skip to main content

Attention:

The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Friday, September 13 until 2:00 AM ET on Saturday, September 14 due to maintenance. We apologize for the inconvenience.


Title: Low‐photobleaching line‐scanning confocal microscopy using dual inclined beams
Abstract

Confocal microscopy is an indispensable tool for biological imaging due to its high resolution and optical sectioning capability. However, its slow imaging speed and severe photobleaching have largely prevented further applications. Here, we present dual inclined beam line‐scanning (LS) confocal microscopy. The reduced excitation intensity of our imaging method enabled a 2‐fold longer observation time of fluorescence compared to traditional LS microscopy while maintaining a good sectioning capability and single‐molecule sensitivity. We characterized the performance of our method and applied it to subcellular imaging and three‐dimensional single‐molecule RNA imaging in mammalian cells.

 
more » « less
Award ID(s):
1805200
NSF-PAR ID:
10452496
Author(s) / Creator(s):
 ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Journal of Biophotonics
Volume:
12
Issue:
10
ISSN:
1864-063X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Confocal microscopy provides optical sectioning that is invaluable for many applications, most notably imaging into thick samples. However, the high cost of commercial confocal microscopes limits uses to specialized research and clinical settings. We present a minimalistic line-scanning confocal microscope costing less than $6,500 with optical performance comparable to a commercial laser scanning system. The optical sectioning and imaging performance are shown through measurement of the axial line-spread function and imaging of biological samples of varying thickness. Comparison is made to commercial widefield and confocal microscopes. The low cost of goods and optical sectioning capability of this microscope will allow the use of confocal microscopy in additional research and educational settings.

     
    more » « less
  2. Single-molecule super-resolution imaging is instrumental in investigating cellular architecture and organization at the nanoscale. Achieving precise 3D nanometric localization when imaging structures throughout mammalian cells, which can be multiple microns thick, requires careful selection of the illumination scheme in order to optimize the fluorescence signal to background ratio (SBR). Thus, an optical platform that combines different wide-field illumination schemes for target-specific SBR optimization would facilitate more precise 3D nanoscale studies of a wide range of cellular structures. Here, we demonstrate a versatile multimodal illumination platform that integrates the sectioning and background reduction capabilities of light sheet illumination with homogeneous, flat-field epi- and TIRF illumination. Using primarily commercially available parts, we combine the fast and convenient switching between illumination modalities with point spread function engineering to enable 3D single-molecule super-resolution imaging throughout mammalian cells. For targets directly at the coverslip, the homogenous intensity profile and excellent sectioning of our flat-field TIRF illumination scheme improves single-molecule data quality by providing low fluorescence background and uniform fluorophore blinking kinetics, fluorescence signal, and localization precision across the entire field of view. The increased contrast achieved with LS illumination, when compared with epi-illumination, makes this illumination modality an excellent alternative when imaging targets that extend throughout the cell. We validate our microscopy platform for improved 3D super-resolution imaging by two-color imaging of paxillin – a protein located in the focal adhesion complex – and actin in human osteosarcoma cells.

     
    more » « less
  3. Abstract

    Digital holographic microscopy enables the 3D reconstruction of volumetric samples from a single-snapshot hologram. However, unlike a conventional bright-field microscopy image, the quality of holographic reconstructions is compromised by interference fringes as a result of twin images and out-of-plane objects. Here, we demonstrate that cross-modality deep learning using a generative adversarial network (GAN) can endow holographic images of a sample volume with bright-field microscopy contrast, combining the volumetric imaging capability of holography with the speckle- and artifact-free image contrast of incoherent bright-field microscopy. We illustrate the performance of this “bright-field holography” method through the snapshot imaging of bioaerosols distributed in 3D, matching the artifact-free image contrast and axial sectioning performance of a high-NA bright-field microscope. This data-driven deep-learning-based imaging method bridges the contrast gap between coherent and incoherent imaging, and enables the snapshot 3D imaging of objects with bright-field contrast from a single hologram, benefiting from the wave-propagation framework of holography.

     
    more » « less
  4. Confocal microscopy is a standard approach for obtaining volumetric images of a sample with high axial and lateral resolution, especially when dealing with scattering samples. Unfortunately, a confocal microscope is quite expensive compared to traditional microscopes. In addition, the point scanning in confocal microscopy leads to slow imaging speed and photobleaching due to the high dose of laser energy. In this paper, we demonstrate how the advances in machine learning can be exploited to teach a traditional wide-field microscope, one that’s available in every lab, into producing 3D volumetric images like a confocal microscope. The key idea is to obtain multiple images with different focus settings using a wide-field microscope and use a 3D generative adversarial network (GAN) based neural network to learn the mapping between the blurry low-contrast image stacks obtained using a wide-field microscope and the sharp, high-contrast image stacks obtained using a confocal microscope. After training the network with widefield-confocal stack pairs, the network can reliably and accurately reconstruct 3D volumetric images that rival confocal images in terms of its lateral resolution, z-sectioning and image contrast. Our experimental results demonstrate generalization ability to handle unseen data, stability in the reconstruction results, high spatial resolution even when imaging thick (∼40 microns) highly-scattering samples. We believe that such learning-based microscopes have the potential to bring confocal imaging quality to every lab that has a wide-field microscope.

     
    more » « less
  5. Vitreous collagen structure plays an important role in ocular mechanics. However, capturing this structure with existing vitreous imaging methods is hindered by the loss of sample position and orientation, low resolution, or a small field of view. The objective of this study was to evaluate confocal reflectance microscopy as a solution to these limitations. Intrinsic reflectance avoids staining, and optical sectioning eliminates the requirement for thin sectioning, minimizing processing for optimal preservation of the natural structure. We developed a sample preparation and imaging strategy usingex vivogrossly sectioned porcine eyes. Imaging revealed a network of uniform diameter crossing fibers (1.1 ± 0.3 µm for a typical image) with generally poor alignment (alignment coefficient = 0.40 ± 0.21 for a typical image). To test the utility of our approach for detecting differences in fiber spatial distribution, we imaged eyes every 1 mm along an anterior-posterior axis originating at the limbus and quantified the number of fibers in each image. Fiber density was higher anteriorly near the vitreous base, regardless of the imaging plane. These data demonstrate that confocal reflectance microscopy addresses the previously unmet need for a robust, micron-scale technique to map features of collagen networksin situacross the vitreous.

     
    more » « less