Automation of Assay Endpoints for Brain Slice Models of Neurodegenerative Disease

描述(由申请人提供)：对于神经和神经精神疾病的新药和药物靶点的发现，从基于细胞的分析的有效性过渡到在全动物模型中受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多地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，尽管基于细胞系和原代培养的分析是快速和廉价的，但当神经元被培养和/或永生化时，它们会受到表型变化的影响，更重要的是，由于正常的三维环境和脑组织结构的局部细胞间相互作用不可避免地丢失。为了帮助弥合基于细胞的疗效研究和整个动物疗效研究之间的差距，我们开发了一系列基于完整脑组织的中枢神经系统疾病模型，包括中风、亨廷顿病(HD)和阿尔茨海默病(AD)。在我们已发表的研究中，我们已经展示了这种分析在推进一系列基因靶标识别和药物开发计划方面的效用。为了在更大规模的发现工作中支持这些脑片外植体模型的使用，我们在过去十年中开发了许多技术和工艺创新，包括高通量脑片和用于将疾病相关基因导入脑片的生物基因枪设备。 和化验报告构建。本提案的首要目标是解决该方法完全可扩展的最终速度限制障碍，即基于脑切片的分析终点的自动化。到目前为止，我们开发的所有大脑切片疾病模型都是使用繁琐的手动终点分析进行分析的；然而，即使是一个中等规模的科学团队，分析吞吐量也足以支持每年筛选数百到数千个化合物或基因靶标。“交钥匙”、无偏见的自动化显微镜和高含量分析(HCA)平台的实施将使这些分析的吞吐量增加10倍或更多，并使大规模系统生物学、生物信息学和药物发现计划能够得到全面支持。这种在细胞模型和全动物模型之间进行高通量生物学筛选的桥梁阶段应该会显著增加药物和药物靶点发现和开发计划的成功可能性，在充分的时间和财政承诺进行全面的体内疗效研究之前，提供完整神经组织分析中的有效性和潜在的不良靶外影响的预览。 公共卫生相关性：神经和神经精神疾病的药物发现和开发的一个主要障碍是，使用原代神经元和细胞系的实验室分析的初步发现与在全动物疾病模型中显示的益处之间的“缺失环节”。虽然基于脑组织的分析在基于细胞的模型和全动物模型之间形成了一座天然的桥梁，但到目前为止，这种分析虽然在生物学和临床上是相关的，但还不是自动化的，因此限制了它们在更大规模的药物发现努力中的适用性。因此，本提案寻求利用系统生物学、生物信息学以及药物和药物靶标发现的自动化、基于图像的分析方面的最新进展来创建分析平台，这些平台将支持基于脑片的无偏见、自动化和完全可扩展的筛查平台，这将成为提高中枢神经系统疾病药物发现和开发计划的成功可能性和速度的强大新工具。

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.