Publications

Mammalian embryo cloning by nuclear transfer has a low success rate. This is hypothesized to correlate with a high variability of early developmental steps that segregate outer cells, which are fated to extra-embryonic tissues, from inner cells, which give rise to the embryo proper. Exploring the cell lineage of wild-type embryos and clones, imaged in toto until hatching, highlights the respective contributions of cell proliferation, death and asymmetric divisions to phenotypic variability. Preferential cell death of inner cells in clones, probably pertaining to the epigenetic plasticity of the transferred nucleus, is identified as a major difference with effects on the proportion of inner cell. In wild type and clones, similar patterns of outer cell asymmetric divisions are shown to be essential to the robust proportion of inner cells observed in wild type. Asymmetric inner cell division, which is not described in mice, is identified as a regulator of the proportion of inner cells and likely gives rise to resilient clones.

Reconstructing the lineage of cells is central to understanding how the wide diversity of cell types develops. Here, we provide the neurosensory lineage reconstruction of a complex sensory organ, the inner ear, by imaging zebrafish embryos in vivo over an extended timespan, combining cell tracing and cell fate marker expression over time. We deliver the first dynamic map of early neuronal and sensory progenitor pools in the whole otic vesicle. It highlights the remodeling of the neuronal progenitor domain upon neuroblast delamination, and reveals that the order and place of neuroblasts’ delamination from the otic epithelium prefigure their position within the SAG. Sensory and non-sensory domains harbor different proliferative activity contributing distinctly to the overall growth of the structure. Therefore, the otic vesicle case exemplifies a generic morphogenetic process where spatial and temporal cues regulate cell fate and functional organization of the rudiment of the definitive organ.

Fluorescent polymer nanoparticles for long‐term labeling and tracking of living cells with any desired color code are developed. They are built from biodegradable poly(lactic‐co‐glycolic acid) polymer loaded with cyanine dyes (DiO, DiI, and DiD) with the help of bulky fluorinated counterions, which minimize aggregation‐caused quenching. At the single particle level, these particles are ≈20‐fold brighter than quantum dots of similar color. Due to their identical 40 nm size and surface properties, these nanoparticles are endocytosed equally well by living cells. Mixing nanoparticles of three colors in different proportions generates a homogeneous RGB (red, green, and blue) barcode in cells, which is transmitted through many cell generations. Cell barcoding is validated on 7 cell lines (HeLa, KB, embryonic kidney (293T), Chinese hamster ovary, rat basophilic leucemia, U97, and D2A1), 13 color codes, and it enables simultaneous tracking of co‐cultured barcoded cell populations for >2 weeks. It is also applied to studying competition among drug‐treated cell populations. This technology enabled six‐color imaging in vivo for (1) tracking xenografted cancer cells and (2) monitoring morphogenesis after microinjection in zebrafish embryos. In addition to a robust method of multicolor cell labeling and tracking, this work suggests that multiple functions can be co‐localized inside cells by combining structurally close nanoparticles carrying different functions.

The study of multicellular development is grounded in two complementary domains: cell biomechanics, which examines how physical forces shape the embryo, and genetic regulation and molecular signalling, which concern how cells determine their states and behaviours. Integrating both sides into a unified framework is crucial to fully understand the self-organized dynamics of morphogenesis. Here we introduce MecaGen, an integrative modelling platform enabling the hypothesis-driven simulation of these dual processes via the coupling between mechanical and chemical variables. Our approach relies upon a minimal ‘cell behaviour ontology’ comprising mesenchymal and epithelial cells and their associated behaviours. MecaGen enables the specification and control of complex collective movements in 3D space through a biologically relevant gene regulatory network and parameter space exploration. Three case studies investigating pattern formation, epithelial differentiation and tissue tectonics in zebrafish early embryogenesis, the latter with quantitative comparison to live imaging data, demonstrate the validity and usefulness of our framework.

The paper presents numerical algorithms, postprocessing and validation steps for an automated cell tracking and cell lineage tree reconstruction from large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebrafish (Danio rerio) embryo development. The cell trajectories are extracted as centered paths inside segmented spatio-temporal tree structures representing cell movements and divisions. Such paths are found by using a suitably designed and computed constrained distance functions and by a backtracking in steepest descent direction of a potential field based on these distance functions combination. Since the calculations are performed on big data, parallelization is required to speed up the processing. By careful choice and tuning of algorithm parameters we can adapt the calculations to the microscope images of vertebrae species. Then we can compare the results with ground truth data obtained by manual checking of cell links by biologists and measure the accuracy of our algorithm. Using automatic validation process and visualisation tool that can display ground truth data and our result simultaneously, along with the original 3D data, we can easily verify the correctness of the tracking.

The recent availability of complete cell lineages from live imaging data opens the way to novel methodologies for the automated analysis of cell dynamics in animal embryogenesis. We propose a method for the calculation of measure-based dissimilarities between cells. These dissimilarity measures allow the use of clustering algorithms for the inference of time-persistent patterns. The method is applied to the digital cell lineages reconstructed from live zebrafish embryos imaged from 6 to 13 hours post fertilization. We show that the position and velocity of cells are sufficient to identify relevant morphological features including bilateral symmetry and coherent cell domains. The method is flexible enough to readily integrate larger sets of measures opening the way to the automated identification of morphogenetic fields.

The paper presents numerical algorithms, postprocessing and validation steps for an automated cell tracking and cell lineage tree reconstruction from large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebrafish (Danio rerio) em- bryo development. The cell trajectories are extracted as centered paths inside segmented spatio-temporal tree structures representing cell movements and divisions. Such paths are found by using a suitably designed and computed constrained distance functions and by a backtracking in the steepest descent direction of a potential field based on a combination of these distance functions combination. Since the calculations are performed on big data, parallelization is required to speed up the processing. By careful choice and tuning of al- gorithm parameters we can adapt the calculations to the microscope images of vertebrae species. Then we can compare the results with ground truth data obtained by manual check- ing of cell links by biologists and measure the accuracy of our algorithm. Using an automatic validation process and visualisation tool that can display ground truth data and our result simultaneously, along with the original 3D data, we can easily verify the correctness of the tracking.

We conducted a quantitative comparison of developing sea urchin embryos based on the analysis of five digital specimens resulting from the automated processing of in toto 3D+time image data. These measurements served the reconstruction of a prototypical cell lineage tree able to predict the spatiotemporal cellular organization of a normal sea urchin blastula. The reconstruction was achieved by designing and tuning a multi-level probabilistic model that reproduced embryo-level dynamics from a small number of statistical parameters characterizing cell proliferation, cell surface area and cell volume evolution along the cell lineage. Our resulting artificial prototype was embedded in 3D space by biomechanical agent-based modeling and simulation, which allowed a systematic exploration and optimization of free parameters to fit the experimental data and test biological hypotheses. The spherical monolayered blastula and the spatial arrangement of its different cell types appeared tightly constrained by cell stiffness, cell-adhesion parameters and blastocoel turgor pressure.

The study of multicellular development is grounded in two complementary domains: cell biomechanics, which examines how physical forces shape the embryo, and genetic regulation and molecular signalling, which concern how cells determine their states and behaviours. Integrating both sides into a unified framework is crucial to fully understand the self-organized dynamics of morphogenesis. Here we introduce MecaGen, an integrative modelling platform enabling the hypothesis-driven simulation of these dual processes via the coupling between mechanical and chemical variables. Our approach relies upon a minimal ‘cell behaviour ontology' comprising mesenchymal and epithelial cells and their associated behaviours. MecaGen enables the specification and control of complex collective movements in 3D space through a biologically relevant gene regulatory network and parameter space exploration. Three case studies investigating pattern formation, epithelial differentiation and tissue tectonics in zebrafish early embryogenesis, the latter with quantitative comparison to live imaging data, demonstrate the validity and usefulness of our framework.

This paper presents a new multiscale method to denoise three-dimensional images of cell nuclei. The specificity of this method is its awareness of the noise distribution and object shapes. It combines a multiscale representation called Isotropic Undecimated Wavelet Transform (IUWT) with a nonlinear transform, a statistical test and a variational method, to retrieve spherical shapes in the image. Beyond extending an existing 2D approach to a 3D problem, our algorithm takes the sampling grid dimensions into account. We compare our method to the two algorithms from which it is derived on a representative image analysis task, and show that it is superior to both of them. It brings a slight improvement in the signal-to-noise ratio and a significant improvement in cell detection.

The precise positioning of organ progenitor cells constitutes an essential, yet poorly understood step during organogenesis. Using primordial germ cells that participate in gonad formation, we present the developmental mechanisms maintaining a motile progenitor cell population at the site where the organ develops. Employing high-resolution live-cell microscopy, we find that repulsive cues coupled with physical barriers confine the cells to the correct bilateral positions. This analysis revealed that cell polarity changes on interaction with the physical barrier and that the establishment of compact clusters involves increased cell–cell interaction time. Using particle-based simulations, we demonstrate the role of reflecting barriers, from which cells turn away on contact, and the importance of proper cell–cell adhesion level for maintaining the tight cell clusters and their correct positioning at the target region. The combination of these developmental and cellular mechanisms prevents organ fusion, controls organ positioning and is thus critical for its proper function.

Digital cell lineages reconstructed from 3D+time imaging data provide unique information to unveil mechanical cues and their role in morphogenetic processes. Our methodology based on a kinematic analysis of cell lineage data reveals deformation patterns and quantitative morphogenetic landmarks for a new type of developmental table. The characteristic spatial and temporal length scales of mechanical deformation patterns derived from a continuous approximation of cell displacements indicate a compressible fluid-like behavior of zebrafish gastrulating tissues. The instantaneous deformation rate at the mesoscopic level of the cell's neighborhood is spatially and temporally heterogeneous. The robustness of mechanical patterns results from their cumulative history along cell trajectories. Unsupervised classification of mechanical descriptor profiles was used to assess the homogeneity of biomechanical cues in cell populations. Further clustering of cell trajectories according to their cumulative mesoscopic biomechanical history during gastrulation revealed ordered and coherent spatiotemporal patterns comparable to that of the embryonic fate map.

Calcium‐activated photoproteins, such as aequorin, have been used as luminescent Ca2+ indicators since 1967. After the cloning of aequorin in 1985, microinjection was substituted by its heterologous expression, which opened the way for a widespread use. Molecular fusion of green fluorescent protein (GFP) to aequorin recapitulated the nonradiative energy transfer process that occurs in the jellyfish Aequorea victoria, from which these two proteins were obtained, resulting in an increase of light emission and a shift to longer wavelength. The abundance and location of the chimera are seen by fluorescence, whereas its luminescence reports Ca2+ levels. GFP‐aequorin is broadly used in an increasing number of studies, from organelles and cells to intact organisms. By fusing other fluorescent proteins to aequorin, the available luminescence color palette has been expanded for multiplexing assays and for in vivo measurements. In this report, we will attempt to review the various photoproteins available, their reported fusions with fluorescent proteins and their biological applications to image Ca2+ dynamics in organelles, cells, tissue explants and in live organisms.

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.

Regionalization is a critical, highly conserved step in the development of the vertebrate brain. Discrepancies exist in how regionalization of the anterior vertebrate forebrain is conceived since the “preoptic area” is proposed to be a part of the telencephalon in tetrapods but not in teleost fish. To gain insight into this complex morphogenesis, formation of the anterior forebrain was analyzed in 3D over time in zebrafish embryos, combining visualization of proliferation and differentiation markers, with that of developmental genes. We found that the region containing the preoptic area behaves as a coherent morphogenetic entity, organized around the optic recess and located between telencephalon and hypothalamus. This optic recess region (ORR) makes clear borders with its neighbor areas and expresses a specific set of genes (dlx2a, sim1a and otpb). We thus propose that the anterior forebrain (secondary prosencephalon) in teleosts contains three morphogenetic entities (telencephalon, ORR and hypothalamus), instead of two (telencephalon and hypothalamus). The ORR in teleosts could correspond to “telencephalic stalk area” and “alar hypothalamus” in tetrapods, resolving current inconsistencies in the comparison of basal forebrain among vertebrates.

The paper presents new numerical algorithm for an automated cell tracking from large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebrafish (Danio rerio) embryo development. The cell trajectories are extracted as centered paths inside segmented spatio-temporal tree structures representing cell movements and divisions. Such paths are found by using a suitably designed and computed constrained distance functions and by a backtracking in steepest descent direction of a potential field based on these distance functions combination. The naturally parallelizable discretization of the eikonal equation which is used for computing distance functions is given and results of the tracking method for real 4D image data are presented and discussed.

Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems (MACS). While taking the emergence of properties seriously, the notion of MACS enables at the same time the design (or “meta-design”) of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems studied in the field of Artificial Life, the specificity of MACS essentially lies in the close relation between their emergent properties and functional properties. Second, we argue that to be a MACS a system does not need to display more than weak emergent properties. Third, since the notion of weak emergence is based on the possibility of simulation, whether computational or mechanistic via machines, we see MACS as good candidates to help design artificial self-architected systems (such as robotic swarms) but also harness and redesign living ones (such as synthetic bacterial films).

We report here a robust and efficient protocol for the expression of fluorescent proteins after mRNA injection into unfertilized oocytes of the cephalochordate amphioxus, Branchiostoma lanceolatum. We use constructs for membrane and nuclear targeted mCherry and eGFP that have been modified to accommodate amphioxus codon usage and Kozak consensus sequences. We describe the type of injection needles to be used, the immobilization protocol for the unfertilized oocytes, and the overall injection set-up. This technique generates fluorescently labeled embryos, in which the dynamics of cell behaviors during early development can be analyzed using the latest in vivo imaging strategies. The development of a microinjection technique in this amphioxus species will allow live imaging analyses of cell behaviors in the embryo as well as gene-specific manipulations, including gene overexpression and knockdown. Altogether, this protocol will further consolidate the basal chordate amphioxus as an animal model for addressing questions related to the mechanisms of embryonic development and, more importantly, to their evolution.

Exogenous probes with far-red or near-infrared (NIR) two-photon absorption and fluorescence emission are highly desirable for deep tissue imaging while limiting autofluorescence. However, molecular probes exhibiting such properties are often hydrophobic. As an attractive alternative, we synthesized water-soluble polymer probes carrying multiple far-red fluorophores and demonstrated here their potential for live cell and zebrafish embryo imaging. First, at concentrations up to 10 μm, these polymer probes were not cytotoxic. They could efficiently label living HeLa cells, T lymphocytes and neurons at an optimal concentration of 0.5 μm. Moreover, they exhibited a high resistance to photobleaching in usual microscopy conditions. In addition, these polymer probes could be successfully used for in toto labeling and in vivo two-photon microscopy imaging of developing zebrafish embryos, with remarkable properties in terms of biocompatibility, internalization, diffusion, stability and wavelength emission range. The near-infrared two-photon absorption peak at 910 nm is particularly interesting since it does not excite the zebrafish endogenous fluorescence and is likely to enable long-term time-lapse imaging with limited photodamage.

The paper presents numerical algorithms leading to an automated cell tracking and reconstruction of the cell lineage tree during the first hours of animal embryogenesis. We present results obtained for large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebrafish (Danio rerio) embryo development. Our approach consists of three basic steps – the image filtering, the cell centers detection and the cell trajectories extraction yielding the lineage tree reconstruction. In all three steps we use nonlinear partial differential equations. For the filtering the geodesic mean curvature flow in level set formulation is used, for the cell center detection the motion of level sets by a constant speed regularized by mean curvature flow is used and the solution of the eikonal equation is essential for the cell trajectories extraction. The core of our new tracking method is an original approach to cell trajectories extraction based on finding a continuous centered paths inside the spatio-temporal tree structures representing cell movement and divisions. Such paths are found by using a suitably designed distance function from cell centers detected in all time steps of the 3D+time image sequence and by a backtracking in the steepest descent direction of a potential field based on this distance function. We also present efficient and naturally parallelizable discretizations of the aforementioned nonlinear PDEs and discuss properties and results of our new tracking method on artificial and real 4D data.

The paper presents numerical algorithms leading to an automated cell tracking and reconstruction of the cell lineage tree during the first hours of animal embryogenesis. We present results obtained for large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebrafish (Danio rerio) embryo development. Our approach consists of three basic steps – the image filtering, the cell centers detection and the cell trajectories extraction yielding the lineage tree reconstruction. In all three steps we use nonlinear partial differential equations. For the filtering the geodesic mean curvature flow in level set formulation is used, for the cell center detection the motion of level sets by a constant speed regularized by mean curvature flow is used and the solution of the eikonal equation is essential for the cell trajectories extraction. The core of our new tracking method is an original approach to cell trajectories extraction based on finding a continuous centered paths inside the spatio-temporal tree structures representing cell movement and divisions. Such paths are found by using a suitably designed distance function from cell centers detected in all time steps of the 3D+time image sequence and by a backtracking in the steepest descent direction of a potential field based on this distance function. We also present efficient and naturally parallelizable discretizations of the aforementioned nonlinear PDEs and discuss properties and results of our new tracking method on artificial and real 4D data.

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.

Members of the Bcl-2 protein family regulate mitochondrial membrane permeability and also localize to the endoplasmic reticulum where they control Ca2+ homeostasis by interacting with inositol 1,4,5-trisphosphate (IP3) receptors (IP3Rs). In zebrafish, Bcl-2–like 10 (Nrz) is required for Ca2+ signaling during epiboly and gastrulation. We characterized the mechanism by which Nrz controls IP3-mediated Ca2+ release during this process. We showed that Nrz was phosphorylated during early epiboly, and that in embryos in which Nrz was knocked down, reconstitution with Nrz bearing mutations designed to prevent its phosphorylation disrupted cyclic Ca2+ transients and the assembly of the actin-myosin ring and led to epiboly arrest. In cultured cells, wild-type Nrz, but not Nrz with phosphomimetic mutations, interacted with the IP3 binding domain of IP3R1, inhibited binding of IP3 to IP3R1, and prevented histamine-induced increases in cytosolic Ca2+. Collectively, these data suggest that Nrz phosphorylation is necessary for the generation of IP3-mediated Ca2+ transients and the formation of circumferential actin-myosin cables required for epiboly. Thus, in addition to their role in apoptosis, by tightly regulating Ca2+ signaling, Bcl-2 family members participate in the cellular events associated with early vertebrate development, including cytoskeletal dynamics and cell movement.

Cell migration requires the generation of branched actin networks that power the protrusion of the plasma membrane in lamellipodia. The actin-related proteins 2 and 3 (Arp2/3) complex is the molecular machine that nucleates these branched actin networks. This machine is activated at the leading edge of migrating cells by Wiskott-Aldrich syndrome protein (WASP)-family verprolin-homologous protein (WAVE, also known as SCAR). The WAVE complex is itself directly activated by the small GTPase Rac, which induces lamellipodia. However, how cells regulate the directionality of migration is poorly understood. Here we identify a new protein, Arpin, that inhibits the Arp2/3 complex in vitro, and show that Rac signalling recruits and activates Arpin at the lamellipodial tip, like WAVE. Consistently, after depletion of the inhibitory Arpin, lamellipodia protrude faster and cells migrate faster. A major role of this inhibitory circuit, however, is to control directional persistence of migration. Indeed, Arpin depletion in both mammalian cells and Dictyostelium discoideum amoeba resulted in straighter trajectories, whereas Arpin microinjection in fish keratocytes, one of the most persistent systems of cell migration, induced these cells to turn. The coexistence of the Rac-Arpin-Arp2/3 inhibitory circuit with the Rac-WAVE-Arp2/3 activatory circuit can account for this conserved role of Arpin in steering cell migration.

Circular codes are mathematical objects studied in combinatorics - theoretical computer science, and theoretical biology. So far, there is no close formulas allowing to determine the growth function (number and list) of circular codes. This combinatorial problem can only be solved by an algorithmic approach. We propose a new algorithm based on a necklace proposition to determine the growth function of trinucleotide circular codes, a trinucleotide being a word of 3 letters on a 4-letter alphabet. This necklace algorithm, unique in its class, can be extended in future to the analysis of codes, e.g. circular codes, containing words greater than 3 letters and also over larger alphabets.

Investigating neural stem cell (NSC) behaviour in vivo, which is a major area of research, requires NSC models to be developed. We carried out a multilevel characterisation of the zebrafish embryo peripheral midbrain layer (PML) and identified a unique vertebrate progenitor population. Located dorsally in the transparent embryo midbrain, these large slow-amplifying progenitors (SAPs) are accessible for long-term in vivo imaging. They form a neuroepithelial layer adjacent to the optic tectum, which has transitory fast-amplifying progenitors (FAPs) at its margin. The presence of these SAPs and FAPs in separate domains provided the opportunity to data mine the ZFIN expression pattern database for SAP markers, which are co-expressed in the retina. Most of them are involved in nucleotide synthesis, or encode nucleolar and ribosomal proteins. A mutant for the cad gene, which is strongly expressed in the PML, reveals severe midbrain defects with massive apoptosis and sustained proliferation. We discuss how fish midbrain and retina progenitors might derive from ancient sister cell types and have specific features that are not shared with other SAPs.

Embryogenesis is a dynamic process with an intrinsic variability whose understanding requires the integration of molecular, genetic, and cellular dynamics. Biological circuits function over time at the level of single cells and require a precise analysis of the topology, temporality, and probability of events. Integrative developmental biology is currently looking for the appropriate strategies to capture the intrinsic properties of biological systems. The “–omic” approaches require disruption of the function of the biological circuit; they provide static information, with low temporal resolution and usually with population averaging that masks fast or variable features at the cellular scale and in a single individual. This data should be correlated with cell behavior as cells are the integrators of biological activity. Cellular dynamics are captured by the in vivo microscopy observation of live organisms. This can be used to reconstruct the 3D + time cell lineage tree to serve as the basis for modeling the organism's multiscale dynamics. We discuss here the progress that has been made in this direction, starting with the reconstruction over time of three-dimensional digital embryos from in toto time-lapse imaging. Digital specimens provide the means for a quantitative description of the development of model organisms that can be stored, shared, and compared. They open the way to in silico experimentation and to a more theoretical approach to biological processes. We show, with some unpublished results, how the proposed methodology can be applied to sea urchin species that have been model organisms in the field of classical embryology and modern developmental biology for over a century.

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.

Motivation: Multi-view microscopy techniques such as Light-Sheet Fluorescence Microscopy (LSFM) are powerful tools for 3D + time studies of live embryos in developmental biology. The sample is imaged from several points of view, acquiring a set of 3D views that are then combined or fused in order to overcome their individual limitations. Views fusion is still an open problem despite recent contributions in the field.

Results: We developed a wavelet-based multi-view fusion method that, due to wavelet decomposition properties, is able to combine the complementary directional information from all available views into a single volume. Our method is demonstrated on LSFM acquisitions from live sea urchin and zebrafish embryos. The fusion results show improved overall contrast and details when compared with any of the acquired volumes. The proposed method does not need knowledge of the system's point spread function (PSF) and performs better than other existing PSF independent fusion methods.

Availability and Implementation: The described method was implemented in Matlab (The Mathworks, Inc., USA) and a graphic user interface was developed in Java.

The software, together with two sample datasets, is available at http://www.die.upm.es/im/software/SPIMFusionGUI.zip

A public release, free of charge for non-commercial use, is planned after the publication of this article.

Digital atlases of animal development provide a quantitative description of morphogenesis, opening the path toward processes modeling. Prototypic atlases offer a data integration framework where to gather information from cohorts of individuals with phenotypic variability. Relevant information for further theoretical reconstruction includes measurements in time and space for cell behaviors and gene expression. The latter as well as data integration in a prototypic model, rely on image processing strategies. Developing the tools to integrate and analyze biological multidimensional data are highly relevant for assessing chemical toxicity or performing drugs preclinical testing. This article surveys some of the most prominent efforts to assemble these prototypes, categorizes them according to salient criteria and discusses the key questions in the field and the future challenges toward the reconstruction of multiscale dynamics in model organisms.

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.

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.

The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the ”in-toto” reconstruction based on different modalities of ”in-vivo” imaging techniques-spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive manual interaction-time and human resources - is always required to enforce coherence. Because of this limitation it is necessary to restrict the experiments or assume an uncontrolled error rate. Is it possible to obtain automated reliable measurements of migration? can we provide a seed for biologists to complete cell lineages efficiently? We propose a filtering technique that considers trajectories as spatio-temporal connected structures that prunes out those that might introduce noise and false positives by using multi-dimensional morphological operators.

We present a theoretical model of animal morphogenesis construed as a self-organized phenomenon emerging from a complex system made of a myriad of individual cell behaviors. It is implemented in an agent-based simulation centered on the mechanic-chemical coupling between cellular and genetic dynamics. The goal is to integrate the collective motion of cells and the dynamics of their gene expression underlying the patterning of morphogenetic fields. Within this larger framework, we examine here cell intercalation, a generic process underlying tissue elongation in vertebrate embryogenesis, in particular the convergence and extension movements shaping the embryonic axes during gastrulation. Cell intercalation is thought to arise from polarized cell movements. In our model, we include monopolar and bipolar protrusive activity of polarized cells to investigate the causal bottom-up link from local cell behavior to global tissue deformation. Conversely, this model also allows reverse inference, e.g., by evolutionary optimization, of the local quantitative features of cell adhesion and polarization from a global 4 D (3 D + time) computational reconstruction of the cell lineage tree, itself based on in toto imaging data of developing zebrafish embryos.

Introducing small DNA molecules (Dbait) impairs the repair of damaged chromosomes and provides a new method for enhancing the efficiency of radiotherapy in radio-resistant tumors. The radiosensitizing activity is dependent upon the efficient delivery of Dbait molecules into the tumor cells. Different strategies have been compared, to improve this key step. We developed a pipeline of assays to select the most efficient nanoparticles and administration protocols before preclinical assays: (i) molecular analyses of complexes formed with Dbait molecules, (ii) cellular tests for Dbait uptake and activity, (iii) live zebrafish embryo confocal microscopy monitoring for in vivo distribution and biological activity of the nanoparticles and (iv) tumor growth and survival measurement on mice with xenografted tumors. Two classes of nanoparticles were compared, polycationic polymers with linear or branched polyethylenimine (PEI) and covalently attached cholesterol (coDbait). The most efficient Dbait transfection was observed with linear PEI complexes, in vitro and in vivo. Doses of coDbait ten-fold higher than PEI/Dbait nanoparticles, and pretreatment with chloroquine, were required to obtain the same antitumoral effect on xenografted melanoma. However, with a 22-fold lower ‘efficacy dose/toxicity dose’ ratio as compared with Dbait/PEI, coDbait was selected for clinical trials.

The digital reconstruction of the embryogenesis of model organisms from 3D+time data is revolutionizing practices in quantitative and integrative Developmental Biology. A manual and fully supervised image analysis of the massive complex data acquired with new microscopy technologies is no longer an option and automated image processing methods are required to fully exploit the potential of imaging data for biological insights. Current developments and challenges in biological image processing include algorithms for microscopy multiview fusion, cell nucleus tracking for quasi-perfect lineage reconstruction, segmentation, and validation methodologies for cell membrane shape identification, single cell gene expression quantification from in situ hybridization data, and multidimensional image registration algorithms for the construction of prototypic models. These tools will be essential to ultimately produce the multilevel in toto reconstruction that combines the cell lineage tree, cells, and tissues structural information and quantitative gene expression data in its spatio-temporal context throughout development.

Nonlinear microscopy can be used to probe the intrinsic optical properties of biological tissues. Using femtosecond pulses, third-harmonic generation (THG) and four-wave mixing (FWM) signals can be efficiently produced and detected simultaneously. Both signals probe a similar parameter, i.e. the real part of the third-order nonlinear susceptibility chi((3)). However THG and FWM images result from different phase matching conditions and provide complementary information. We analyze this complementarity using calculations, z-scan measurements on water and oils, and THG-FWM imaging of cell divisions in live zebrafish embryos. The two signals exhibit different sensitivity to sample size and clustering in the half-wavelength regime. Far from resonance, THG images reveal spatial variations |Deltachi((3))(-3omega;omega,omega,omega)| with remarkable sensitivity while FWM directly reflects the distribution of chi((3))(-2omega(1) + omega(2);omega(1), -omega(2), omega(1)). We show that FWM images provide chi((3)) maps useful for proper interpretation of cellular THG signals, and that combined imaging carries additional structural information. Finally we present simultaneous imaging of intrinsic THG, FWM, second-harmonic (SHG) and two-photon-excited fluorescence (2PEF) signals in live Caenorhabditis elegans worms illustrating the information provided by multimodal nonlinear imaging of unstained tissue.

We present a set of techniques that enable us to segment objects from 3D cell membrane images. Particularly, we propose methods for detection of approximate cell nuclei centers, extraction of the inner cell boundaries, the surface of the organism and the intercellular borders--the so called intercellular skeleton. All methods are based on numerical solution of partial differential equations. The center detection problem is represented by a level set equation for advective motion in normal direction with curvature term. In case of the inner cell boundaries and the global surface, we use the generalized subjective surface model. The intercellular borders are segmented by the advective level set equation where the velocity field is given by the gradient of the signed distance function to the segmented inner cell boundaries. The distance function is computed by solving the time relaxed eikonal equation. We describe the mathematical models, explain their numerical approximation and finally we present various possible practical applications on the images of zebrafish embryogenesis--computation of important quantitative characteristics, evaluation of the cell shape, detection of cell divisions and others.

Owing to its phylogenetic position at the base of the chordates, the cephalochordate amphioxus is an emerging model system carrying immense significance for understanding the evolution of vertebrate development. One important shortcoming of amphioxus as a model organism has been the unavailability of animal husbandry protocols to maintain amphioxus adults away from the field. Here, we present the first report of successful maintenance and spawning of Branchiostoma lanceolatum adults in a facility run on artificial seawater. B. lanceolatum has been chosen for this study because it is the only amphioxus species that can be induced to spawn. We provide a step-by-step guide for the assembly of such a facility and discuss the day-to-day operations required for successful animal husbandry of B. lanceolatum adults. This work also includes a detailed description of the B. lanceolatum spawning behavior in captivity. Our analysis shows that the induced spawning efficiency is not sex biased, but increases as the natural spawning season progresses. We find that a minor fraction of the animals undergo phases of spontaneous spawning in the tanks and that this behavior is not affected by the treatment used to induce spawning. Moreover, the induced spawning efficiency is not discernibly correlated with spontaneous spawning in the facility. Last, we describe a protocol for long-term cryopreservation of B. lanceolatum sperm. Taken together, this work represents an important step toward further establishing amphioxus as a laboratory animal making it more amenable to experimental research, and hence assists the coming of age of this emerging model.

Quantifying cell behaviors in animal early embryogenesis remains a challenging issue requiring in toto imaging and automated image analysis. We designed a framework for imaging and reconstructing unstained whole zebrafish embryos for their first 10 cell division cycles and report measurements along the cell lineage with micrometer spatial resolution and minute temporal accuracy. Point-scanning multiphoton excitation optimized to preferentially probe the innermost regions of the embryo provided intrinsic signals highlighting all mitotic spindles and cell boundaries. Automated image analysis revealed the phenomenology of cell proliferation. Blastomeres continuously drift out of synchrony. After the 32-cell stage, the cell cycle lengthens according to cell radial position, leading to apparent division waves. Progressive amplification of this process is the rule, contrasting with classical descriptions of abrupt changes in the system dynamics.

In this paper, we introduce a set of methods for processing and analyzing long time series of 3D images representing embryo evolution. The images are obtained by in vivo scanning using a confocal microscope where one of the channels represents the cell nuclei and the other one the cell membranes. Our image processing chain consists of three steps: image filtering, object counting (center detection) and segmentation. The corresponding methods are based on numerical solution of nonlinear PDEs, namely the geodesic mean curvature flow model, flux-based level set center detection and generalized subjective surface equation. All three models have a similar character and therefore can be solved using a common approach. We explain in details our semi-implicit time discretization and finite volume space discretization. This part is concluded by a short description of parallelization of the algorithms. In the part devoted to experiments, we provide the experimental order of convergence of the numerical scheme, the validation of the methods and numerous experiments with the data representing an early developmental stage of a zebrafish embryo.

We present a strategy for automatic classification and density estimation of epithelial enveloping layer (EVL) and deep layer (DEL) cells, throughout zebrafish early embryonic stages. Automatic cells classification provides the bases to measure the variability of relevant parameters, such as cells density, in different classes of cells and is finalized to the estimation of effectiveness and selectivity of anticancer drug in vivo. We aim at approaching these measurements through epithelial/deep cells classification, epithelial area and thickness measurement, and density estimation from scattered points. Our procedure is based on Minimal Surfaces, Otsu clustering, Delaunay Triangulation, and Within-R cloud of points density estimation approaches. In this paper, we investigated whether the distance between nuclei and epithelial surface is sufficient to discriminate epithelial cells from deep cells. Comparisons of different density estimators, experimental results, and extensively accuracy measurements are included.

We present nonlinear diffusion equations, numerical schemes to solve them and their application for filtering 3D images obtained from laser scanning microscopy (LSM) of living zebrafish embryos, with a goal to identify the optimal filtering method and its parameters. In the large scale applications dealing with analysis of 3D+time embryogenesis images, an important objective is a correct detection of the number and position of cell nuclei yielding the spatio-temporal cell lineage tree of embryogenesis. The filtering is the first and necessary step of the image analysis chain and must lead to correct results, removing the noise, sharpening the nuclei edges and correcting the acquisition errors related to spuriously connected subregions. In this paper we study such properties for the regularized Perona-Malik model and for the generalized mean curvature flow equations in the level-set formulation. A comparison with other nonlinear diffusion filters, like tensor anisotropic diffusion and Beltrami flow, is also included. All numerical schemes are based on the same discretization principles, i.e. finite volume method in space and semi-implicit scheme in time, for solving nonlinear partial differential equations. These numerical schemes are unconditionally stable, fast and naturally parallelizable. The filtering results are evaluated and compared first using the Mean Hausdorff distance between a gold standard and different isosurfaces of original and filtered data. Then, the number of isosurface connected components in a region of interest (ROI) detected in original and after the filtering is compared with the corresponding correct number of nuclei in the gold standard. Such analysis proves the robustness and reliability of the edge preserving nonlinear diffusion filtering for this type of data and lead to finding the optimal filtering parameters for the studied models and numerical schemes. Further comparisons consist in ability of splitting the very close objects which are artificially connected due to acquisition error intrinsically linked to physics of LSM. In all studied aspects it turned out that the nonlinear diffusion filter which is called geodesic mean curvature flow (GMCF) has the best performance.

We designed a strategy for extracting the shapes of cell membranes and nuclei from time lapse confocal images taken throughout early zebrafish embryogenesis using a partial-differential-equation-based segmentation. This segmentation step is a prerequisite for an accurate quantitative analysis of cell morphodynamics during embryogenesis and it is the basis for an integrated understanding of biological processes. The segmentation of embryonic cells requires live zebrafish embryos fluorescently labeled to highlight sub-cellular structures and designing specific algorithms by adapting classical methods to image features. Our strategy includes the following steps: the signal-to-noise ratio is first improved by an edge-preserving filtering, then the cell shape is reconstructed applying a fully automated algorithm based on a generalized version of the Subjective Surfaces technique. Finally we present a procedure for the algorithm validation either from the accuracy and the robustness perspective.

In this paper, an efficient finite volume method for image segmentation is introduced. The method is based on surface evolution governed by a nonlinear PDE, the generalized subjective surfaces equation. Our numerical method is based on semi-implicit time discretization and finite volume space approximation. We show examples of image segmentation - particularly, we deal with images of early embryogenesis of zebrafish obtained by a confocal microscope. We mention how the segmentation can be useful for analysis of the embryo images and reconstruction of the embryo evolution.