Light-Sheet Microscopy and Its Potential for Understanding Developmental Processes

In Vivo Microrheology Reveals Local Elastic and Plastic Responses Inside 3D Bacterial Biofilms

Bacterial biofilms are highly abundant 3D living materials capable of performing complex biomechanical and biochemical functions, including programmable growth, self-repair, filtration, and bioproduction. Methods to measure internal mechanical properties of biofilms in vivo with spatial resolution on the cellular scale have been lacking. Here, thousands of cells are tracked inside living 3D biofilms of the bacterium Vibrio cholerae during and after the application of shear stress, for a wide range of stress amplitudes, periods, and biofilm sizes, which revealed anisotropic elastic and plastic responses of both cell displacements and cell reorientations. Using cellular tracking to infer parameters of a general mechanical model, spatially-resolved measurements of the elastic modulus inside the biofilm are obtained, which correlate with the spatial distribution of the polysaccharides within the biofilm matrix. The noninvasive microrheology and force-inference approach introduced here provides a general framework for studying mechanical properties with high spatial resolution in living materials.

An emerging role for tissue plasticity in developmental precision

Reproducible tissue morphology is a fundamental feature of embryonic development. To ensure such robustness during tissue morphogenesis, inherent noise in biological processes must be buffered. While redundant genes, parallel signaling pathways and intricate network topologies are known to reduce noise, over the last few years, mechanical properties of tissues have been shown to play a vital role. Here, taking the example of somite shape changes, I will discuss how tissues are highly plastic in their ability to change shapes leading to increased precision and reproducibility.

Tissue clearing and imaging approaches for in toto analysis of the reproductive system†

New microscopy techniques in combination with tissue clearing protocols and emerging analytical approaches have presented researchers with the tools to understand dynamic biological processes in a three-dimensional context. This paves the road for the exploration of new research questions in reproductive biology, for which previous techniques have provided only approximate resolution. These new methodologies now allow for contextualized analysis of far-larger volumes than was previously possible. Tissue optical clearing and three-dimensional imaging techniques posit the bridging of molecular mechanisms, macroscopic morphogenic development, and maintenance of reproductive function into one cohesive and comprehensive understanding of the biology of the reproductive system. In this review, we present a survey of the various tissue clearing techniques and imaging systems, as they have been applied to the developing and adult reproductive system. We provide an overview of tools available for analysis of experimental data, giving particular attention to the emergence of artificial intelligence-assisted methods and their applicability to image analysis. We conclude with an evaluation of how novel image analysis approaches that have been applied to other organ systems could be incorporated into future experimental evaluation of reproductive biology.

Unraveling the Neural Circuits: Techniques, Opportunities and Challenges in Epilepsy Research

Epilepsy, a prevalent neurological disorder characterized by high morbidity, frequent recurrence, and potential drug resistance, profoundly affects millions of people globally. Understanding the microscopic mechanisms underlying seizures is crucial for effective epilepsy treatment, and a thorough understanding of the intricate neural circuits underlying epilepsy is vital for the development of targeted therapies and the enhancement of clinical outcomes. This review begins with an exploration of the historical evolution of techniques used in studying neural circuits related to epilepsy. It then provides an extensive overview of diverse techniques employed in this domain, discussing their fundamental principles, strengths, limitations, as well as their application. Additionally, the synthesis of multiple techniques to unveil the complexity of neural circuits is summarized. Finally, this review also presents targeted drug therapies associated with epileptic neural circuits. By providing a critical assessment of methodologies used in the study of epileptic neural circuits, this review seeks to enhance the understanding of these techniques, stimulate innovative approaches for unraveling epilepsy's complexities, and ultimately facilitate improved treatment and clinical translation for epilepsy.

Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders

Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.

Emergence of a left-right symmetric body plan in vertebrate embryos

External bilateral symmetry is a prevalent feature in vertebrates, which emerges during early embryonic development. To begin with, vertebrate embryos are largely radially symmetric before transitioning to bilaterally symmetry, after which, morphogenesis of various bilateral tissues (e.g somites, otic vesicle, limb bud), and structures (e.g palate, jaw) ensue. While a significant amount of work has probed the mechanisms behind symmetry breaking in the left-right axis leading to asymmetric positioning of internal organs, little is known about how bilateral tissues emerge at the same time with the same shape and size and at the same position on the two sides of the embryo. By discussing emergence of symmetry in many bilateral tissues and structures across vertebrate model systems, we highlight that understanding symmetry establishment is largely an open field, which will provide deep insights into fundamental problems in developmental biology for decades to come.

SHR and SCR coordinate root patterning and growth early in the cell cycle

Precise control of cell division is essential for proper patterning and growth during the development of multicellular organisms. Coordination of formative divisions that generate new tissue patterns with proliferative divisions that promote growth is poorly understood. SHORTROOT (SHR) and SCARECROW (SCR) are transcription factors that are required for formative divisions in the stem cell niche of Arabidopsis roots1,2. Here we show that levels of SHR and SCR early in the cell cycle determine the orientation of the division plane, resulting in either formative or proliferative cell division. We used 4D quantitative, long-term and frequent (every 15 min for up to 48 h) light sheet and confocal microscopy to probe the dynamics of SHR and SCR in tandem within single cells of living roots. Directly controlling their dynamics with an SHR induction system enabled us to challenge an existing bistable model3 of the SHR-SCR gene-regulatory network and to identify key features that are essential for rescue of formative divisions in shr mutants. SHR and SCR kinetics do not align with the expected behaviour of a bistable system, and only low transient levels, present early in the cell cycle, are required for formative divisions. These results reveal an uncharacterized mechanism by which developmental regulators directly coordinate patterning and growth.

Successful 3D imaging of cleared biological samples with light sheet fluorescence microscopy

In parallel with the development of tissue-clearing methods, over the last decade, light sheet fluorescence microscopy has contributed to major advances in various fields, such as cell and developmental biology and neuroscience. While biologists are increasingly integrating three-dimensional imaging into their research projects, their experience with the technique is not always up to their expectations. In response to a survey of specific challenges associated with sample clearing and labeling, image acquisition, and data analysis, we have critically assessed the recent literature to characterize the difficulties inherent to light sheet fluorescence microscopy applied to cleared biological samples and to propose solutions to overcome them. This review aims to provide biologists interested in light sheet fluorescence microscopy with a primer for the development of their imaging pipeline, from sample preparation to image analysis. Importantly, we believe that issues could be avoided with better anticipation of image analysis requirements, which should be kept in mind while optimizing sample preparation and acquisition parameters.

Culture conditions in the IVF laboratory: state of the ART and possible new directions

In the last four decades, the assisted reproductive technology (ART) field has witnessed advances, resulting in improving pregnancy rates and diminishing complications, in particular reduced incidence of multiple births. These improvements are secondary to advanced knowledge on embryonic physiology and metabolism, resulting in the ability to design new and improved culture conditions. Indeed, the incubator represents only a surrogate of the oviduct and uterus, and the culture conditions are only imitating the physiological environment of the female reproductive tract. In vivo, the embryo travels through a dynamic and changing environment from the oviduct to the uterus, while in vitro, the embryo is cultured in a static fashion. Importantly, while culture media play a critical role in optimising embryo development, a large host of additional factors are equally important. Additional potential variables, including but not limited to pH, temperature, osmolality, gas concentrations and light exposure need to be carefully controlled to prevent stress and permit optimal implantation potential. This manuscript will provide an overview of how different current culture conditions may affect oocyte and embryo viability with particular focus on human literature.

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.

Exploring the Impact of Controlled Ovarian Stimulation and Non-Invasive Oocyte Assessment in ART Treatments

Invasive and noninvasive features are normally applied to select developmentally competent oocytes and embryos that can increase the take-home baby rates in assisted reproductive technology. The noninvasive approach mainly applied to determine oocyte and embryo competence has been, since the early days of IVF, the morphological evaluation of the mature cumulus-oocyte complex at the time of pickup, first polar body, zona pellucida thickness, perivitelline space and cytoplasm appearance. Morphological evaluation of oocyte quality is one of the options used to predict successful fertilization, early embryo development, uterine implantation and the capacity of an embryo to generate a healthy pregnancy to term. Thus, this paper aims to provide an analytical revision of the current literature relating to the correlation between ovarian stimulation procedures and oocyte/embryo quality. In detail, several aspects of oocyte quality such as morphological features, oocyte competence and its surrounding environment will be discussed. In addition, the main noninvasive features as well as novel approaches to biomechanical parameters of oocytes that might be correlated with the competence of embryos to produce a healthy pregnancy and live birth will be illustrated.

A biologist's guide to planning and performing quantitative bioimaging experiments

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. This Essay provides a navigational guide for experimental biologists to aid understanding of quantitative bioimaging from sample preparation through to image acquisition, image analysis, and data interpretation. We discuss the interconnectedness of these steps, and for each, we provide general recommendations, key questions to consider, and links to high-quality open-access resources for further learning. This synthesis of information will empower biologists to plan and execute rigorous quantitative bioimaging experiments efficiently.

Viewing life without labels under optical microscopes

Optical microscopes today have pushed the limits of speed, quality, and observable space in biological specimens revolutionizing how we view life today. Further, specific labeling of samples for imaging has provided insight into how life functions. This enabled label-based microscopy to percolate and integrate into mainstream life science research. However, the use of labelfree microscopy has been mostly limited, resulting in testing for bio-application but not bio-integration. To enable bio-integration, such microscopes need to be evaluated for their timeliness to answer biological questions uniquely and establish a long-term growth prospect. The article presents key label-free optical microscopes and discusses their integrative potential in life science research for the unperturbed analysis of biological samples.

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.

Airy beam light sheet microscopy boosted by deep learning deconvolution

Common light sheet microscopy comes with a trade-off between light sheet width defining the optical sectioning and the usable field of view arising from the divergence of the illuminating Gaussian beam. To overcome this, low-diverging Airy beams have been introduced. Airy beams, however, exhibit side lobes degrading image contrast. Here, we constructed an Airy beam light sheet microscope, and developed a deep learning image deconvolution to remove the effects of the side lobes without knowledge of the point spread function. Using a generative adversarial network and high-quality training data, we significantly enhanced image contrast and improved the performance of a bicubic upscaling. We evaluated the performance with fluorescently labeled neurons in mouse brain tissue samples. We found that deep learning-based deconvolution was about 20-fold faster than the standard approach. The combination of Airy beam light sheet microscopy and deep learning deconvolution allows imaging large volumes rapidly and with high quality.

Marine animal evolutionary developmental biology-Advances through technology development

Evolutionary developmental biology, the interdisciplinary effort of illuminating the conserved similarities and differences during animal development across all phylogenetic clades, has gained renewed interest in the past decades. As technology (immunohistochemistry, next-generation sequencing, advanced imaging, and computational resources) has advanced, so has our ability of resolving fundamental hypotheses and overcoming the genotype-phenotype gap. This rapid progress, however, has also exposed gaps in the collective knowledge around the choice and representation of model organisms. It has become clear that evo-devo requires a comparative, large-scale approach including marine invertebrates to resolve some of the most urgent questions about the phylogenetic positioning and character traits of the last common ancestors. Many invertebrates at the base of the tree of life inhabit marine environments and have been used for some years due to their accessibility, husbandry, and morphology. Here, we briefly review the major concepts of evolutionary developmental biology and discuss the suitability of established model organisms to address current research questions, before focussing on the importance, application, and state-of-the-art of marine evo-devo. We highlight novel technical advances that progress evo-devo as a whole.

Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations

We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8% of cell lineages spanning 1 h, as compared to 31.8% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging

Although light-sheet-based super-resolution microscopy is an excellent detection technique for biological samples because of minimal photodamage, uneven light paths due to solid-angle illumination limits it, resulting in an optical illusion. Furthermore, the optical illusion limits the observations of individual molecules in diffraction. In this study, a four-dimensional cuboid multiangle illumination-based light-sheet super-resolution (4D CMLS) imaging system was developed to minimize optical illusions in cells. The lab-built 4D CMLS imaging system was integrated with total internal reflection fluorescence and a differential interference contrast microscope. A specially designed rotatable cuboid prism simply overcame the optical illusion by rotating a specimen on the prism to change the direction of light coming from an illumination lens. 4D CMLS reconstructed images of nanoparticles of different sizes were acquired in multi-illumination angles of 0°, 90°, 180°, and 270°. Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. The 4D CMLS imaging method demonstrates the in-depth 4D observation of samples at an optimum angle that can be used in various applications, such as single-molecule and subcellular organelle observations in single cells at subdiffraction limit resolutions that describe the scenario of nature.

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.

Deep learning in single-molecule imaging and analysis: recent advances and prospects

Single-molecule microscopy is advantageous in characterizing heterogeneous dynamics at the molecular level. However, there are several challenges that currently hinder the wide application of single molecule imaging in bio-chemical studies, including how to perform single-molecule measurements efficiently with minimal run-to-run variations, how to analyze weak single-molecule signals efficiently and accurately without the influence of human bias, and how to extract complete information about dynamics of interest from single-molecule data. As a new class of computer algorithms that simulate the human brain to extract data features, deep learning networks excel in task parallelism and model generalization, and are well-suited for handling nonlinear functions and extracting weak features, which provide a promising approach for single-molecule experiment automation and data processing. In this perspective, we will highlight recent advances in the application of deep learning to single-molecule studies, discuss how deep learning has been used to address the challenges in the field as well as the pitfalls of existing applications, and outline the directions for future development.

Understanding Breast Cancers through Spatial and High-Resolution Visualization Using Imaging Technologies

Breast cancer is the most common cancer affecting women worldwide. Although many analyses and treatments have traditionally targeted the breast cancer cells themselves, recent studies have focused on investigating entire cancer tissues, including breast cancer cells. To understand the structure of breast cancer tissues, including breast cancer cells, it is necessary to investigate the three-dimensional location of the cells and/or proteins comprising the tissues and to clarify the relationship between the three-dimensional structure and malignant transformation or metastasis of breast cancers. In this review, we aim to summarize the methods for analyzing the three-dimensional structure of breast cancer tissue, paying particular attention to the recent technological advances in the combination of the tissue-clearing method and optical three-dimensional imaging. We also aimed to identify the latest methods for exploring the relationship between the three-dimensional cell arrangement in breast cancer tissues and the gene expression of each cell. Finally, we aimed to describe the three-dimensional imaging features of breast cancer tissues using noninvasive photoacoustic imaging methods.

Beyond the centrosome: The mystery of microtubule organising centres across mammalian preimplantation embryos

Mammalian preimplantation embryogenesis depends on the spatio-temporal dynamics of the microtubule cytoskeleton to enable exceptionally fast changes in cell number, function, architecture, and fate. Microtubule organising centres (MTOCs), which coordinate the remodelling of microtubules, are therefore of fundamental significance during the first days of a new life. Despite its indispensable role during early mammalian embryogenesis, the origin of microtubule growth remains poorly understood. In this review, we summarise the most recent discoveries on microtubule organisation and function during early human embryogenesis and compare these to innovative studies conducted in alternative mammalian models. We emphasise the differences and analogies of centriole inheritance and their role during the first cleavage. Furthermore, we highlight the significance of non-centrosomal MTOCs for embryo viability and discuss the potential of novel in vitro models and light-inducible approaches towards unravelling microtubule formation in research and assisted reproductive technologies.

A squash and a squeeze

Advanced imaging techniques reveal details of the interactions between the two layers of the embryonic midgut that influence its ultimate shape.

Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification

Current imaging approaches limit the ability to perform multi-scale characterization of three-dimensional (3D) organotypic cultures (organoids) in large numbers. Here, we present an automated multi-scale 3D imaging platform synergizing high-density organoid cultures with rapid and live 3D single-objective light-sheet imaging. It is composed of disposable microfabricated organoid culture chips, termed JeWells, with embedded optical components and a laser beam-steering unit coupled to a commercial inverted microscope. It permits streamlining organoid culture and high-content 3D imaging on a single user-friendly instrument with minimal manipulations and a throughput of 300 organoids per hour. We demonstrate that the large number of 3D stacks that can be collected via our platform allows training deep learning-based algorithms to quantify morphogenetic organizations of organoids at multi-scales, ranging from the subcellular scale to the whole organoid level. We validated the versatility and robustness of our approach on intestine, hepatic, neuroectoderm organoids and oncospheres.

The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology?

Modern biology and biomedicine are undergoing a big data explosion, needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome project: a framework and approach for creating, sharing, and using biophysics-based computational models of single-cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date toward creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and reusability of computational models of cells at scale. We conclude with a look forward at steps that will help fully realize this exciting new field of mechanistic biomedical data science. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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.

Bioimaging approaches for quantification of individual cell behavior during cell fate decisions

Tracking individual cells has allowed a new understanding of cellular behavior in human health and disease by adding a dynamic component to the already complex heterogeneity of single cells. Technically, despite countless advances, numerous experimental variables can affect data collection and interpretation and need to be considered. In this review, we discuss the main technical aspects and biological findings in the analysis of the behavior of individual cells. We discuss the most relevant contributions provided by these approaches in clinically relevant human conditions like embryo development, stem cells biology, inflammation, cancer and microbiology, along with the cellular mechanisms and molecular pathways underlying these conditions. We also discuss the key technical aspects to be considered when planning and performing experiments involving the analysis of individual cells over long periods. Despite the challenges in automatic detection, features extraction and long-term tracking that need to be tackled, the potential impact of single-cell bioimaging is enormous in understanding the pathogenesis and development of new therapies in human pathophysiology.

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

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

Non-invasive oocyte quality assessment

Oocyte quality is perhaps the most important limiting factor in female fertility; however, the current methods of determining oocyte competence are only marginally capable of predicting a successful pregnancy. We aim to review the predictive value of non-invasive techniques for the assessment of human oocytes and their related cells and biofluids that pertain to their developmental competence. Investigation of the proteome, transcriptome, and hormonal makeup of follicular fluid, as well as cumulus-oocyte complexes are currently underway; however, prospective randomized non-selection-controlled trials of the future are needed before determining their prognostic value. The biological significance of polar body morphology and genetics are still unknown and the subject of debate. The predictive utility of zygotic viscoelasticity for embryo development has been demonstrated, but similar studies performed on oocytes have yet to be conducted. Metabolic profiling of culture media using human oocytes are also limited and may require integration of automated, high-throughput targeted metabolomic assessments in real time with microfluidic platforms. Light exposure to oocytes can be detrimental to subsequent development and utilization of time-lapse imaging and morphometrics of oocytes is wanting. Polarized light, Raman microspectroscopy, and coherent anti-Stokes Raman scattering are a few novel imaging tools that may play a more important role in future oocyte assessment. Ultimately, the integration of chemistry, genomics, microfluidics, microscopy, physics, and other biomedical engineering technologies into the basic studies of oocyte biology, and in testing and perfecting practical solutions of oocyte evaluation, are the future for non-invasive assessment of oocytes.

Imaging Dynamic Processes in Multiple Dimensions and Length Scales

Optical microscopy has become an invaluable tool for investigating complex samples. Over the years, many advances to optical microscopes have been made that have allowed us to uncover new insights into the samples studied. Dynamic changes in biological and chemical systems are of utmost importance to study. To probe these samples, multidimensional approaches have been developed to acquire a fuller understanding of the system of interest. These dimensions include the spatial information, such as the three-dimensional coordinates and orientation of the optical probes, and additional chemical and physical properties through combining microscopy with various spectroscopic techniques. In this review, we survey the field of multidimensional microscopy and provide an outlook on the field and challenges that may arise. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Development of a 3D atlas of the embryonic pancreas for topological and quantitative analysis of heterologous cell interactions

Generating comprehensive image maps, while preserving spatial three-dimensional (3D) context, is essential in order to locate and assess quantitatively specific cellular features and cell-cell interactions during organ development. Despite recent advances in 3D imaging approaches, our current knowledge of the spatial organization of distinct cell types in the embryonic pancreatic tissue is still largely based on two-dimensional histological sections. Here, we present a light-sheet fluorescence microscopy approach to image the pancreas in three dimensions and map tissue interactions at key time points in the mouse embryo. We demonstrate the utility of the approach by providing volumetric data, 3D distribution of three main cellular components (epithelial, mesenchymal and endothelial cells) within the developing pancreas, and quantification of their relative cellular abundance within the tissue. Interestingly, our 3D images show that endocrine cells are constantly and increasingly in contact with endothelial cells forming small vessels, whereas the interactions with mesenchymal cells decrease over time. These findings suggest distinct cell-cell interaction requirements for early endocrine cell specification and late differentiation. Lastly, we combine our image data in an open-source online repository (referred to as the Pancreas Embryonic Cell Atlas).

Summary: A light-sheet fluorescence microscopy approach is used for 3D imaging of the pancreas and to quantitatively map its interactions with surrounding tissues at key development time points in the mouse embryo.

Revealing epithelial morphogenetic mechanisms through live imaging

Epithelial morphogenesis is guided by mechanical forces and biochemical signals that vary spatiotemporally. As many morphogenetic events are driven by rapid cellular processes, understanding morphogenesis requires monitoring development in real time. Here, we discuss how live-imaging approaches can help identify morphogenetic mechanisms otherwise missed in static snapshots of development. We begin with a summary of live-imaging strategies, including recent advances that push the limits of spatiotemporal resolution and specimen size. We then describe recent efforts that employ live imaging to uncover morphogenetic mechanisms. We conclude by discussing how information collected from live imaging can be enhanced by genetically encoded biosensors and spatiotemporal perturbation techniques to determine the dynamics of patterning of developmental signals and their importance for guiding morphogenesis.

Imaging Approaches for the Study of Metabolism in Real Time Using Genetically Encoded Reporters

Metabolism comprises of two axes in order to serve homeostasis: anabolism and catabolism. Both axes are interbranched with the so-called bioenergetics aspect of metabolism. There is a plethora of analytical biochemical methods to monitor metabolites and reactions in lysates, yet there is a rising need to monitor, quantify and elucidate in real time the spatiotemporal orchestration of complex biochemical reactions in living systems and furthermore to analyze the metabolic effect of chemical compounds that are destined for the clinic. The ongoing technological burst in the field of imaging creates opportunities to establish new tools that will allow investigators to monitor dynamics of biochemical reactions and kinetics of metabolites at a resolution that ranges from subcellular organelle to whole system for some key metabolites. This article provides a mini review of available toolkits to achieve this goal but also presents a perspective on the open space that can be exploited to develop novel methodologies that will merge classic biochemistry of metabolism with advanced imaging. In other words, a perspective of "watching metabolism in real time."

Pulling back the curtain: The hidden functions of receptor tyrosine kinases in development

Receptor tyrosine kinases (RTKs) are a conserved superfamily of transmembrane growth factor receptors that drive numerous cellular processes during development and in the adult. Upon activation, multiple adaptors and signaling effector proteins are recruited to binding site motifs located within the intracellular domain of the RTK. These RTK-effector interactions drive subsequent intracellular signaling cascades involved in canonical RTK signaling. Genetic dissection has revealed that alleles of Fibroblast Growth Factor receptors (FGFRs) that lack all canonical RTK signaling still retain some kinase-dependent biological activity. Here we examine how genetic analysis can be used to understand the mechanism by which RTKs drive multiple developmental processes via canonical signaling while revealing noncanonical activities. Recent data from both FGFRs and other RTKs highlight potential noncanonical roles in cell adhesion and nuclear signaling. The data supporting such functions are discussed as are recent technologies that have the potential to provide valuable insight into the developmental significance of these noncanonical activities.

Imaging Fluorescent Nuclear Pore Complex Proteins in C. elegans

C. elegans is a well-characterized and relatively simple model organism, making it attractive for studying nuclear pore complex proteins in cell and developmental biology. C. elegans is transparent and highly amendable to genetic manipulation. Therefore, it is possible to generate fluorescently tagged proteins and combine this with various light microscopy techniques to study protein behavior in space and time. Here, we provide protocols to prepare both fixed and live C. elegans for confocal and light sheet microscopy. This enables the analysis of nuclear pore complex proteins from embryonic stages to the aging adult.

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

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

Cell3: a new vision for study of the endomembrane system in mammalian cells

The endomembrane system of mammalian cells provides massive capacity for the segregation of biochemical reactions into discrete locations. The individual organelles of the endomembrane system also require the ability to precisely transport material between these compartments in order to maintain cell homeostasis; this process is termed membrane traffic. For several decades, researchers have been systematically identifying and dissecting the molecular machinery that governs membrane trafficking pathways, with the overwhelming majority of these studies being carried out in cultured cells growing as monolayers. In recent years, a number of methodological innovations have provided the opportunity for cultured cells to be grown as 3-dimensional (3D) assemblies, for example as spheroids and organoids. These structures have the potential to better replicate the cellular environment found in tissues and present an exciting new opportunity for the study of cell function. In this mini-review, we summarize the main methods used to generate 3D cell models and highlight emerging studies that have started to use these models to study basic cellular processes. We also describe a number of pieces of work that potentially provide the basis for adaptation for deeper study of how membrane traffic is coordinated in multicellular assemblies. Finally, we comment on some of the technological challenges that still need to be overcome if 3D cell biology is to become a mainstream tool toward deepening our understanding of the endomembrane system in mammalian cells.

OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies

The rapid pace of innovation in biological imaging and the diversity of its applications have prevented the establishment of a community-agreed standardized data format. We propose that complementing established open formats such as OME-TIFF and HDF5 with a next-generation file format such as Zarr will satisfy the majority of use cases in bioimaging. Critically, a common metadata format used in all these vessels can deliver truly findable, accessible, interoperable and reusable bioimaging data.

Towards non-blind optical tweezing by finding 3D refractive index changes through off-focus interferometric tracking

In modern 3D microscopy, holding and orienting arbitrary biological objects with optical forces instead of using coverslips and gel cylinders is still a vision. Although optical trapping forces are strong enough and related photodamage is acceptable, the precise (re-) orientation of large specimen with multiple optical traps is difficult, since they grab blindly at the object and often slip off. Here, we present an approach to localize and track regions with increased refractive index using several holographic optical traps with a single camera in an off-focus position. We estimate the 3D grabbing positions around several trapping foci in parallel through analysis of the beam deformations, which are continuously measured by defocused camera images of cellular structures inside cell clusters. Although non-blind optical trapping is still a vision, this is an important step towards fully computer-controlled orientation and feature-optimized laser scanning of sub-mm sized biological specimen for future 3D light microscopy.

Spectrally Gated Microscopy (SGM) with Meta Optics for Parallel Three-Dimensional Imaging

Volumetric imaging with high spatiotemporal resolution is of utmost importance for various applications ranging from aerospace and defense to real-time imaging of dynamic biological processes. To facilitate three-dimensional sectioning, current technology relies on mechanisms to reject light from adjacent out-of-focus planes either spatially or by other means. Yet, the combination of rapid acquisition time and high axial resolution is still elusive, motivating a persistent pursuit for emerging imaging approaches. Here we introduce and experimentally demonstrate a concept named spectrally gated microscopy (SGM), which enables a single-shot interrogation over the full axial dimension while maintaining a submicron sectioning resolution. SGM utilizes two important features enabled by flat optics (i.e., metalenses or diffractive lenses), namely, a short focal length and strong chromatic aberrations. Using SGM we demonstrate three-dimensional imaging of millimeter-scale samples while scanning only the lateral dimension, presenting a significant advantage over state-of-the-art technology.

Navigating the Light-Sheet Image Analysis Software Landscape: Concepts for Driving Cohesion From Data Acquisition to Analysis

From the combined perspective of biologists, microscope instrumentation developers, imaging core facility scientists, and high performance computing experts, we discuss the challenges faced when selecting imaging and analysis tools in the field of light-sheet microscopy. Our goal is to provide a contextual framework of basic computing concepts that cell and developmental biologists can refer to when mapping the peculiarities of different light-sheet data to specific existing computing environments and image analysis pipelines. We provide our perspective on efficient processes for tool selection and review current hardware and software commonly used in light-sheet image analysis, as well as discuss what ideal tools for the future may look like.

Mechanics of neural tube morphogenesis

The neural tube is an important model system of morphogenesis representing the developmental module of out-of-plane epithelial deformation. As the embryonic precursor of the central nervous system, the neural tube also holds keys to many defects and diseases. Recent advances begin to reveal how genetic, cellular and environmental mechanisms work in concert to ensure correct neural tube shape. A physical model is emerging where these factors converge at the regulation of the mechanical forces and properties within and around the tissue that drive tube formation towards completion. Here we review the dynamics and mechanics of neural tube morphogenesis and discuss the underlying cellular behaviours from the viewpoint of tissue mechanics. We will also highlight some of the conceptual and technical next steps.

Current approaches to fate mapping and lineage tracing using image data

Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.

Super-Resolution Fluorescence Microscopy Methods for Assessing Mouse Biology

Super-resolution (diffraction unlimited) microscopy was developed 15 years ago; the developers were awarded the Nobel Prize in Chemistry in recognition of their work in 2014. Super-resolution microscopy is increasingly being applied to diverse scientific fields, from single molecules to cell organelles, viruses, bacteria, plants, and animals, especially the mammalian model organism Mus musculus. In this review, we explain how super-resolution microscopy, along with fluorescence microscopy from which it grew, has aided the renaissance of the light microscope. We cover experiment planning and specimen preparation and explain structured illumination microscopy, super-resolution radial fluctuations, stimulated emission depletion microscopy, single-molecule localization microscopy, and super-resolution imaging by pixel reassignment. The final section of this review discusses the strengths and weaknesses of each super-resolution technique and how to choose the best approach for your research. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.

Deep learning-based autofocus method enhances image quality in light-sheet fluorescence microscopy

Light-sheet fluorescence microscopy (LSFM) is a minimally invasive and high throughput imaging technique ideal for capturing large volumes of tissue with sub-cellular resolution. A fundamental requirement for LSFM is a seamless overlap of the light-sheet that excites a selective plane in the specimen, with the focal plane of the objective lens. However, spatial heterogeneity in the refractive index of the specimen often results in violation of this requirement when imaging deep in the tissue. To address this issue, autofocus methods are commonly used to refocus the focal plane of the objective-lens on the light-sheet. Yet, autofocus techniques are slow since they require capturing a stack of images and tend to fail in the presence of spherical aberrations that dominate volume imaging. To address these issues, we present a deep learning-based autofocus framework that can estimate the position of the objective-lens focal plane relative to the light-sheet, based on two defocused images. This approach outperforms or provides comparable results with the best traditional autofocus method on small and large image patches respectively. When the trained network is integrated with a custom-built LSFM, a certainty measure is used to further refine the network's prediction. The network performance is demonstrated in real-time on cleared genetically labeled mouse forebrain and pig cochleae samples. Our study provides a framework that could improve light-sheet microscopy and its application toward imaging large 3D specimens with high spatial resolution.

From whole organism to ultrastructure: progress in axonal imaging for decoding circuit development

Since the pioneering work of Ramón y Cajal, scientists have sought to unravel the complexities of axon development underlying neural circuit formation. Micrometer-scale axonal growth cones navigate to targets that are often centimeters away. To reach their targets, growth cones react to dynamic environmental cues that change in the order of seconds to days. Proper axon growth and guidance are essential to circuit formation, and progress in imaging has been integral to studying these processes. In particular, advances in high- and super-resolution microscopy provide the spatial and temporal resolution required for studying developing axons. In this Review, we describe how improved microscopy has revolutionized our understanding of axonal development. We discuss how novel technologies, specifically light-sheet and super-resolution microscopy, led to new discoveries at the cellular scale by imaging axon outgrowth and circuit wiring with extreme precision. We next examine how advanced microscopy broadened our understanding of the subcellular dynamics driving axon growth and guidance. We finally assess the current challenges that the field of axonal biology still faces for imaging axons, and examine how future technology could meet these needs.

Illuminating Plasmodium invasion by lattice-light-sheet microscopy

Plasmodium merozoites invade erythrocytes in a stepwise manner through ligand binding, calcium signaling, and membrane deformation. Using a recently developed light-sheet microscope, Geoghegan et al. investigated invasion with unprecedented temporal resolution. Their spectacular footage revealed roles for host cell cholesterol and pore formation at the parasite-host cell interface.

Removing striping artifacts in light-sheet fluorescence microscopy: a review

In recent years, light-sheet fluorescence microscopy (LSFM) has found a broad application for imaging of diverse biological samples, ranging from sub-cellular structures to whole animals, both in-vivo and ex-vivo, owing to its many advantages relative to point-scanning methods. By providing the selective illumination of sample single planes, LSFM achieves an intrinsic optical sectioning and direct 2D image acquisition, with low out-of-focus fluorescence background, sample photo-damage and photo-bleaching. On the other hand, such an illumination scheme is prone to light absorption or scattering effects, which lead to uneven illumination and striping artifacts in the images, oriented along the light sheet propagation direction. Several methods have been developed to address this issue, ranging from fully optical solutions to entirely digital post-processing approaches. In this work, we present them, outlining their advantages, performance and limitations.

Mechanical Patterning in Animal Morphogenesis

Morphogenesis is one of the most remarkable examples of biological pattern formation. Despite substantial progress in the field, we still do not understand the organizational principles responsible for the robust convergence of the morphogenesis process across scales to form viable organisms under variable conditions. Achieving large-scale coordination requires feedback between mechanical and biochemical processes, spanning all levels of organization and relating the emerging patterns with the mechanisms driving their formation. In this review, we highlight the role of mechanics in the patterning process, emphasizing the active and synergistic manner in which mechanical processes participate in developmental patterning rather than merely following a program set by biochemical signals. We discuss the value of applying a coarse-grained approach toward understanding this complex interplay, which considers the large-scale dynamics and feedback as well as complementing the reductionist approach focused on molecular detail. A central challenge in this approach is identifying relevant coarse-grained variables and developing effective theories that can serve as a basis for an integrated framework for understanding this remarkable pattern-formation process. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 37 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.