High spatiotemporal optical imaging to study dynamics of 3D cell motion and behavior in living organisms

高时空光学成像用于研究活体生物体中 3D 细胞运动和行为的动力学

• 批准号: 10715637
• 负责人: Juhyun Lee
• 金额: $ 37.54万
• 依托单位: UNIVERSITY OF TEXAS ARLINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10715637
• 关键词: 3-Dimensional; Algorithms; Behavior; Behavioral; Biomedical Research; Cell Shape; Cell Size; Cell model; Cell physiology; Cells; Cellular biology; Dependence; Dimensions; Ensure; Evaluation; Event; Fluorescence; Functional disorder; Histopathology; Image; Imaging Device; Imaging Techniques; Individual; Lateral; Light; Maximum Likelihood Estimate; Microscope; Microscopic; Microscopy; Modality; Monitor; Morphogenesis; Morphology; Motion; Noise; Optics; Organism; Organogenesis; Outcome; Phenotype; Research Personnel; Resolution; Signal Transduction; Techniques; Technology; Tissues; Training; attenuation; automated segmentation; cell behavior; cell motility; cellular imaging; deep learning; detector; high resolution imaging; improved; in vivo; in vivo monitoring; learning network; lens; mechanical stimulus; migration; millimeter; nanometer; nanometer resolution; nanoscale; next generation; novel; optical imaging; response; restoration; sensor; spatiotemporal; temporal measurement; ultra high resolution

PROJECT SUMMARY/ABSTRACT Behavioral analysis of individual cells that determines the structural phenotypes in response to the mechanical stimuli or cell migration is important in organogenesis or tissue morphogenesis. Dynamic cell tracking, migration trajectory monitoring, or temporal changes in cell shape or size are essential for modeling cellular interactions. However, optical limits imposed by microscope objective lenses and light attenuation in tissue hinder high- resolution evaluation of cell physiology on the dimension scale of μm to nm. Hence, several super-resolution fluorescence modalities have been developed in recent years to enable nanoscale tissue characterization and less damage to tissue histopathology. On the other hand, isotropic nanometer optical resolution for super- resolution modalities is restricted to micron scale field-of-view (FOV). This physical limitation reflects in vivo characterization up to cellular events only. Therefore, we propose to develop an advanced optical imaging technique to achieve sub-cellular resolution, while providing user capability to modulate millimeter to centimeter FOV for in vivo monitoring. Light-sheet fluorescent microscopy (LSFM) has emerged as a popular optical sectioning modality in biomedical research, owing to rapid camera frame rates in conjunction with long working distance excitation optics. Although LSFM provides intermediate-to-high resolution images, the resolution is highly dependent on the confocal range of the excitation objective. To overcome this challenge, we propose to apply the rolling shutter (RS) based-axially sweeping LSFM technique to de-couple the dependence of light sheet FOV on excitation numerical aperture (NA). RS is a type of image capture in sCMOS camera that record the frame line by line on an image sensor instead of capturing the entire frame all at once to improve signal-to-noise, but it can create some unintended image distortions. Thus, we will incorporate the application of maximum likelihood estimation as a post-acquisition restoration strategy to remove optical distortions introduced by RS image acquisition to ensure isotropic lateral and axial nanometer resolution. After the acquisition, we will segment and extract information on cell motion and morphology using a feature detector framework based on the Hessian difference of Gaussian in combination with the watershed algorithm. The feature detector has been validated to separate adjacent clustered cells in 3D undergoing rapid motion with high sensitivity. In addition, we will further train our segmented cell images for deep-learning network and use for automatic segmentation and tracking. The proposed microscopic technology will enable the quantitative characterization of cellular behavior effectively in arbitrary FOV.

项目总结/文摘