Automation of Assay Endpoints for Brain Slice Models of Neurodegenerative Disease

神经退行性疾病脑切片模型检测终点的自动化

• 批准号: 8460306
• 负责人: DONALD C LO
• 金额: $ 24.41万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8460306
• 关键词: 3-Dimensional; Address; Adverse effects; Alzheimer' s Disease; Amyotrophic Lateral Sclerosis; Animal Disease Models; Animal Experiments; Animal Model; Architecture; Area; Automation; Bioinformatics; Biolistics; Biological Assay; Biology; Brain; Brain imaging; Cell Line; Cells; Central Nervous System Diseases; Devices; Disease; Disease model; Drug Delivery Systems; End Point Assay; Future; Gene Targeting; Genes; Goals; Huntington Disease; Image; Investigation; Laboratories; Link; Manuals; Methodology; Microscopic; Microscopy; Modeling; Nerve Degeneration; Neurodegenerative Disorders; Neurologic; Neurons; Optics; Parkinson Disease; Pharmaceutical Preparations; Process; Program Development; Publishing; Reporter; Resources; Screening procedure; Series; Slice; Speed; Spinal Cord; Staging; Stroke; Systems Biology; Techniques; Time; Tissues; Transfection; animal efficacy; base; brain tissue; cell type; clinically relevant; drug development; drug discovery; environmental stressor; flexibility; gene gun; in vivo; innovation; instrument; large scale production; nervous system disorder; neuropsychiatry; portability; programs; relating to nervous system; research study; success; tau Proteins; tool

DESCRIPTION (provided by applicant): For new drug and drug target discovery in neurological and neuropsychiatric disorders, transitioning from efficacy in cell-based assays to benefit in whole-animal models has always been difficult and uncertain. Ideally, drug discovery studies would be conducted, as much as possible, in whole-animal models of disease, but in vivo animal experiments are tremendously costly and time- consuming. Conversely, while cell line and primary culture-based assays are rapid and inexpensive, they are compromised by phenotypic changes when neurons are cultured and/or immortalized, and, importantly, by the normal 3-dimensional milieu and local inter-cellular interactions of brain tissue architecture being unavoidably lost. To help bridge this gap between cell-based and whole-animal efficacy studies, we have developed a series of intact brain tissue-based models for CNS disorders including stroke, Huntington's disease (HD), and Alzheimer's disease (AD). In our published studies, we have shown the utility of such assays in advancing a range of gene target identification and drug development programs. To support the use of these brain slice explant models in the context of larger-scale discovery efforts, we have developed numerous technological and process innovations over the last decade, including high-throughput brain slicing and biolistic gene gun devices for transfection of brain slices with disease-relevant genes and assay reporter constructs. The overarching goal of the present proposal is to solve the final rate-limiting barrier to full scalability of this approach, namely, the automation of brain slice-based assay endpoints. To date, all of the brain slice disease models we have developed have been analyzed using laborious manual endpoint assays; nevertheless, assay throughput has been sufficient to support the screening of hundreds to thousands of compounds or gene targets per year even with a modest-sized scientific team. Implementation of "turnkey" unbiased, automated microscopy and high-content analysis (HCA) platforms would increase the throughput of these assays by 10-fold or more, and enable full support of large-scale systems biology, bioinformatics, and drug discovery programs. Such a bridging stage of "high-throughput biology" screening between cell-based and whole-animal models should significantly increase the likelihood of success of drug and drug target discovery and development programs, by providing a preview of both efficacy as well as potential adverse off-target effects in intact neurl tissue assays before substantial time and financial commitments are made to full in vivo efficacy studies. PUBLIC HEALTH RELEVANCE: A major obstacle in drug discovery and development for neurological and neuropsychiatric disorders is the "missing link" between initial findings in laboratory assays using primary neurons and cell lines, and showing benefit in whole-animal models of disease. While brain tissue-based assays form a natural bridge between cell-based and whole-animal models, to date such assays, while biologically and clinically relevant, have not been automatable, and have thereby limited their applicability in larger-scale drug discovery efforts. Thus, the present proposal seeks to take advantage of recent advances in automated, image-based analysis for systems biology, bioinformatics, and drug and drug target discovery to create assay platforms that will support unbiased, automated, and fully scalable brain-slice based screening platforms that will be powerful new tools for increasing the likelihood of success and speed of drug discovery and development programs for CNS diseases.

描述（由申请人提供）：对于神经系统和神经精神疾病的新药和药物靶点发现，从基于细胞的试验中的疗效过渡到整个动物模型中的获益一直是困难和不确定的。理想情况下，药物发现研究将尽可能在疾病的全动物模型中进行，但体内动物实验非常昂贵和耗时。相反，虽然基于细胞系和原代培养的测定快速且廉价，但它们受到培养和/或永生化神经元时的表型变化的影响，并且重要的是，受到正常的三维环境和脑组织结构的局部细胞间相互作用的影响。为了帮助弥合基于细胞和全动物疗效研究之间的这一差距，我们开发了一系列基于完整脑组织的CNS疾病模型，包括中风、亨廷顿病（HD）和阿尔茨海默病（AD）。在我们发表的研究中，我们已经展示了这种测定在推进一系列基因靶点鉴定和药物开发计划中的实用性。为了支持在更大规模的发现工作中使用这些脑切片外植体模型，我们在过去十年中开发了许多技术和工艺创新，包括高通量脑切片和用于转染具有疾病相关基因的脑切片的生物射弹基因枪装置 和测定报告构建体。本提案的总体目标是解决该方法完全可扩展性的最终限速障碍，即基于脑切片的测定终点的自动化。到目前为止，我们开发的所有脑切片疾病模型都是使用费力的手动终点测定进行分析的;尽管如此，即使是中等规模的科学团队，测定通量也足以支持每年筛选数百至数千种化合物或基因靶点。“交钥匙”无偏自动化显微镜和高含量分析（HCA）平台的实施将使这些检测的吞吐量增加10倍或更多，并能够全面支持大规模系统生物学，生物信息学和药物发现计划。在基于细胞的模型和全动物模型之间的这种“高通量生物学”筛选的桥接阶段应该显著增加药物和药物靶点发现和开发计划成功的可能性，通过在对完整的神经组织测定进行大量时间和财务承诺之前提供功效以及潜在的不良脱靶效应的预览来进行完整的体内功效研究。 公共卫生关系：神经和神经精神疾病药物发现和开发的一个主要障碍是在使用原代神经元和细胞系的实验室测定中的初步发现与在疾病的全动物模型中显示出益处之间的“缺失环节”。虽然基于脑组织的测定在基于细胞的模型和全动物模型之间形成天然桥梁，但迄今为止，这种测定虽然在生物学和临床上相关，但还不能自动化，从而限制了它们在大规模药物发现工作中的适用性。因此，本提案寻求利用用于系统生物学、生物信息学以及药物和药物靶标发现的自动化、基于图像的分析的最新进展来创建将支持无偏、自动化和完全可扩展的基于脑切片的筛选平台的测定平台，所述筛选平台将是用于增加CNS疾病的药物发现和开发计划的成功可能性和速度的强大新工具。