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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.

项目总结