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Adaptive Tracking and Quantum Imaging for Protein-Protein Interactions

蛋白质-蛋白质相互作用的自适应跟踪和量子成像

基本信息

批准号：
10706952
负责人：
Francisco Elohim Becerra Chavez
金额：
$ 49.39万
依托单位：
UNIVERSITY OF NEW MEXICO
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-21 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10706952
关键词：
Algorithms Area Bayesian Analysis Bayesian Method Binding Biomedical Research Blinking Cell membrane Cell physiology Cells Collaborations Color Computer software Data Data Analyses Detection Development Diffuse Diffusion Disease Dyes Feedback Goals Hypersensitivity Image Kinetics Label Libraries Light Lighting Malignant Neoplasms Markov Chains Measurement Measures Membrane Proteins Methods Microscope Microscopy Noise Optics Paper Parameter Estimation Pattern Phase Photobleaching Photons Process Proteins Publishing Pythons Quantum Dots Recording of previous events Reporting Research Personnel Resolution Sampling Scheme Signal Transduction Source Speed Techniques Technology Time Toxic effect Uncertainty Visualization active control biological systems density dimer fluorophore heterodyning imaging approach imaging modality imaging system improved innovation molecular imaging movie novel particle protein protein interaction quantum single molecule technology development ultra high resolution

项目摘要

Project Summary This project describes a technology development effort that will generate three complementary methods for measuring Protein-Protein Interaction (PPI) kinetic rates between membrane proteins. In Aim 1, we develop a new algorithmic approach for single-particle tracking analysis that generates trajectories from image/movie data. It is based on Bayesian inference strategy. We then extend this to extracting kinetic rates of PPIs from two color single particle tracking data. In Aim 2, we develop a ‘smart’ microscope that is capable of adapting illumination and frame rates when a PPI is imminent (particles diffuse close to each other), thereby reducing photobleaching, allowing long-term tracking with organic fluorophores and gaining a factor of 10 to 50 in imaging speed during an interaction. In Aim 3 we implement and demonstrate a ‘quantum imaging’ approach for making a quantum optimal estimation of the distance between two fluorophores of the same type. This method can estimate the distance between incoherent point sources with an uncertainty in the distance measurement near the limit of any possible measurement and substantially better than classical image-then-estimate approaches. In practice, it gives the benefits of two-color tracking using a simplified one-color labeling scheme. Direct detection of PPIs at the single molecule level in living cells is difficult because labeling must be done at densities low enough for single fluorescent labels to be identified and detected with diffraction limited optics. Since molecules must come into contact with each other to initiate a PPI, often through diffusion limited processes, the observed interactions can be temporally rare. The new methods proposed here will allow for other fluorophores, including organic dyes and fluorescent proteins, to be used to quantify PPIs. Our long-term goal is to provide a set of methods that can report on the dynamics of various types of PPIs. The rationale for the proposed Aims is that by providing these new methods, a wider range of PPIs can be studied on living cells, opening new doors for biomedical research. This technology development project is a collaboration between three investigators with complementary expertise. K. Lidke (PI) is an expert on single molecule imaging and microscopy development. F. Becerra (co-PI) is a world leader in the area of ultra-sensitive measurements of coherent states of light using optimized photon counting measurements with fast feedback. D. Lidke (co-I) has developed and applied innovative single molecule techniques to quantify PPI in living cells.

项目概要该项目描述了一项技术开发工作，它将产生三种互补的方法测量膜蛋白之间的蛋白质-蛋白质相互作用 (PPI) 动力学速率。在目标 1 中，我们开发了用于单粒子跟踪分析的新算法方法，可从图像/电影生成轨迹数据。它基于贝叶斯推理策略。然后我们将其扩展到从中提取 PPI 的动力学速率两种颜色的单粒子跟踪数据。在目标 2 中，我们开发了一种“智能”显微镜，能够适应 PPI 即将到来时的照明和帧速率（粒子扩散到彼此附近），从而减少光漂白，允许使用有机荧光团进行长期追踪，并获得 10 至 50 倍的光漂白效果交互过程中的成像速度。在目标 3 中，我们实施并演示了“量子成像”方法用于对相同类型的两个荧光团之间的距离进行量子最优估计。这方法可以估计距离不确定的非相干点源之间的距离测量接近任何可能测量的极限，并且明显优于经典测量图像然后估计方法。在实践中，它提供了使用简化的双色跟踪的好处单色标签方案。在活细胞中直接检测单分子水平的 PPI 很困难，因为标记必须在密度足够低，可以用衍射限制光学器件识别和检测单个荧光标记。由于分子必须相互接触才能引发 PPI，通常是通过有限扩散过程中，观察到的相互作用可能暂时很少见。这里提出的新方法将允许其他荧光团，包括有机染料和荧光蛋白，用于量化 PPI。我们的长期目标是提供一组可以报告各种类型 PPI 动态的方法。理由拟议的目标是通过提供这些新方法，可以在生活中研究更广泛的 PPI 细胞，为生物医学研究打开了新的大门。该技术开发项目是三位研究人员之间的合作，互补性强专业知识。 K. Lidke (PI) 是单分子成像和显微镜开发方面的专家。 F·贝塞拉 (co-PI) 是使用优化的光相干态超灵敏测量领域的世界领先者具有快速反馈的光子计数测量。 D. Lidke (co-I) 开发并应用了创新型单量化活细胞中 PPI 的分子技术。