Image-based single cell analysis is essential to study gene expression levels and subcellular functions with preserving the native spatial locations of biomolecules. However, its low throughput has prevented its wide use to fundamental biology and biomedical applications which require large cellular populations in a rapid and efficient fashion. Here, we report a 2.5D microcopy (2.5DM) that significantly improves the image acquisition rate while maintaining high-resolution and single molecule sensitivity. Unlike serial z-scanning in conventional approaches, volumetric information is simultaneously projected onto a 2D image plane in a single shot by engineering the fluorescence light using a novel phase pattern. The imaging depth can be flexibly adjusted and multiple fluorescent markers can be readily visualized. We further enhance the transmission efficiency of 2.5DM by ~2-fold via configuring the spatial light modulator used for the phase modulation in a polarization-insensitive manner. Our approach provides a uniform focal response within a specific imaging depth, allowing to perform quantitative high-throughput single-molecule RNA measurements for mammalian cells over a 2 x 2 mm2 region within an imaging depth of ~5 µm in less than 10 min and immunofluorescence imaging at a volumetric imaging rate of > 30 Hz with significantly reduced light exposure. With implementation of an adaptive element, our microscope provides an extra degree of freedom in correcting aberrations induced by specimens and optical components, showing its capability of imaging thick specimens with high-fidelity of preserving volumetric information with fast imaging speed. We also demonstrate multimodal imaging that can be switched from 2.5DM to a 3D single-molecule localization imaging platform by encoding the depth information of each emitter into the shape of point spread function, which enables us to obtain a resolution of < 50 nm. Our microscope offers multi-functional capability from fast volumetric high-throughput imaging, multi-color imaging to super-resolution imaging.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1747 |
Date | 01 January 2021 |
Creators | Ren, Jinhan |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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