Multi-sample SPIM image acquisition, processing and analysis of vascular growth in zebrafish

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the fundamental task. Only by segmenting, can we define the quantitative spatial unit for collecting measurements to draw biological conclusions. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation and computation. However 3D cell segmentation, which requires dense annotation of 2D slices still poses significant challenges. Labelling every cell in every 2D slice is prohibitive. Moreover it is ambiguous, necessitating cross-referencing with other orthoviews. Lastly, there is limited ability to unambiguously record and visualize 1000's of annotated cells. Here we develop a theory and toolbox, u-Segment3D for 2D-to-3D segmentation, compatible with any 2D segmentation method. Given optimal 2D segmentations, u-Segment3D generates the optimal 3D segmentation without data training, as demonstrated on 11 real life datasets, >70,000 cells, spanning single cells, cell aggregates and tissue.

Mesoscopic Oblique Plane Microscopy via Light-sheet Mirroring

Understanding the intricate interplay and inter-connectivity of biological processes across an entire organism is important in various fields of biology, including cardiovascular research, neuroscience, and developmental biology. Here, we present a mesoscopic oblique plane microscope (OPM) that enables whole organism imaging with high speed and subcellular resolution. A microprism underneath the sample enhances the axial resolution and optical sectioning through total internal reflection of the light-sheet. Through rapid refocusing of the light-sheet, the imaging depth is extended up to threefold while keeping the axial resolution constant. Using low magnification objectives with a large field of view, we realize mesoscopic imaging over a volume of 3.7×1.5×1 mm3 with ~2.3 microns lateral and ~9.2 microns axial resolution. Applying the mesoscopic OPM, we demonstrate in vivo and in toto whole organism imaging of the zebrafish vasculature and its endothelial nuclei, and blood flow dynamics at 12 Hz acquisition rate, resulting in a quantitative map of blood flow across the entire organism.

Light-sheets and smart microscopy, an exciting future is dawning

Light-sheet fluorescence microscopy has transformed our ability to visualize and quantitatively measure biological processes rapidly and over long time periods. In this review, we discuss current and future developments in light-sheet fluorescence microscopy that we expect to further expand its capabilities. This includes smart and adaptive imaging schemes to overcome traditional imaging trade-offs, i.e., spatiotemporal resolution, field of view and sample health. In smart microscopy, a microscope will autonomously decide where, when, what and how to image. We further assess how image restoration techniques provide avenues to overcome these tradeoffs and how "open top" light-sheet microscopes may enable multi-modal imaging with high throughput. As such, we predict that light-sheet microscopy will fulfill an important role in biomedical and clinical imaging in the future.

Three-dimensional cerebral vasculature topological parameter extraction of transgenic zebrafish embryos with a filling-enhancement deep learning network

Quantitative analysis of zebrafish cerebral vasculature is essential for the study of vascular development and disease. We developed a method to accurately extract the cerebral vasculature topological parameters of transgenic zebrafish embryos. The intermittent and hollow vascular structures of transgenic zebrafish embryos, obtained from 3D light-sheet imaging, were transformed into continuous solid structures with a filling-enhancement deep learning network. The enhancement enables the extraction of 8 vascular topological parameters accurately. Quantitation of the zebrafish cerebral vasculature vessels with the topological parameters show a developmental pattern transition from 2.5 to 5.5 dpf.

Modeling Lung Carcinoids with Zebrafish Tumor Xenograft

Lung carcinoids are neuroendocrine tumors that comprise well-differentiated typical (TCs) and atypical carcinoids (ACs). Preclinical models are indispensable for cancer drug screening since current therapies for advanced carcinoids are not curative. We aimed to develop a novel in vivo model of lung carcinoids based on the xenograft of lung TC (NCI-H835, UMC-11, and NCI-H727) and AC (NCI-H720) cell lines and patient-derived cell cultures in Tg(fli1a:EGFP)^y1 zebrafish embryos. We exploited this platform to test the anti-tumor activity of sulfatinib. The tumorigenic potential of TC and AC implanted cells was evaluated by the quantification of tumor-induced angiogenesis and tumor cell migration as early as 24 h post-injection (hpi). The characterization of tumor-induced angiogenesis was performed in vivo and in real time, coupling the tumor xenograft with selective plane illumination microscopy on implanted zebrafish embryos. TC-implanted cells displayed a higher pro-angiogenic potential compared to AC cells, which inversely showed a relevant migratory behavior within 48 hpi. Sulfatinib inhibited tumor-induced angiogenesis, without affecting tumor cell spread in both TC and AC implanted embryos. In conclusion, zebrafish embryos implanted with TC and AC cells faithfully recapitulate the tumor behavior of human lung carcinoids and appear to be a promising platform for drug screening.

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.

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.

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.

Hand2 delineates mesothelium progenitors and is reactivated in mesothelioma

The mesothelium lines body cavities and surrounds internal organs, widely contributing to homeostasis and regeneration. Mesothelium disruptions cause visceral anomalies and mesothelioma tumors. Nonetheless, the embryonic emergence of mesothelia remains incompletely understood. Here, we track mesothelial origins in the lateral plate mesoderm (LPM) using zebrafish. Single-cell transcriptomics uncovers a post-gastrulation gene expression signature centered on hand2 in distinct LPM progenitor cells. We map mesothelial progenitors to lateral-most, hand2-expressing LPM and confirm conservation in mouse. Time-lapse imaging of zebrafish hand2 reporter embryos captures mesothelium formation including pericardium, visceral, and parietal peritoneum. We find primordial germ cells migrate with the forming mesothelium as ventral migration boundary. Functionally, hand2 loss disrupts mesothelium formation with reduced progenitor cells and perturbed migration. In mouse and human mesothelioma, we document expression of LPM-associated transcription factors including Hand2, suggesting re-initiation of a developmental program. Our data connects mesothelium development to Hand2, expanding our understanding of mesothelial pathologies.

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.

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.

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.

Singularity Containers Improve Reproducibility and Ease of Use in Computational Image Analysis Workflows

Reproducing computational workflows in image analysis and microscopy can be a daunting task due to different software versions and dependencies. This is especially true for users with little specific knowledge of scientific computation. To overcome these challenges, we introduce Singularity containers as a useful tool to run and share image analysis workflows among many users, even years later after establishing them. Unfortunately, containers are rarely used so far in the image analysis field. To address this lack of use, we provide a detailed step-by-step protocol to package a state-of-the-art segmentation algorithm into a container on a local Windows machine to run the container on a high-performance cluster computer.

KLC4 shapes axon arbors during development and mediates adult behavior

Development of elaborate and polarized neuronal morphology requires precisely regulated transport of cellular cargos by motor proteins such as kinesin-1. Kinesin-1 has numerous cellular cargos which must be delivered to unique neuronal compartments. The process by which this motor selectively transports and delivers cargo to regulate neuronal morphogenesis is poorly understood, although the cargo-binding kinesin light chain (KLC) subunits contribute to specificity. Our work implicates one such subunit, KLC4, as an essential regulator of axon branching and arborization pattern of sensory neurons during development. Using live imaging approaches in klc4 mutant zebrafish, we show that KLC4 is required for stabilization of nascent axon branches, proper microtubule (MT) dynamics, and endosomal transport. Furthermore, KLC4 is required for proper tiling of peripheral axon arbors: in klc4 mutants, peripheral axons showed abnormal fasciculation, a behavior characteristic of central axons. This result suggests that KLC4 patterns axonal compartments and helps establish molecular differences between central and peripheral axons. Finally, we find that klc4 mutant larva are hypersensitive to touch and adults show anxiety-like behavior in a novel tank test, implicating klc4 as a new gene involved in stress response circuits.

KRas-transformed epithelia cells invade and partially dedifferentiate by basal cell extrusion

Metastasis is the main cause of carcinoma-related death, yet we know little about how it initiates due to our inability to visualize stochastic invasion events. Classical models suggest that cells accumulate mutations that first drive formation of a primary mass, and then downregulate epithelia-specific genes to cause invasion and metastasis. Here, using transparent zebrafish epidermis to model simple epithelia, we can directly image invasion. We find that KRas-transformation, implicated in early carcinogenesis steps, directly drives cell invasion by hijacking a process epithelia normally use to promote death-cell extrusion. Cells invading by basal cell extrusion simultaneously pinch off their apical epithelial determinants, endowing new plasticity. Following invasion, cells divide, enter the bloodstream, and differentiate into stromal, neuronal-like, and other cell types. Yet, only invading KRas^V12 cells deficient in p53 survive and form internal masses. Together, we demonstrate that KRas-transformation alone causes cell invasion and partial dedifferentiation, independently of mass formation.

Impairing flow-mediated endothelial remodeling reduces extravasation of tumor cells

Tumor progression and metastatic dissemination are driven by cell-intrinsic and biomechanical cues that favor the growth of life-threatening secondary tumors. We recently identified pro-metastatic vascular regions with blood flow profiles that are permissive for the arrest of circulating tumor cells. We have further established that such flow profiles also control endothelial remodeling, which favors extravasation of arrested CTCs. Yet, how shear forces control endothelial remodeling is unknown. In the present work, we aimed at dissecting the cellular and molecular mechanisms driving blood flow-dependent endothelial remodeling. Transcriptomic analysis of endothelial cells revealed that blood flow enhanced VEGFR signaling, among others. Using a combination of in vitro microfluidics and intravital imaging in zebrafish embryos, we now demonstrate that the early flow-driven endothelial response can be prevented upon specific inhibition of VEGFR tyrosine kinase and subsequent signaling. Inhibitory targeting of VEGFRs reduced endothelial remodeling and subsequent metastatic extravasation. These results confirm the importance of VEGFR-dependent endothelial remodeling as a driving force of CTC extravasation and metastatic dissemination. Furthermore, the present work suggests that therapies targeting endothelial remodeling might be a relevant clinical strategy in order to impede metastatic progression.

Membrane-coated 3D architectures for bottom-up synthetic biology

One of the great challenges of bottom-up synthetic biology is to recreate the cellular geometry and surface functionality required for biological reactions. Of particular interest are lipid membrane interfaces where many protein functions take place. However, cellular 3D geometries are often complex, and custom-shaping stable lipid membranes on relevant spatial scales in the micrometer range has been hard to accomplish reproducibly. Here, we use two-photon direct laser writing to 3D print microenvironments with length scales relevant to cellular processes and reactions. We formed lipid bilayers on the surfaces of these printed structures, and we evaluated multiple combinatorial scenarios, where physiologically relevant membrane compositions were generated on several different polymer surfaces. Functional dynamic protein systems were reconstituted in vitro and their self-organization was observed in response to the 3D geometry. This method proves very useful to template biological membranes with an additional spatial dimension, and thus allows a better understanding of protein function in relation to the complex morphology of cells and organelles.

Cerebrovascular development: mechanisms and experimental approaches

The cerebral vasculature plays a central role in human health and disease and possesses several unique anatomic, functional and molecular characteristics. Despite their importance, the mechanisms that determine cerebrovascular development are less well studied than other vascular territories. This is in part due to limitations of existing models and techniques for visualisation and manipulation of the cerebral vasculature. In this review we summarise the experimental approaches used to study the cerebral vessels and the mechanisms that contribute to their development.

Discovering New Progenitor Cell Populations through Lineage Tracing and In Vivo Imaging

Identification of progenitor cells that generate differentiated cell types during development, regeneration, and disease states is central to understanding the mechanisms governing such transitions. For more than a century, different lineage-tracing strategies have been developed, which helped disentangle the complex relationship between progenitor cells and their progenies. In this review, we discuss how lineage-tracing analyses have evolved alongside technological advances, and how this approach has contributed to the identification of progenitor cells in different contexts of cell differentiation. We also highlight a few examples in which lineage-tracing experiments have been instrumental for resolving long-standing debates and for identifying unexpected cellular origins. This discussion emphasizes how this century-old quest to delineate cellular lineage relationships is still active, and new discoveries are being made with the development of newer methodologies.

Long-term in vivo imaging reveals tumor-specific dissemination and captures host tumor interaction in zebrafish xenografts

Understanding mechanisms mediating tumor metastasis is crucial for diagnostic and therapeutic targeting. Here, we take advantage of a transparent embryonic zebrafish xenograft model (eZXM) to visualize and track metastatic cells in real time using selective plane illumination microscopy (SPIM) for up to 30 h. Injected human leukemic and breast cancer cells exhibited cell-type specific patterns of intravascular distribution with leukemic cells moving faster than breast cancer cells. Tracking of tumor cells from high-resolution images revealed acute differences in intravascular speed and distance covered by cells. While the majority of injected breast cancer cells predominantly adhered to nearby vasculature, about 30% invaded the non-vascularized tissue, reminiscent of their metastatic phenotype. Survival of the injected tumor cells appeared to be partially inhibited and time-lapse imaging showed a possible role for host macrophages of the recipient embryos. Leukemic cell dissemination could be effectively blocked by pharmacological ROCK1 inhibition using Fasudil. These observations, and the ability to image several embryos simultaneously, support the use of eZXM and SPIM imaging as a functional screening platform to identify compounds that suppress cancer cell spread and invasion.

Live-cell imaging in the era of too many microscopes

At the time of this writing, searching Google Scholar for 'light-sheet microscopy' returns almost 8500 results; over three-quarters of which were published in the last 5 years alone. Searching for other advanced imaging methods in the last 5 years yields similar results: 'super-resolution microscopy' (>16 000), 'single-molecule imaging' (almost 10 000), SPIM (Single Plane Illumination Microscopy, 5000), and 'lattice light-sheet' (1300). The explosion of new imaging methods has also produced a dizzying menagerie of acronyms, with over 100 different species of 'light-sheet' alone, from SPIM to UM (Ultra microscopy) to SiMView (Simultaneous MultiView) to iSPIM (inclined SPIM, not to be confused with iSPIM, inverted SPIM). How then is the average biologist, without an advanced degree in physics, optics, or computer science supposed to make heads or tails of which method is best suited for their needs? Let us also not forget the plight of the optical physicist, who at best might need help with obtaining healthy samples and keeping them that way, or at worst may not realize the impact their newest technique could have for biologists. This review will not attempt to solve all these problems, but instead highlight some of the most recent, successful mergers between biology and advanced imaging technologies, as well as hopefully provide some guidance for anyone interested in journeying into the world of live-cell imaging.

Standardized mounting method of (zebrafish) embryos using a 3D-printed stamp for high-content, semi-automated confocal imaging

Background

Developmental biology relies to a large extent on the observation and comparison of phenotypic traits through time using high resolution microscopes. In this context, transparent model organisms such as the zebrafish Danio rerio in which developing tissues and organs can be easily observed and imaged using fluorescent proteins have become very popular. One limiting factor however is the acquisition of a sufficient amount of data, in standardized and reproducible conditions, to allow robust quantitative analysis. One way to improve this is by developing mounting methods to increase the number of embryos that can be imaged simultaneously in near-to-identical orientation.

Results

Here we present an improved mounting method allowing semi-automated and high-content imaging of zebrafish embryos. It is based on a 3D-printed stamp which is used to create a 2D coordinate system of multiple μ-wells in an agarose cast. Each μ-well models a negative of the average zebrafish embryo morphology between 22 and 96 h-post-fertilization. Due to this standardized and reproducible arrangement, it is possible to define a custom well plate in the respective imaging software that allows for a semi-automated imaging process. Furthermore, the improvement in Z-orientation significantly reduces post-processing and improves comparability of volumetric data while reducing light exposure and thus photo-bleaching and photo-toxicity, and improving signal-to-noise ratio (SNR).

Conclusions

We present here a new method that allows to standardize and improve mounting and imaging of embryos. The 3D-printed stamp creates a 2D coordinate system of μ-wells in an agarose cast thus standardizing specimen mounting and allowing high-content imaging of up to 44 live or mounted zebrafish embryos simultaneously in a semi-automated, well-plate like manner on inverted confocal microscopes. In summary, image data quality and acquisition efficiency (amount of data per time) are significantly improved. The latter might also be crucial when using the services of a microscopy facility.