Core C: Spatial Multiomics Core

核心 C：空间多组学核心

• 批准号: 10555895
• 负责人: Hemali Phatnani
• 金额: $ 140.05万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10555895
• 关键词: 3-Dimensional; Address; Adopted; Age; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease risk; Amyloid; Antibodies; Autopsy; Blood Vessels; Brain; Brain Mapping; Brain region; Cerebral Amyloid Angiopathy; Clinical; Computer Analysis; Data; Data Set; Development; Disease; Ensure; Etiology; Freezing; Functional disorder; Gene Expression; Gene Expression Profile; Generations; Genetic Transcription; Goals; Health; Human; Human Resources; Image; Indirect Immunofluorescence; Individual; Laboratories; Lead; Link; Management Information Systems; Maps; Methods; Molecular; Neocortex; Participant; Pathologic; Pathology; Pattern; Physiology; Play; Population; Prefrontal Cortex; Process; Proteomics; Protocols documentation; Publishing; Reproducibility; Research; Resolution; Risk Factors; Role; Sampling; Source; Standardization; Structure; Superior temporal gyrus; Techniques; Technology; Testing; Tissue Sample; Tissues; Validation; Work; age related; aging brain; brain tissue; cell assembly; cell type; data acquisition; data integration; data quality; experimental study; information processing; innovation; large scale data; multimodal data; multiple omics; neocortical; new technology; novel; programs; protein aggregation; protein biomarkers; protein expression; secondary analysis; single nucleus RNA-sequencing; single-cell RNA sequencing; tau Proteins; tissue preparation; transcriptomics; validation studies

SPATIAL MULTIOMICS CORE: PROJECT SUMMARY/ABSTRACT To investigate how disease relevant changes, such as Alzheimer’s disease, are linked to specific risk factors (e.g., age-related changes, protein aggregates, vascular pathologies, etc.) to alter the spatial arrangement of cell types in the brain and their gene expression profiles, we need to build high-resolution maps of brain tissue at the cellular level in individuals with and without pathology. Building these maps requires proper characterization of the pathological features, as well as a reproducible workflow for data generation and imaging. To this end, the Spatial Multiomics Core will work closely with the Biospecimen Core, the Integrated Computational Analysis Core, and the four Projects to provide standardized, high quality generation and integration of large-scale spatial molecular data. Thus, the overall proposal will directly address an unmet need in the field to provide state of the art, rigorous, spatially resolved transcriptomic and proteomic data acquisition and integration methods, applied to human postmortem tissue at scale. This Core encompasses the generation of this data required for the research in the four main Projects in this proposal. Specifically, this Core will perform spatially resolved transcriptomics (ST) and multiplexed proteomics using iterative indirect immunofluorescence imaging (4i) experiments in postmortem tissue spanning a range of ages and pathologies and age-matched controls. The overarching aims of this core are: i) to build and optimize robust workflows based on existing protocols, to thereby enable the generation of Project data at high throughput and scale (Aims 1 and 2); and ii) to adopt new protocols for imaging-based validation studies on fixed and frozen tissue, to thereby enable the integration of new technology into the multiomics workflow (Aim 3). The completion of these objectives will provide a standardized body of data and analysis workflows for the Projects in this proposal, setting the stage for the careful cell type and gene expression signature analyses carried out in all of these projects. Finally, this overall framework will ultimately provide a rigorously curated, large-scale data set that will enable novel understanding of how differing etiologies produce specific pathological features, how these relate to physiology in each CNS cell type, and how the dysfunction in the various assemblies of cell types within brain regions lead to differing clinical presentation.

空间多学科核心：项目摘要/摘要 研究阿尔茨海默氏症等疾病相关变化与特定风险因素之间的关系 (例如，与年龄相关的变化、蛋白质聚集体、血管病理等)改变空间排列的步骤 对于大脑中的细胞类型及其基因表达谱，我们需要建立高分辨率的大脑地图 有病理和无病理个体的细胞水平的组织。构建这些地图需要适当的 病理特征的表征，以及用于数据生成和复制的可重复工作流 成像。为此，空间多组学核心将与Biosecimen核心，即集成的 计算分析核心和四个项目，以提供标准化、高质量的生成和 大比例尺空间分子数据集成。因此，总体提案将直接解决未得到满足的 需要在该领域提供最先进的、严格的、空间分辨的转录和蛋白质组数据 采集和整合方法，适用于大规模的人死后组织。这一核心包括 本提案中的四个主要项目的研究所需的数据的生成。具体来说， 该核心将执行空间分辨转录组学(ST)和多路蛋白质组学使用迭代 间接免疫荧光成像(4I)在不同年龄和范围的死后组织中的实验 病理和年龄匹配的对照。该核心的首要目标是：i)构建和优化健壮 基于现有协议的工作流，从而能够以高吞吐量生成项目数据 和比例尺(目标1和目标2)；和2)采用新的方案，对固定和 冷冻组织，从而使新技术能够融入多组学工作流程(目标3)。这个 完成这些目标将提供标准化的数据和分析工作流程 本提案中的项目，为仔细的细胞类型和基因表达签名分析奠定了基础 在所有这些项目中都进行了。最后，这个整体框架最终将提供一个经过严格策划的、 大规模数据集，将使人们能够以新的方式理解不同的病因如何产生特定的 病理特征，这些如何在每种中枢神经系统细胞类型中与生理相关，以及如何在 脑区细胞类型的不同组合会导致不同的临床表现。