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.

空间多组学核心：项目摘要/摘要 为了研究疾病相关的变化（例如阿尔茨海默氏病）如何与特定危险因素有关 （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 大脑中的细胞类型及其基因表达谱，我们需要构建大脑的高分辨率图 有或没有病理的个体的细胞水平的组织。构建这些地图需要正确 病理特征的表征，以及可重现的数据生成和 成像。为此，空间多图形核心将与Biospecipimen Core紧密合作，该核心是集成的 计算分析核心以及提供标准化，高质量生成和的四个项目 大规模空间分子数据的整合。这，总体建议将直接解决未满足的 在现场需要提供最先进的状态，严格，空间分辨的转录组和蛋白质组学数据 采集和整合方法，按大规模应用于人类后组织。此核心包括 在本提案中的四个主要项目中，研究所需的这些数据产生。具体来说， 该核心将使用迭代进行空间分辨的转录组学（ST）和多路复用蛋白质组学 横跨一系列年龄的验尸组织中的间接免疫荧光成像（4i）实验 病理和年龄匹配的对照。该核心的总体目的是：i）构建和优化可靠的 基于现有协议的工作流程，从而使高通量的项目数据生成 和比例（目标1和2）； ii）采用新协议，以基于成像的验证研究对固定和 冷冻组织，从而使新技术将新技术集成到多组学工作流程中（AIM 3）。 这些目标的完成将为标准化的数据和分析工作流提供 该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 在所有这些项目中执行。最后，这个整体框架最终将提供严格的策划， 大规模数据集将使人们能够对区分病因的方式进行新的了解 病理特征，这些特征与每种CNS细胞类型中的生理学之间如何相关，以及如何在 大脑区域内细胞类型的各种组装导致临床表现区分。