High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
基本信息
- 批准号:7905666
- 负责人:
- 金额:$ 29.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2008
- 资助国家:美国
- 起止时间:2008-08-01 至 2012-07-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAntibodiesBiologyCell membraneCell physiologyCellsCellular biologyDataDetectionDevelopmentDevicesDimensionsDisadvantagedDiscriminationEarly EndosomeEndocytosisEndocytosis PathwayEndosomesEndothelial CellsEventExocytosisFluorescence MicroscopyGlassImageImmunoglobulin GIn VitroIndividualInvestigationLabelLeadLifeLightingLocationMedicineMethodologyMicroscopeMicroscopyModalityModelingMonitorNIH Program AnnouncementsNanotechnologyNational Institute of General Medical SciencesOpticsPathway interactionsPharmaceutical PreparationsPhotobleachingPopulationPositioning AttributeProcessProteinsQuantum DotsRecyclingResearch PersonnelResolutionSamplingSorting - Cell MovementSourceSubcellular structureTechnologyTestingTherapeuticThree-dimensional analysisTimeVesicleanalytical methodanalytical toolbaseexpectationimaging modalityimprovedin vivoinsightmacromoleculemethod developmentnanoscalenanosciencenew technologynovelpreventpublic health relevanceresponsesingle moleculethree dimensional structuretooltrafficking
项目摘要
DESCRIPTION (provided by applicant): The elucidation of intracellular trafficking pathways is a major challenge in cell biology and promises to lead to significant new insights into basic cellular processes. The advances in single molecule methodologies hold the expectation that the trafficking mechanisms for proteins/macromolecules can be unraveled not only for bulk populations, but even at the level of individual molecules. Due to the photo-stability of quantum dots (QDs) it is possible to observe QD-labeled molecules for extended observation periods, which is necessary to follow intracellular pathways of individual molecules. However, current microscopy modalities are not well suited to address problems related to intracellular trafficking in three dimensions. Whereas classical microscopes image one focal plane at a time, cells are three dimensional objects and the trafficking pathways are not typically restricted to one focal plane. This, combined with the fact that the dynamics are often very fast, means that detailed trafficking studies are often not possible since the pathways cannot be captured. A further significant problem is the low depth discrimination capability of a classical microscope. This means that from an image it is very difficult to determine the three dimensional position of an object such as a QD-labeled single molecule. This makes it highly problematic to study in detail processes such as the pathway from endocytosis to early endosome or the pathway from sorting endosome to exocytosis. To address these problems we have recently developed a new imaging modality with which different focal planes can be imaged at the same time. This modality includes the capability to image events at the plasma membrane with total internal reflection fluorescence microscopy, whilst simultaneously capturing processes in the interior of the cell using epifluorescence mode in higher focal planes. Using this approach QD-labeled proteins can be imaged as they follow a three dimensional pathway through a cell. Equally important is the promise that the depth discrimination problem can be overcome with this approach. A central aspect of this project will be to develop algorithms with which the three dimensional location of a single molecule can be identified. The proposed approaches will be tested on an important trafficking problem, i.e. the intracellular trafficking, endocytosis and exocytosis of QD-labeled immunoglobulin G molecules. Our Specific aims are: 1. To develop analytical tools to determine the 3D location of a QD-labeled protein in a cell. 2. To analyze how accurately the 3D position of a QD labeled protein can be determined. 3. To test the proposed algorithms on experimental data. PUBLIC HEALTH RELEVANCE: We propose to develop a new technology for the imaging of living cells. This technology promises to overcome significant limitations in existing approaches which have to date prevented researchers from studying central aspects of the functioning of cells. The new technology will permit investigations that are important to increase our understanding of how cells function. Significantly, this technology will also improve the tools that researchers have available to investigate how a rapidly expanding class of therapeutics, namely antibody-based drugs, interact with cells.
描述(由申请人提供):细胞内运输途径的阐明是细胞生物学中的主要挑战,并有望导致对基本细胞过程的重要新见解。单分子方法学的进展使人们期望不仅可以解开大分子群体的蛋白质/大分子的运输机制,甚至可以在单个分子的水平上解开。由于量子点(QD)的光稳定性,可以在延长的观察期内观察QD标记的分子,这对于跟踪单个分子的细胞内途径是必要的。然而,目前的显微镜模式不太适合于解决与细胞内贩运的三个维度的问题。尽管经典显微镜一次成像一个焦平面,但细胞是三维物体,并且运输途径通常不限于一个焦平面。这一点,再加上动态往往非常迅速,意味着往往不可能进行详细的贩运研究,因为无法掌握贩运途径。另一个重要的问题是传统显微镜的深度分辨能力低。这意味着从图像中很难确定物体(例如QD标记的单分子)的三维位置。这使得详细研究诸如从内吞作用到早期内体的途径或从分选内体到胞吐作用的途径等过程成为高度问题。为了解决这些问题,我们最近开发了一种新的成像方式,不同的焦平面可以同时成像。这种模式包括能够在质膜与全内反射荧光显微镜的图像事件,同时捕捉过程中的细胞内部使用epifluorescence模式在更高的焦平面。使用这种方法,量子点标记的蛋白质可以成像,因为它们遵循三维途径通过细胞。同样重要的是,这种方法可以克服深度歧视问题。该项目的一个中心方面将是开发算法,可以识别单个分子的三维位置。所提出的方法将测试一个重要的贩运问题,即细胞内的运输,内吞和胞吐的量子点标记的免疫球蛋白G分子。我们的具体目标是:1。开发分析工具,以确定细胞中QD标记蛋白质的3D位置。2.分析如何准确地确定QD标记的蛋白质的3D位置。3.在实验数据上测试所提出的算法。公共卫生相关性:我们建议开发一种新的活细胞成像技术。这项技术有望克服现有方法的重大局限性,这些局限性迄今为止一直阻碍研究人员研究细胞功能的核心方面。这项新技术将允许进行重要的研究,以增加我们对细胞功能的理解。值得注意的是,这项技术还将改善研究人员现有的工具,以研究快速扩展的一类疗法,即基于抗体的药物如何与细胞相互作用。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
RAIMUND J OBER其他文献
RAIMUND J OBER的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('RAIMUND J OBER', 18)}}的其他基金
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
8728931 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
8578477 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
7514587 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
8118982 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
7667217 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
High accuracy quantum dot tracking in live cells
活细胞中的高精度量子点追踪
- 批准号:
8962334 - 财政年份:2008
- 资助金额:
$ 29.83万 - 项目类别:
相似海外基金
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
- 批准号:
2337776 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
- 批准号:
2338816 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
- 批准号:
2338846 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
- 批准号:
2348261 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
- 批准号:
2348457 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
- 批准号:
2404989 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
- 批准号:
2339310 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
- 批准号:
2339669 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Continuing Grant
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
- 批准号:
EP/Y029089/1 - 财政年份:2024
- 资助金额:
$ 29.83万 - 项目类别:
Research Grant