Transcriptional, functional, and circuit profiling at single cell resolution of neuronal ensembles engaged by heroin relapse

Abstract: Opiate addiction extorts a tremendous toll on society, but a mechanistic understanding of how repeated exposure to opioids such as heroin ultimately results in compulsive drug-taking and -seeking behavior in some individuals, but not others, is still not known. A longstanding idea is that enduring changes in neural circuit function occur because of drug-induced gene expression changes in certain brain cells. This facilitates subsequent drug-taking and -seeking behaviors in vulnerable individuals. Unfortunately, identifying cell-type specific alterations following drug use (typically performed in established animal models of addiction), is generally a slow and tedious process as changes in gene expression following in vivo drug exposure are typically assayed in series, within heterogeneous brain regions, in an a-priori hypothesis driven fashion (i.e. previous knowledge predicting a specific gene may be involved). This dramatically limits the throughput of data collection and likely complicates the subsequent interpretation as gene expression patterns data are typically captured from thousands to millions of homogenized cells. Given that the nervous system is composed of highly heterogeneous tissue, re-assessing cell type specific gene expression changes in an unbiased manner from 1000's of individual cells is desperately needed. Here, we propose to combine our expertise in order to generate comprehensive datasets aimed at understanding how single-cell gene expression, circuit connectivity, and neural activity patterns are impacted by previous drug-taking behavior. These data will provide a much-needed cellular atlas and resource for the addiction neuroscience community and will likely lead to the identification of many novel cell type, gene expression changes, and ensembles that can be leveraged for future study.