Optical sectioning deep inside live embryos by selective plane illumination microscopy

Challenges and advances in optical 3D mesoscale imaging

Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.

Bessel-beam illumination Raman microscopy

We demonstrate the use of Bessel beams for side illumination slit-scanning Raman imaging for label-free and hyperspectral analysis of cell spheroids. The background elimination by the side illumination and the aberration-resistant Bessel beam drastically improves the image contrast in Raman observation, allowing label-free investigation of intracellular molecules in thick biological samples. Live cell spheroids were observed to confirm the improvement in image contrast and background reduction with Bessel illumination compared to conventional epi-line illumination.

Analytical Approaches for the Segmentation of the Zebrafish Brain Vasculature

With advancements in imaging techniques, data visualization allows new insights into fundamental biological processes of development and disease. However, although biomedical science is heavily reliant on imaging data, interpretation of datasets is still often based on subjective visual assessment rather than rigorous quantitation. This overview presents steps to validate image processing and segmentation using the zebrafish brain vasculature data acquired with light sheet fluorescence microscopy as a use case. Blood vessels are of particular interest to both medical and biomedical science. Specific image enhancement filters have been developed that enhance blood vessels in imaging data prior to segmentation. Using the Sato enhancement filter as an example, we discuss how filter application can be evaluated and optimized. Approaches from the medical field such as simulated, experimental, and augmented datasets can be used to gain the most out of the data at hand. Using such datasets, we provide an overview of how biologists and data analysts can assess the accuracy, sensitivity, and robustness of their segmentation approaches that allow extraction of objects from images. Importantly, even after optimization and testing of a segmentation workflow (e.g., from a particular reporter line to another or between immunostaining processes), its generalizability is often limited, and this can be tested using double-transgenic reporter lines. Lastly, due to the increasing importance of deep learning networks, a comparative approach can be adopted to study their applicability to biological datasets. In summary, we present a broad methodological overview ranging from image enhancement to segmentation with a mixed approach of experimental, simulated, and augmented datasets to assess and validate vascular segmentation using the zebrafish brain vasculature as an example. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. HIGHLIGHTS: Simulated, experimental, and augmented datasets provide an alternative to overcome the lack of segmentation gold standards and phantom models for zebrafish cerebrovascular segmentation. Direct generalization of a segmentation approach to the data for which it was not optimized (e.g., different transgenics or antibody stainings) should be treated with caution. Comparison of different deep learning segmentation methods can be used to assess their applicability to data. Here, we show that the zebrafish cerebral vasculature can be segmented with U-Net-based architectures, which outperform SegNet architectures.

Combining multiple fluorescence imaging techniques in biology: when one microscope is not enough

While fluorescence microscopy has proven to be an exceedingly useful tool in bioscience, it is difficult to offer simultaneous high resolution, fast speed, large volume, and good biocompatibility in a single imaging technique. Thus, when determining the image data required to quantitatively test a complex biological hypothesis, it often becomes evident that multiple imaging techniques are necessary. Recent years have seen an explosion in development of novel fluorescence microscopy techniques, each of which features a unique suite of capabilities. In this Technical Perspective, we highlight recent studies to illustrate the benefits, and often the necessity, of combining multiple fluorescence microscopy modalities. We provide guidance in choosing optimal technique combinations to effectively address a biological question. Ultimately, we aim to promote a more well-rounded approach in designing fluorescence microscopy experiments, leading to more robust quantitative insight.

Smart imaging to empower brain-wide neuroscience at single-cell levels

A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.

A non-canonical Raf function is required for dorsal-ventral patterning during Drosophila embryogenesis

Proper embryonic development requires directional axes to pattern cells into embryonic structures. In Drosophila, spatially discrete expression of transcription factors determines the anterior to posterior organization of the early embryo, while the Toll and TGFβ signalling pathways determine the early dorsal to ventral pattern. Embryonic MAPK/ERK signaling contributes to both anterior to posterior patterning in the terminal regions and to dorsal to ventral patterning during oogenesis and embryonic stages. Here we describe a novel loss of function mutation in the Raf kinase gene, which leads to loss of ventral cell fates as seen through the loss of the ventral furrow, the absence of Dorsal/NFκB nuclear localization, the absence of mesoderm determinants Twist and Snail, and the expansion of TGFβ. Gene expression analysis showed cells adopting ectodermal fates much like loss of Toll signaling. Our results combine novel mutants, live imaging, optogenetics and transcriptomics to establish a novel role for Raf, that appears to be independent of the MAPK cascade, in embryonic patterning.

Intraoperative imaging in pathology-assisted surgery

The pathological assessment of surgical specimens during surgery can reduce the incidence of positive resection margins, which otherwise can result in additional surgeries or aggressive therapeutic regimens. To improve patient outcomes, intraoperative spectroscopic, fluorescence-based, structural, optoacoustic and radiological imaging techniques are being tested on freshly excised tissue. The specific clinical setting and tumour type largely determine whether endogenous or exogenous contrast is to be detected and whether the tumour specificity of the detected biomarker, image resolution, image-acquisition times or penetration depth are to be prioritized. In this Perspective, we describe current clinical standards for intraoperative tissue analysis and discuss how intraoperative imaging is being implemented. We also discuss potential implementations of intraoperative pathology-assisted surgery for clinical decision-making.

Optimized U-Net model for 3D light-sheet image segmentation of zebrafish trunk vessels

The growth of zebrafish's vessels can be used as an indicator of the vascular development process and to study the biological mechanisms. The three-dimensional (3D) structures of zebrafish's trunk vessels could be imaged by state-of-art light-sheet fluorescent microscopy with high efficiency. A large amount of data was then produced. Accurate segmentation of these 3D images becomes a new bottleneck for automatic and quantitative analysis. Here, we propose a Multi-scale 3D U-Net model to perform the segmentation of trunk vessels. The segmentation accuracies of 82.3% and 83.0%, as evaluated by the IoU (Intersection over Union) parameter, were achieved for intersegmental vessels and the dorsal longitudinal anastomotic vessels respectively. The growth of zebrafish vasculature from 42-62 hours was then analyzed quantitatively.

Development of Microscopic Techniques for the Visualization of Plant–Root-Knot Nematode Interaction

Plant-parasitic nematodes are a significant cause of yield losses and food security issues. Specifically, nematodes of the genus Meloidogyne can cause significant production losses in horticultural crops around the world. Understanding the mechanisms of the ever-changing physiology of plant roots by imaging the galls induced by nematodes could provide a great insight into their control. However, infected roots are unsuitable for light microscopy investigation due to the opacity of plant tissues. Thus, samples must be cleared to visualize the interior of whole plants in order to make them transparent using clearing agents. This work aims to identify which clearing protocol and microscopy system is the most appropriate to obtain 3D images of tomato cv. Durinta and eggplant cv. Cristal samples infected with Meloidogyne incognita to visualize and study the root–nematode interaction. To that extent, two clearing solutions (BABB and ECi), combined with three different dehydration solvents (ethanol, methanol and 1-propanol), are tested. In addition, the advantages and disadvantages of alternative imaging techniques to confocal microscopy are analyzed by employing an experimental custom-made setup that combines two microscopic techniques, light sheet fluorescence microscopy and optical projection tomography, on a single instrument.

When Super-Resolution Localization Microscopy Meets Carbon Nanotubes

We recently assisted in a revolution in the realm of fluorescence microscopy triggered by the advent of super-resolution techniques that surpass the classic diffraction limit barrier. By providing optical images with nanometer resolution in the far field, super-resolution microscopy (SRM) is currently accelerating our understanding of the molecular organization of bio-specimens, bridging the gap between cellular observations and molecular structural knowledge, which was previously only accessible using electron microscopy. SRM mainly finds its roots in progress made in the control and manipulation of the optical properties of (single) fluorescent molecules. The flourishing development of novel fluorescent nanostructures has recently opened the possibility of associating super-resolution imaging strategies with nanomaterials’ design and applications. In this review article, we discuss some of the recent developments in the field of super-resolution imaging explicitly based on the use of nanomaterials. As an archetypal class of fluorescent nanomaterial, we mainly focus on single-walled carbon nanotubes (SWCNTs), which are photoluminescent emitters at near-infrared (NIR) wavelengths bearing great interest for biological imaging and for information optical transmission. Whether for fundamental applications in nanomaterial science or in biology, we show how super-resolution techniques can be applied to create nanoscale images “in”, “of” and “with” SWCNTs.

Digital Brain Maps and Virtual Neuroscience: An Emerging Role for Light-Sheet Fluorescence Microscopy in Drug Development

The mammalian brain is by far the most advanced organ to have evolved and the underlying biology is extremely complex. However, with aging populations and sedentary lifestyles, the prevalence of neurological disorders is increasing around the world. Consequently, there is a dire need for technologies that can help researchers to better understand the complexity of the brain and thereby accelerate therapies for diseases with origin in the central nervous system. One such technology is light-sheet fluorescence microscopy (LSFM) which in combination with whole organ immunolabelling has made it possible to visualize an intact mouse brain with single cell resolution. However, the price for this level of detail comes in form of enormous datasets that often challenges extraction of quantitative information. One approach for analyzing whole brain data is to align the scanned brains to a reference brain atlas. Having a fixed spatial reference provides each voxel of the sample brains with x-, y-, z-coordinates from which it is possible to obtain anatomical information on the observed fluorescence signal. An additional and important benefit of aligning light sheet data to a reference brain is that the aligned data provides a digital map of gene expression or cell counts which can be deposited in databases or shared with other scientists. This review focuses on the emerging field of virtual neuroscience using digital brain maps and discusses some of challenges incurred when registering LSFM recorded data to a standardized brain template.

A Model of Discovery: The Role of Imaging Established and Emerging Non-mammalian Models in Neuroscience

Rodents have been the dominant animal models in neurobiology and neurological disease research over the past 60 years. The prevalent use of rats and mice in neuroscience research has been driven by several key attributes including their organ physiology being more similar to humans, the availability of a broad variety of behavioral tests and genetic tools, and widely accessible reagents. However, despite the many advances in understanding neurobiology that have been achieved using rodent models, there remain key limitations in the questions that can be addressed in these and other mammalian models. In particular, in vivo imaging in mammals at the cell-resolution level remains technically difficult and demands large investments in time and cost. The simpler nervous systems of many non-mammalian models allow for precise mapping of circuits and even the whole brain with impressive subcellular resolution. The types of non-mammalian neuroscience models available spans vertebrates and non-vertebrates, so that an appropriate model for most cell biological questions in neurodegenerative disease likely exists. A push to diversify the models used in neuroscience research could help address current gaps in knowledge, complement existing rodent-based bodies of work, and bring new insight into our understanding of human disease. Moreover, there are inherent aspects of many non-mammalian models such as lifespan and tissue transparency that can make them specifically advantageous for neuroscience studies. Crispr/Cas9 gene editing and decreased cost of genome sequencing combined with advances in optical microscopy enhances the utility of new animal models to address specific questions. This review seeks to synthesize current knowledge of established and emerging non-mammalian model organisms with advances in cellular-resolution in vivo imaging techniques to suggest new approaches to understand neurodegeneration and neurobiological processes. We will summarize current tools and in vivo imaging approaches at the single cell scale that could help lead to increased consideration of non-mammalian models in neuroscience research.

High activity and high functional connectivity are mutually exclusive in resting state zebrafish and human brains

Background

The structural connectivity of neurons in the brain allows active neurons to impact the physiology of target neuron types with which they are functionally connected. While the structural connectome is at the basis of functional connectome, it is the functional connectivity measured through correlations between time series of individual neurophysiological events that underlies behavioral and mental states. However, in light of the diverse neuronal cell types populating the brain and their unique connectivity properties, both neuronal activity and functional connectivity are heterogeneous across the brain, and the nature of their relationship is not clear. Here, we employ brain-wide calcium imaging at cellular resolution in larval zebrafish to understand the principles of resting state functional connectivity.

Results

We recorded the spontaneous activity of >12,000 neurons in the awake resting state forebrain. By classifying their activity (i.e., variances of ΔF/F across time) and functional connectivity into three levels (high, medium, low), we find that highly active neurons have low functional connections and highly connected neurons are of low activity. This finding holds true when neuronal activity and functional connectivity data are classified into five instead of three levels, and in whole brain spontaneous activity datasets. Moreover, such activity-connectivity relationship is not observed in randomly shuffled, noise-added, or simulated datasets, suggesting that it reflects an intrinsic brain network property. Intriguingly, deploying the same analytical tools on functional magnetic resonance imaging (fMRI) data from the resting state human brain, we uncover a similar relationship between activity (signal variance over time) and functional connectivity, that is, regions of high activity are non-overlapping with those of high connectivity.

Conclusions

We found a mutually exclusive relationship between high activity (signal variance over time) and high functional connectivity of neurons in zebrafish and human brains. These findings reveal a previously unknown and evolutionarily conserved brain organizational principle, which has implications for understanding disease states and designing artificial neuronal networks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01286-3.

Polarized illumination coded structured illumination microscopy (picoSIM): experimental results

The need for acquiring at least three images to reconstruct an optical section of a sample limits the acquisition rate in structured illumination microscopy (SIM) for optical sectioning. In polarized illumination coded structured illumination microscopy (picoSIM) the three individual light patterns are encoded in a single polarized illumination light distribution, enabling the acquisition of the complete SIM data in a single exposure. Here, we describe our experimental set-up and show experimental results acquired with sequential and single-shot picoSIM. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Quasi-non-diffracting static light sheets generated by holistically optimized pupil masks

Thin and wide light sheets are crucial for light sheet microscopy with wide field of views and near diffraction-limited resolutions. Non-diffracting light sheets feature wide span ranges but often come with strong sidelobes or increased thicknesses. We develop a computational optimization method for creating light sheets that balance the trade-offs between thickness, non-diffracting range and sidelobes. We show in theory and experiment that our optimized mask extends the static light sheet's non-diffracting range by 50 % while keeping its sidelobes below the 20 % level.

Meta-lens light-sheet fluorescence microscopy for in vivo imaging

Light-sheet fluorescent microscopy has become the leading technique for in vivo imaging in the fields of disease, medicine, and cell biology research. However, designing proper illumination for high image resolution and optical sectioning is challenging. Another issue is geometric constraints arising from the multiple bulky components for illumination and detection. Here, we demonstrate that those issues can be well addressed by integrating nanophotonic meta-lens as the illumination component for LSFM. The meta-lens is composed of 800-nm-thick GaN nanostructures and is designed for a light-sheet well-adapted to biological specimens such as the nematode Caenorhabditis elegans (C. elegans). With the meta-lens, the complexity of the LSFM system is significantly reduced, and it is capable of performing multicolor fluorescent imaging of live C. elegans with cellular resolution. Considering the miniature size and plane geometry of the meta-lens, our system enables a new design for LSFM to acquire in vivo images of biological specimens with high resolution.

Current Advances in 3D Bioprinting for Cancer Modeling and Personalized Medicine

Tumor cells evolve in a complex and heterogeneous environment composed of different cell types and an extracellular matrix. Current 2D culture methods are very limited in their ability to mimic the cancer cell environment. In recent years, various 3D models of cancer cells have been developed, notably in the form of spheroids/organoids, using scaffold or cancer-on-chip devices. However, these models have the disadvantage of not being able to precisely control the organization of multiple cell types in complex architecture and are sometimes not very reproducible in their production, and this is especially true for spheroids. Three-dimensional bioprinting can produce complex, multi-cellular, and reproducible constructs in which the matrix composition and rigidity can be adapted locally or globally to the tumor model studied. For these reasons, 3D bioprinting seems to be the technique of choice to mimic the tumor microenvironment in vivo as closely as possible. In this review, we discuss different 3D-bioprinting technologies, including bioinks and crosslinkers that can be used for in vitro cancer models and the techniques used to study cells grown in hydrogels; finally, we provide some applications of bioprinted cancer models.

3D Volume Rendering of Invertebrates Using Light-Sheet Fluorescence Microscopy

Light-Sheet Fluorescence Microscopy has recently emerged as the technique of choice for obtaining high quality three-dimensional (3D) images of whole organisms, with low photo-damage and fast acquisition rates. Unlike conventional optical and confocal microscopy or scanning electron microscopy systems, it offers the possibility of obtaining multiple views of the sample by rotating it. We show that the use of light-sheet fluorescence microscopy, for the analysis of invertebrates, provides a fair compromise compared to scanning electron microscopy in terms of resolution, but avoids some of its drawbacks, such as sample preparation or limited three-dimensional perspectives. In this paper, we will show how LSFM techniques can provide a cheap, high quality, multicolor, 3D alternative to classic microscopes, for the study of the morphological structure of insects and invertebrates in morphogenesis studies of the whole animal.

Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke

As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.

DaXi-high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy

The promise of single-objective light-sheet microscopy is to combine the convenience of standard single-objective microscopes with the speed, coverage, resolution and gentleness of light-sheet microscopes. We present DaXi, a single-objective light-sheet microscope design based on oblique plane illumination that achieves: (1) a wider field of view and high-resolution imaging via a custom remote focusing objective; (2) fast volumetric imaging over larger volumes without compromising image quality or necessitating tiled acquisition; (3) fuller image coverage for large samples via multi-view imaging and (4) higher throughput multi-well imaging via remote coverslip placement. Our instrument achieves a resolution of 450 nm laterally and 2 μm axially over an imaging volume of 3,000 × 800 × 300 μm. We demonstrate the speed, field of view, resolution and versatility of our instrument by imaging various systems, including Drosophila egg chamber development, zebrafish whole-brain activity and zebrafish embryonic development – up to nine embryos at a time.

The DaXi single-objective light-sheet microscope achieves fast, high-quality imaging of large volumes. DaXi’s design allows increased scanning range without sacrificing imaging speed or quality, multiview imaging and versatile sample mounting.

Present Application and Perspectives of Organoid Imaging Technology

An organoid is a miniaturized and simplified in vitro model with a similar structure and function to a real organ. In recent years, the use of organoids has increased explosively in the field of growth and development, disease simulation, drug screening, cell therapy, etc. In order to obtain necessary information, such as morphological structure, cell function and dynamic signals, it is necessary and important to directly monitor the culture process of organoids. Among different detection technologies, imaging technology is a simple and convenient choice and can realize direct observation and quantitative research. In this review, the principle, advantages and disadvantages of imaging technologies that have been applied in organoids research are introduced. We also offer an overview of prospective technologies for organoid imaging. This review aims to help biologists find appropriate imaging techniques for different areas of organoid research, and also contribute to the development of organoid imaging systems.

Multiresolution nondestructive 3D pathology of whole lymph nodes for breast cancer staging

SIGNIFICANCE

For breast cancer patients, the extent of regional lymph node (LN) metastasis influences the decision to remove all axillary LNs. Metastases are currently identified and classified with visual analysis of a few thin tissue sections with conventional histology that may underrepresent the extent of metastases.

AIM

We sought to enable nondestructive three-dimensional (3D) pathology of human axillary LNs and to develop a practical workflow for LN staging with our method. We also sought to evaluate whether 3D pathology improves staging accuracy in comparison to two-dimensional (2D) histology.

APPROACH

We developed a method to fluorescently stain and optically clear LN specimens for comprehensive imaging with multiresolution open-top light-sheet microscopy. We present an efficient imaging and data-processing workflow for rapid evaluation of H&E-like datasets in 3D, with low-resolution screening to identify potential metastases followed by high-resolution localized imaging to confirm malignancy.

RESULTS

We simulate LN staging with 3D and 2D pathology datasets from 10 metastatic nodes, showing that 2D pathology consistently underestimates metastasis size, including instances in which 3D pathology would lead to upstaging of the metastasis with important implications on clinical treatment.

CONCLUSIONS

Our 3D pathology method may improve clinical management for breast cancer patients by improving staging accuracy of LN metastases.

Zebrafish as a tractable model of human cardiovascular disease

Mammalian models including non-human primates, pigs and rodents have been used extensively to study the mechanisms of cardiovascular disease. However, there is an increasing desire for alternative model systems that provide excellent scientific value while replacing or reducing the use of mammals. Here, we review the use of zebrafish, Danio rerio, to study cardiovascular development and disease. The anatomy and physiology of zebrafish and mammalian cardiovascular systems are compared, and we describe the use of zebrafish models in studying the mechanisms of cardiac (e.g. congenital heart defects, cardiomyopathy, conduction disorders and regeneration) and vascular (endothelial dysfunction and atherosclerosis, lipid metabolism, vascular ageing, neurovascular physiology and stroke) pathologies. We also review the use of zebrafish for studying pharmacological responses to cardiovascular drugs and describe several features of zebrafish that make them a compelling model for in vivo screening of compounds for the treatment cardiovascular disease. LINKED ARTICLES: This article is part of a themed issue on Preclinical Models for Cardiovascular disease research (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.5/issuetoc.

Wavefront engineered light needle microscopy for axially resolved rapid volumetric imaging

Increasing the acquisition speed of three-dimensional volumetric images is important-particularly in biological imaging-to unveil the structural dynamics and functionalities of specimens in detail. In conventional laser scanning fluorescence microscopy, volumetric images are constructed from optical sectioning images sequentially acquired by changing the observation plane, limiting the acquisition speed. Here, we present a novel method to realize volumetric imaging from two-dimensional raster scanning of a light needle spot without sectioning, even in the traditional framework of laser scanning microscopy. Information from multiple axial planes is simultaneously captured using wavefront engineering for fluorescence signals, allowing us to readily survey the entire depth range while maintaining spatial resolution. This technique is applied to real-time and video-rate three-dimensional tracking of micrometer-sized particles, as well as the prompt visualization of thick fixed biological specimens, offering substantially faster volumetric imaging.

Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy

Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one-photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The use of two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation of neuronal circuit dynamics. However, due to the low efficiency of the 2P absorption process, the imaging speed of this technique is typically limited by the signal-to-noise-ratio. Here, we describe a 2P LSFM setup designed for non-invasive imaging that enables quintuplicating state-of-the-art volumetric acquisition rate of the larval zebrafish brain (5 Hz) while keeping low the laser intensity on the specimen. We applied our system to the study of pharmacologically-induced acute seizures, characterizing the spatial-temporal dynamics of pathological activity and describing for the first time the appearance of caudo-rostral ictal waves (CRIWs).

Finding Needles in a Haystack with Light: Resolving the Microcircuitry of the Brain with Fluorescence Microscopy

To understand the microcircuitry of the brain, the anatomical and functional connectivity among neurons must be resolved. One of the technical hurdles to achieving this goal is that the anatomical connections, or synapses, are often smaller than the diffraction limit of light and thus are difficult to resolve by conventional microscopy, while the microcircuitry of the brain is on the scale of 1 mm or larger. To date, the gold standard method for microcircuit reconstruction has been electron microscopy (EM). However, despite its rapid development, EM has clear shortcomings as a method for microcircuit reconstruction. The greatest weakness of this method is arguably its incompatibility with functional and molecular analysis. Fluorescence microscopy, on the other hand, is readily compatible with numerous physiological and molecular analyses. We believe that recent advances in various fluorescence microscopy techniques offer a new possibility for reliable synapse detection in large volumes of neural circuits. In this minireview, we summarize recent advances in fluorescence-based microcircuit reconstruction. In the same vein as these studies, we introduce our recent efforts to analyze the long-range connectivity among brain areas and the subcellular distribution of synapses of interest in relatively large volumes of cortical tissue with array tomography and superresolution microscopy.

Single-shot optical sectioning microscopy based on structured illumination

In this Letter, we present a single-shot 3D-resolved structured illumination microscopy (SIM) based on a digital micromirror device (DMD), a galvanometric mirror, and the HiLo algorithm. During imaging, the DMD rapidly generates sinusoidal and plane illuminations in the focal region. By synchronizing the DMD with a galvanometric scanner and exploiting the unique data readout process of the camera, the emissions from the specimen under two different illuminations, i.e., structured and uniform illumination, are projected to different regions on a camera, achieving high-resolution single-exposure optical sectioning at the camera's limiting speed, i.e., 200 Hz, without sacrificing the resolution. A model has been developed to guide the design and optimization of the optical system. Imaging experiments on pollen and mouse kidney samples have been performed to verify the predicted performance. The results show that the single-shot SIM with the HiLo algorithm achieves comparable resolution to the standard two-shot HiLo method with a twofold speed enhancement, which may find important applications in biophotonics, e.g., visualizing high-speed biological events in vivo.

Multi-view confocal microscopy enables multiple organ and whole organism live-imaging

Understanding how development is coordinated in multiple tissues and gives rise to fully functional organs or whole organisms necessitates microscopy tools. Over the last decade numerous advances have been made in live-imaging, enabling high resolution imaging of whole organisms at cellular resolution. Yet, these advances mainly rely on mounting the specimen in agarose or aqueous solutions, precluding imaging of organisms whose oxygen uptake depends on ventilation. Here, we implemented a multi-view multi-scale microscopy strategy based on confocal spinning disk microscopy, called Multi-View confocal microScopy (MuViScopy). MuViScopy enables live-imaging of multiple organs with cellular resolution using sample rotation and confocal imaging without the need of sample embedding. We illustrate the capacity of MuViScopy by live-imaging Drosophila melanogaster pupal development throughout metamorphosis, highlighting how internal organs are formed and multiple organ development is coordinated. We foresee that MuViScopy will open the path to better understand developmental processes at the whole organism scale in living systems that require gas exchange by ventilation.

Computational hyperspectral light-sheet microscopy

We describe a computational light-sheet microscope designed for hyperspectral acquisition at high spectral resolution. The fluorescence light emitted from the full field-of-view is focused along the entrance slit of an imaging spectrometer using a cylindrical lens. To acquire the spatial dimension orthogonal to the slit of the spectrometer, we propose to illuminate the specimen with a sequence of structured light patterns and to solve the image reconstruction problem. Beam shaping is obtained simply using a digital micromirror device in conjunction with a traditional selective plane illumination microscopy setup. We demonstrate the feasibility of this method and report the first results in vivo in hydra specimens labeled using two fluorophores.

LABKIT: Labeling and Segmentation Toolkit for Big Image Data

We present LABKIT, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. LABKIT is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as well as a memory efficient and fast implementation of the random forest based pixel classification algorithm as the foundation of our software. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. LABKIT is easy to install on virtually all laptops and workstations. Additionally, LABKIT is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in LABKIT via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Finally, LABKIT comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use LABKIT in a number of practical real-world use-cases.

Modular multimodal platform for classical and high throughput light sheet microscopy

Light-sheet fluorescence microscopy (LSFM) has become an important tool for biological and biomedical research. Although several illumination and detection strategies have been developed, the sample mounting still represents a cumbersome procedure as this is highly dependent on the type of sample and often this might be time consuming. This prevents the use of LSFM in other promising applications in which a fast and straightforward sample-mounting procedure and imaging are essential. These include the high-throughput research fields, e.g. in drug screenings and toxicology studies. Here we present a new imaging paradigm for LSFM, which exploits modularity to offer multimodal imaging and straightforward sample mounting strategy, enhancing the flexibility and throughput of the system. We describe its implementation in which the sample can be imaged either as in any classical configuration, as it flows through the light-sheet using a fluidic approach, or a combination of both. We also evaluate its ability to image a variety of samples, from zebrafish embryos and larvae to 3D complex cell cultures.

Development of a water refractive index-matched microneedle integrated into a light sheet microscopy system for continuous embryonic cell imaging

In this study, microneedle-integrated light sheet microscopy (LSM) was developed for trapping and continuously imaging embryos of Caenorhabditis elegans with subcellular resolution. To reduce aberrations when the light sheet was propagated into the device, a microneedle was fabricated using a transparent, water refractive index-matched polymer. It was proven that when the light sheet emerged from the water-immersed objective and penetrated through the microneedle with a circular surface, even with a non-perpendicular incident angle, fewer aberrations were found. An embryo was injected into and trapped at the tip of the microneedle, which was positioned at the interrogation window of the LSM apparatus with the image plane perpendicular to the light sheet, and this setup was used to sequentially acquire embryo images. By applying the light sheet, higher-resolution, higher-contrast images were obtained. The system also showed low photobleaching and low phototoxicity to embryos of C. elegans. Furthermore, three-dimensional embryo images with a whole field of view of the microneedle could be achieved by stitching together images and reconstructing sequential two-dimensional embryo images.

Zebrafish vascular quantification: a tool for quantification of three-dimensional zebrafish cerebrovascular architecture by automated image analysis

Zebrafish transgenic lines and light sheet fluorescence microscopy allow in-depth insights into three-dimensional vascular development in vivo. However, quantification of the zebrafish cerebral vasculature in 3D remains highly challenging. Here, we describe and test an image analysis workflow for 3D quantification of the total or regional zebrafish brain vasculature, called zebrafish vasculature quantification (ZVQ). It provides the first landmark- or object-based vascular inter-sample registration of the zebrafish cerebral vasculature, producing population average maps allowing rapid assessment of intra- and inter-group vascular anatomy. ZVQ also extracts a range of quantitative vascular parameters from a user-specified region of interest, including volume, surface area, density, branching points, length, radius and complexity. Application of ZVQ to 13 experimental conditions, including embryonic development, pharmacological manipulations and morpholino-induced gene knockdown, shows that ZVQ is robust, allows extraction of biologically relevant information and quantification of vascular alteration, and can provide novel insights into vascular biology. To allow dissemination, the code for quantification, a graphical user interface and workflow documentation are provided. Together, ZVQ provides the first open-source quantitative approach to assess the 3D cerebrovascular architecture in zebrafish.

Summary: An image analysis workflow pipeline for 3D quantification of the total or regional zebrafish brain vasculature, called zebrafish vasculature quantification or ZVQ.

Multiple-scattering suppressive refractive index tomography for the label-free quantitative assessment of multicellular spheroids

Refractive index (RI) tomography is a quantitative tomographic technique used to visualize the intrinsic contrast of unlabeled biological samples. Conventional RI reconstruction algorithms are based on weak-scattering approximation, such as the Born or Rytov approximation. Although these linear algorithms are computationally efficient, they are invalid when the fields are strongly distorted by multiple scattering (MS) of specimens. Herein, we propose an approach to reconstruct the RI distributions of MS objects even under weak-scattering approximation using an MS-suppressive operation. The operation converts the distorted fields into MS-suppressed fields, where weak-scattering approximation is applicable. Using this approach, we reconstructed a whole multicellular spheroid and successfully visualized its internal subcellular structures. Our work facilitates the realization of RI tomography of MS specimens and label-free quantitative analysis of 3D multicellular specimens.

Development of Planar Illumination Strategies for Solving Mysteries in the Sub-Cellular Realm

Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system's point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.

Imaging Erythrocyte Sedimentation in Whole Blood

The erythrocyte sedimentation rate (ESR) is one of the oldest medical diagnostic tools. However, currently there is some debate on the structure formed by the cells during the sedimentation process. While the conventional view is that erythrocytes sediment as separate aggregates, others have suggested that they form a percolating gel, similar to other colloidal suspensions. However, visualization of aggregated erythrocytes, which would settle the question, has always been challenging. Direct methods usually study erythrocytes in 2D situations or low hematocrit (∼1%). Indirect methods, such as scattering or electric measurements, provide insight on the suspension evolution, but cannot directly discriminate between open or percolating structures. Here, we achieved a direct probing of the structures formed by erythrocytes in blood at stasis. We focused on blood samples at rest with controlled hematocrit of 45%, from healthy donors, and report observations from three different optical imaging techniques: direct light transmission through thin samples, two-photon microscopy and light-sheet microscopy. The three techniques, used in geometries with thickness from 150 μm to 3 mm, highlight that erythrocytes form a continuous network with characteristic cracks, i.e., a colloidal gel. The characteristic distance between the main cracks is of the order of ∼100 μm. A complete description of the structure then requires a field of view of the order of ∼1 mm, in order to obtain a statistically relevant number of structural elements. A quantitative analysis of the erythrocyte related processes and interactions during the sedimentation need a further refinement of the experimental set-ups.

Three-dimensional label-free histological imaging of whole organs by microtomy-assisted autofluorescence tomography

Three-dimensional (3D) histology is vitally important to characterize disease-induced tissue heterogeneity at the individual cell level. However, it remains challenging for both high-throughput 3D imaging and volumetric reconstruction. Here we propose a label-free, cost-effective, and ready-to-use 3D histological imaging technique, termed microtomy-assisted autofluorescence tomography with ultraviolet excitation (MATE). With the combination of block-face imaging and serial microtome sectioning, MATE can achieve rapid and label-free imaging of paraffin-embedded whole organs at an acquisition speed of 1 cm3 per 4 h with a voxel resolution of 1.2 × 1.2 × 10 μm3. We demonstrate that MATE enables simultaneous visualization of cell nuclei, fiber tracts, and blood vessels in mouse/human brains without tissue staining or clearing. Moreover, diagnostic features, including nuclear size and packing density, can be quantitatively extracted with high accuracy. MATE is augmented to the current slide-based 2D histology, holding great promise to facilitate histopathological interpretation at the organelle level.

Regional synapse gain and loss accompany memory formation in larval zebrafish

Defining the structural and functional changes in the nervous system underlying learning and memory represents a major challenge for modern neuroscience. Although changes in neuronal activity following memory formation have been studied [B. F. Grewe et al., Nature 543, 670-675 (2017); M. T. Rogan, U. V. Stäubli, J. E. LeDoux, Nature 390, 604-607 (1997)], the underlying structural changes at the synapse level remain poorly understood. Here, we capture synaptic changes in the midlarval zebrafish brain that occur during associative memory formation by imaging excitatory synapses labeled with recombinant probes using selective plane illumination microscopy. Imaging the same subjects before and after classical conditioning at single-synapse resolution provides an unbiased mapping of synaptic changes accompanying memory formation. In control animals and animals that failed to learn the task, there were no significant changes in the spatial patterns of synapses in the pallium, which contains the equivalent of the mammalian amygdala and is essential for associative learning in teleost fish [M. Portavella, J. P. Vargas, B. Torres, C. Salas, Brain Res. Bull 57, 397-399 (2002)]. In zebrafish that formed memories, we saw a dramatic increase in the number of synapses in the ventrolateral pallium, which contains neurons active during memory formation and retrieval. Concurrently, synapse loss predominated in the dorsomedial pallium. Surprisingly, we did not observe significant changes in the intensity of synaptic labeling, a proxy for synaptic strength, with memory formation in any region of the pallium. Our results suggest that memory formation due to classical conditioning is associated with reciprocal changes in synapse numbers in the pallium.

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future

Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aβ) plaques in the brain. The disease was first described in 1906 by Alois Alzheimer, and since then, there have been many advancements in technologies that have aided in unlocking the secrets of this devastating disease. Such advancements include improving microscopy and staining techniques, refining diagnostic criteria for the disease, and increased appreciation for disease heterogeneity both in neuroanatomic location of abnormalities as well as overlap with other brain diseases; for example, Lewy body disease and vascular dementia. Despite numerous advancements, there is still much to achieve as there is not a cure for AD and postmortem histological analyses is still the gold standard for appreciating AD neuropathologic changes. Recent technological advances such as in-vivo biomarkers and machine learning algorithms permit great strides in disease understanding, and pave the way for potential new therapies and precision medicine approaches. Here, we review the history of human AD neuropathology research to include the notable advancements in understanding common co-pathologies in the setting of AD, and microscopy and staining methods. We also discuss future approaches with a specific focus on deep phenotyping using machine learning.

Innovations in ex vivo Light Sheet Fluorescence Microscopy

Light Sheet Fluorescence Microscopy (LSFM) has revolutionized how optical imaging of biological specimens can be performed as this technique allows to produce 3D fluorescence images of entire samples with a high spatiotemporal resolution. In this manuscript, we aim to provide readers with an overview of the field of LSFM on ex vivo samples. Recent advances in LSFM architectures have made the technique widely accessible and have improved its acquisition speed and resolution, among other features. These developments are strongly supported by quantitative analysis of the huge image volumes produced thanks to the boost in computational capacities, the advent of Deep Learning techniques, and by the combination of LSFM with other imaging modalities. Namely, LSFM allows for the characterization of biological structures, disease manifestations and drug effectivity studies. This information can ultimately serve to develop novel diagnostic procedures, treatments and even to model the organs physiology in healthy and pathological conditions.

Neurophotonic tools for microscopic measurements and manipulation: status report

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Methods for the Study of Apical Constriction During Ascidian Gastrulation

Gastrulation is the first major morphogenetic event during ascidian embryogenesis. Ascidian gastrulation begins with the invagination of the endodermal progenitors, a two-step process driven by individual cell shape changes of endoderm cells. During the first step, endoderm cells constrict apically, thereby flattening the vegetal side of the embryo. During the second step, endoderm cells shorten along their apicobasal axis and tissue invagination ensues. Individual cell shape changes are mediated by localized actomyosin contractile activity. Here, we describe methods used during ascidian endoderm apical constriction to study myosin activity and cellular morphodynamics with confocal and light sheet microscopy and followed by quantitative image analysis.

A Workflow to Track and Analyze Endothelial Migration During Vascular Development in Zebrafish Embryos Using Lightsheet Microscopy

Zebrafish allow unrivalled in vivo imaging of vascular development due to their optical translucency and the availability of transgenic lines which fluorescently label cells and tissues of interest. Advances in light sheet fluorescence microscopy allow longer and faster imaging of live embryos at higher resolutions than previously possible, which facilitates study of dynamic cellular and molecular mechanisms underlying vessel formation and function. Here we describe a workflow using lightsheet microscopy to quantify endothelial cell (EC) migration dynamics during vascular development. Tracking movement of EC nuclei and analyzing the properties of EC migration trajectories permit detailed studies of angiogenesis and vascular remodeling in different contexts.

Compressed sensing in fluorescence microscopy

Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from under-sampled data with respect to the Nyquist criterium. CS exploits sparsity constraints based on the knowledge of prior information, relative to the structure of the object in the spatial or other domains. It is commonly used in image and video compression as well as in scientific and medical applications, including computed tomography and magnetic resonance imaging. In the field of fluorescence microscopy, it has been demonstrated to be valuable for fast and high-resolution imaging, from single-molecule localization, super-resolution to light-sheet microscopy. Furthermore, CS has found remarkable applications in the field of mesoscopic imaging, facilitating the study of small animals' organs and entire organisms. This review article illustrates the working principles of CS, its implementations in optical imaging and discusses several relevant uses of CS in the field of fluorescence imaging from super-resolution microscopy to mesoscopy.

Two plus one is almost three: a fast approximation for multi-view deconvolution

Multi-view deconvolution is a powerful image-processing tool for light sheet fluorescence microscopy, providing isotropic resolution and enhancing the image content. However, performing these calculations on large datasets is computationally demanding and time-consuming even on high-end workstations. Especially in long-time measurements on developing animals, huge amounts of image data are acquired. To keep them manageable, redundancies should be removed right after image acquisition. To this end, we report a fast approximation to three-dimensional multi-view deconvolution, denoted 2D+1D multi-view deconvolution, which is able to keep up with the data flow. It first operates on the two dimensions perpendicular and subsequently on the one parallel to the rotation axis, exploiting the rotational symmetry of the point spread function along the rotation axis. We validated our algorithm and evaluated it quantitatively against two-dimensional and three-dimensional multi-view deconvolution using simulated and real image data. 2D+1D multi-view deconvolution takes similar computation time but performs markedly better than the two-dimensional approximation only. Therefore, it will be most useful for image processing in time-critical applications, where the full 3D multi-view deconvolution cannot keep up with the data flow.

Lineage recording in human cerebral organoids

Induced pluripotent stem cell (iPSC)-derived organoids provide models to study human organ development. Single-cell transcriptomics enable highly resolved descriptions of cell states within these systems; however, approaches are needed to directly measure lineage relationships. Here we establish iTracer, a lineage recorder that combines reporter barcodes with inducible CRISPR-Cas9 scarring and is compatible with single-cell and spatial transcriptomics. We apply iTracer to explore clonality and lineage dynamics during cerebral organoid development and identify a time window of fate restriction as well as variation in neurogenic dynamics between progenitor neuron families. We also establish long-term four-dimensional light-sheet microscopy for spatial lineage recording in cerebral organoids and confirm regional clonality in the developing neuroepithelium. We incorporate gene perturbation (iTracer-perturb) and assess the effect of mosaic TSC2 mutations on cerebral organoid development. Our data shed light on how lineages and fates are established during cerebral organoid formation. More broadly, our techniques can be adapted in any iPSC-derived culture system to dissect lineage alterations during normal or perturbed development.

Capturing the third dimension in drug discovery: Spatially-resolved tools for interrogation of complex 3D cell models

Advanced three-dimensional (3D) cell models have proven to be capable of depicting architectural and microenvironmental features of several tissues. By providing data of higher physiological and pathophysiological relevance, 3D cell models have been contributing to a better understanding of human development, pathology onset and progression mechanisms, as well as for 3D cell-based assays for drug discovery. Nonetheless, the characterization and interrogation of these tissue-like structures pose major challenges on the conventional analytical methods, pushing the development of spatially-resolved technologies. Herein, we review recent advances and pioneering technologies suitable for the interrogation of multicellular 3D models, while capable of retaining biological spatial information. We focused on imaging technologies and omics tools, namely transcriptomics, proteomics and metabolomics. The advantages and shortcomings of these novel methodologies are discussed, alongside the opportunities to intertwine data from the different tools.

QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis

BACKGROUND

The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language-quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data.

RESULTS

QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data.

CONCLUSIONS

The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview.