Image analysis for understanding embryo development: a bridge from microscopy to biological insights

Mapping human tissues with highly multiplexed RNA in situ hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. There has been a surge of multiplexed RNA in situ mapping techniques but their application to human tissues has been limited due to their large size, general lower tissue quality and high autofluorescence. Here we report DART-FISH, a padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections. We introduce an omni-cell type cytoplasmic stain that substantially improves the segmentation of cell bodies. Our enzyme-free isothermal decoding procedure allows us to image 121 genes in large sections from the human neocortex in <10 h. We successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

Mapping Human Tissues with Highly Multiplexed RNA in situ Hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. Recently there has been a surge of multiplexed RNA in situ techniques but their application to human tissues and clinical biopsies has been limited due to their large size, general lower tissue quality and high background autofluorescence. Here we report DART-FISH, a versatile padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections at cellular resolution. We introduced an omni-cell type cytoplasmic stain, dubbed RiboSoma that substantially improves the segmentation of cell bodies. We developed a computational decoding-by-deconvolution workflow to extract gene spots even in the presence of optical crowding. Our enzyme-free isothermal decoding procedure allowed us to image 121 genes in a large section from the human neocortex in less than 10 hours, where we successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. Additionally, we demonstrated the detection of transcripts as short as 461 nucleotides, including neuropeptides and discovered new cortical layer markers. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

From Cell States to Cell Fates: How Cell Proliferation and Neuronal Differentiation Are Coordinated During Embryonic Development

The central nervous system (CNS) exhibits an extraordinary diversity of neurons, with the right cell types and proportions at the appropriate sites. Thus, to produce brains with specific size and cell composition, the rates of proliferation and differentiation must be tightly coordinated and balanced during development. Early on, proliferation dominates; later on, the growth rate almost ceases as more cells differentiate and exit the cell cycle. Generation of cell diversity and morphogenesis takes place concomitantly. In the vertebrate brain, this results in dramatic changes in the position of progenitor cells and their neuronal derivatives, whereas in the spinal cord morphogenetic changes are not so important because the structure mainly grows by increasing its volume. Morphogenesis is under control of specific genetic programs that coordinately unfold over time; however, little is known about how they operate and impact in the pools of progenitor cells in the CNS. Thus, the spatiotemporal coordination of these processes is fundamental for generating functional neuronal networks. Some key aims in developmental neurobiology are to determine how cell diversity arises from pluripotent progenitor cells, and how the progenitor potential changes upon time. In this review, we will share our view on how the advance of new technologies provides novel data that challenge some of the current hypothesis. We will cover some of the latest studies on cell lineage tracing and clonal analyses addressing the role of distinct progenitor cell division modes in balancing the rate of proliferation and differentiation during brain morphogenesis. We will discuss different hypothesis proposed to explain how progenitor cell diversity is generated and how they challenged prevailing concepts and raised new questions.

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

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

Spatial protein analysis in developing tissues: a sampling-based image processing approach

Advances in fluorescence microscopy approaches have made it relatively easy to generate multi-dimensional image volumes and have highlighted the need for flexible image analysis tools for the extraction of quantitative information from such data. Here we demonstrate that by focusing on simplified feature-based nuclear segmentation and probabilistic cytoplasmic detection we can create a tool that is able to extract geometry-based information from diverse mammalian tissue images. Our open-source image analysis platform, called 'SilentMark', can cope with three-dimensional noisy images and with crowded fields of cells to quantify signal intensity in different cellular compartments. Additionally, it provides tissue geometry related information, which allows one to quantify protein distribution with respect to marked regions of interest. The lightweight SilentMark algorithms have the advantage of not requiring multiple processors, graphics cards or training datasets and can be run even with just several hundred megabytes of memory. This makes it possible to use the method as a Web application, effectively eliminating setup hurdles and compatibility issues with operating systems. We test this platform on mouse pre-implantation embryos, embryonic stem cell-derived embryoid bodies and mouse embryonic heart, and relate protein localization to tissue geometry. This article is part of a discussion meeting issue 'Contemporary morphogenesis'.

Zebrafish: an emerging real-time model system to study Alzheimer's disease and neurospecific drug discovery

Zebrafish (Danio rerio) is emerging as an increasingly successful model for translational research on human neurological disorders. In this review, we appraise the high degree of neurological and behavioural resemblance of zebrafish with humans. It is highly validated as a powerful vertebrate model for investigating human neurodegenerative diseases. The neuroanatomic and neurochemical pathways of zebrafish brain exhibit a profound resemblance with the human brain. Physiological, emotional and social behavioural pattern similarities between them have also been well established. Interestingly, zebrafish models have been used successfully to simulate the pathology of Alzheimer’s disease (AD) as well as Tauopathy. Their relatively simple nervous system and the optical transparency of the embryos permit real-time neurological imaging. Here, we further elaborate on the use of recent real-time imaging techniques to obtain vital insights into the neurodegeneration that occurs in AD. Zebrafish is adeptly suitable for Ca²⁺ imaging, which provides a better understanding of neuronal activity and axonal dystrophy in a non-invasive manner. Three-dimensional imaging in zebrafish is a rapidly evolving technique, which allows the visualisation of the whole organism for an elaborate in vivo functional and neurophysiological analysis in disease condition. Suitability to high-throughput screening and similarity with humans makes zebrafish an excellent model for screening neurospecific compounds. Thus, the zebrafish model can be pivotal in bridging the gap from the bench to the bedside. This fish is becoming an increasingly successful model to understand AD with further scope for investigation in neurodevelopment and neurodegeneration, which promises exciting research opportunities in the future.

Possibilities and limitations of three-dimensional reconstruction and simulation techniques to identify patterns, rhythms and functions of apoptosis in the early developing neural tube

The now classical idea that programmed cell death (apoptosis) contributes to a plethora of developmental processes still has lost nothing of its impact. It is, therefore, important to establish effective three-dimensional (3D) reconstruction as well as simulation techniques to decipher the exact patterns and functions of such apoptotic events. The present study focuses on the question whether and how apoptosis promotes neurulation-associated processes in the spinal cord of Tupaia belangeri (Tupaiidae, Scandentia, Mammalia). Our 3D reconstructions demonstrate that at least two craniocaudal waves of apoptosis consecutively pass through the dorsal spinal cord. The first wave appears to be involved in neural fold fusion and/or in selection processes among premigratory neural crest cells. The second one seems to assist in establishing the dorsal signaling center known as the roof plate. In the hindbrain, in contrast, apoptosis among premigratory neural crest cells progresses craniocaudally but discontinuously, in a segment-specific manner. Unlike apoptosis in the spinal cord, these segment-specific apoptotic events, however, precede later ones that seemingly support neural fold fusion and/or postfusion remodeling. Arguing with Whitehead that biological patterns and rhythms differ in that biological rhythms depend "upon the differences involved in each exhibition of the pattern" (Whitehead in An enquiry concerning the principles of natural knowledge. Cambridge University Press, London, 1919, p. 198) we show that 3D reconstruction and simulation techniques can contribute to distinguish between (static) patterns and (dynamic) rhythms of apoptosis. By deciphering novel patterns and rhythms of developmental apoptosis, our reconstructions help to reconcile seemingly inconsistent earlier findings in chick and mouse embryos, and to create rules for computer simulations.

Deciphering tissue morphodynamics using bioimage informatics

In recent years developmental biology has greatly benefited from the latest advances in fluorescence microscopy techniques. Consequently, quantitative and automated analysis of this data is becoming a vital first step in the quest for novel insights into the various aspects of development. Here we present an introductory overview of the various image analysis methods proposed for developmental biology images, with particular attention to openly available software packages. These tools, as well as others to come, are rapidly paving the way towards standardized and reproducible bioimaging studies at the whole-tissue level. Reflecting on these achievements, we discuss the remaining challenges and the future endeavours lying ahead in the post-image analysis era.This article is part of the themed issue 'Systems morphodynamics: understanding the development of tissue hardware'.

Microfluidics for High-Throughput Quantitative Studies of Early Development

Developmental biology has traditionally relied on qualitative analyses; recently, however, as in other fields of biology, researchers have become increasingly interested in acquiring quantitative knowledge about embryogenesis. Advances in fluorescence microscopy are enabling high-content imaging in live specimens. At the same time, microfluidics and automation technologies are increasing experimental throughput for studies of multicellular models of development. Furthermore, computer vision methods for processing and analyzing bioimage data are now leading the way toward quantitative biology. Here, we review advances in the areas of fluorescence microscopy, microfluidics, and data analysis that are instrumental to performing high-content, high-throughput studies in biology and specifically in development. We discuss a case study of how these techniques have allowed quantitative analysis and modeling of pattern formation in the Drosophila embryo.

A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage

The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology.

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.

Shaped 3D singular spectrum analysis for quantifying gene expression, with application to the early zebrafish embryo

Recent progress in microscopy technologies, biological markers, and automated processing methods is making possible the development of gene expression atlases at cellular-level resolution over whole embryos. Raw data on gene expression is usually very noisy. This noise comes from both experimental (technical/methodological) and true biological sources (from stochastic biochemical processes). In addition, the cells or nuclei being imaged are irregularly arranged in 3D space. This makes the processing, extraction, and study of expression signals and intrinsic biological noise a serious challenge for 3D data, requiring new computational approaches. Here, we present a new approach for studying gene expression in nuclei located in a thick layer around a spherical surface. The method includes depth equalization on the sphere, flattening, interpolation to a regular grid, pattern extraction by Shaped 3D singular spectrum analysis (SSA), and interpolation back to original nuclear positions. The approach is demonstrated on several examples of gene expression in the zebrafish egg (a model system in vertebrate development). The method is tested on several different data geometries (e.g., nuclear positions) and different forms of gene expression patterns. Fully 3D datasets for developmental gene expression are becoming increasingly available; we discuss the prospects of applying 3D-SSA to data processing and analysis in this growing field.

Segmentation and tracking of adherens junctions in 3D for the analysis of epithelial tissue morphogenesis

Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (http://github.com/morganrcu/TTT)

Epithelia are the most common tissue type in multicellular organisms. Understanding processes that make them acquire their final shape has implications to pathologies such as cancer progression and birth defects such as spina bifida. During development, epithelial tissues are remodeled by mechanical forces applied at the Adherens Junctions (AJs). The AJs form a belt-like structure below the apical surface that functions to both mechanically link epithelial cells and enable cells to remodel their shape and contacts with their neighbors. In order to study epithelial morphogenesis in a quantitative and systematic way, it is necessary to measure the changes in the shape of the AJs over time. To this end we have built a complete computational pipeline to process image volumes generated by laser scanning confocal microscopy of epithelial tissues where the AJs have been marked with AJ proteins tagged with GFP. The system transforms input voxel intensity values into a symbolic description of the cells in the tissue, their connectivity and their temporal evolution, including the discovery of mitosis and apoptosis. As a proof of concept, we employed the data generated by our system to study aspects of morphogenesis of the Drosophila notum.

A digital framework to build, visualize and analyze a gene expression atlas with cellular resolution in zebrafish early embryogenesis

A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.

We propose a workflow to map the expression domains of multiple genes onto a series of 3D templates, or “atlas”, during early embryogenesis. It was applied to the zebrafish at different stages between 4 and 6.3 hpf, generating 6 templates. Our system overcomes the lack of significant morphological landmarks in early development by relying on the expression of a reference gene (goosecoid, gsc) and nuclear staining to guide the registration of the analyzed genes. The proposed method also successfully maps gene domains from partially imaged embryos, thus allowing greater microscope magnification and cellular resolution. By using the workflow to construct a spatiotemporal database of zebrafish, we opened the way to a systematic analysis of vertebrate embryogenesis. The atlas database, together with the mapping software (Match-IT), a custom-made visualization platform (Atlas-IT), and step-by-step user guides are available from the Supplementary Material. We expect that this will encourage other laboratories to generate, map, visualize and analyze new gene expression datasets.

Comparing mRNA levels using in situ hybridization of a target gene and co-stain

In situ hybridization is an important technique for measuring the spatial expression patterns of mRNA in cells, tissues, and whole animals. However, mRNA levels cannot be compared across experiments using typical protocols. Here we present a semi-quantitative method to compare mRNA levels of a gene across multiple samples. This method yields an estimate of the error in the measurement to allow statistical comparison. Our method uses a typical in situ hybridization protocol to stain for a target gene and an internal standard, which we refer to as a co-stain. As a proof of concept, we apply this method to multiple lines of transgenic Drosophila embryos, harboring constructs that express reporter genes to different levels. We generated this test set by mutating enhancer sequences to contain different numbers of binding sites for Zelda, a transcriptional activator. We demonstrate that using a co-stain with in situ hybridization is an effective method to compare mRNA levels across samples. This method requires only minor modifications to existing in situ hybridization protocols and uses straightforward analysis techniques. This strategy can be broadly applied to detect quantitative, spatially resolved changes in mRNA levels.

Evaluation of the effectiveness of simple nuclei-segmentation methods on Caenorhabditis elegans embryogenesis images

BACKGROUND

For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei.

RESULTS

Here, we selected six simple methods from various watershed based and local maxima detection based methods that are frequently used for nuclei segmentation, and evaluated their segmentation accuracy for each developmental stage of the Caenorhabditis elegans. We included a 4D noise filter, in addition to 2D and 3D noise filters, as a pre-processing step to evaluate the potential of simple methods as widely as possible. By applying the methods to image data between the 50- to 500-cell developmental stages at 50-cell intervals, the error rate for nuclei detection could be reduced to ≤ 2.1% at every stage until the 350-cell stage. The fractions of total errors throughout the stages could be reduced to ≤ 2.4%. The error rates improved at most of the stages and the total errors improved when a 4D noise filter was used. The methods with the least errors were two watershed-based methods with 4D noise filters. For all the other methods, the error rate and the fraction of errors could be reduced to ≤ 4.2% and ≤ 4.1%, respectively. The minimum error rate for each stage between the 400- to 500-cell stages ranged from 6.0% to 8.4%. However, similarities between the computational and manual segmentations measured by volume overlap and Hausdorff distance were not good. The methods were also applied to Drosophila and zebrafish embryos and found to be effective.

CONCLUSIONS

The simple segmentation methods were found to be useful for detecting nuclei until the 350-cell stage, but not very useful after the 400-cell stage. The incorporation of a 4D noise filter to the simple methods could improve their performances. Error types and the temporal biases of errors were dependent on the methods used. Combining multiple simple methods could also give good segmentations.

Automated processing of zebrafish imaging data: a survey

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

Quantitative semi-automated analysis of morphogenesis with single-cell resolution in complex embryos

A quantitative understanding of tissue morphogenesis requires description of the movements of individual cells in space and over time. In transparent embryos, such as C. elegans, fluorescently labeled nuclei can be imaged in three-dimensional time-lapse (4D) movies and automatically tracked through early cleavage divisions up to ~350 nuclei. A similar analysis of later stages of C. elegans development has been challenging owing to the increased error rates of automated tracking of large numbers of densely packed nuclei. We present Nucleitracker4D, a freely available software solution for tracking nuclei in complex embryos that integrates automated tracking of nuclei in local searches with manual curation. Using these methods, we have been able to track >99% of all nuclei generated in the C. elegans embryo. Our analysis reveals that ventral enclosure of the epidermis is accompanied by complex coordinated migration of the neuronal substrate. We can efficiently track large numbers of migrating nuclei in 4D movies of zebrafish cardiac morphogenesis, suggesting that this approach is generally useful in situations in which the number, packing or dynamics of nuclei present challenges for automated tracking.

Computational multiscale modeling of embryo development

Recent advances in live imaging and genetics of mammalian development which integrate observations of biochemical activity, cell-cell signaling and mechanical interactions between cells pave the way for predictive mathematical multi-scale modeling. In early mammalian embryo development, two of the most critical events which lead to tissue patterning involve changes in gene expression as well as mechanical interactions between cells. We discuss the relevance of mathematical modeling of multi-cellular systems and in particular in simulating these patterns and describe some of the technical challenges one encounters. Many of these issues are not unique for the embryonic system but are shared by other multi-cellular modeling areas.

3D+t morphological processing: applications to embryogenesis image analysis

We propose to directly process 3D + t image sequences with mathematical morphology operators using a new classification of the 3D+t structuring elements. Several methods (filtering, tracking, segmentation) dedicated to the analysis of 3D + t datasets of zebrafish embryogenesis are introduced and validated through a synthetic dataset. Then, we illustrate the application of these methods to the analysis of datasets of zebrafish early development acquired with various microscopy techniques. This processing paradigm produces spatio-temporal coherent results as it benefits from the intrinsic redundancy of the temporal dimension and minimizes the needs for human intervention in semi-automatic algorithms.

Methodology for reconstructing early zebrafish development from in vivo multiphoton microscopy

Investigating cell dynamics during early zebrafish embryogenesis requires specific image acquisition and analysis strategies. Multiharmonic microscopy, i.e., second- and third-harmonic generations, allows imaging cell divisions and cell membranes in unstained zebrafish embryos from 1- to 1000-cell stage. This paper presents the design and implementation of a dedicated image processing pipeline (tracking and segmentation) for the reconstruction of cell dynamics during these developmental stages. This methodology allows the reconstruction of the cell lineage tree including division timings, spatial coordinates, and cell shape until the 1000-cell stage with minute temporal accuracy and micrometer spatial resolution. Data analysis of the digital embryos provides an extensive quantitative description of early zebrafish embryogenesis.