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Subcellular Resolution Light Sheet Microscope with a Large Field of View

大视场亚细胞分辨率光片显微镜

基本信息

批准号：
10025178
负责人：
Yang Liu
金额：
$ 3.98万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-23 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10025178
关键词：
3-Dimensional Algorithms Animal Model Area Axon Biological Brain Caliber Computer software Computers Custom Detection Dimensions Drosophila genus Electrophysiology (science)Fertilization Filopodia Fluorescence Microscopy Fluorescent Dyes Fruit Goals Health Hour Human Image Individual Institutes Larva Lateral Lead Light Lighting Materials Testing Measurement Measures Medical Methods Microscope Microscopy Midbrain structure Monitor Morphologic artifacts Muscle Nature Nervous system structure Neuraxis Neurologic Neurosciences Performance Photic Stimulation Problem Solving Procedures Process Research Resolution Sampling Speed Structure Subcellular structure Synapses System Techniques Testing Thick Time Zebrafish base biological systems cost cost effective design experimental study fluorescence microscope imaging system improved instrument lens nervous system disorder neural network novel novel strategies optical lattices postsynaptic reconstruction relating to nervous system virtual

项目摘要

PROJECT SUMMARY The ability to capture large regions of the neural network in living model organisms such as zebrafish and fruit flies at a subcellular scale will further advance neurological research. In this project, we aim to provide a microscopy platform that is able to capture images of a 286 to 300 micron area of the nervous system in living zebrafish and fruit files at subcellular resolution. We plan to combine super-resolution techniques with light sheet fluorescence microscopy to accomplish this goal. Aim 1 combines super-resolution structured illumination microscopy (SR-SIM) with multi-direction illumination light sheet fluorescence microscopy in a single objective configuration. We expect that the system should be able to achieve a resolution of 161nm in all lateral directions, and axial resolution of 458nm and 916nm in 3D SR-SIM mode and 2D SR-SIM mode, respectively. We expect that the proposed method will provide a highly detailed image of the entire midbrain structure and activity in 6 to 7 week post-fertilization zebrafish larvae. Aim 2 will achieve isotropic resolution at subcellular level (241nm lateral, 336nm axial) while maintaining a 286 to 300 micron field of view. We expect that the proposed method will result in the capability to image dynamics of postsynaptic filopodia across multiple muscle groups over a long period of time (longer than 1 hour). Aim 3 will develop a novel computer reconstruction algorithm to boost the effective frame rate and alleviate the artifacts in the resulting image. In the final result, we expect to see a 20% decrease in artifacts and an increase in speed by a factor of 3.

项目总结