Simulating the mammalian blastocyst--molecular and mechanical interactions pattern the embryo

Cavity oscillation drives pattern formation in early mammalian embryos

During the second cell fate in mouse embryos, the inner cell mass (ICM) segregates into the spatially distinct epiblast (EPI) and primitive endoderm (PrE) layers. The mechanism driving this pattern formation, however, remains unresolved. Here, we report that, concomitant with the segregation process of EPI/PrE precursors starting from mid-blastocyst, the blastocyst cavity begins to oscillate cyclically with rapid contraction yet slow expansion, triggering a phase transition in the ICM to a fluid-like state. This asymmetric oscillation of the blastocyst cavity facilitates EPI/PrE segregation by enhancing cell-cell contact fluctuations within the ICM and initiating convergent cell flows, which induce movement of these two cell types in opposite directions, wherein PrE precursors move toward the ICM-lumen interface, whereas EPI precursors move toward the trophectoderm. Last, we found that both PDGFRα expression and YAP nuclear accumulation in PrE precursors increase in response to blastocyst cavity oscillation. This study reveals the foundational role of physical oscillation in driving embryonic pattern formation during early mammalian embryonic development.

Generative model for the first cell fate bifurcation in mammalian development

The first cell fate bifurcation in mammalian development directs cells toward either the trophectoderm (TE) or inner cell mass (ICM) compartments in preimplantation embryos. This decision is regulated by the subcellular localization of a transcriptional co-activator YAP and takes place over several progressively asynchronous cleavage divisions. As a result of this asynchrony and variable arrangement of blastomeres, reconstructing the dynamics of the TE/ICM cell specification from fixed embryos is extremely challenging. To address this, we developed a live imaging approach and applied it to measure pairwise dynamics of nuclear YAP and its direct target genes, CDX2 and SOX2, key transcription factors of TE and ICM, respectively. Using these datasets, we constructed a generative model of the first cell fate bifurcation, which reveals the time-dependent statistics of the TE and ICM cell allocation. In addition to making testable predictions for the joint dynamics of the full YAP/CDX2/SOX2 motif, the model revealed the stochastic nature of the induction timing of the key cell fate determinants and identified the features of YAP dynamics that are necessary or sufficient for this induction. Notably, temporal heterogeneity was particularly prominent for SOX2 expression among ICM cells. As heterogeneities within the ICM have been linked to the initiation of the second cell fate decision in the embryo, understanding the origins of this variability is of key significance. The presented approach reveals the dynamics of the first cell fate choice and lays the groundwork for dissecting the next cell fate bifurcations in mouse development.

AI-powered simulation-based inference of a genuinely spatial-stochastic gene regulation model of early mouse embryogenesis

Understanding how multicellular organisms reliably orchestrate cell-fate decisions is a central challenge in developmental biology, particularly in early mammalian development, where tissue-level differentiation arises from seemingly cell-autonomous mechanisms. In this study, we present a multi-scale, spatial-stochastic simulation framework for mouse embryogenesis, focusing on inner cell mass (ICM) differentiation into epiblast (EPI) and primitive endoderm (PRE) at the blastocyst stage. Our framework models key regulatory and tissue-scale interactions in a biophysically realistic fashion, capturing the inherent stochasticity of intracellular gene expression and intercellular signaling, while efficiently simulating these processes by advancing event-driven simulation techniques. Leveraging the power of Simulation-Based Inference (SBI) through the AI-driven Sequential Neural Posterior Estimation (SNPE) algorithm, we conduct a large-scale Bayesian inferential analysis to identify parameter sets that faithfully reproduce experimentally observed features of ICM specification. Our results reveal mechanistic insights into how the combined action of autocrine and paracrine FGF4 signaling coordinates stochastic gene expression at the cellular scale to achieve robust and reproducible ICM patterning at the tissue scale. We further demonstrate that the ICM exhibits a specific time window of sensitivity to exogenous FGF4, enabling lineage proportions to be adjusted based on timing and dosage, thereby extending current experimental findings and providing quantitative predictions for both mutant and wild-type ICM systems. Notably, FGF4 signaling not only ensures correct EPI-PRE lineage proportions but also enhances ICM resilience to perturbations, reducing fate-proportioning errors by 10-20% compared to a purely cell-autonomous system. Additionally, we uncover a surprising role for variability in intracellular initial conditions, showing that high gene-expression heterogeneity can improve both the accuracy and precision of cell-fate proportioning, which remains robust when fewer than 25% of the ICM population experiences perturbed initial conditions. Our work offers a comprehensive, spatial-stochastic description of the biochemical processes driving ICM differentiation and identifies the necessary conditions for its robust unfolding. It also provides a framework for future exploration of similar spatial-stochastic systems in developmental biology.

Effective mechanical potential of cell-cell interaction in tissues harboring cavity and in cell sheet toward morphogenesis

Measuring mechanical forces of cell-cell interactions is important for studying morphogenesis in multicellular organisms. We previously reported an image-based statistical method for inferring effective mechanical potentials of pairwise cell-cell interactions by fitting cell tracking data with a theoretical model. However, whether this method is applicable to tissues with non-cellular components such as cavities remains elusive. Here we evaluated the applicability of the method to cavity-harboring tissues. Using synthetic data generated by simulations, we found that the effect of expanding cavities was added to the pregiven potentials used in the simulations, resulting in the inferred effective potentials having an additional repulsive component derived from the expanding cavities. Interestingly, simulations by using the effective potentials reproduced the cavity-harboring structures. Then, we applied our method to the mouse blastocysts, and found that the inferred effective potentials can reproduce the cavity-harboring structures. Pairwise potentials with additional repulsive components were also detected in two-dimensional cell sheets, by which curved sheets including tubes and cups were simulated. We conclude that our inference method is applicable to tissues harboring cavities and cell sheets, and the resultant effective potentials are useful to simulate the morphologies.

Chronic exposure to tire rubber-derived contaminant 6PPD-quinone impairs sperm quality and induces the damage of reproductive capacity in male mice

It has been reported that N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q), a derivative of the tire antioxidant, N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD), exhibits acute toxicity towards organisms. However, the possible reproductive toxicity of 6PPD-Q in mammals has rarely been reported. In this study, the effects of 6PPD-Q on the reproductive toxicity of C57Bl/6 male mice were assessed after exposure to 6PPD-Q for 40 days at 4 mg/kg body weight (bw). Exposure to 6PPD-Q not only led to a decrease in testosterone levels but also adversely affected semen quality and in vitro fertilization (IVF) outcomes, thereby indicating impaired male fertility resulting from 6PPD-Q exposure. Additionally, transcriptomic and metabolomic analyses revealed that 6PPD-Q elicited differential expression of genes and metabolites primarily enriched in spermatogenesis, apoptosis, arginine biosynthesis, and sphingolipid metabolism in the testes of mice. In conclusion, our study reveals the toxicity of 6PPD-Q on the reproductive capacity concerning baseline endocrine disorders, sperm quality, germ cell apoptosis, and the sphingolipid signaling pathway in mice. These findings contribute to an enhanced understanding of the health hazards posed by 6PPD-Q to mammals, thereby facilitating the development of more robust safety regulations governing the utilization and disposal of rubber products.

Biophysical models of early mammalian embryogenesis

Embryo development is a critical and fascinating stage in the life cycle of many organisms. Despite decades of research, the earliest stages of mammalian embryogenesis are still poorly understood, caused by a scarcity of high-resolution spatial and temporal data, the use of only a few model organisms, and a paucity of truly multidisciplinary approaches that combine biological research with biophysical modeling and computational simulation. Here, we explain the theoretical frameworks and biophysical processes that are best suited to modeling the early mammalian embryo, review a comprehensive list of previous models, and discuss the most promising avenues for future work.

Journey of the mouse primitive endoderm: from specification to maturation

The blastocyst is a conserved stage and distinct milestone in the development of the mammalian embryo. Blastocyst stage embryos comprise three cell lineages which arise through two sequential binary cell fate specification steps. In the first, extra-embryonic trophectoderm (TE) cells segregate from inner cell mass (ICM) cells. Subsequently, ICM cells acquire a pluripotent epiblast (Epi) or extra-embryonic primitive endoderm (PrE, also referred to as hypoblast) identity. In the mouse, nascent Epi and PrE cells emerge in a salt-and-pepper distribution in the early blastocyst and are subsequently sorted into adjacent tissue layers by the late blastocyst stage. Epi cells cluster at the interior of the ICM, while PrE cells are positioned on its surface interfacing the blastocyst cavity, where they display apicobasal polarity. As the embryo implants into the maternal uterus, cells at the periphery of the PrE epithelium, at the intersection with the TE, break away and migrate along the TE as they mature into parietal endoderm (ParE). PrE cells remaining in association with the Epi mature into visceral endoderm. In this review, we discuss our current understanding of the PrE from its specification to its maturation. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'.

A theoretical understanding of mammalian preimplantation development

The blastocyst has long been a hallmark system of study in developmental biology due to its importance in mammalian development and clinical relevance for assisted reproductive technologies. In recent years, the blastocyst is emerging as a system of study for mathematical modelling. In this review, we compile, to our knowledge, all models describing preimplantation development. Coupled with experiments, these models have provided insight regarding the morphogenesis and cell-fate specification throughout preimplantation development. In the case of cell-fate specification, theoretical models have provided mechanisms explaining how proportion of cell types are established and maintained when confronted to perturbations. For cell-shape based models, they have described quantitatively how mechanical forces sculpt the blastocyst and even predicted how morphogenesis could be manipulated. As theoretical biology develops, we believe the next critical stage in modelling involves an integration of cell fate and mechanics to provide integrative models of development at distinct spatiotemporal scales. We discuss how, building on a balanced base of mechanical and chemical models, the preimplantation embryo will play a key role in integrating these two faces of the same coin.

Glucocorticoids, Stress and Delta-9 Tetrahydrocannabinol (THC) during Early Embryonic Development

Elevated molecular stress in women is known to have negative impacts on the reproductive development of oocytes and the embryos prior to implantation. In recent years, the prevalence of cannabis use among women of reproductive age has risen due to its ability to relieve psychological stress and nausea, which are mediated by its psychoactive component, ∆-9-tetrahydrocannabinol (THC). Although cannabis is the most popular recreational drug of the 21st century, much is unknown about its influence on molecular stress in reproductive tissues. The current literature has demonstrated that THC causes dose- and time-dependent alterations in glucocorticoid signaling, which have the potential to compromise morphology, development, and quality of oocytes and embryos. However, there are inconsistencies across studies regarding the mechanisms for THC-dependent changes in stress hormones and how either compounds may drive or arrest development. Factors such as variability between animal models, physiologically relevant doses, and undiscovered downstream gene targets of both glucocorticoids and THC could account for such inconsistencies. This review evaluates the results of studies which have investigated the effects of glucocorticoids on reproductive development and how THC may alter stress signaling in relevant tissues.

A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development

During early mammalian embryo development, a small number of cells make robust fate decisions at particular spatial locations in a tight time window to form inner cell mass (ICM), and later epiblast (Epi) and primitive endoderm (PE). While recent single-cell transcriptomics data allows scrutinization of heterogeneity of individual cells, consistent spatial and temporal mechanisms the early embryo utilize to robustly form the Epi/PE layers from ICM remain elusive. Here we build a multiscale three-dimensional model for mammalian embryo to recapitulate the observed patterning process from zygote to late blastocyst. By integrating the spatiotemporal information reconstructed from multiple single-cell transcriptomic datasets, the data-informed modeling analysis suggests two major processes critical to the formation of Epi/PE layers: a selective cell-cell adhesion mechanism (via EphA4/EphrinB2) for fate-location coordination and a temporal attenuation mechanism of cell signaling (via Fgf). Spatial imaging data and distinct subsets of single-cell gene expression data are then used to validate the predictions. Together, our study provides a multiscale framework that incorporates single-cell gene expression datasets to analyze gene regulations, cell-cell communications, and physical interactions among cells in complex geometries at single-cell resolution, with direct application to late-stage development of embryogenesis.

HGF/c-Met signaling regulates early differentiation of placental trophoblast cells

Depletion of hepatocyte growth factor (HGF) or mesenchymal-epithelial transition factor (c-Met) in mice leads to fetal lethality and placental maldevelopment. However, the dynamic change pattern of HGF/c-Met signaling during placental development and its involvement in the early differentiation of trophoblasts remain to be elucidated. In this study, using in situ hybridization assay, we elaborately demonstrated the spatial-temporal expression of Hgf and c-Met in mouse placenta from E5.5, the very early stage after embryonic implantation, to E12.5, when the placental structure is well developed. The concentration of the soluble form of c-Met (sMet) in maternal circulation peaked at E10.5. By utilizing the induced differentiation model of mouse trophoblast stem cells (mTSCs), we found that HGF significantly promoted mTSC differentiation into syncytiotrophoblasts (STBs) and invasive parietal trophoblast giant cells (PTGCs). Interestingly, sMet efficiently reversed the effect of HGF on mTSC differentiation. These findings indicate that HGF/c-Met signaling participates in regulating placental trophoblast cell fate at the early differentiation stage and that sMet acts as an endogenous antagonist in this aspect.

Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach

During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell-cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.

Measuring and Modeling Single-Cell Heterogeneity and Fate Decision in Mouse Embryos

Cellular heterogeneity is a property of any living system; however, its relationship with cellular fate decision remains an open question. Recent technological advances have enabled valuable insights, especially in complex systems such as the mouse embryo. In this review, we discuss recent studies that characterize cellular heterogeneity at different levels during mouse development, from the two-cell stage up to gastrulation. In addition to key experimental findings, we review mathematical modeling approaches that help researchers interpret these findings. Disentangling the role of heterogeneity in cell fate decision will likely rely on the refined integration of experiments, large-scale omics data, and mathematical modeling, complemented by the use of synthetic embryos and gastruloids as promising in vitro models.

Predicting pattern formation in embryonic stem cells using a minimalist, agent-based probabilistic model

The mechanisms of pattern formation during embryonic development remain poorly understood. Embryonic stem cells in culture self-organise to form spatial patterns of gene expression upon geometrical confinement indicating that patterning is an emergent phenomenon that results from the many interactions between the cells. Here, we applied an agent-based modelling approach in order to identify plausible biological rules acting at the meso-scale within stem cell collectives that may explain spontaneous patterning. We tested different models involving differential motile behaviours with or without biases due to neighbour interactions. We introduced a new metric, termed stem cell aggregate pattern distance (SCAPD) to probabilistically assess the fitness of our models with empirical data. The best of our models improves fitness by 70% and 77% over the random models for a discoidal or an ellipsoidal stem cell confinement respectively. Collectively, our findings show that a parsimonious mechanism that involves differential motility is sufficient to explain the spontaneous patterning of the cells upon confinement. Our work also defines a region of the parameter space that is compatible with patterning. We hope that our approach will be applicable to many biological systems and will contribute towards facilitating progress by reducing the need for extensive and costly experiments.

The transition from local to global patterns governs the differentiation of mouse blastocysts

During mammalian blastocyst development, inner cell mass (ICM) cells differentiate into epiblast (Epi) or primitive endoderm (PrE). These two fates are characterized by the expression of the transcription factors NANOG and GATA6, respectively. Here, we investigate the spatio-temporal distribution of NANOG and GATA6 expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single cell-based neighbourhood analyses. We define the cell neighbourhood by local features, which include the expression levels of both fate markers expressed in each cell and its neighbours, and the number of neighbouring cells. We further include the position of a cell relative to the centre of the ICM as a global positional feature. Our analyses reveal a local three-dimensional pattern that is already present in early blastocysts: 1) Cells expressing the highest NANOG levels are surrounded by approximately nine neighbours, while 2) cells expressing GATA6 cluster according to their GATA6 levels. This local pattern evolves into a global pattern in the ICM that starts to emerge in mid blastocysts. We show that FGF/MAPK signalling is involved in the three-dimensional distribution of the cells and, using a mutant background, we further show that the GATA6 neighbourhood is regulated by NANOG. Our quantitative study suggests that the three-dimensional cell neighbourhood plays a role in Epi and PrE precursor specification. Our results highlight the importance of analysing the three-dimensional cell neighbourhood while investigating cell fate decisions during early mouse embryonic development.

Specification of the First Mammalian Cell Lineages In Vivo and In Vitro

Our understanding of how the first mammalian cell lineages arise has been shaped largely by studies of the preimplantation mouse embryo. Painstaking work over many decades has begun to reveal how a single totipotent cell is transformed into a multilayered structure representing the foundations of the body plan. Here, we review how the first lineage decision is initiated by epigenetic regulation but consolidated by the integration of morphological features and transcription factor activity. The establishment of pluripotent and multipotent stem cell lines has enabled deeper analysis of molecular and epigenetic regulation of cell fate decisions. The capability to assemble these stem cells into artificial embryos is an exciting new avenue of research that offers a long-awaited window into cell fate specification in the human embryo. Together, these approaches are poised to profoundly increase our understanding of how the first lineage decisions are made during mammalian embryonic development.

Bioengineered microenvironment to culture early embryos

The abnormalities of early post-implantation embryos can lead to early pregnancy loss and many other syndromes. However, it is hard to study embryos after implantation due to the limited accessibility. The success of embryo culture in vitro can avoid the challenges of embryonic development in vivo and provide a powerful research platform for research in developmental biology. The biophysical and chemical cues of the microenvironments impart significant spatiotemporal effects on embryonic development. Here, we summarize the main strategies which enable researchers to grow embryos outside of the body while overcoming the implantation barrier, highlight the roles of engineered microenvironments in regulating early embryonic development, and finally discuss the future challenges and new insights of early embryo culture.

Self-Assembling Scaffolds Supported Long-Term Growth of Human Primed Embryonic Stem Cells and Upregulated Core and Naïve Pluripotent Markers

The maintenance and expansion of human embryonic stem cells (ESCs) in two-dimensional (2-D) culture is technically challenging, requiring routine manipulation and passaging. We developed three-dimensional (3-D) scaffolds to mimic the in vivo microenvironment for stem cell proliferation. The scaffolds were made of two 8-arm polyethylene glycol (PEG) polymers functionalized with thiol (PEG-8-SH) and acrylate (PEG-8-Acr) end groups, which self-assembled via a Michael addition reaction. When primed ESCs (H9 cells) were mixed with PEG polymers, they were encapsulated and grew for an extended period, while maintaining their viability, self-renewal, and differentiation potential both in vitro and in vivo. Three-dimensional (3-D) self-assembling scaffold-grown cells displayed an upregulation of core pluripotency genes, OCT4, NANOG, and SOX2. In addition, the expression of primed markers decreased, while the expression of naïve markers substantially increased. Interestingly, the expression of mechanosensitive genes, YAP and TAZ, was also upregulated. YAP inhibition by Verteporfin abrogated the increased expression of YAP/TAZ as well as core and naïve pluripotent markers. Evidently, the 3-D culture conditions induced the upregulation of makers associated with a naïve state of pluripotency in the primed cells. Overall, our 3-D culture system supported the expansion of a homogenous population of ESCs and should be helpful in advancing their use for cell therapy and regenerative medicine.

Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data

Background

Single cell RNA sequencing (scRNA-seq) is applied to assay the individual transcriptomes of large numbers of cells. The gene expression at single-cell level provides an opportunity for better understanding of cell function and new discoveries in biomedical areas. To ensure that the single-cell based gene expression data are interpreted appropriately, it is crucial to develop new computational methods.

Results

In this article, we try to re-construct a neural network based on Gene Ontology (GO) for dimension reduction of scRNA-seq data. By integrating GO with both unsupervised and supervised models, two novel methods are proposed, named GOAE (Gene Ontology AutoEncoder) and GONN (Gene Ontology Neural Network) respectively.

Conclusions

The evaluation results show that the proposed models outperform some state-of-the-art dimensionality reduction approaches. Furthermore, incorporating with GO, we provide an opportunity to interpret the underlying biological mechanism behind the neural network-based model.

Theoretical tool bridging cell polarities with development of robust morphologies

Despite continual renewal and damages, a multicellular organism is able to maintain its complex morphology. How is this stability compatible with the complexity and diversity of living forms? Looking for answers at protein level may be limiting as diverging protein sequences can result in similar morphologies. Inspired by the progressive role of apical-basal and planar cell polarity in development, we propose that stability, complexity, and diversity are emergent properties in populations of proliferating polarized cells. We support our hypothesis by a theoretical approach, developed to effectively capture both types of polar cell adhesions. When applied to specific cases of development – gastrulation and the origins of folds and tubes – our theoretical tool suggests experimentally testable predictions pointing to the strength of polar adhesion, restricted directions of cell polarities, and the rate of cell proliferation to be major determinants of morphological diversity and stability.

Cells have the power to organise themselves to form complex and stable structures, whether it is to create a fully shaped baby from a single egg, or to allow adult salamanders to grow a new limb after losing a leg. This ability has been scrutinised at many different levels. For example, researchers have looked at the chemical messages exchanged by cells, or they have recorded the different shapes an embryo goes through during development. However, it is still difficult to reconcile the information from these approaches into a description that makes sense at multiple scales.

When an embryo develops, sheets of cells fold and unfold to create complex 3D shapes, like the tubes that make our lungs. Moulding sheets into tubes relies on interactions between cells that are not the same in all directions. In fact, two types of asymmetry (or polarity) guide these interactions. Apical-basal polarity runs across a sheet of cells, which means that the top surface of the sheet differs from the bottom. Planar cell polarity runs along the sheet and distinguishes one end from the other. For instance, apical-basal polarity marks the inner and outer surfaces of our skin, while planar cell polarity controls the direction in which our hair grows.

Nissen et al. set out to investigate how these polarities help cells in an embryo organise themselves to form complicated folds and tubes. To do this, simple mathematical representations of both apical-basal and planar cell polarities were designed. The representations were then combined to create computer simulations of groups of cells as these divide and interact with each other.

Simulations of ‘cells’ with only apical-basal polarity were able to generate different shapes in the ‘tissues’ produced, including many found in living organisms. External conditions, such as how cells were arranged to start with, determined the resulting shape. With both apical-basal and planar cell polarities, the simulations reproduced an important change that occurs during early development. They also replicated how the tubes that transport nutrients and oxygen form.

These results show that simple properties of individual cells, such as polarities, can produce different shapes in developing tissues and organs, without the need for a complicated overarching program. Abnormal changes in cell polarity are also associated with diseases such as cancer. The mathematical model developed by Nissen et al. could therefore be a useful tool to study these events.

Mouse ICM Organoids Reveal Three-Dimensional Cell Fate Clustering

During mammalian preimplantation, cells of the inner cell mass (ICM) adopt either an embryonic or an extraembryonic fate. This process is tightly regulated in space and time and has been studied previously in mouse embryos and embryonic stem cell models. Current research suggests that cell fates are arranged in a salt-and-pepper pattern of random cell positioning or a spatially alternating pattern. However, the details of the three-dimensional patterns of cell fate specification have not been investigated in the embryo nor in in vitro systems. We developed ICM organoids as a, to our knowledge, novel three-dimensional in vitro stem cell system to model mechanisms of fate decisions that occur in the ICM. ICM organoids show similarities to the in vivo system that arise regardless of the differences in geometry and total cell number. Inspecting ICM organoids and mouse embryos, we describe a so far unknown local clustering of cells with identical fates in both systems. These findings are based on the three-dimensional quantitative analysis of spatiotemporal patterns of NANOG and GATA6 expression in combination with computational rule-based modeling. The pattern identified by our analysis is distinct from the current view of a salt-and-pepper pattern. Our investigation of the spatial distributions both in vivo and in vitro dissects the contributions of the different parts of the embryo to cell fate specifications. In perspective, our combination of quantitative in vivo and in vitro analyses can be extended to other mammalian organisms and thus creates a powerful approach to study embryogenesis.

Kinetic models of hematopoietic differentiation

As cell and molecular biology is becoming increasingly quantitative, there is an upsurge of interest in mechanistic modeling at different levels of resolution. Such models mostly concern kinetics and include gene and protein interactions as well as cell population dynamics. The final goal of these models is to provide experimental predictions, which is now taking on. However, even without matured predictions, kinetic models serve the purpose of compressing a plurality of experimental results into something that can empower the data interpretation, and importantly, suggesting new experiments by turning "knobs" in silico. Once formulated, kinetic models can be executed in terms of molecular rate equations for concentrations or by stochastic simulations when only a limited number of copies are involved. Developmental processes, in particular those of stem and progenitor cell commitments, are not only topical but also particularly suitable for kinetic modeling due to the finite number of key genes involved in cellular decisions. Stem and progenitor cell commitment processes have been subject to intense experimental studies over the last decade with some emphasis on embryonic and hematopoietic stem cells. Gene and protein interactions governing these processes can be modeled by binary Boolean rules or by continuous-valued models with interactions set by binding strengths. Conceptual insights along with tested predictions have emerged from such kinetic models. Here we review kinetic modeling efforts applied to stem cell developmental systems with focus on hematopoiesis. We highlight the future challenges including multi-scale models integrating cell dynamical and transcriptional models. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Developmental Biology > Stem Cell Biology and Regeneration.

Modeling-Based Investigation of the Effect of Noise in Cellular Systems

Noise is pervasive in cellular biology and inevitably affects the dynamics of cellular processes. Biological systems have developed regulatory mechanisms to ensure robustness with respect to noise or to take advantage of stochasticity. We review here, through a couple of selected examples, some insights on possible robustness factors and constructive roles of noise provided by computational modeling. In particular, we focus on (1) factors that likely contribute to the robustness of oscillatory processes such as the circadian clocks and the cell cycle, (2) how reliable coding/decoding of calcium-mediated signaling could be achieved in presence of noise and, in some cases, enhanced through stochastic resonance, and (3) how embryonic cell differentiation processes can exploit stochasticity to create heterogeneity in a population of identical cells.

Primitive Endoderm Differentiation: From Specification to Epithelialization

At the time of implantation, the mouse blastocyst has developed three cell lineages: the epiblast (Epi), the primitive endoderm (PrE), and the trophectoderm (TE). The PrE and TE are extraembryonic tissues but their interactions with the Epi are critical to sustain embryonic growth, as well as to pattern the embryo. We review here the cellular and molecular events that lead to the production of PrE and Epi lineages and discuss the different hypotheses that are proposed for the induction of these cell types. In the second part, we report the current knowledge about the epithelialization of the PrE.

Programming Morphogenesis through Systems and Synthetic Biology

Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids.

Four simple rules that are sufficient to generate the mammalian blastocyst

Early mammalian development is both highly regulative and self-organizing. It involves the interplay of cell position, predetermined gene regulatory networks, and environmental interactions to generate the physical arrangement of the blastocyst with precise timing. However, this process occurs in the absence of maternal information and in the presence of transcriptional stochasticity. How does the preimplantation embryo ensure robust, reproducible development in this context? It utilizes a versatile toolbox that includes complex intracellular networks coupled to cell-cell communication, segregation by differential adhesion, and apoptosis. Here, we ask whether a minimal set of developmental rules based on this toolbox is sufficient for successful blastocyst development, and to what extent these rules can explain mutant and experimental phenotypes. We implemented experimentally reported mechanisms for polarity, cell-cell signaling, adhesion, and apoptosis as a set of developmental rules in an agent-based in silico model of physically interacting cells. We find that this model quantitatively reproduces specific mutant phenotypes and provides an explanation for the emergence of heterogeneity without requiring any initial transcriptional variation. It also suggests that a fixed time point for the cells' competence of fibroblast growth factor (FGF)/extracellular signal-regulated kinase (ERK) sets an embryonic clock that enables certain scaling phenomena, a concept that we evaluate quantitatively by manipulating embryos in vitro. Based on these observations, we conclude that the minimal set of rules enables the embryo to experiment with stochastic gene expression and could provide the robustness necessary for the evolutionary diversification of the preimplantation gene regulatory network.

Gene Expression Noise Enhances Robust Organization of the Early Mammalian Blastocyst

A critical event in mammalian embryo development is construction of an inner cell mass surrounded by a trophoectoderm (a shell of cells that later form extraembryonic structures). We utilize multi-scale, stochastic modeling to investigate the design principles responsible for robust establishment of these structures. This investigation makes three predictions, each supported by our quantitative imaging. First, stochasticity in the expression of critical genes promotes cell plasticity and has a critical role in accurately organizing the developing mouse blastocyst. Second, asymmetry in the levels of noise variation (expression fluctuation) of Cdx2 and Oct4 provides a means to gain the benefits of noise-mediated plasticity while ameliorating the potentially detrimental effects of stochasticity. Finally, by controlling the timing and pace of cell fate specification, the embryo temporally modulates plasticity and creates a time window during which each cell can continually read its environment and adjusts its fate. These results suggest noise has a crucial role in maintaining cellular plasticity and organizing the blastocyst.

A critical event in mammalian embryo development is construction of a mass of embryonic stem cells surrounded by a distinct shell that later forms the placenta along with other structures. Despite sustained investigation, multiple hypotheses for what is responsible for this organization persist and it remains unclear what is responsible for the robust organization (remarkable ability for embryos to pattern correctly) of these structures. Here, we utilize multi-scale, stochastic modeling along with fluorescence imaging to investigate the factors that contribute to the incredible robustness of this organizational process. Results point to two factors that contribute to this robustness: 1) the timing and pace of cell fate specification and 2) stochastic gene regulatory effects. The former creates a window of time during which each cell can continually read their environment and adjust their gene expressions (and consequently fate) in response to dynamic rearrangements of cells arising from cell divisions and motions. The latter improves cell plasticity, providing the capability for cells to adjust to changes in their local environment. Fluorescence imaging results demonstrate that the magnitude and structure of gene expression variations match those predicted to promote organizational robustness.

Mathematical Models of Pluripotent Stem Cells: At the Dawn of Predictive Regenerative Medicine

Regenerative medicine, ranging from stem cell therapy to organ regeneration, is promising to revolutionize treatments of diseases and aging. These approaches require a perfect understanding of cell reprogramming and differentiation. Predictive modeling of cellular systems has the potential to provide insights about the dynamics of cellular processes, and guide their control. Moreover in many cases, it provides alternative to experimental tests, difficult to perform for practical or ethical reasons. The variety and accuracy of biological processes represented in mathematical models grew in-line with the discovery of underlying molecular mechanisms. High-throughput data generation led to the development of models based on data analysis, as an alternative to more established modeling based on prior mechanistic knowledge. In this chapter, we give an overview of existing mathematical models of pluripotency and cell fate, to illustrate the variety of methods and questions. We conclude that current approaches are yet to overcome a number of limitations: Most of the computational models have so far focused solely on understanding the regulation of pluripotency, and the differentiation of selected cell lineages. In addition, models generally interrogate only a few biological processes. However, a better understanding of the reprogramming process leading to ESCs and iPSCs is required to improve stem-cell therapies. One also needs to understand the links between signaling, metabolism, regulation of gene expression, and the epigenetics machinery.

Lineage specification in the mouse preimplantation embryo

During mouse preimplantation embryo development, totipotent blastomeres generate the first three cell lineages of the embryo: trophectoderm, epiblast and primitive endoderm. In recent years, studies have shown that this process appears to be regulated by differences in cell-cell interactions, gene expression and the microenvironment of individual cells, rather than the active partitioning of maternal determinants. Precisely how these differences first emerge and how they dictate subsequent molecular and cellular behaviours are key questions in the field. As we review here, recent advances in live imaging, computational modelling and single-cell transcriptome analyses are providing new insights into these questions.

Short-range growth inhibitory signals from the epithelium can drive non-stereotypic branching in the pancreas

Many organs such as the vasculature, kidney, lungs, pancreas and several other glands form ramified networks of tubes that either maximize exchange surfaces between two compartments or minimize the volume of an organ dedicated to the production and local delivery of a cell-derived product. The structure of these tubular networks can be stereotyped, as in the lungs, or stochastic with large variations between individuals, as in the pancreas. The principles driving stereotyped branching have attracted much attention and several models have been proposed and refined. Here we focus on the pancreas, as a model of non-stereotyped branching. In many ramified tubular organs, an important role of the mesenchyme as a source of branching signals has been proposed, including in the pancreas. However, our previous work has shown that in the absence of mesenchyme, epithelial cells seeded in vitro in Matrigel form heavily branched organoids. Here we experimentally show that pancreatic organoids grow primarily at the tips. Furthermore, in contrast to classical 'depletion of activator' mechanisms, organoids growing in close vicinity seem not to affect each other's growth before they get in contact. We recapitulate these observations in an in silico model of branching assuming a 'local inhibitor' is secreted by the epithelium. Remarkably this simple mechanism is sufficient to generate branched organoids similar to those observed in vitro, including their transition from filled spheres to a tree like structure. Quantifying the similarity between in silico and in vitro development through a normalized surface to volume ratio, our in silico model predicts that inhibition is likely to be cooperative and that the diffusing inhibitor decays within a length scale of 10-20 μm.

Emerging Modeling Concepts and Solutions in Stem Cell Research

Modern stem cell research, as well as other fields of contemporary biology involves quantitative sciences in many ways. Identifying candidates for key differentiation or reprogramming factors, tracing global transcriptome changes, or finding drugs is now broadly involves bioinformatics and biostatistics. However, the next key step, understanding the underlying reasons and establishing causal links leading to differentiation or reprogramming requires qualitative and quantitative biological models describing complex biological systems. Currently, quantitative modeling is a challenging science, capable to deliver rather modest results or predictions. What model types are the most popular and what features of stem cell behavior they are capturing? What new insights do we expect from the computational modeling of stem cells in the foreseeable future? Current review attempts to approach these essential questions by considering published quantitative models and solutions emerging in the area of stem cell research.

Computational modelling of epidermal stratification highlights the importance of asymmetric cell division for predictable and robust layer formation

Skin is a complex organ tasked with, among other functions, protecting the body from the outside world. Its outermost protective layer, the epidermis, is comprised of multiple cell layers that are derived from a single-layered ectoderm during development. Using a new stochastic, multi-scale computational modelling framework, the anisotropic subcellular element method, we investigate the role of cell morphology and biophysical cell-cell interactions in the formation of this layered structure. This three-dimensional framework describes interactions between collections of hundreds to thousands of cells and (i) accounts for intracellular structure and morphology, (ii) easily incorporates complex cell-cell interactions and (iii) can be efficiently implemented on parallel architectures. We use this approach to construct a model of the developing epidermis that accounts for the internal polarity of ectodermal cells and their columnar morphology. Using this model, we show that cell detachment, which has been previously suggested to have a role in this process, leads to unpredictable, randomized stratification and that this cannot be abrogated by adjustment of cell-cell adhesion interaction strength. Polarized distribution of cell adhesion proteins, motivated by epithelial polarization, can however eliminate this detachment, and in conjunction with asymmetric cell division lead to robust and predictable development.

Towards understanding the roles of position and geometry on cell fate decisions during preimplantation development

The first lineage segregation event in mouse embryos produces two separate cell populations: inner cell mass and trophectoderm. This is understood to be brought about by cells sensing their position within the embryo and differentiating accordingly. The cellular and molecular underpinnings of this process remain under investigation and have variously been considered to be completely stochastic or alternately, subject to some predisposition set up at fertilisation or before. Here, we consider these views in light of recent publications, discuss the possible role of cell geometry and mechanical forces in this process and describe how modelling could contribute in addressing this issue.

Single cells get together: High-resolution approaches to study the dynamics of early mouse development

Embryonic development is a complex and highly dynamic process during which individual cells interact with one another, adopt different identities and organize themselves in three-dimensional space to generate an entire organism. Recent technical developments in genomics and high-resolution quantitative imaging are making it possible to study cellular populations at single-cell resolution and begin to integrate different inputs, for example genetic, physical and chemical factors, that affect cell differentiation over spatial and temporal scales. The preimplantation mouse embryo allows the analysis of cell fate decisions in vivo with high spatiotemporal resolution. In this review we highlight how the application of live imaging and single-cell resolution analysis pipelines is providing an unprecedented level of insight on the processes that shape the earliest stages of mammalian development.

Computational modelling of embryonic stem-cell fate control

The maintenance of pluripotency in embryonic stem cells (ESCs), its loss during lineage specification or its re-induction to generate induced pluripotent stem cells are central topics in stem cell biology. To uncover the molecular basis and the design principles of pluripotency control, a multitude of experimental, but also an increasing number of computational, studies have been published. Here, we consider recent reports that apply computational or mathematical modelling approaches to describe the regulatory processes that underlie cell fate decisions in mouse ESCs. We summarise the principles, the strengths and potentials but also the limitations of different computational strategies.

Primitive endoderm differentiation: from specification to epithelium formation

In amniotes, primitive endoderm (PrE) plays important roles not only for nutrient support but also as an inductive tissue required for embryo patterning. PrE is an epithelial monolayer that is visible shortly before embryo implantation and is one of the first three cell lineages produced by the embryo. We review here the molecular mechanisms that have been uncovered during the past 10 years on PrE and epiblast cell lineage specification within the inner cell mass of the blastocyst and on their subsequent steps of differentiation.

A close look at the mammalian blastocyst: epiblast and primitive endoderm formation

During early development, the mammalian embryo undergoes a series of profound changes that lead to the formation of two extraembryonic tissues--the trophectoderm and the primitive endoderm. These tissues encapsulate the pluripotent epiblast at the time of implantation. The current model proposes that the formation of these lineages results from two consecutive binary cell fate decisions. The first controls the formation of the trophectoderm and the inner cell mass, and the second controls the formation of the primitive endoderm and the epiblast within the inner cell mass. While early mammalian embryos develop with extensive plasticity, the embryonic pattern prior to implantation is remarkably reproducible. Here, we review the molecular mechanisms driving the cell fate decision between primitive endoderm and epiblast in the mouse embryo and integrate data from recent studies into the current model of the molecular network regulating the segregation between these lineages and their subsequent differentiation.

Cell fate regulation during preimplantation development: a view of adhesion-linked molecular interactions

In the developmental process of the early mammalian embryo, it is crucial to understand how the identical cells in the early embryo later develop different fates. Along with existing models, many recently discovered molecular, cellular and developmental factors play roles in cell position, cell polarity and transcriptional networks in cell fate regulation during preimplantation. A structuring process known as compaction provides the "start signal" for cells to differentiate and orchestrates the developmental cascade. The proper intercellular junctional complexes assembled between blastomeres act as a conducting mechanism governing cellular diversification. Here, we provide an overview of the diversification process during preimplantation development as it relates to intercellular junctional complexes. We also evaluate transcriptional differences between embryonic lineages according to cell- cell adhesion and the contributions of adhesion to lineage commitment. These series of processes indicate that proper cell fate specification in the early mammalian embryo depends on junctional interactions and communication, which play essential roles during early morphogenesis.

A molecular basis for developmental plasticity in early mammalian embryos

Early mammalian embryos exhibit remarkable plasticity, as highlighted by the ability of separated early blastomeres to produce a whole organism. Recent work in the mouse implicates a network of transcription factors in governing the establishment of the primary embryonic lineages. A combination of genetics and embryology has uncovered the organisation and function of the components of this network, revealing a gradual resolution from ubiquitous to lineage-specific expression through a combination of defined regulatory relationships, spatially organised signalling, and biases from mechanical inputs. Here, we summarise this information, link it to classical embryology and propose a molecular framework for the establishment and regulation of developmental plasticity.

A self-organization framework for symmetry breaking in the mammalian embryo

The mechanisms underlying the appearance of asymmetry between cells in the early embryo and consequently the specification of distinct cell lineages during mammalian development remain elusive. Recent experimental advances have revealed unexpected dynamics of and new complexity in this process. These findings can be integrated in a new unified framework that regards the early mammalian embryo as a self-organizing system.

Breast-cancer anti-estrogen resistance 4 (BCAR4) encodes a novel maternal-effect protein in bovine and is expressed in the oocyte of humans and other non-rodent mammals

STUDY QUESTION

Does BCAR4 have a role in mammalian embryo development?

SUMMARY ANSWER

Expression, localization and functional data support that BCAR4 is a maternal-effect protein in non-rodent mammals.

WHAT IS KNOWN ALREADY

BCAR4 was previously identified as an oocyte-specific gene in cattle, and as a marker of certain breast tumors in humans.

STUDY DESIGN, SIZE, DURATION

Human oocytes were obtained from patients undergoing IVF, but had failed to mature after ovarian stimulation. Dog oocytes were obtained from ovariectomized bitches. Pig, horse and bovine ovaries were obtained from commercial slaughterhouses for extraction of immature oocyte-cumulus complexes. In vivo matured bovine matured oocytes were obtained after ovulation induction and ovulation inducing treatment of Montbeliard heifers.

MATERIALS, SETTING AND METHODS

Expression at the RNA level was analyzed by reverse transcription coupled to polymerase chain reaction. Western blot and immunolabeling coupled to confocal or electronic microscopy were used to analyze bovine protein expression and intracellular localization. For the functional approach, short-interfering RNA were microinjected into mature bovine oocytes, followed by IVF; cleavage and embryo development were recorded.

MAIN RESULTS AND THE ROLE OF CHANCE

The BCAR4 gene is conserved in mammalian species from various orders and has been lost in rodents after divergence with lagomorphs. The transcript is expressed in the oocytes of humans and domestic species. We bring the first experimental evidence of the BCAR4 protein in mammals. In cattle, the protein is not detected in immature oocytes but starts to be synthesized during maturation, increases in the zygote and persists until the morula stage. The protein is detected throughout the cytoplasm in mature oocytes, concentrates in and around the pronuclei in the zygote, and appears to shuttle in and out of the nuclei starting in the 2-cell embryo; BCAR4 is also present at the junctions between blastomeres from 2-cell to morula. In our functional approach, targeting the BCAR4 transcript by small-interfering RNA significantly compromised development to the morula or/and blastocyst stages (P < 0.05, logistic regression).

LIMITATIONS, REASONS FOR CAUTION

As indicated above, protein expression and function were investigated in cattle and mostly in vitro matured oocytes were used.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides a novel candidate gene whose mutation or deregulation may underlie certain cases of unexplained female infertility.

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.