权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

A hyperspectral microscope optimized for spectrally multiplexed live cell imaging

针对光谱多重活细胞成像进行优化的高光谱显微镜

基本信息

批准号：
7997202
负责人：
Keith A Lidke
金额：
$ 16.68万
依托单位：
UNIVERSITY OF NEW MEXICO
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-02-01 至 2012-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7997202
关键词：
Affinity Algorithms Behavior Biological Cancer Center Cell Surface Receptors Cells Color Custom Data Data Analyses Data Set Development Electrons Environment Fluorescence Fluorescent Probes Funding Goals Homo Housing IgE IgE Receptors Image Immune system Integral Membrane Protein Knowledge Label Laboratories Lasers Length Life Light Malignant Neoplasms Membrane Membrane Proteins Microscope Motion New Mexico Optics Performance Photobleaching Physics Process Proteins Quantum Dots Reagent Receptor Activation Reporting Research Personnel Resolution Sampling Scanning Signal Pathway Signal Transduction Spatial Distribution Speed System Techniques Time Universities base cellular imaging charge coupled device camera computing resources crosslink design fluorescence microscope improved insight instrument particle protein protein interaction public health relevance receptor

项目摘要

DESCRIPTION (provided by applicant): This project is the development of a fluorescence hyperspectral microscope. A hyperspectral microscope collects a broad region of the spectrum with high spectral resolution in every sampled spatial volume. This microscope will improve and optimize the design of a Sandia National Laboratories designed hyperspectral microscope that incorporates a high throughput prism spectrometer and state of the art electron multiplied CCD cameras. Optimizations will include a focus on speed, with a target of full spectral imaging at 30 Hz, and will be based on a commercial inverted microscope to allow standard accessories and practices used for live cell imaging. High spectral resolution will allow separation of up to eight spectrally distinct quantum dots, which due to their broad excitation spectra can be excited simultaneously with a 488 nm laser. Spectral separation combined with the ability of single particle tracking to localize single particles to less than 10 nm will allow the observation of either hetero or homo protein-protein interactions at length scales close to 10 nm, much less than the 250 nm resolution of a fluorescence microscope. The project will begin with a redesign of the Sandia hyperspectral microscope to incorporate line scanning for optimal speed. Analysis techniques will be developed to utilize knowledge about the single particle, diffraction limited spatial signature of the probes to enhance spectral separation and localization. The first application will be to study the dynamic homo-interaction between the membrane protein FceRI. The microscope will be developed and housed in a laboratory in the University of New Mexico physics department, and after construction, is expected to be heavily used by researchers of the UNM cancer centers. Public Health Relevance Statement: This project will fund the development of a 'fluorescence hyperspectral microscope' that will make use of new fluorescent probes (quantum dots) and spectral multiplexing to observe the dynamics of protein-protein interactions at the 10 nm scale. Data generated with this instrument is expected to give new insight into cellular signaling pathways, including those involved in the immune system and cancer.

项目描述（申请人提供）：本项目是荧光高光谱显微镜的开发。高光谱显微镜在每个采样空间体积中以高光谱分辨率收集光谱的宽区域。该显微镜将改进和优化桑迪亚国家实验室设计的高光谱显微镜的设计，该显微镜采用了高通量棱镜光谱仪和最先进的电子倍增CCD相机。优化将包括专注于速度，目标是在30 Hz下进行全光谱成像，并将基于商业倒置显微镜，以允许用于活细胞成像的标准配件和实践。高光谱分辨率将允许分离多达八个光谱上不同的量子点，由于它们的宽激发光谱，可以用488 nm激光同时激发。光谱分离结合单粒子跟踪定位单个粒子到小于10 nm的能力，将允许在接近10 nm的长度尺度上观察异质或同质蛋白质-蛋白质相互作用，远小于荧光显微镜的250 nm分辨率。该项目将开始重新设计的桑迪亚高光谱显微镜，以纳入线扫描的最佳速度。将开发分析技术，以利用有关探针的单粒子、衍射限制空间特征的知识，增强光谱分离和定位。第一个应用将是研究膜蛋白FceRI之间的动态同源相互作用。该显微镜将在新墨西哥州大学物理系的一个实验室内开发和安装，建成后，预计将被UNM癌症中心的研究人员大量使用。公共卫生相关性声明：该项目将资助“荧光高光谱显微镜”的开发，该显微镜将利用新的荧光探针（量子点）和光谱多路复用来观察10 nm尺度下蛋白质-蛋白质相互作用的动态。该仪器产生的数据有望为细胞信号通路提供新的见解，包括参与免疫系统和癌症的信号通路。