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.

Imaging the onset of oscillatory signaling dynamics during mouse embryo gastrulation.

A fundamental requirement for embryonic development is the coordination of signaling activities in space and time. A notable example in vertebrate embryos is found during somitogenesis, where gene expression oscillations linked to the segmentation clock are synchronized across cells in the presomitic mesoderm (PSM) and result in tissue-level wave patterns. To examine their onset during mouse embryo development, we studied the dynamics of the segmentation clock gene Lfng during gastrulation. To this end, we established an imaging setup using selective plane illumination microscopy (SPIM) that enables culture and simultaneous imaging of up to four embryos ('SPIM- for-4'). Using SPIM-for-4, combined with genetically encoded signaling reporters, we detected the onset of Lfng oscillations within newly formed mesoderm at presomite stages. Functionally, we found that initial synchrony and the first ∼6-8 oscillation cycles occurred even when Notch signaling was impaired, revealing similarities to previous findings made in zebrafish embryos. Finally, we show that a spatial period gradient is present at the onset of oscillatory activity, providing a potential mechanism accounting for our observation that wave patterns build up gradually over the first oscillation cycles.

Hinge point emergence in mammalian spinal neurulation.

Neurulation is the process in early vertebrate embryonic development during which the neural plate folds to form the neural tube. Spinal neural tube folding in the posterior neuropore changes over time, first showing a median hinge point, then both the median hinge point and dorsolateral hinge points, followed by dorsolateral hinge points only. The biomechanical mechanism of hinge point formation in the mammalian neural tube is poorly understood. Here we employ a mechanical finite element model to study neural tube formation. The computational model mimics the mammalian neural tube using microscopy data from mouse and human embryos. While intrinsic curvature at the neural plate midline has been hypothesized to drive neural tube folding, intrinsic curvature was not sufficient for tube closure in our simulations. We achieved neural tube closure with an alternative model combining mesoderm expansion, nonneural ectoderm expansion, and neural plate adhesion to the notochord. Dorsolateral hinge points emerged in simulations with low mesoderm expansion and zippering. We propose that zippering provides the biomechanical force for dorsolateral hinge point formation in settings where the neural plate lateral sides extend above the mesoderm. Together, these results provide a perspective on the biomechanical and molecular mechanism of mammalian spinal neurulation.

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.

Characterization of a common progenitor pool of the epicardium and myocardium.

The mammalian heart is derived from multiple cell lineages; however, our understanding of when and how the diverse cardiac cell types arise is limited. We mapped the origin of the embryonic mouse heart at single-cell resolution using a combination of transcriptomic, imaging, and genetic lineage labeling approaches. This mapping provided a transcriptional and anatomic definition of cardiac progenitor types. Furthermore, it revealed a cardiac progenitor pool that is anatomically and transcriptionally distinct from currently known cardiac progenitors. Besides contributing to cardiomyocytes, these cells also represent the earliest progenitor of the epicardium, a source of trophic factors and cells during cardiac development and injury. This study provides detailed insights into the formation of early cardiac cell types, with particular relevance to the development of cell-based cardiac regenerative therapies.

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.

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.

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.

Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.

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

Light-sheet microscopy is a powerful method for imaging the development and function of complex biological systems at high spatiotemporal resolution and over long time scales. Such experiments typically generate terabytes of multidimensional image data, and thus they demand efficient computational solutions for data management, processing and analysis. We present protocols and software to tackle these steps, focusing on the imaging-based study of animal development. Our protocols facilitate (i) high-speed lossless data compression and content-based multiview image fusion optimized for multicore CPU architectures, reducing image data size 30-500-fold; (ii) automated large-scale cell tracking and segmentation; and (iii) visualization, editing and annotation of multiterabyte image data and cell-lineage reconstructions with tens of millions of data points. These software modules are open source. They provide high data throughput using a single computer workstation and are readily applicable to a wide spectrum of biological model systems.

Whole-central nervous system functional imaging in larval Drosophila.

Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord.

Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data.

The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (i) generality by reconstructing cell lineages in four-dimensional, terabyte-sized image data sets of fruit fly, zebrafish and mouse embryos acquired with three types of fluorescence microscopes, (ii) scalability by analyzing advanced stages of development with up to 20,000 cells per time point at 26,000 cells min(-1) on a single computer workstation and (iii) ease of use by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities. Using our system, we performed the first cell lineage reconstruction of early Drosophila melanogaster nervous system development, revealing neuroblast dynamics throughout an entire embryo.

Generation and live imaging of an endogenous Cdx2 reporter mouse line.

To understand cell fate specification and maintenance during development, it is essential to visualize both lineage markers and cell behaviors in real time using endogenous markers to report cell fate. We have generated a reporter line in which eGFP is fused to the endogenous locus of Cdx2, a transcription factor essential for trophectoderm specification, allowing us to visualize cell fate decisions in the preimplantation mouse embryo. We used two-photon laser scanning microscopy to visualize expression of the endogenous Cdx2 fusion protein and show that Cdx2 undergoes phases of upregulation. Additionally, we show that as late as the 32-cell stage, outer trophectoderm cells may change their fates by migrating inward and losing Cdx2 expression. Furthermore, the tools and techniques we report allow for dual-colored imaging, which will greatly facilitate the study of not only preimplantation development, but later stages of development and tissues where Cdx2 plays an important role.

The function of lamins in the context of tissue building and maintenance.

Lamins are the major structural components of the nuclear lamina found in metazoan organisms. Extensive studies using tissue culture cells have shown that lamins are involved in a wide range of basic cell functions. This has led to the prevailing idea that a given animal cell needs at least one lamin protein for its basic proliferation and survival. However, recent studies have shown that lamins are dispensable for the proliferation and survival of mouse embryonic stem cells (ESC). In contrast to a lack of essential functions in ESCs, certain differentiated cells lacking B-type lamins exhibit increased cell cycle exit rates and enhanced senescence. In this Extra View, we discuss how studies using animal models and cell cultures have begun to reveal cell-type specific functions of lamins in tissue building and homeostasis.

Mouse B-type lamins are required for proper organogenesis but not by embryonic stem cells.

B-type lamins, the major components of the nuclear lamina, are believed to be essential for cell proliferation and survival. We found that mouse embryonic stem cells (ESCs) do not need any lamins for self-renewal and pluripotency. Although genome-wide lamin-B binding profiles correlate with reduced gene expression, such binding is not directly required for gene silencing in ESCs or trophectoderm cells. However, B-type lamins are required for proper organogenesis. Defects in spindle orientation in neural progenitor cells and migration of neurons probably cause brain disorganizations found in lamin-B null mice. Thus, our studies not only disprove several prevailing views of lamin-Bs but also establish a foundation for redefining the function of the nuclear lamina in the context of tissue building and homeostasis.

Lineage mapping the pre-implantation mouse embryo by two-photon microscopy, new insights into the segregation of cell fates.

The first lineage segregation in the pre-implantation mouse embryo gives rise to cells of the inner cell mass and the trophectoderm. Segregation into these two lineages during the 8-cell to 32-cell stages is accompanied by a significant amount of cell displacement, and as such it has been difficult to accurately track cellular behavior using conventional imaging techniques. Consequently, how cellular behaviors correlate with cell fate choices is still not fully understood. To achieve the high spatial and temporal resolution necessary for tracking individual cell lineages, we utilized two-photon light-scanning microscopy (TPLSM) to visualize and follow every cell in the embryo using fluorescent markers. We found that cells undergoing asymmetric cell fate divisions originate from a unique population of cells that have been previously classified as either outer or inner cells. This imaging technique coupled with a tracking algorithm we developed allows us to show that these cells, which we refer to as intermediate cells, share features of inner cells but exhibit different dynamic behaviors and a tendency to expose their cell surface in the mouse embryo between the fourth and fifth cleavages. We provide an accurate description of the correlation between cell division order and cell fate, and demonstrate that cell cleavage angle is a more accurate indicator of cellular polarity than cell fate. Our studies demonstrate the utility of two-photon imaging in answering questions in the pre-implantation field that have previously been difficult or impossible to address. Our studies provide a framework for the future use of specific markers to track cell fate molecularly and with high accuracy.