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.

项目摘要该项目描述了一项技术开发工作，该工作将为测量膜蛋白之间的蛋白质蛋白相互作用（PPI）动力学速率。在AIM 1中，我们开发了一个单粒子跟踪分析的新算法方法，从图像/电影产生轨迹数据。它基于贝叶斯推论策略。然后，我们将其扩展到从中提取PPI的动力学速率两个颜色的单粒子跟踪数据。在AIM 2中，我们开发了一个能够适应的“智能”显微镜当PPI即将到来（粒子彼此弥漫）时，照明和帧速率，从而减少光漂白，允许使用有机荧光团的长期跟踪，并获得10至50倍互动过程中的成像速度。在AIM 3中，我们实施并演示了“量子成像”方法用于对同一类型的两个荧光团之间的距离进行量子最佳估计。这方法可以估计距离不确定性的不一致点源之间的距离测量接近任何可能的测量的极限，并且比经典的测量要好得多图像 - 然后使用的方法。实际上，它使用简化的单色标记方案。在活细胞中的单分子水平上直接检测PPI很难在密度足够低，可以通过衍射有限的光学元件识别并检测到单个荧光标签。由于分子必须相互接触才能引发PPI，通常是通过扩散限制过程，观察到的相互作用可能暂时罕见。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，用于定量PPI。我们的长期目标是提供一组可以报告各种PPI的动态的方法。理由拟议的目的是，通过提供这些新方法，可以研究更广泛的PPI 细胞，为生物医学研究打开新的门。该技术开发项目是三名调查员之间的合作专业知识。 K. Lidke（PI）是单分子成像和显微镜开发的专家。 F. Becerra （Co-Pi）是使用优化的相干状态的超敏感测量领域的世界领导者具有快速反馈的光子计数测量值。 D. Lidke（Co-I）已开发和应用创新单一分子技术来量化活细胞中的PPI。