High-Content Imaging & Analysis Core

高内涵成像

• 批准号: 10525286
• 负责人: Gustavo Kunde Rohde
• 金额: $ 34.38万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-12 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10525286
• 关键词: Address; Antibodies; Area; Biological; Cell membrane; Cells; Cellular Structures; Chromosomes; Collaborations; Colorectal Cancer; Complex; Cultured Cells; Custom; Data; Data Science; Data Set; Development; Endosomes; Enzymes; Epidermal Growth Factor Receptor; Excision; Fluorescence; Fluorescence Microscopy; Generations; Glioblastoma; Goals; Image; Image Analysis; Imaging Device; Imaging Techniques; Immunofluorescence Immunologic; In Vitro; Indirect Immunofluorescence; Individual; Lead; Libraries; Malignant Neoplasms; Measurement; Measures; Metabolic; Metaphase; Metastatic Neoplasm to the Liver; Microscopy; Mitochondria; Mitotic; Modeling; Molecular; Molecular Analysis; Morphology; Organelles; Organoids; Pattern; Population; Post-Translational Protein Processing; Primary Neoplasm; Procedures; Proteins; Protocols documentation; Reproducibility; Research Personnel; Research Project Grants; Resolution; Sampling; Scientific Advances and Accomplishments; Services; Shapes; Signal Pathway; Signal Transduction; Signaling Molecule; Stains; Statistical Models; Stress; Subcellular structure; Surface; Systems Analysis; Systems Biology; Techniques; Testing; Texture; Time; Tissue imaging; Tissues; United States National Institutes of Health; Vacuole; Validation; base; cancer cell; colorectal cancer metastasis; computing resources; experimental study; feature detection; feature extraction; image registration; imaging Segmentation; imaging approach; imaging modality; in vivo; malignant breast neoplasm; microscopic imaging; novel; programs; protein protein interaction; quantitative imaging; recruit; support tools; tool; tumor

PROJECT ABSTRACT/SUMMARY The High-Content Imaging & Analysis Core will provide the three SASCO Center projects with experimental and computational resources to analyze different biological samples by multiplexed fluorescence microscopy and to extract quantitative data from microscopy-based images. The core will develop, validate, and apply highly multiplexed (iterative) imaging approaches, integrate subcellular imaging data collected across multiple rounds of iterative imaging, and build customized tools for image analysis, feature recognition, and extraction. The generated multi-parametric datasets will address specific needs of each project, enabling model- experiment iterations involving diverse cancer drivers, signaling pathways, and subcellular organelles in multiple biological contexts. The High-Content Imaging & Analysis Core will be co-led by two investigators (Fallahi-Sichani and Rohde) with complementary expertise in multiplexed immunofluorescence imaging, image analysis, and data science. Aim #1 will support the development, validation, and application of highly multiplexed immunofluorescence staining and imaging procedures to measure molecular features at cellular, subcellular, and organelle resolution. These procedures will enable the molecular analysis of mitotic signaling pathways and recruitment patterns in metaphase chromosomes derived from breast cancer organoids (Project 1), mitochondrial morphology, cell signaling and metabolic enzymes in colorectal cancer cells and tumors (Project 2), and post-translational modifications of key EGFR signaling molecules, protein-protein interactions, and their subcellular localization in glioblastoma cells (Project 3). Aim #2 will customize tools for quantitative image analysis, including image alignment and tracking, segmentation of cells and subcellular structures, as well as feature extraction and recognition. The High-Content Imaging & Analysis Core will provide all three projects the necessary expertise and tools for quantifying information about cells, cultures, and tissues from image data to support hypothesis generation and model testing related to the overall hypotheses of the SASCO Center.

项目摘要/总结 高内涵成像和分析核心将为SASCO中心的三个项目提供实验性的 和计算资源，通过多路荧光显微镜分析不同的生物样品 并从基于显微镜的图像中提取定量数据。核心将开发、验证和应用 高度多路复用（迭代）成像方法，整合多个亚细胞成像数据收集 迭代成像，并构建用于图像分析，特征识别和提取的定制工具。 生成的多参数数据集将满足每个项目的特定需求，使模型- 实验迭代涉及不同的癌症驱动因素，信号通路和亚细胞器， 多种生物学背景。高内涵成像和分析核心将由两名研究人员共同领导 （Fallahi-Sichani和Rohde）在多重免疫荧光成像，图像 分析和数据科学。目标#1将支持开发、验证和应用高度 多重免疫荧光染色和成像程序来测量细胞的分子特征， 亚细胞和细胞器分辨率。这些程序将使有丝分裂信号的分子分析成为可能 来源于乳腺癌类器官的中期染色体的途径和募集模式（项目 1）、结直肠癌细胞和肿瘤中的线粒体形态、细胞信号传导和代谢酶 （项目2），和关键EGFR信号分子的翻译后修饰，蛋白质-蛋白质相互作用， 及其在胶质母细胞瘤细胞中的亚细胞定位（项目3）。目标#2将定制工具， 图像分析，包括图像对齐和跟踪，细胞和亚细胞结构的分割， 以及特征提取和识别。高内涵成像和分析核心将提供所有三个 项目必要的专业知识和工具，用于量化有关细胞，培养物和组织的信息， 图像数据，以支持假设生成和模型测试有关的整体假设的 SASCO中心。