Mapping brain-wide opioid actions by profiling neuronal activities and in vivo cellular target engagement

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Abstract Opioids are highly effective at reducing pain, but their potential for addiction and overdose has led to a growing public health crisis. Researchers have attempted to develop new opioid compounds that are less likely to be abused and have fewer side effects, but these efforts have been difficult. The endogenous opioid system has multiple receptors and ligands heterogeneously expressed across different parts of the body and cell types. Tremendous work has been done to delineate the relationships between opioid receptors (ORs) and ligands. However, the specificity of ligand-receptor engagement often depends on relative affinities at predetermined targets. In general, in vivo spatial and cellular heterogeneity of the brain obscure opioid actions, making them hard to predict based on receptor affinity alone. Currently, single-cell and spatial transcriptomics are transforming our understanding of brain architecture. However, there is a significant gap in how we measure opioid actions and align them with the spatially resolved cellular atlas of the brain. Levering emerging CATCH and inverse activity marker (IAM) techniques, we propose multimodal profiling of opioid actions with spatial and single-cell resolution across the entire mouse brain. Using three pharmacologically diverse opioids, we aim to map neuronal activities and cellular binding of these drugs onto the entire mouse brain in an unbiased way and register them with cell types identified from single-cell transcriptomics. Furthermore, we will test whether a drug’s affinities across different ORs determine its in vivo cell and neural ensemble engagement. Not only would this project provide a circuit-level mechanism linking the molecular pharmacology to brain-wide opioid actions, but also lay out a roadmap for evaluating and developing new opioids, e.g., by incorporating regional and cell-type preference into the structure-activity-relationship for lead optimization or by revealing on- and off-target sites to guide further cell-type specific in vitro chemical screening and optimization.