Project Abstract Over 50 million Americans experience chronic pain annually, which has led to increases in opioid prescription rates. While effective analgesics, opioids produce harmful side effects like euphoria and physical dependence, which has led to a nationwide opioid epidemic and a need for efficacious analgesics that lack harmful side effects. Understanding how opioids impact the nervous system is important to distinguish the neural circuits driving opioid analgesia from circuits underlying unwanted side effects. Opioids target the mu opioid receptor (MOR), an inhibitory G-protein coupled receptor expressed by neurons throughout the brain. Neurons in the periaqueductal gray (PAG) express high levels of MOR and, upon electrical or morphine stimulation, produce both analgesic and rewarding behaviors. Distinguishing opioid-dependent PAG circuits driving analgesia from rewarding circuits may reveal a powerful, non-addictive therapy for pain relief. Characterizing the composition and organizational connectivity of the PAG is necessary to target distinct opioid-dependent circuits. PAG neurons vary in function, location, and molecular composition, but have not been comprehensively characterized using single-cell approaches. The PAG relays sensory and affective information to and from various brain structures during opioid use, but the configuration of presynaptic inputs and projection targets of opioid-sensitive MOR+ PAG neurons is unknown. Understanding the composition and organization of opioid- sensitive neural circuits is important to discern where opioids act to produce analgesic and rewarding effects. In preliminary single-cell RNA-sequencing (scRNAseq) experiments I identified 14 PAG transcriptionally distinct neuron subtypes that expressed various levels of the gene encoding MOR (Oprm1). In Aim 1, I will use spatial transcriptomics to determine the distribution and cellular heterogeneity of Oprm1+ PAG neurons. I will then resolve the architecture of opioid-sensitive circuits in the PAG using input-output circuit mapping. In Aim 2, I will first determine whether PAG neurons can be genetically classified based on their projection target using retro-seq. I will also use inhibitory chemogenetics during sensory, affective, and motivational behavior assays to investigate whether PAG neurons with different projection targets contribute to specific opioid- induced behaviors. The combined molecular, spatial, and circuit data generated from these experiments will provide a means to manipulate specific PAG circuits and reveal which neurons are receptive to opioids. Furthermore, results from loss-of-function behavioral assays will demonstrate whether specific PAG circuits preferentially contribute to the sensory or affective effects of opioids. The proposed research will be conducted under the mentorship of Dr. Gregory Scherrer. Dr. Scherrer has extensive experience integrating mouse genetics, functional neuroanatomy, and complex behavioral assays to investigate the neural circuits underlying opioid behaviors. Collectively, this project will help me develop into an independent researcher and provide the research community with resources for investigating opioid circuits.

Project Narrative Opioids are powerful analgesics, but their harmful side effects have led to a nationwide opioid epidemic. Neurons in the periaqueductal gray (PAG) contribute to the pain-relieving and rewarding effects of opioids, but the organization of these circuits and how they contribute to opioid-induced behaviors remains unclear. To elucidate how opioids affect PAG neurons, I will characterize the organization of PAG neural circuits and investigate how they contribute to opioid-induced behaviors using input-output circuit mapping, single-cell transcriptomics, and circuit-specific neuromodulation experiments in freely moving animals.