multiple performance parameters and experimentally benchmarked using all-optical electrophysiology in neuronal cultures. Top-performing variants are integrated with two-photon optogenetic approaches to establish an all-optical platform capable of resolving unitary synaptic excitation and inhibition in intact neural circuits during behavior. By enabling direct optical measurement of synaptic signaling during behavior, this work overcomes a critical technical barrier in systems neuroscience and provides new tools for investigating circuit plasticity mechanisms underlying learning, memory, and neurological disorders.

Title: Multiomic Dissection of Striatal Subregion and Cell Type Vulnerabilities in Huntington’s Disease

Speaker: Raleigh Linville (Heiman Lab)

Abstract: The striatum is critical for decision-making, movement, and reward processing, functions achieved through subregional cellular and molecular specialization. Striatal cell types and subregions are differentially implicated in neurodegenerative and neuropsychiatric disorders, yet the mechanisms underlying these vulnerabilities remain poorly understood. Using single-nucleus RNA sequencing across 109 human samples spanning dorsal and ventral striatum, we present a comprehensive atlas of striatal subregional neuronal specialization including characterization of transcriptional gradients along the dorsolateral-ventromedial axis. Harnessing this atlas, we investigate the molecular basis of the progressive and selective loss of medium spiny neurons (MSNs) with a characteristic dorsal-to-ventral gradient, a hallmark of HD neuropathology. Through paired single-cell transcriptomic and somatic HTT CAG repeat expansion measurements in human postmortem tissue, we demonstrate that within the same HD brains, the dorsal striatum displays greater MSN loss, transcriptional dysregulation, and HTT CAG repeat instability relative to the ventral striatum. Furthermore, dorsolateral MSN identity predicts CAG repeat length-dependent gene programs, linking single-cell resolution measurements to the established dorso-ventral axis of HD neuropathology. Lastly, applying both single-cell and spatial transcriptomics, we characterize a rare population of MSNs that emerge in HD and are marked by aberrant gene expression consistent with loss of polycomb repressive complex function, intranuclear mutant HTT inclusions, and engagement of multifaceted compensatory programs. Together, our findings establish a framework for understanding how striatal cell type identity and subregional position shape vulnerability in HD, with implications for early-stage therapeutic targeting.