Optimal four-dimensional imaging requires high spatial resolution in all dimensions, high speed and minimal photobleaching and damage. We developed a dual-view, plane illumination microscope with improved spatiotemporal resolution by switching illumination and detection between two perpendicular objectives in an alternating duty cycle. Computationally fusing the resulting volumetric views provides an isotropic resolution of 330 nm. As the sample is stationary and only two views are required, we achieve an imaging speed of 200 images/s (i.e., 0.5 s for a 50-plane volume). Unlike spinning-disk confocal or Bessel beam methods, which illuminate the sample outside the focal plane, we maintain high spatiotemporal resolution over hundreds of volumes with negligible photobleaching. To illustrate the ability of our method to study biological systems that require high-speed volumetric visualization and/or low photobleaching, we describe microtubule tracking in live cells, nuclear imaging over 14 h during nematode embryogenesis and imaging of neural wiring during Caenorhabditis elegans brain development over 5 h.

The Caenorhabditis elegans embryo is a powerful model for studying neural development, but conventional imaging methods are either too slow or phototoxic to take full advantage of this system. To solve these problems, we developed an inverted selective plane illumination microscopy (iSPIM) module for noninvasive high-speed volumetric imaging of living samples. iSPIM is designed as a straightforward add-on to an inverted microscope, permitting conventional mounting of specimens and facilitating SPIM use by development and neurobiology laboratories. iSPIM offers a volumetric imaging rate 30× faster than currently used technologies, such as spinning-disk confocal microscopy, at comparable signal-to-noise ratio. This increased imaging speed allows us to continuously monitor the development of C, elegans embryos, scanning volumes every 2 s for the 14-h period of embryogenesis with no detectable phototoxicity. Collecting ∼25,000 volumes over the entirety of embryogenesis enabled in toto visualization of positions and identities of cell nuclei. By merging two-color iSPIM with automated lineaging techniques we realized two goals: (i) identification of neurons expressing the transcription factor CEH-10/Chx10 and (ii) visualization of their neurodevelopmental dynamics. We found that canal-associated neurons use somal translocation and amoeboid movement as they migrate to their final position in the embryo. We also visualized axon guidance and growth cone dynamics as neurons circumnavigate the nerve ring and reach their targets in the embryo. The high-speed volumetric imaging rate of iSPIM effectively eliminates motion blur from embryo movement inside the egg case, allowing characterization of dynamic neurodevelopmental events that were previously inaccessible.fast 4D imaging | axon growth | neuron migration P roper neural circuit assembly requires the coordinated execution of multiple events, including cell migration, axon guidance, and synaptogenesis (1, 2). During neurodevelopment, these events are orchestrated between pre-and postsynaptic partners, resulting in the correct wiring of the nervous system. The mechanisms that enable proper wiring in vivo are not well understood.Caenorhabditis elegans provides an excellent model to understand how neural circuit assembly occurs in vivo. With only 302 neurons, ∼7,000 synapses, and an available and comprehensive neural connectivity map (3), the nervous system of C. elegans is well characterized and relatively simple. The molecular mechanisms that control neurodevelopmental decisions in the nematode are well conserved throughout evolution (4), and several genetic programs that control terminal differentiation of neuronal identity were first identified and characterized in C. elegans (5, 6). Studies in C. elegans have also significantly contributed to our understanding of neuroblast migration and axon guidance (7,8).

Reassortment of influenza viral RNA (vRNA) segments in co-infected cells can lead to the emergence of viruses with pandemic potential. Replication of influenza vRNA occurs in the nucleus of infected cells, while progeny virions bud from the plasma membrane. However, the intracellular mechanics of vRNA assembly into progeny virions is not well understood. Here we used recent advances in microscopy to explore vRNA assembly and transport during a productive infection. We visualized four distinct vRNA segments within a single cell using fluorescent in situ hybridization (FISH) and observed that foci containing more than one vRNA segment were found at the external nuclear periphery, suggesting that vRNA segments are not exported to the cytoplasm individually. Although many cytoplasmic foci contain multiple vRNA segments, not all vRNA species are present in every focus, indicating that assembly of all eight vRNA segments does not occur prior to export from the nucleus. To extend the observations made in fixed cells, we used a virus that encodes GFP fused to the viral polymerase acidic (PA) protein (WSN PA-GFP) to explore the dynamics of vRNA assembly in live cells during a productive infection. Since WSN PA-GFP colocalizes with viral nucleoprotein and influenza vRNA segments, we used it as a surrogate for visualizing vRNA transport in 3D and at high speed by inverted selective-plane illumination microscopy. We observed cytoplasmic PA-GFP foci colocalizing and traveling together en route to the plasma membrane. Our data strongly support a model in which vRNA segments are exported from the nucleus as complexes that assemble en route to the plasma membrane through dynamic colocalization events in the cytoplasm.

No abstract

We describe the construction and use of a compact dual-view inverted selective plane illumination microscope (diSPIM) for time-lapse volumetric (4D) imaging of living samples at subcellular resolution. Our protocol enables a biologist with some prior microscopy experience to assemble a diSPIM from commercially available parts, to align optics and test system performance, to prepare samples, and to control hardware and data processing with our software. Unlike existing light sheet microscopy protocols, our method does not require the sample to be embedded in agarose; instead, samples are prepared conventionally on glass coverslips. Tissue culture cells and Caenorhabditis elegans embryos are used as examples in this protocol; successful implementation of the protocol results in isotropic resolution and acquisition speeds up to several volumes per s on these samples. Assembling and verifying diSPIM performance takes ~6 d, sample preparation and data acquisition take up to 5 d and postprocessing takes 3–8 h, depending on the size of the data.

We demonstrate residual channel attention networks (RCAN) for restoring and enhancing volumetric time-lapse (4D) fluorescence microscopy data. First, we modify RCAN to handle image volumes, showing that our network enables denoising competitive with three other state-of-the-art neural networks. We use RCAN to restore noisy 4D super-resolution data, enabling image capture over tens of thousands of images (thousands of volumes) without apparent photobleaching. Second, using simulations we show that RCAN enables class-leading resolution enhancement, superior to other networks. Third, we exploit RCAN for denoising and resolution improvement in confocal microscopy, enabling ~2.5-fold lateral resolution enhancement using stimulated emission depletion (STED) microscopy ground truth. Fourth, we develop methods to improve spatial resolution in structured illumination microscopy using expansion microscopy ground truth, achieving improvements of ~1.4-fold laterally and ~3.4-fold axially. Finally, we characterize the limits of denoising and resolution enhancement, suggesting practical benchmarks for evaluating and further enhancing network performance.data, which we deconvolved to yield high SNR 'ground truth'. We then used 30 of these volumes for training and held out volumes for testing network performance. Using the same training and test data, we compared four networks: RCAN, CARE, SRResNET 20 , and ESRGAN 21 . SRResNet and ESRGAN are both class-leading deep residual networks used in image super-resolution, with ESRGAN winning the 2018 Perceptual Image Restoration and Manipulation challenge on perceptual image super-resolution 22 .For the mEmerald-Tomm20 label, RCAN, CARE, ESRGAN, and SRResNET predictions all provided 88 clear improvements in visual appearance, structural similarity index (SSIM) and peak signal-to-noise-89 ratio (PSNR) metrics relative to the raw input (Fig. 1b), also outperforming direct deconvolution on the noisy input data (Supplementary Fig. 1). The RCAN output provided PSNR and SSIM values competitive with the other networks (Fig. 1b), prompting us to investigate whether this performance held for other organelles. We thus conducted similar experiments for fixed U2OS cells with labeled actin, endoplasmic reticulum (ER), golgi, lysosomes, and microtubules (Supplementary Fig. 2), acquiring 15-23 volumes of training data and training independent networks for each organelle. In almost all cases, RCAN performance met or exceeded the other networks (Supplementary Fig. 3, Supplementary Table 3).An essential consideration when using any deep learning method is understanding when network performance deteriorates. Independently training an ensemble of networks and computing measures of network disagreement can provide insight into this issue 9,16 , yet such measures were not generally predictive of disagreement between ground truth and RCAN output (Supplementary Fig. 4). Instead, we found that estimating the per-pixel SNR in the raw input (Methods, Supplementary Fig. 4) seemed to better correlate with network ...

No abstract

Autofluorescence of rabbit and human epithelial tissues were studied by using a depth-resolved fluorescence spectroscopy system with multiple excitations. Keratinization was found to be common in the squamous epithelium. Strong keratin fluorescence with excitation and emission characteristics similar to collagen were observed in the topmost layer of the keratinized squamous epithelium. The keratin signal created interference in the assessment of the endogenous fluorescence signals (NADH/FAD fluorescence in epithelium and collagen fluorescence in stroma) associated with the development of epithelial precancer. Furthermore, the keratinized epithelial layer attenuated the excitation light and reduced the fluorescence signals from underlying tissue layers. The autofluorescence of columnar epithelium was found to be dominated by NADH and FAD signals, identical to the autofluorescence measured from nonkeratinized squamous epithelium. The study also demonstrated that a fluorescence signal excited at 355 nm produced sufficient contrast to resolve the layered structure of epithelial tissue, while the signal excited at 405 nm provided the information for a good estimation of epithelial redox ratios that are directly related to tissue metabolism. Overall, the depth-resolved measurements are crucial to isolate the fluorescence signals from different sublayers of the epithelial tissue and provide more accurate information for the tissue diagnosis.