A robust platform for multiplexed, subcellular proteomic imaging in human tissue

用于人体组织多重亚细胞蛋白质组成像的强大平台

基本信息

批准号：
10247827
负责人：
Robert michael Angelo
金额：
$ 54.7万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-11 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10247827
关键词：
Allergic Antibodies Archives Area Back Basic Science Biopsy Cell Nucleus Cells Clinical Cloud Computing Communities Data Data Set Decidua Development Disease Equipment Event Extramural Activities Feedback First Pregnancy Trimester Formalin Foundations Freeze Drying Funding Goals Granuloma Health Hippocampus (Brain)Histologic Hour Human Human BioMolecular Atlas Program Image Imaging Techniques Imaging technology Immune Immunosuppression Individual Institutes Ions Letters Link Machine Learning Medical center Messenger RNA Metals Morphology Multiplexed Ion Beam Imaging Noninfiltrating Intraductal Carcinoma Optics Organ Paraffin Embedding Pathology Peer Review Phenotype Population Proteins Proteomics Protocols documentation Pulmonary Tuberculosis Readiness Reagent Reproducibility Resolution Resources Sampling Scanning Signal Transduction Site Spectrometry, Mass, Secondary Ion Stains Standardization Structure Technology Three-Dimensional Image Time Tissue Embedding Tissues Translational Research United States National Institutes of Health Work cancer immunotherapy cohort computational pipelines computational platform computerized tools design feature extraction graphical user interface high dimensionality high resolution imaging human imaging human tissue imaging Segmentation imaging modality imaging platform insight instrumentation ion source machine learning method multiplexed imaging new technology next generation protein expression quantitative imaging reagent standardization technology validation tool tumor microenvironment user-friendly virtual

项目摘要

Project Summary Multiplexed Ion Beam Imaging by Time of Flight (MIBI-TOF) uses secondary ion mass spectrometry and metal conjugated primary antibodies to simultaneously visualize dozens of proteins at subcellular resolution in a single tissue section. This technology is back compatible with archival formalin fixed, paraffin embedded tissue (FFPE) and has been used in peer-reviewed work to simultaneously visualize and quantify 36 proteins in retrospective human tissue cohorts. In line with the stated goals of the HuBMAP consortium to develop both “High-sensitivity, high-resolution imaging techniques that can rapidly provide spectral data over large areas of tissue” and “Quantitative imaging analysis tools, including automated 3D image segmentation, feature extraction, and image annotation,” the work outlined here will create a standardized, high throughput, and user-friendly workflow for using MIBI-TOF in basic and translational research to gain insight into how single cell phenotype and tissue structure are functionally-linked in health and disease. To achieve this, we will validate 100 FFPE antibodies and optimize ready-to-use multiplexed staining panels in lyophilized format that will permit storage for at least two years. Protocols and reagents for multiplexed signal amplification of protein and mRNA targets will be further refined, while next generation instrumentation will increase sample throughput to permit full tissue section imaging of up to 40 proteins in 1 hour. Standardized reagents and more robust instrumentation will be accompanied by an automated computational pipeline that utilizes a standard set of segmentation markers and machine learning to accurately identify nuclei and cell borders in any non-neural human tissue. This data will be used to cluster single cell events into functionally distinct populations according to morphology, protein expression, and histological distribution. The reagents and computational pipeline proposed here synergize with existing HuBMAP-funded platforms and could be readily generalized to virtually any high dimensional imaging modality. Thus, this work will not only provide a practical, back compatible imaging platform for high throughput multiplexed imaging, but will also accelerate development of other complimentary imaging technologies as well.

项目概要飞行时间多重离子束成像 (MIBI-TOF) 使用二次离子质谱和金属缀合一抗可在单个抗体中以亚细胞分辨率同时可视化数十种蛋白质该技术与档案福尔马林固定石蜡包埋组织 (FFPE) 兼容。并已用于同行评审工作中，以回顾性方式同时可视化和量化 36 种蛋白质符合 HuBMAP 联盟开发“高灵敏度、高分辨率成像技术，可以快速提供大面积组织的光谱数据”和 “定量成像分析工具，包括自动 3D 图像分割、特征提取和图像注释”，这里概述的工作将为以下内容创建一个标准化、高吞吐量和用户友好的工作流程在基础和转化研究中使用 MIBI-TOF 来深入了解单细胞表型和组织如何结构在健康和疾病中具有功能相关性为了实现这一目标，我们将验证 100 种 FFPE 抗体。并以冻干形式优化即用型多重染色板，允许存储至少用于蛋白质和 mRNA 靶标多重信号放大的方案和试剂将进一步开发。改进，而下一代仪器将增加样品通量以允许完整的组织切片标准化试剂和更强大的仪器将在 1 小时内对多达 40 种蛋白质进行成像。伴随着自动计算管道，该管道利用一组标准的分割标记和机器学习可以准确识别任何非神经人体组织中的细胞核和细胞边界。用于根据形态、蛋白质将单细胞事件聚类成功能不同的群体这里提出的试剂和计算流程与表达和组织学分布协同作用。现有的 HuBMAP 资助的平台，可以很容易地推广到几乎任何高维成像因此，这项工作不仅提供了一个实用的、向后兼容的高通量成像平台。多重成像，但也将加速其他互补成像技术的发展。