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

海洛因复吸所涉及的神经元群的单细胞分辨率转录、功能和回路分析

基本信息

批准号：
10292403
负责人：
Susan Marie Ferguson
金额：
$ 56.99万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10292403
关键词：
Address Affect Anatomy Animal Behavior Animal Model Atlases Behavior Bioinformatics Biological Assay Brain Brain region Calcium Cells Chromatin Communities Cues Data Data Collection Data Set Development Dorsal Drug Exposure Drug Modelings Drug usage Exposure to Fluorescent in Situ Hybridization Future Gene Expression Gene Expression Profile Gene Expression Profiling Genes Genetic Transcription Gold Heroin Heroin Dependence Human Image Individual Individual Differences Infusion procedures Knowledge Lead Light Measurement Medial Microscopy Modeling Molecular Nature Nervous system structure Neurons Neurosciences Nucleus Accumbens Opiate Addiction Opioid Pattern Pharmaceutical Preparations Population Process Publishing RNA Rattus Relapse Research Resolution Resources Sampling Self Administration Series Signal Transduction Slice Societies Standardization System Thalamic structure Tissue-Specific Gene Expression Tissues addiction base behavioral phenotyping brain cell brain tissue cell type cohort drug development drug seeking behavior in vivo in vivo calcium imaging molecular marker neural circuit novel opioid use relating to nervous system response single cell sequencing single-cell RNA sequencing therapeutic candidate therapeutic target

项目摘要

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.

抽象的：鸦片成瘾勒索了社会的巨大损失，但对重复暴露的机械理解对于海洛因等阿片类药物，最终导致某些人的强迫毒品和寻求行为，但是没有其他人仍然不知道。一个长期的想法是，神经回路功能的持久变化发生由于药物诱导的基因表达在某些脑细胞中的变化。这有助于随后的吸毒和 - 弱势个人的寻求行为。不幸的是，识别以下细胞类型的特定更改吸毒（通常在成瘾的动物模型中进行），通常是一个缓慢而乏味的过程随着体内药物暴露后基因表达的变化通常以串联测定以A-Priori假设为驱动的方式，异质的大脑区域（即先前的知识预测可能涉及特定基因）。这极大地限制了数据收集的吞吐量，并可能使其复杂化随后作为基因表达模式数据的解释通常从数千到数百万捕获均质细胞。鉴于神经系统由高度异构组织组成，重新评估细胞类型特异性基因表达以公正的方式从1000个单个细胞中变化是拼命的需要。在这里，我们建议将我们的专业知识结合起来，以生成针对的全面数据集了解单细胞基因表达，电路连通性和神经活动模式如何受到影响以前的吸毒行为。这些数据将为急需的蜂窝图集和资源提供成瘾神经科学社区，可能会导致许多新型细胞类型的鉴定表达变化，以及可以利用的合奏来进行未来的研究。