Investigation of the Synaptic Molecular Network using Multiplexed Imaging

项目摘要 突触分子网络是一个复杂的，紧密相互作用的系统，由数百种蛋白质组成， 学习、记忆和其他大脑功能的基础。它是许多神经系统， 神经退行性疾病和精神疾病，并且是小分子精神病药物的作用焦点。 治疗。了解这个网络和控制它的规则对于理解分子生物学是必要的。 脑疾病的病因学，以及精神药物的合理设计。为达致这个目的，我们建议 PRISM是最近开发的一种多路成像工具，可以在原位测量许多蛋白质， 单突触分辨率，以构建和验证因果关系，预测模型之间的相互依赖性 神经元突触的蛋白质，它们的亚基组成和激活状态。我们将扩大 PRISM可获得的目标库，并在跨神经元的大量突触中测量这些目标。 各种化学环境。这将用于两个目的：测量突触的许多“快照” 分子网络被拉向不同的方向，这是后续模型学习所必需的， 表征包括抗抑郁药在内的扰动的下游突触生化作用， 不同的班级我们还将结合联合收割机敏感的活钙成像的突触活动与随后的PRISM 测量相同的突触。然后，我们将使用这些数据来构建贝叶斯网络模型， 这些测量的概率分布之间的因果依赖关系。贝叶斯网络将 产生关于节点之间的因果关系和扰动某些目标的下游效应的预测， 我们随后将进行测试。这项研究的结果将是一个强大的预测模型， 蛋白质水平、亚基组成、磷酸化状态和突触活性的测量。这种模式的 提供一个统一的背景，将特定突触参与者之间相互作用的机制细节整合到一个 对突触的整体理解它还将提供有关系统级影响的预测， 化学扰动，可能为一种全新的体外筛选模式铺平道路， 精神治疗

PROJECT SUMMARY The synaptic molecular network is a complex, tightly interacting system of hundreds of proteins that forms the basis for learning, memory, and other brain functions. It is a disrupted locus of many neurological, neurodegenerative, and psychiatric disorders, and is a focal point of action for small molecule psychiatric treatments. Understanding this network and the rules that govern it is necessary for understanding the molecular etiology of brain diseases, and for the rational design of psychiatric drugs. To achieve this, we propose to apply PRISM, a recently developed multiplexed imaging tool which allows in-situ measurements of many proteins at single-synapse resolution, to construct and validate a causal, predictive model of interdependencies among proteins of the glutamatergic synapse, their subunit composition, and activation state. We will expand the repertoire of targets available for PRISM and measure these targets in a large population of synapses across a variety of chemical environments. This will serve two purposes: measurement of many ‘snapshots’ of the synaptic molecular network pulled in different directions, which is necessary for subsequent model learning, and in-depth characterization of the downstream synaptic biochemical effects of perturbations that include antidepressants of different classes. We will also combine sensitive live calcium imaging of synapse activity with subsequent PRISM measurements of the same synapses. We will then use these data to construct a Bayesian network model of causal dependencies between the probability distributions of these measurements. This Bayesian network will yield predictions about causal connections between nodes and downstream effects of perturbing certain targets, which we will subsequently test. The result of this study will be a powerful, predictive model connecting up to 30 measures of protein levels, subunit compositions, phosphorylation states, and synapse activity. This model will provide a unifying context to integrate mechanistic details of interactions between specific synaptic actors into a holistic understanding of the synapse as a whole. It will also provide predictions about system-level effects of chemical perturbations, potentially paving the way for an entirely novel modality for in vitro screening of psychiatric treatments.