Efficient processing and analysis of large-scale light-sheet microscopy data

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

Imaging actin organisation and dynamics in 3D

The actin cytoskeleton plays a critical role in cell architecture and the control of fundamental processes including cell division, migration and survival. The dynamics and organisation of F-actin have been widely studied in a breadth of cell types on classical two-dimensional (2D) surfaces. Recent advances in optical microscopy have enabled interrogation of these cytoskeletal networks in cells within three-dimensional (3D) scaffolds, tissues and in vivo. Emerging studies indicate that the dimensionality experienced by cells has a profound impact on the structure and function of the cytoskeleton, with cells in 3D environments exhibiting cytoskeletal arrangements that differ to cells in 2D environments. However, the addition of a third (and fourth, with time) dimension leads to challenges in sample preparation, imaging and analysis, necessitating additional considerations to achieve the required signal-to-noise ratio and spatial and temporal resolution. Here, we summarise the current tools for imaging actin in a 3D context and highlight examples of the importance of this in understanding cytoskeletal biology and the challenges and opportunities in this domain.

Imagining the future of optical microscopy: everything, everywhere, all at once

The optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.

Tissue clearing applications in memory engram research

A memory engram is thought to be the physical substrate of the memory trace within the brain, which is generally depicted as a neuronal ensemble activated by learning to fire together during encoding and retrieval. It has been postulated that engram cell ensembles are functionally interconnected across multiple brain regions to store a single memory as an "engram complex", but visualizing this engram complex across the whole brain has for long been hindered by technical limitations. With the recent development of tissue clearing techniques, advanced light-sheet microscopy, and automated 3D image analysis, it has now become possible to generate a brain-wide map of engram cells and thereby to visualize the "engram complex". In this review, we first provide a comprehensive summary of brain-wide engram mapping studies to date. We then compile a guide on implementing the optimal tissue clearing technique for engram tagging approaches, paying particular attention to visualize engram reactivation as a critical mnemonic property, for which whole-brain multiplexed immunostaining becomes a challenging prerequisite. Finally, we highlight the potential of tissue clearing to simultaneously shed light on both the circuit connectivity and molecular underpinnings of engram cells in a single snapshot. In doing so, novel brain regions and circuits can be identified for subsequent functional manipulation, thus providing an opportunity to robustly examine the "engram complex" underlying memory storage.

Morphogenesis: Unstable rods and how genetics tames them

Rods under mechanical stress are a classic example of dynamic instability. Axis elongation in Drosophila usually leads to a U-shaped axis, but folded or twisted axes are observed in certain mutants. Analysis of these mutants now reveals the source of the instability and the mechanism for maintaining left-right symmetry.

Lossy Image Compression in a Preclinical Multimodal Imaging Study

The growing use of multimodal high-resolution volumetric data in pre-clinical studies leads to challenges related to the management and handling of the large amount of these datasets. Contrarily to the clinical context, currently there are no standard guidelines to regulate the use of image compression in pre-clinical contexts as a potential alleviation of this problem. In this work, the authors study the application of lossy image coding to compress high-resolution volumetric biomedical data. The impact of compression on the metrics and interpretation of volumetric data was quantified for a correlated multimodal imaging study to characterize murine tumor vasculature, using volumetric high-resolution episcopic microscopy (HREM), micro-computed tomography (µCT), and micro-magnetic resonance imaging (µMRI). The effects of compression were assessed by measuring task-specific performances of several biomedical experts who interpreted and labeled multiple data volumes compressed at different degrees. We defined trade-offs between data volume reduction and preservation of visual information, which ensured the preservation of relevant vasculature morphology at maximum compression efficiency across scales. Using the Jaccard Index (JI) and the average Hausdorff Distance (HD) after vasculature segmentation, we could demonstrate that, in this study, compression that yields to a 256-fold reduction of the data size allowed to keep the error induced by compression below the inter-observer variability, with minimal impact on the assessment of the tumor vasculature across scales.

Automated contour extraction for light-sheet microscopy images of zebrafish embryos based on object edge detection algorithm

Embryo contour extraction is the initial step in the quantitative analysis of embryo morphology, and it is essential for understanding the developmental process. Recent developments in light-sheet microscopy have enabled the in toto time-lapse imaging of embryos, including zebrafish. However, embryo contour extraction from images generated via light-sheet microscopy is challenging owing to the large amount of data and the variable sizes, shapes, and textures of objects. In this report, we provide a workflow for extracting the contours of zebrafish blastula and gastrula without contour labeling of an embryo. This workflow is based on the edge detection method using a change point detection approach. We assessed the performance of the edge detection method and compared it with widely used edge detection and segmentation methods. The results showed that the edge detection accuracy of the proposed method was superior to those of the Sobel, Laplacian of Gaussian, adaptive threshold, Multi Otsu, and k-means clustering-based methods, and the noise robustness of the proposed method was superior to those of the Multi Otsu and k-means clustering-based methods. The proposed workflow was shown to be useful for automating small-scale contour extractions of zebrafish embryos that cannot be specifically labeled owing to constraints, such as the availability of microscopic channels. This workflow may offer an option for contour extraction when deep learning-based approaches or existing non-deep learning-based methods cannot be applied.

Nondestructive 3D Pathology with Light-Sheet Fluorescence Microscopy for Translational Research and Clinical Assays

In recent years, there has been a revived appreciation for the importance of spatial context and morphological phenotypes for both understanding disease progression and guiding treatment decisions. Compared with conventional 2D histopathology, which is the current gold standard of medical diagnostics, nondestructive 3D pathology offers researchers and clinicians the ability to visualize orders of magnitude more tissue within their natural volumetric context. This has been enabled by rapid advances in tissue-preparation methods, high-throughput 3D microscopy instrumentation, and computational tools for processing these massive feature-rich data sets. Here, we provide a brief overview of many of these technical advances along with remaining challenges to be overcome. We also speculate on the future of 3D pathology as applied in translational investigations, preclinical drug development, and clinical decision-support assays.

Practical considerations for quantitative light sheet fluorescence microscopy

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast. However, the defining characteristics of light sheet microscopes subsequently warrant unique considerations in their use for quantitative experiments. In this Perspective, we outline many of the pitfalls in LSFM that can compromise analysis and confound interpretation. Moreover, we offer guidance in addressing these caveats when possible. In doing so, we hope to provide a useful resource for life scientists seeking to adopt LSFM to quantitatively address complex biological hypotheses.

Label-Free Imaging Analysis of Patient-Derived Cholangiocarcinoma Organoids after Sorafenib Treatment

Monitoring tumor growth dynamics is crucial for understanding cancer. To establish an in vitro method for the continuous assessment of patient-specific tumor growth, tumor organoids were generated from patients with intrahepatic CCA (iCCA). Organoid growth was monitored for 48 h by label-free live brightfield imaging. Growth kinetics were calculated and validated by MTS assay as well as immunohistochemistry of Ki67 to determine proliferation rates. We exposed iCCA organoids (iCCAOs) and non-tumor intrahepatic cholangiocyte organoids (ICOs) to sub-therapeutic concentrations of sorafenib. Monitoring the expansion rate of iCCAOs and ICOs revealed that iCCAO growth was inhibited by sorafenib in a time- and dose-dependent fashion, while ICOs were unaffected. Quantification of the proliferation marker Ki67 confirmed inhibition of iCCAO growth by roughly 50% after 48 h of treatment with 4 µM sorafenib. We established a robust analysis pipeline combining brightfield microscopy and a straightforward image processing approach for the label-free growth monitoring of patient-derived iCCAOs. Combined with bioanalytical validation, this approach is suitable for a fast and efficient high-throughput drug screening in tumor organoids to develop patient-specific systemic treatment options.

EZ Clear for simple, rapid, and robust mouse whole organ clearing

Tissue clearing for whole organ cell profiling has revolutionized biology and imaging for exploration of organs in three-dimensional space without compromising tissue architecture. But complicated, laborious procedures, or expensive equipment, as well as the use of hazardous, organic solvents prevent the widespread adoption of these methods. Here, we report a simple and rapid tissue clearing method, EZ Clear, that can clear whole adult mouse organs in 48 hr in just three simple steps. Samples stay at room temperature and remain hydrated throughout the clearing process, preserving endogenous and synthetic fluorescence, without altering sample size. After wholemount clearing and imaging, samples processed with EZ Clear can be subjected to downstream applications, such as tissue embedding and cryosectioning followed by standard histology or immunofluorescent staining without loss of fluorescence signal from endogenous or synthetic reporters. Furthermore, we demonstrate that wholemount adult mouse brains processed with EZ Clear can be successfully immunolabeled for fluorescent imaging while still retaining signal from endogenous fluorescent reporters. Overall, the simplicity, speed, and flexibility of EZ Clear make it easy to adapt and implement in diverse imaging modalities in biomedical research.

Parallel Discrete Convolutions on Adaptive Particle Representations of Images

We present data structures and algorithms for native implementations of discrete convolution operators over Adaptive Particle Representations (APR) of images on parallel computer architectures. The APR is a content-adaptive image representation that locally adapts the sampling resolution to the image signal. It has been developed as an alternative to pixel representations for large, sparse images as they typically occur in fluorescence microscopy. It has been shown to reduce the memory and runtime costs of storing, visualizing, and processing such images. This, however, requires that image processing natively operates on APRs, without intermediately reverting to pixels. Designing efficient and scalable APR-native image processing primitives, however, is complicated by the APR's irregular memory structure. Here, we provide the algorithmic building blocks required to efficiently and natively process APR images using a wide range of algorithms that can be formulated in terms of discrete convolutions. We show that APR convolution naturally leads to scale-adaptive algorithms that efficiently parallelize on multi-core CPU and GPU architectures. We quantify the speedups in comparison to pixel-based algorithms and convolutions on evenly sampled data. We achieve pixel-equivalent throughputs of up to 1TB/s on a single Nvidia GeForce RTX 2080 gaming GPU, requiring up to two orders of magnitude less memory than a pixel-based implementation.

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.

Tutorial: methods for three-dimensional visualization of archival tissue material

Analysis of three-dimensional patient specimens is gaining increasing relevance for understanding the principles of tissue structure as well as the biology and mechanisms underlying disease. New technologies are improving our ability to visualize large volume of tissues with subcellular resolution. One resource often overlooked is archival tissue maintained for decades in hospitals and research archives around the world. Accessing the wealth of information stored within these samples requires the use of appropriate methods. This tutorial introduces the range of sample preparation and microscopy approaches available for three-dimensional visualization of archival tissue. We summarize key aspects of the relevant techniques and common issues encountered when using archival tissue, including registration and antibody penetration. We also discuss analysis pipelines required to process, visualize and analyze the data and criteria to guide decision-making. The methods outlined in this tutorial provide an important and sustainable avenue for validating three-dimensional tissue organization and mechanisms of disease.

Optical Clearing and Light Sheet Microscopy Imaging of Amphioxus

Cephalochordates (amphioxi or lancelets) are representatives of the most basally divergent group of the chordate phylum. Studies of amphioxus development and anatomy hence provide a key insight into vertebrate evolution. More widespread use of amphioxus in the evo-devo field would be greatly facilitated by expanding the methodological toolbox available in this model system. For example, evo-devo research on amphioxus requires deep understanding of animal anatomy. Although conventional confocal microscopy can visualize transparent amphioxus embryos and early larvae, the imaging of later developmental stages is problematic because of the size and opaqueness of the animal. Here, we show that light sheet microscopy combined with tissue clearing methods enables exploration of large amphioxus specimens while keeping the surface and the internal structures intact. We took advantage of the phenomenon of autofluorescence of amphioxus larva to highlight anatomical details. In order to investigate molecular markers at the single-cell level, we performed antibody-based immunodetection of melanopsin and acetylated-α-tubulin to label rhabdomeric photoreceptors and the neuronal scaffold. Our approach that combines light sheet microscopy with the clearing protocol, autofluorescence properties of amphioxus, and antibody immunodetection allows visualizing anatomical structures and even individual cells in the 3D space of the entire animal body.

Automation of Organoid Cultures: Current Protocols and Applications

GRAPHICAL ABSTRACT

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It's clearly the heart! Optical transparency, cardiac tissue imaging, and computer modelling

Recent developments in clearing and microscopy enable 3D imaging with cellular resolution up to the whole organ level. These methods have been used extensively in neurobiology, but their uptake in other fields has been much more limited. Application of this approach to the human heart and effective use of the data acquired present challenges of scale and complexity. Four interlinked issues need to be addressed: 1) efficient clearing and labelling of heart tissue, 2) fast microscopic imaging of human-scale samples, 3) handling and processing of multi-terabyte 3D images, and 4) extraction of structural information in computationally tractable structure-based models of cardiac function. Preliminary studies show that each of these requirements can be achieved with the appropriate application and development of existing technologies.

An early cell shape transition drives evolutionary expansion of the human forebrain

The human brain has undergone rapid expansion since humans diverged from other great apes, but the mechanism of this human-specific enlargement is still unknown. Here, we use cerebral organoids derived from human, gorilla, and chimpanzee cells to study developmental mechanisms driving evolutionary brain expansion. We find that neuroepithelial differentiation is a protracted process in apes, involving a previously unrecognized transition state characterized by a change in cell shape. Furthermore, we show that human organoids are larger due to a delay in this transition, associated with differences in interkinetic nuclear migration and cell cycle length. Comparative RNA sequencing (RNA-seq) reveals differences in expression dynamics of cell morphogenesis factors, including ZEB2, a known epithelial-mesenchymal transition regulator. We show that ZEB2 promotes neuroepithelial transition, and its manipulation and downstream signaling leads to acquisition of nonhuman ape architecture in the human context and vice versa, establishing an important role for neuroepithelial cell shape in human brain expansion.

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Human brain organoids are expanded relative to nonhuman apes prior to neurogenesis

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Ape neural progenitors go through a newly identified transition morphotype state

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Delayed morphological transition with shorter cell cycles underlie human expansion

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ZEB2 is as an evolutionary regulator of this transition

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

A guidebook for DISCO tissue clearing

Histological analysis of biological tissues by mechanical sectioning is significantly time-consuming and error-prone due to loss of important information during sample slicing. In the recent years, the development of tissue clearing methods overcame several of these limitations and allowed exploring intact biological specimens by rendering tissues transparent and subsequently imaging them by laser scanning fluorescence microscopy. In this review, we provide a guide for scientists who would like to perform a clearing protocol from scratch without any prior knowledge, with an emphasis on DISCO clearing protocols, which have been widely used not only due to their robustness, but also owing to their relatively straightforward application. We discuss diverse tissue-clearing options and propose solutions for several possible pitfalls. Moreover, after surveying more than 30 researchers that employ tissue clearing techniques in their laboratories, we compiled the most frequently encountered issues and propose solutions. Overall, this review offers an informative and detailed guide through the growing literature of tissue clearing and can help with finding the easiest way for hands-on implementation.

High-Throughput Lossy-to-Lossless 3D Image Compression

The rapid increase in medical and biomedical image acquisition rates has opened up new avenues for image analysis, but has also introduced formidable challenges. This is evident, for example, in selective plane illumination microscopy where acquisition rates of about 1-4 GB/s sustained over several days have redefined the scale of I/O bandwidth required by image analysis tools. Although the effective bandwidth could, principally, be increased by lossy-to-lossless data compression, this is of limited value in practice due to the high computational demand of current schemes such as JPEG2000 that reach compression throughput of one order of magnitude below that of image acquisition. Here we present a novel lossy-to-lossless data compression scheme with a compression throughput well above 4 GB/s and compression rates and rate-distortion curves competitive with those achieved by JPEG2000 and JP3D.

The level of oncogenic Ras determines the malignant transformation of Lkb1 mutant tissue in vivo

The genetic and metabolic heterogeneity of RAS-driven cancers has confounded therapeutic strategies in the clinic. To address this, rapid and genetically tractable animal models are needed that recapitulate the heterogeneity of RAS-driven cancers in vivo. Here, we generate a Drosophila melanogaster model of Ras/Lkb1 mutant carcinoma. We show that low-level expression of oncogenic Ras (RasLow) promotes the survival of Lkb1 mutant tissue, but results in autonomous cell cycle arrest and non-autonomous overgrowth of wild-type tissue. In contrast, high-level expression of oncogenic Ras (RasHigh) transforms Lkb1 mutant tissue resulting in lethal malignant tumors. Using simultaneous multiview light-sheet microcopy, we have characterized invasion phenotypes of Ras/Lkb1 tumors in living larvae. Our molecular analysis reveals sustained activation of the AMPK pathway in malignant Ras/Lkb1 tumors, and demonstrate the genetic and pharmacologic dependence of these tumors on CaMK-activated Ampk. We further show that LKB1 mutant human lung adenocarcinoma patients with high levels of oncogenic KRAS exhibit worse overall survival and increased AMPK activation. Our results suggest that high levels of oncogenic KRAS is a driving event in the malignant transformation of LKB1 mutant tissue, and uncovers a vulnerability that may be used to target this aggressive genetic subset of RAS-driven tumors.

Current Status of Tissue Clearing and the Path Forward in Neuroscience

Due to the complexity and limited availability of human brain tissues, for decades, pathologists have sought to maximize information gained from individual samples, based on which (patho)physiological processes could be inferred. Recently, new understandings of chemical and physical properties of biological tissues and multiple chemical profiling have given rise to the development of scalable tissue clearing methods allowing superior optical clearing of across-the-scale samples. In the past decade, tissue clearing techniques, molecular labeling methods, advanced laser scanning microscopes, and data visualization and analysis have become commonplace. Combined, they have made 3D visualization of brain tissues with unprecedented resolution and depth widely accessible. To facilitate further advancements and applications, here we provide a critical appraisal of these techniques. We propose a classification system of current tissue clearing and expansion methods that allows users to judge the applicability of individual ones to their questions, followed by a review of the current progress in molecular labeling, optical imaging, and data processing to demonstrate the whole 3D imaging pipeline based on tissue clearing and downstream techniques for visualizing the brain. We also raise the path forward of tissue-clearing-based imaging technology, that is, integrating with state-of-the-art techniques, such as multiplexing protein imaging, in situ signal amplification, RNA detection and sequencing, super-resolution imaging techniques, multiomics studies, and deep learning, for drawing the complete atlas of the human brain and building a 3D pathology platform for central nervous system disorders.

New techniques for studying neurodevelopment

The extraordinary diversity, variability, and complexity of cell types in the vertebrate brain is overwhelming and far exceeds that of any other organ. This complexity is the result of multiple cell divisions and intricate gene regulation and cell movements that take place during embryonic development. Understanding the cellular and molecular mechanisms underlying these complicated developmental processes requires the ability to obtain a complete registry of interconnected events often taking place far apart from each other. To assist with this challenging task, developmental neuroscientists take advantage of a broad set of methods and technologies, often adopted from other fields of research. Here, we review some of the methods developed in recent years whose use has rapidly spread for application in the field of developmental neuroscience. We also provide several considerations regarding the promise that these techniques hold for the near future and share some ideas on how existing methods from other research fields could help with the analysis of how neural circuits emerge.

Nuclear crowding and nonlinear diffusion during interkinetic nuclear migration in the zebrafish retina

An important question in early neural development is the origin of stochastic nuclear movement between apical and basal surfaces of neuroepithelia during interkinetic nuclear migration. Tracking of nuclear subpopulations has shown evidence of diffusion - mean squared displacements growing linearly in time - and suggested crowding from cell division at the apical surface drives basalward motion. Yet, this hypothesis has not yet been tested, and the forces involved not quantified. We employ long-term, rapid light-sheet and two-photon imaging of early zebrafish retinogenesis to track entire populations of nuclei within the tissue. The time-varying concentration profiles show clear evidence of crowding as nuclei reach close-packing and are quantitatively described by a nonlinear diffusion model. Considerations of nuclear motion constrained inside the enveloping cell membrane show that concentration-dependent stochastic forces inside cells, compatible in magnitude to those found in cytoskeletal transport, can explain the observed magnitude of the diffusion constant.

Light up the embryos: knock-in reporter generation for mouse developmental biology

Developmental biology seeks to understand the sophisticated regulated process through which a single cell – a fertilized egg – generates a highly organized organism. The most effective way to reveal the nature of these processes is to follow single cells and cell lineages in real-time. Recent advances in imaging equipment, fluorescent tags and computational tools have made long term multi-color imaging of cells and embryos possible. However, there is still one major challenging for achieving live imaging of mammalian embryos- the generation of embryos carrying reporters that recapitulate the endogenous expression pattern of marker genes. Recent developments of genome editing technology played important roles in enabling efficient generation of reporter mouse models. This mini review discusses recent developments of technologies for efficiently generate knock-in reporter mice and the application of these models in live imaging development. With these developments, we are starting to realize the long-sought promises of realtime analysis of mammalian development.

Hydra image processor: 5-D GPU image analysis library with MATLAB and python wrappers

SUMMARY

Light microscopes can now capture data in five dimensions at very high frame rates producing terabytes of data per experiment. Five-dimensional data has three spatial dimensions (x, y, z), multiple channels (λ) and time (t). Current tools are prohibitively time consuming and do not efficiently utilize available hardware. The hydra image processor (HIP) is a new library providing hardware-accelerated image processing accessible from interpreted languages including MATLAB and Python. HIP automatically distributes data/computation across system and video RAM allowing hardware-accelerated processing of arbitrarily large images. HIP also partitions compute tasks optimally across multiple GPUs. HIP includes a new kernel renormalization reducing boundary effects associated with widely used padding approaches.

AVAILABILITY AND IMPLEMENTATION

HIP is free and open source software released under the BSD 3-Clause License. Source code and compiled binary files will be maintained on http://www.hydraimageprocessor.com. A comprehensive description of all MATLAB and Python interfaces and user documents are provided. HIP includes GPU-accelerated support for most common image processing operations in 2-D and 3-D and is easily extensible. HIP uses the NVIDIA CUDA interface to access the GPU. CUDA is well supported on Windows and Linux with macOS support in the future.

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.

Reprint of "Multi-modal image cytometry approach - From dynamic to whole organ imaging"

Optical imaging is a valuable tool to visualise biological processes in the context of the tissue. Each imaging modality provides the biologist with different types of information - cell dynamics and migration over time can be tracked with time-lapse imaging (e.g. intra-vital imaging); an overview of whole tissues can be acquired using optical clearing in conjunction with light sheet microscopy; finer details such as cellular morphology and fine nerve tortuosity can be imaged at higher resolution using the confocal microscope. Multi-modal imaging combined with image cytometry - a form of quantitative analysis of image datasets - provides an objective basis for comparing between sample groups. Here, we provide an overview of technical aspects to look out for in an image cytometry workflow, and discuss issues related to sample preparation, image post-processing and analysis for intra-vital and whole organ imaging.

Tissue clearing and its applications in neuroscience

State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.

Embryo-Based Large Fragment Knock-in in Mammals: Why, How and What's Next

Endonuclease-mediated genome editing technologies, most notably CRISPR/Cas9, have revolutionized animal genetics by allowing for precise genome editing directly through embryo manipulations. As endonuclease-mediated model generation became commonplace, large fragment knock-in remained one of the most challenging types of genetic modification. Due to their unique value in biological and biomedical research, however, a diverse range of technological innovations have been developed to achieve efficient large fragment knock-in in mammalian animal model generation, with a particular focus on mice. Here, we first discuss some examples that illustrate the importance of large fragment knock-in animal models and then detail a subset of the recent technological advancements that have allowed for efficient large fragment knock-in. Finally, we envision the future development of even larger fragment knock-ins performed in even larger animal models, the next step in expanding the potential of large fragment knock-in in animal models.

Light-Sheet Microscopy and Its Potential for Understanding Developmental Processes

The ability to visualize and quantitatively measure dynamic biological processes in vivo and at high spatiotemporal resolution is of fundamental importance to experimental investigations in developmental biology. Light-sheet microscopy is particularly well suited to providing such data, since it offers exceptionally high imaging speed and good spatial resolution while minimizing light-induced damage to the specimen. We review core principles and recent advances in light-sheet microscopy, with a focus on concepts and implementations relevant for applications in developmental biology. We discuss how light-sheet microcopy has helped advance our understanding of developmental processes from single-molecule to whole-organism studies, assess the potential for synergies with other state-of-the-art technologies, and introduce methods for computational image and data analysis. Finally, we explore the future trajectory of light-sheet microscopy, discuss key efforts to disseminate new light-sheet technology, and identify exciting opportunities for further advances.

Single-Cell Reconstruction of Emerging Population Activity in an Entire Developing Circuit

Animal survival requires a functioning nervous system to develop during embryogenesis. Newborn neurons must assemble into circuits producing activity patterns capable of instructing behaviors. Elucidating how this process is coordinated requires new methods that follow maturation and activity of all cells across a developing circuit. We present an imaging method for comprehensively tracking neuron lineages, movements, molecular identities, and activity in the entire developing zebrafish spinal cord, from neurogenesis until the emergence of patterned activity instructing the earliest spontaneous motor behavior. We found that motoneurons are active first and form local patterned ensembles with neighboring neurons. These ensembles merge, synchronize globally after reaching a threshold size, and finally recruit commissural interneurons to orchestrate the left-right alternating patterns important for locomotion in vertebrates. Individual neurons undergo functional maturation stereotypically based on their birth time and anatomical origin. Our study provides a general strategy for reconstructing how functioning circuits emerge during embryogenesis. VIDEO ABSTRACT.

Light sheet microscopy for histopathology applications

Light sheet microscopy (LSM) is an evolving optical imaging technique with a plane illumination for optical sectioning and volumetric imaging spanning cell biology, embryology, and in vivo live imaging. Here, we focus on emerging biomedical applications of LSM for tissue samples. Decoupling of the light sheet illumination from detection enables high-speed and large field-of-view imaging with minimal photobleaching and phototoxicity. These unique characteristics of the LSM technique can be easily adapted and potentially replace conventional histopathological procedures. In this review, we cover LSM technology from its inception to its most advanced technology; in particular, we highlight the human histopathological imaging applications to demonstrate LSM's rapid diagnostic ability in comparison with conventional histopathological procedures. We anticipate that the LSM technique can become a useful three-dimensional imaging tool for assessing human biopsies in the near future.

Stripe artifact reduction for digital scanned structured illumination light sheet microscopy

Light sheet microscopy is an important and widely used method for studying large and semi-opaque biological specimens. One drawback of the approach is that it often results in stripe artifacts due to absorption and scattering in the illumination path. Here we describe a new approach which will effectively mitigate the artifacts in digital scanned light sheet microscopy (DSLM) and digital scanned structured illumination light sheet microscopy (DSLM-SI). We further improve the results of DSLM-SI through a new reconstruction method which achieves clearer reconstructed images. We demonstrate the reduction of stripe artifacts by imaging 156 microns deep into the larval zebrafish central nervous system. The magnitude of stripe artifacts is reduced by an average of 20% across three datasets.

Practical Considerations in Particle and Object Tracking and Analysis

The rapid advancement of live-cell imaging technologies has enabled biologists to generate high-dimensional data to follow biological movement at the microscopic level. Yet, the "perceived" ease of use of modern microscopes has led to challenges whereby sub-optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill-advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image-processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. © 2019 by John Wiley & Sons, Inc.

Big data in nanoscale connectomics, and the greed for training labels

The neurosciences have developed methods that outpace most other biomedical fields in terms of acquired bytes. We review how the information content and analysis challenge of such data indicates that electron microscopy (EM)-based connectomics is an especially hard problem. Here, as in many other current machine learning applications, the need for excessive amounts of labelled data while utilizing only a small fraction of available raw image data for algorithm training illustrates the still fundamental gap between artificial and biological intelligence. Substantial improvements of label and energy efficiency in machine learning may be required to address the formidable challenge of acquiring the nanoscale connectome of a human brain.

A practical guide to adaptive light-sheet microscopy

We describe the implementation and use of an adaptive imaging framework for optimizing spatial resolution and signal strength in a light-sheet microscope. The framework, termed AutoPilot, comprises hardware and software modules for automatically measuring and compensating for mismatches between light-sheet and detection focal planes in living specimens. Our protocol enables researchers to introduce adaptive imaging capabilities in an existing light-sheet microscope or use our SiMView microscope blueprint to set up a new adaptive multiview light-sheet microscope. The protocol describes (i) the mechano-optical implementation of the adaptive imaging hardware, including technical drawings for all custom microscope components; (ii) the algorithms and software library for automated adaptive imaging, including the pseudocode and annotated source code for all software modules; and (iii) the execution of adaptive imaging experiments, as well as the configuration and practical use of the AutoPilot framework. Setup of the adaptive imaging hardware and software takes 1-2 weeks each. Previous experience with light-sheet microscopy and some familiarity with software engineering and building of optical instruments are recommended. Successful implementation of the protocol recovers near diffraction-limited performance in many parts of typical multicellular organisms studied with light-sheet microscopy, such as fruit fly and zebrafish embryos, for which resolution and signal strength are improved two- to fivefold.

A Preferred Curvature-Based Continuum Mechanics Framework for Modeling Embryogenesis

Mechanics plays a key role in the development of higher organisms. However, understanding this relationship is complicated by the difficulty of modeling the link between local forces generated at the subcellular level and deformations observed at the tissue and whole-embryo levels. Here we propose an approach first developed for lipid bilayers and cell membranes, in which force-generation by cytoskeletal elements enters a continuum mechanics formulation for the full system in the form of local changes in preferred curvature. This allows us to express and solve the system using only tissue strains. Locations of preferred curvature are simply related to products of gene expression. A solution, in that context, means relaxing the system's mechanical energy to yield global morphogenetic predictions that accommodate a tendency toward the local preferred curvature, without a need to explicitly model force-generation mechanisms at the molecular level. Our computational framework, which we call SPHARM-MECH, extends a 3D spherical harmonics parameterization known as SPHARM to combine this level of abstraction with a sparse shape representation. The integration of these two principles allows computer simulations to be performed in three dimensions on highly complex shapes, gene expression patterns, and mechanical constraints. We demonstrate our approach by modeling mesoderm invagination in the fruit-fly embryo, where local forces generated by the acto-myosin meshwork in the region of the future mesoderm lead to formation of a ventral tissue fold. The process is accompanied by substantial changes in cell shape and long-range cell movements. Applying SPHARM-MECH to whole-embryo live imaging data acquired with light-sheet microscopy reveals significant correlation between calculated and observed tissue movements. Our analysis predicts the observed cell shape anisotropy on the ventral side of the embryo and suggests an active mechanical role of mesoderm invagination in supporting the onset of germ-band extension.

Ex Utero Culture and Imaging of Mouse Embryos

Mouse genetic approaches when combined with live imaging tools are revolutionizing our current understanding of mammalian developmental biology. The availability and improvement of a wide variety of genetically encoded fluorescent proteins have provided indispensable tools to visualize cells and subcellular features in living organisms. It is now possible to generate genetically modified mouse lines expressing several spectrally distinct fluorescent proteins in a tissue-specific or -inducible manner. Such reporter-expressing lines make it possible to image dynamic cellular behaviors in the context of living embryos undergoing normal or aberrant development. As with all viviparous mammals, mouse embryos develop within the uterus, and so live imaging experiments require culture conditions that closely mimic the in vivo environment. Over the past decades, significant advances have been made in developing conditions for culturing both pre- and postimplantation-stage mouse embryos. In this chapter, we discuss routine methods for ex utero culture of preimplantation- and postimplantation-stage mouse embryos. In particular, we describe protocols for collecting mouse embryos of various stages, setting up culture conditions for their ex utero culture and imaging, and using laser scanning confocal microscopy to visualize live processes in mouse embryos expressing fluorescent reporters.

Choosing the right microscope to image mitosis in zebrafish embryos: A practical guide

Tissue growth and organismal development require orchestrated cell proliferation. To understand how cell division guides development, it is important to explore mitosis at the tissue-wide, cellular, and subcellular scale. At the tissue level this includes determining a tissue's mitotic index, at the cellular level the tracing of cell lineages, and at the subcellular level the characterization of intracellular components. These different tasks can be addressed by different imaging approaches (e.g., laser-scanning confocal, spinning disk confocal, and light-sheet fluorescence microscopy). Here, we summarize three protocols for exploring different facets of mitosis in developing zebrafish embryos. Zebrafish embryos are transparent and their rapid external development greatly facilitates the study of cellular processes and developmental dynamics using microscopy. A critical step in all imaging studies of mitosis in development is to choose the most suitable microscope for each scientific question. This choice is important in order to ensure a balance between the required temporal and spatial resolution and minimal phototoxicity that could otherwise perturb the process of interest. The use of different microscopy techniques, best suited for the purpose of each experiment, thus permits to generate a comprehensive and unbiased view on how mitosis influences development.

A call for public archives for biological image data

Public data archives are the backbone of modern biological research. Biomolecular archives are well established, but bioimaging resources lag behind them. The technology required for imaging archives is now available, thus enabling the creation of the first public bioimage datasets. We present the rationale for the construction of bioimage archives and their associated databases to underpin the next revolution in bioinformatics discovery.

In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level

The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource. VIDEO ABSTRACT.

Multidirectional digital scanned light-sheet microscopy enables uniform fluorescence excitation and contrast-enhanced imaging

Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful method for rapid and optically efficient 3D microscopy. Initial LSFM designs utilized a static sheet of light, termed selective plane illumination microscopy (SPIM), which exhibited shadowing artifacts and deteriorated contrast due to light scattering. These issues have been addressed, in part, by multidirectional selective plane illumination microscopy (mSPIM), in which rotation of the light sheet is used to mitigate shadowing artifacts, and digital scanned light-sheet microscopy (DSLM), in which confocal line detection is used to reject scattered light. Here we present a simple and passive multidirectional digital scanned light-sheet microscopy (mDSLM) architecture that combines the benefits of mSPIM and DSLM. By utilizing an elliptical Gaussian beam with increased angular diversity in the imaging plane, mDSLM provides mitigation of shadowing artifacts and contrast-enhanced imaging of fluorescently labeled samples.