Therapeutic targeting of vascular malformation in a zebrafish model of hereditary haemorrhagic telangiectasia.

Hereditary haemorrhagic telangiectasia (HHT) causes arteriovenous malformations (AVMs) in multiple organs to cause bleeding, neurological and other complications. HHT is caused by mutations in the BMP co-receptor endoglin. We characterised a range of vascular phenotypes in embryonic and adult endoglin mutant zebrafish and the effect of inhibiting different pathways downstream of Vegf signalling. Adult endoglin mutant zebrafish developed skin AVMs, retinal vascular abnormalities and cardiac enlargement. Embryonic endoglin mutants developed an enlarged basilar artery (similar to the previously described enlarged aorta and cardinal vein) and larger numbers of endothelial membrane cysts (kugeln) on cerebral vessels. Vegf inhibition prevented these embryonic phenotypes, leading us to investigate specific Vegf signalling pathways. Inhibiting mTOR or MEK pathways prevented abnormal trunk and cerebral vasculature phenotypes, whereas inhibiting Nos or Mapk pathways had no effect. Combined subtherapeutic mTOR and MEK inhibition prevented vascular abnormalities, confirming synergy between these pathways in HHT. These results indicate that the HHT-like phenotype in zebrafish endoglin mutants can be mitigated through modulation of Vegf signalling. Combined low-dose MEK and mTOR pathway inhibition could represent a novel therapeutic strategy in HHT.

GliaMorph: a modular image analysis toolkit to quantify Müller glial cell morphology.

Cell morphology is crucial for all cell functions. This is particularly true for glial cells as they rely on complex shape to contact and support neurons. However, methods to quantify complex glial cell shape accurately and reproducibly are lacking. To address this, we developed the image analysis pipeline 'GliaMorph'. GliaMorph is a modular analysis toolkit developed to perform (1) image pre-processing, (2) semi-automatic region-of-interest selection, (3) apicobasal texture analysis, (4) glia segmentation, and (5) cell feature quantification. Müller glia (MG) have a stereotypic shape linked to their maturation and physiological status. Here, we characterized MG on three levels: (1) global image-level, (2) apicobasal texture, and (3) regional apicobasal vertical-to-horizontal alignment. Using GliaMorph, we quantified MG development on a global and single-cell level, showing increased feature elaboration and subcellular morphological rearrangement in the zebrafish retina. As proof of principle, we analysed expression changes in a mouse glaucoma model, identifying subcellular protein localization changes in MG. Together, these data demonstrate that GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina.

Glia Cell Morphology Analysis Using the Fiji GliaMorph Toolkit.

Glial cells are the support cells of the nervous system. Glial cells typically have elaborate morphologies that facilitate close contacts with neighboring neurons, synapses, and the vasculature. In the retina, Müller glia (MG) are the principal glial cell type that supports neuronal function by providing a myriad of supportive functions via intricate cell morphologies and precise contacts. Thus, complex glial morphology is critical for glial function, but remains challenging to resolve at a sub-cellular level or reproducibly quantify in complex tissues. To address this issue, we developed GliaMorph as a Fiji-based macro toolkit that allows 3D glial cell morphology analysis in the developing and mature retina. As GliaMorph is implemented in a modular fashion, here we present guides to (a) setup of GliaMorph, (b) data understanding in 3D, including z-axis intensity decay and signal-to-noise ratio, (c) pre-processing data to enhance image quality, (d) performing and examining image segmentation, and (e) 3D quantification of MG features, including apicobasal texture analysis. To allow easier application, GliaMorph tools are supported with graphical user interfaces where appropriate, and example data are publicly available to facilitate adoption. Further, GliaMorph can be modified to meet users' morphological analysis needs for other glial or neuronal shapes. Finally, this article provides users with an in-depth understanding of data requirements and the workflow of GliaMorph. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Download and installation of GliaMorph components including example data Basic Protocol 2: Understanding data properties and quality 3D-essential for subsequent analysis and capturing data property issues early Basic Protocol 3: Pre-processing AiryScan microscopy data for analysis Alternate Protocol: Pre-processing confocal microscopy data for analysis Basic Protocol 4: Segmentation of glial cells Basic Protocol 5: 3D quantification of glial cell morphology.

Meeting in the Middle: Towards Successful Multidisciplinary Bioimage Analysis Collaboration.

With an increase in subject knowledge expertise required to solve specific biological questions, experts from different fields need to collaborate to address increasingly complex issues. To successfully collaborate, everyone involved in the collaboration must take steps to "meet in the middle". We thus present a guide on truly cross-disciplinary work using bioimage analysis as a showcase, where it is required that the expertise of biologists, microscopists, data analysts, clinicians, engineers, and physicists meet. We discuss considerations and best practices from the perspective of both users and technology developers, while offering suggestions for working together productively and how this can be supported by institutes and funders. Although this guide uses bioimage analysis as an example, the guiding principles of these perspectives are widely applicable to other cross-disciplinary work.

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.

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.

Engaging new audiences with imaging and microscopy.

In this Spotlight, we hear first-hand accounts from five scientists and educators who use microscopy and imaging to engage, entertain, educate and inspire new audiences with science and the field of developmental biology in particular. The 'voices' that follow each convey each authors' own personal take on why microscopy is such a powerful tool for capturing the minds, and the hearts, of scientists, students and the public alike. They discuss how microscopy and imaging can reveal new worlds, and improve our communication and understanding of developmental biology, as well as break down barriers and promote diversity for future generations of scientific researchers.

The "Neuro-Glial-Vascular" Unit: The Role of Glia in Neurovascular Unit Formation and Dysfunction.

The neurovascular unit (NVU) is a complex multi-cellular structure consisting of endothelial cells (ECs), neurons, glia, smooth muscle cells (SMCs), and pericytes. Each component is closely linked to each other, establishing a structural and functional unit, regulating central nervous system (CNS) blood flow and energy metabolism as well as forming the blood-brain barrier (BBB) and inner blood-retina barrier (BRB). As the name suggests, the "neuro" and "vascular" components of the NVU are well recognized and neurovascular coupling is the key function of the NVU. However, the NVU consists of multiple cell types and its functionality goes beyond the resulting neurovascular coupling, with cross-component links of signaling, metabolism, and homeostasis. Within the NVU, glia cells have gained increased attention and it is increasingly clear that they fulfill various multi-level functions in the NVU. Glial dysfunctions were shown to precede neuronal and vascular pathologies suggesting central roles for glia in NVU functionality and pathogenesis of disease. In this review, we take a "glio-centric" view on NVU development and function in the retina and brain, how these change in disease, and how advancing experimental techniques will help us address unanswered questions.

The effect of absent blood flow on the zebrafish cerebral and trunk vasculature.

The role of blood flow in vascular development is complex and context-dependent. In this study, we quantify the effect of the lack of blood flow on embryonic vascular development on two vascular beds, namely the cerebral and trunk vasculature in zebrafish. We perform this by analysing vascular topology, endothelial cell (EC) number, EC distribution, apoptosis, and inflammatory response in animals with normal blood flow or absent blood flow. We find that absent blood flow reduced vascular area and EC number significantly in both examined vascular beds, but the effect is more severe in the cerebral vasculature, and severity increases over time. Absent blood flow leads to an increase in non-EC-specific apoptosis without increasing tissue inflammation, as quantified by cerebral immune cell numbers and nitric oxide. Similarly, while stereotypic vascular patterning in the trunk is maintained, intra-cerebral vessels show altered patterning, which is likely to be due to vessels failing to initiate effective fusion and anastomosis rather than sprouting or path-seeking. In conclusion, blood flow is essential for cellular survival in both the trunk and cerebral vasculature, but particularly intra-cerebral vessels are affected by the lack of blood flow, suggesting that responses to blood flow differ between these two vascular beds.

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.

The effect of hyperglycemia on neurovascular coupling and cerebrovascular patterning in zebrafish.

Neurovascular coupling (through which local cerebral blood flow changes in response to neural activation are mediated) is impaired in many diseases including diabetes. Current preclinical rodent models of neurovascular coupling rely on invasive surgery and instrumentation, but transgenic zebrafish coupled with advances in imaging techniques allow non-invasive quantification of cerebrovascular anatomy, neural activation, and cerebral vessel haemodynamics. We therefore established a novel non-invasive, non-anaesthetised zebrafish larval model of neurovascular coupling, in which visual stimulus evokes neuronal activation in the optic tectum that is associated with a specific increase in red blood cell speed in tectal blood vessels. We applied this model to the examination of the effect of glucose exposure on cerebrovascular patterning and neurovascular coupling. We found that chronic exposure of zebrafish to glucose impaired tectal blood vessel patterning and neurovascular coupling. The nitric oxide donor sodium nitroprusside rescued all these adverse effects of glucose exposure on cerebrovascular patterning and function. Our results establish the first non-mammalian model of neurovascular coupling, offering the potential to perform more rapid genetic modifications and high-throughput screening than is currently possible using rodents. Furthermore, using this zebrafish model, we reveal a potential strategy to ameliorate the effects of hyperglycemia on cerebrovascular function.

Cerebrovascular endothelial cells form transient Notch-dependent cystic structures in zebrafish.

We identify a novel endothelial membrane behaviour in transgenic zebrafish. Cerebral blood vessels extrude large transient spherical structures that persist for an average of 23 min before regressing into the parent vessel. We term these structures "kugeln", after the German for sphere. Kugeln are only observed arising from the cerebral vessels and are present as late as 28 days post fertilization. Kugeln do not communicate with the vessel lumen and can form in the absence of blood flow. They contain little or no cytoplasm, but the majority are highly positive for nitric oxide reactivity. Kugeln do not interact with brain lymphatic endothelial cells (BLECs) and can form in their absence, nor do they perform a scavenging role or interact with macrophages. Inhibition of actin polymerization, Myosin II, or Notch signalling reduces kugel formation, while inhibition of VEGF or Wnt dysregulation (either inhibition or activation) increases kugel formation. Kugeln represent a novel Notch-dependent NO-containing endothelial organelle restricted to the cerebral vessels, of currently unknown function.

Enhancement and Segmentation Workflow for the Developing Zebrafish Vasculature.

Zebrafish have become an established in vivo vertebrate model to study cardiovascular development and disease. However, most published studies of the zebrafish vascular architecture rely on subjective visual assessment, rather than objective quantification. In this paper, we used state-of-the-art light sheet fluorescence microscopy to visualize the vasculature in transgenic fluorescent reporter zebrafish. Analysis of image quality, vascular enhancement methods, and segmentation approaches were performed in the framework of the open-source software Fiji to allow dissemination and reproducibility. Here, we build on a previously developed image processing pipeline; evaluate its applicability to a wider range of data; apply and evaluate an alternative vascular enhancement method; and, finally, suggest a work-flow for successful segmentation of the embryonic zebrafish vasculature.

meRanTK: methylated RNA analysis ToolKit.

UNLABELLED: The significance and function of posttranscriptional cytosine methylation in poly(A)RNA attracts great interest but is still poorly understood. High-throughput sequencing of RNA treated with bisulfite (RNA-BSseq) or subjected to enrichment techniques like Aza-IP or miCLIP enables transcriptome wide studies of this particular modification at single base pair resolution. However, to date, there are no specialized software tools available for the analysis of RNA-BSseq or Aza-IP data. Therefore, we developed meRanTK, the first publicly available tool kit which addresses the special demands of high-throughput RNA cytosine methylation data analysis. It provides fast and easy to use splice-aware bisulfite sequencing read mapping, comprehensive methylation calling and identification of differentially methylated cytosines by statistical analysis of single- and multi-replicate experiments. Application of meRanTK to RNA-BSseq or Aza-IP data produces accurate results in standard compliant formats. AVAILABILITY AND IMPLEMENTATION: meRanTK, source code and test data are released under the GNU GPLv3+ license and are available at http://icbi.at/software/meRanTK/ CONTACT: dietmar.rieder@i-med.ac.at.