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Investigation of the Synaptic Molecular Network using Multiplexed Imaging

使用多重成像研究突触分子网络

基本信息

批准号：
10510057
负责人：
Mark Bathe
金额：
$ 22.91万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10510057
关键词：
Antidepressive Agents Award BRAIN initiative Bayesian Analysis Bayesian Modeling Bayesian Network Bayesian Prediction Biochemical Brain Brain Diseases Calcium Chemicals Complex DNA Data Data Set Dependence Derivation procedure Disease Environment Etiology Excitatory Synapse Generations Genes Glutamates Health Hippocampus (Brain)Image Imaging Device In Situ In Vitro Intervention Investigation Learning Measurement Measures Memory Mental disorders Modality Modeling Molecular Morbidity - disease rate Morphologic artifacts Mutation Neuraxis Neurodegenerative Disorders Neurons Neurosciences Pharmaceutical Preparations Phosphorylation Phosphotransferases Population Probability Process Proteins Proteome Protocols documentation Psychiatric therapeutic procedure Quality Control Rattus Reagent Research Personnel Resolution Resources Role Schizophrenia Site Stains Structure Synapses System Techniques Testing Time antibody conjugate autism spectrum disorder base drug candidate drug development experimental study genetic regulatory protein high dimensionality in vitro testing knock-down molecular imaging molecular phenotype multiplexed imaging nervous system disorder novel predictive modeling rational design receptor scaffold screening small molecule synaptic function therapy design tool

项目摘要

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.

项目总结