Nanog-dependent feedback loops regulate murine embryonic stem cell heterogeneity

Crosstalk between lipid metabolism and EMT: emerging mechanisms and cancer therapy

Lipids are the key component of all membranes composed of a variety of molecules that transduce intracellular signaling and provide energy to the cells in the absence of nutrients. Alteration in lipid metabolism is a major factor for cancer heterogeneity and a newly identified cancer hallmark. Reprogramming of lipid metabolism affects the diverse cancer phenotypes, especially epithelial-mesenchymal transition (EMT). EMT activation is considered to be an essential step for tumor metastasis, which exhibits a crucial role in the biological processes including development, wound healing, and stem cell maintenance, and has been widely reported to contribute pathologically to cancer progression. Altered lipid metabolism triggers EMT and activates multiple EMT-associated oncogenic pathways. Although the role of lipid metabolism-induced EMT in tumorigenesis is an attractive field of research, there are still significant gaps in understanding the underlying mechanisms and the precise contributions of this interplay. Further study is needed to clarify the specific molecular mechanisms driving the crosstalk between lipid metabolism and EMT, as well as to determine the potential therapeutic implications. The increased dependency of tumor cells on lipid metabolism represents a novel therapeutic target, and targeting altered lipid metabolism holds promise as a strategy to suppress EMT and ultimately inhibit metastasis.

A bipartite function of ESRRB can integrate signaling over time to balance self-renewal and differentiation

Cooperative DNA binding of transcription factors (TFs) integrates the cellular context to support cell specification during development. Naive mouse embryonic stem cells are derived from early development and can sustain their pluripotent identity indefinitely. Here, we ask whether TFs associated with pluripotency evolved to directly support this state or if the state emerges from their combinatorial action. NANOG and ESRRB are key pluripotency factors that co-bind DNA. We find that when both factors are expressed, ESRRB supports pluripotency. However, when NANOG is absent, ESRRB supports a bistable culture of cells with an embryo-like primitive endoderm identity ancillary to pluripotency. The stoichiometry between NANOG and ESRRB allows quantitative titration of this differentiation, and in silico modeling of bipartite ESRRB activity suggests it safeguards plasticity in differentiation. Thus, the concerted activity of cooperative TFs can transform their effect to sustain intermediate cell identities and allow ex vivo expansion of immortal stem cells. A record of this paper's transparent peer review process is included in the supplemental information.

Esrrb Regulates Specific Feed-Forward Loops to Transit From Pluripotency Into Early Stages of Differentiation

Characterization of pluripotent states, in which cells can both self-renew or differentiate, with the irreversible loss of pluripotency, are important research areas in developmental biology. Although microRNAs (miRNAs) have been shown to play a relevant role in cellular differentiation, the role of miRNAs integrated into gene regulatory networks and its dynamic changes during these early stages of embryonic stem cell (ESC) differentiation remain elusive. Here we describe the dynamic transcriptional regulatory circuitry of stem cells that incorporate protein-coding and miRNA genes based on miRNA array expression and quantitative sequencing of short transcripts upon the downregulation of the Estrogen Related Receptor Beta (Esrrb). The data reveals how Esrrb, a key stem cell transcription factor, regulates a specific stem cell miRNA expression program and integrates dynamic changes of feed-forward loops contributing to the early stages of cell differentiation upon its downregulation. Together these findings provide new insights on the architecture of the combined transcriptional post-transcriptional regulatory network in embryonic stem cells.

An oscillatory network controlling self-renewal of skeletal muscle stem cells

The balance between proliferation and differentiation of muscle stem cells is tightly controlled, ensuring the maintenance of a cellular pool needed for muscle growth and repair. Muscle stem cells can proliferate, they can generate differentiating cells, or they self-renew to produce new stem cells. Notch signaling plays a crucial role in this process. Recent studies revealed that expression of the Notch effector HES1 oscillates in activated muscle stem cells. The oscillatory expression of HES1 periodically represses transcription from the genes encoding the myogenic transcription factor MYOD and the Notch ligand DLL1, thereby driving MYOD and DLL1 oscillations. This oscillatory network allows muscle progenitor cells and activated muscle stem cells to remain in a proliferative and 'undecided' state, in which they can either differentiate or self-renew. When HES1 is downregulated, MYOD oscillations become unstable and are replaced by sustained expression, which drives the cells into terminal differentiation. During development and regeneration, proliferating stem cells contact each other and the stability of the oscillatory expression depends on regular DLL1 inputs provided by neighboring cells. In such communities of cells that receive and provide Notch signals, the appropriate timing of DLL1 inputs is important, as sustained DLL1 cannot replace oscillatory DLL1. Thus, in cell communities, DLL1 oscillations ensure the appropriate balance between self-renewal and differentiation. In summary, oscillations in myogenic cells are an important example of dynamic gene expression determining cell fate.

On the origins and conceptual frameworks of natural plasticity-Lessons from single-cell models in C. elegans

How flexible are cell identities? This problem has fascinated developmental biologists for several centuries and can be traced back to Abraham Trembley's pioneering manipulations of Hydra to test its regeneration abilities in the 1700s. Since the cell theory in the mid-19th century, developmental biology has been dominated by a single framework in which embryonic cells are committed to specific cell fates, progressively and irreversibly acquiring their differentiated identities. This hierarchical, unidirectional and irreversible view of cell identity has been challenged in the past decades through accumulative evidence that many cell types are more plastic than previously thought, even in intact organisms. The paradigm shift introduced by such plasticity calls into question several other key traditional concepts, such as how to define a differentiated cell or more generally cellular identity, and has brought new concepts, such as distinct cellular states. In this review, we want to contribute to this representation by attempting to clarify the conceptual and theoretical frameworks of cell plasticity and identity. In the context of these new frameworks we describe here an atlas of natural plasticity of cell identity in C. elegans, including our current understanding of the cellular and molecular mechanisms at play. The worm further provides interesting cases at the borderlines of cellular plasticity that highlight the conceptual challenges still ahead. We then discuss a set of future questions and perspectives arising from the studies of natural plasticity in the worm that are shared with other reprogramming and plasticity events across phyla.

An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feed Forward Loop Interactions

Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory “dimensions” coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module.

Noise and the molecular processes underlying cell fate decision-making

Cell fate decision-making events involve the interplay of many molecular processes, ranging from signal transduction to genetic regulation, as well as a set of molecular and physiological feedback loops. Each aspect offers a rich field of investigation in its own right, but to understand the whole process, even in simple terms, we need to consider them together. Here we attempt to characterise this process by focussing on the roles of noise during cell fate decisions. We use a range of recent results to develop a view of the sequence of events by which a cell progresses from a pluripotent or multipotent to a differentiated state: chromatin organisation, transcription factor stoichiometry, and cellular signalling all change during this progression, and all shape cellular variability, which becomes maximal at the transition state.

Fine-tuning Nanog expression heterogeneity in embryonic stem cells by regulating a Nanog transcript-specific microRNA

In embryonic stem cells (ESCs), the transcription factor Nanog maintains the stemness of ESCs despite exhibiting heterogeneous expression patterns under varied culture conditions. Efficient fine-tuning of Nanog expression heterogeneity could enable ESC proliferation and differentiation along specific lineages to be regulated. Herein, by employing a stochastic modeling approach, we show that Nanog expression heterogeneity can be controlled by modulating the regulatory features of a Nanog transcript-specific microRNA, mir-296. We demonstrate how and why the extent of origin-dependent fluctuations in Nanog expression level can be altered by varying either the binding efficiency of the microRNA-mRNA complex or the expression level of mir-296. Moreover, our model makes experimentally feasible and insightful predictions to maneuver Nanog expression heterogeneity explicitly to achieve cell-type-specific differentiation of ESCs.

A Similar Speciation Process Relying on Cellular Stochasticity in Microbial and Cancer Cell Populations

Similarities between microbial and cancer cells were noticed in recent years and serve as a basis for an atavism theory of cancer. Cancer cells would rely on the reactivation of an ancestral "genetic program" that would have been repressed in metazoan cells. Here we argue that cancer cells resemble unicellular organisms mainly in their similar way to exploit cellular stochasticity to produce cell specialization and maximize proliferation. Indeed, the relationship between low stochasticity, specialization, and quiescence found in normal differentiated metazoan cells is lost in cancer. On the contrary, low stochasticity and specialization are associated with high proliferation among cancer cells, as it is observed for the "specialist" cells in microbial populations that fully exploit nutritional resources to maximize proliferation. Thus, we propose a model where the appearance of cancer phenotypes can be solely due to an adaptation and a speciation process based on initial increase in cellular stochasticity.

Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor

Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τ_T, that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance Rα2. Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk.

No two cells are identical. Even isogenic cells, living in the same environment and expressing the same set of genes display measurable differences or variation in the expression level of any of these genes. How much of the differences in expression levels are permanent and how much of these differences vanish in time has intrigued us for generations. We develop a theoretical framework based on a stochastic model and put it to work in the analysis of T cell receptor expression level in CD4 T cells. We show that T cell populations with genetically diverse receptors display stable variation in receptor expression but, surprisingly, we detect persistent differences in receptor levels among uniform transgenic T cells. The analysis, being based on the mean cohort expression levels logarithm, can be applied to techniques that measure expression at single-cell level and also to the myriad of genomics and proteomics techniques that measure expression in bulk populations.

A Darwinian and Physical Look at Stem Cell Biology Helps Understanding the Role of Stochasticity in Development

Single-cell analysis allows biologists to gain huge insight into cell differentiation and tissue structuration. Randomness of differentiation, both in vitro and in vivo, of pluripotent (multipotent) stem cells is now demonstrated to be mainly based on stochastic gene expression. Nevertheless, it remains necessary to incorporate this inherent stochasticity of developmental processes within a coherent scheme. We argue here that the theory called ontophylogenesis is more relevant and better fits with experimental data than alternative theories which have been suggested based on the notions of self-organization and attractor states. The ontophylogenesis theory considers the generation of a differentiated state as a constrained random process: randomness is provided by the stochastic dynamics of biochemical reactions while the environmental constraints, including cell inner structures and cell-cell interactions, drive the system toward a stabilized state of equilibrium. In this conception, biological organization during development can be seen as the result of multiscale constraints produced by the dynamical organization of the biological system which retroacts on the stochastic dynamics at lower scales. This scheme makes it possible to really understand how the generation of reproducible structures at higher organization levels can be fully compatible with probabilistic behavior at the lower levels. It is compatible with the second law of thermodynamics but allows the overtaking of the limitations exhibited by models only based on entropy exchanges which cannot cope with the description nor the dynamics of the mesoscopic and macroscopic organization of biological systems.

DNA methylation and the core pluripotency network

From the onset of fertilization, the genome undergoes cell division and differentiation. All of these developmental transitions and differentiation processes include cell-specific signatures and gradual changes of the epigenome. Understanding what keeps stem cells in the pluripotent state and what leads to differentiation are fascinating and biomedically highly important issues. Numerous studies have identified genes, proteins, microRNAs and small molecules that exert essential effects. Notably, there exists a core pluripotency network that consists of several transcription factors and accessory proteins. Three eminent transcription factors, OCT4, SOX2 and NANOG, serve as hubs in this core pluripotency network. They bind to the enhancer regions of their target genes and modulate, among others, the expression levels of genes that are associated with Gene Ontology terms related to differentiation and self-renewal. Also, much has been learned about the epigenetic rewiring processes during these changes of cell fate. For example, DNA methylation dynamics is pivotal during embryonic development. The main goal of this review is to highlight an intricate interplay of (a) DNA methyltransferases controlling the expression levels of core pluripotency factors by modulation of the DNA methylation levels in their enhancer regions, and of (b) the core pluripotency factors controlling the transcriptional regulation of DNA methyltransferases. We discuss these processes both at the global level and in atomistic detail based on information from structural studies and from computer simulations.

Ferulic acid maintains the self-renewal capacity of embryo stem cells and adipose-derived mesenchymal stem cells in high fat diet-induced obese mice

Self-renewal is required for embryo stem cells (ESCs) and adipose-derived mesenchymal stem cells (ADMSCs). This study examined the ability of ferulic acid in mouse ESCs and ADMSCs, in a high fat diet-induced mouse model. Initially, five natural compounds of ferulic acid, xanthohumol, curcumin, ascorbic acid, and quercetin were screened in ESCs using an alkaline phosphate ⁺(AP⁺) assay, as a self-renewal biomarker. A ferulic acid treatment was the highest AP⁺ staining in hop-hit screening compounds. Also a ferulic acid increased Nanog mRNA levels in ESCs. The in vivo effects of ferulic acid were next examined in an obese mouse model. C57BL/6 J male mice were fed either a high fat diet (HFD) or control diet with ferulic acid (5 g/kg diet) for 8 weeks. Ferulic acid exhibited weight loss and improved glucose homeostasis, lipid profiling, and hepatic steatosis in a HFD-induced mouse model. Next, ADMSCs (Sca-1⁺CD45^-), a hallmark of fat stem cells, were then isolated and quantified from mouse abdominal adipose tissue. A HFD decreased the Sca-1⁺CD45^- cell population of ADMSCs, but HFD-induced obese mice given ferulic acid showed an increased the Sca-1⁺CD45^- cell population of ADMSCs. Moreover, ferulic acid enhanced NANOG mRNA levels in human ADMSCs and its related gene mRNA expression. Overall, this study suggests that ferulic acid preserves self-renewal in ESCs, and contributes to ADMSCs self-renewal and effective weight control in obesity.

Control over single-cell distribution of G1 lengths by WNT governs pluripotency

The link between single-cell variation and population-level fate choices lacks a mechanistic explanation despite extensive observations of gene expression and epigenetic variation among individual cells. Here, we found that single human embryonic stem cells (hESCs) have different and biased differentiation potentials toward either neuroectoderm or mesendoderm depending on their G1 lengths before the onset of differentiation. Single-cell variation in G1 length operates in a dynamic equilibrium that establishes a G1 length probability distribution for a population of hESCs and predicts differentiation outcome toward neuroectoderm or mesendoderm lineages. Although sister stem cells generally share G1 lengths, a variable proportion of cells have asymmetric G1 lengths, which maintains the population dispersion. Environmental Wingless-INT (WNT) levels can control the G1 length distribution, apparently as a means of priming the fate of hESC populations once they undergo differentiation. As a downstream mechanism, global 5-hydroxymethylcytosine levels are regulated by G1 length and thereby link G1 length to differentiation outcomes of hESCs. Overall, our findings suggest that intrapopulation heterogeneity in G1 length underlies the pluripotent differentiation potential of stem cell populations.

The link between single-cell variation and population-level fate choices lacks a mechanistic explanation. This study finds that the duration of the G1 cell cycle phase in stem cells varies within the population, giving rise to a probability distribution of G1 length that is responsive to Wnt signalling and that predicts cells’ differentiation potential upon exit from pluripotency.

Stem Cell Differentiation as a Non-Markov Stochastic Process

Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. This chain of hidden states allows individual cells to record their position on the differentiation trajectory, thereby encoding a simple form of cellular memory. We suggest a statistical mechanics interpretation of these results that distinguishes between functionally distinct cellular “macrostates” and functionally similar molecular “microstates” and propose a model of stem cell differentiation as a non-Markov stochastic process.

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We profile individual stem cells as they differentiate along the neural lineage

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Regulatory network changes and increased cell variability accompany differentiation

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Analysis of dynamics with a hidden Markov model reveals unobserved molecular states

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We propose a model of stem cell differentiation as a non-Markov stochastic process

Id1 Stabilizes Epiblast Identity by Sensing Delays in Nodal Activation and Adjusting the Timing of Differentiation

Controlling responsiveness to prevailing signals is critical for robust transitions between cell states during development. For example, fibroblast growth factor (FGF) drives naive pluripotent cells into extraembryonic lineages before implantation but sustains pluripotency in primed cells of the post-implantation epiblast. Nanog supports pluripotency in naive cells, while Nodal supports pluripotency in primed cells, but the handover from Nanog to Nodal does not proceed seamlessly, opening up the risk of aberrant differentiation if FGF is activated before Nodal. Here, we report that Id1 acts as a sensor to detect delays in Nodal activation after the downregulation of Nanog. Id1 then suppresses FGF activity to delay differentiation. Accordingly, Id1 is not required for naive or primed pluripotency but rather stabilizes epiblast identity during the transition between these states. These findings help explain how development proceeds robustly in the face of imprecise signals and highlight the importance of mechanisms that stabilize cell identity during developmental transitions.

Oscillations of MyoD and Hes1 proteins regulate the maintenance of activated muscle stem cells

Lahmann et al. show that Hes1 controls the balance between proliferation and differentiation of activated muscle stem cells in both developing and regenerating muscle. Hes1 is expressed in an oscillatory manner in activated stem cells, where it drives the oscillatory expression of MyoD.

The balance between proliferation and differentiation of muscle stem cells is tightly controlled, ensuring the maintenance of a cellular pool needed for muscle growth and repair. We demonstrate here that the transcriptional regulator Hes1 controls the balance between proliferation and differentiation of activated muscle stem cells in both developing and regenerating muscle. We observed that Hes1 is expressed in an oscillatory manner in activated stem cells where it drives the oscillatory expression of MyoD. MyoD expression oscillates in activated muscle stem cells from postnatal and adult muscle under various conditions: when the stem cells are dispersed in culture, when they remain associated with single muscle fibers, or when they reside in muscle biopsies. Unstable MyoD oscillations and long periods of sustained MyoD expression are observed in differentiating cells. Ablation of the Hes1 oscillator in stem cells interfered with stable MyoD oscillations and led to prolonged periods of sustained MyoD expression, resulting in increased differentiation propensity. This interfered with the maintenance of activated muscle stem cells, and impaired muscle growth and repair. We conclude that oscillatory MyoD expression allows the cells to remain in an undifferentiated and proliferative state and is required for amplification of the activated stem cell pool.

Machine Learning of Stem Cell Identities From Single-Cell Expression Data via Regulatory Network Archetypes

The molecular regulatory network underlying stem cell pluripotency has been intensively studied, and we now have a reliable ensemble model for the "average" pluripotent cell. However, evidence of significant cell-to-cell variability suggests that the activity of this network varies within individual stem cells, leading to differential processing of environmental signals and variability in cell fates. Here, we adapt a method originally designed for face recognition to infer regulatory network patterns within individual cells from single-cell expression data. Using this method we identify three distinct network configurations in cultured mouse embryonic stem cells-corresponding to naïve and formative pluripotent states and an early primitive endoderm state-and associate these configurations with particular combinations of regulatory network activity archetypes that govern different aspects of the cell's response to environmental stimuli, cell cycle status and core information processing circuitry. These results show how variability in cell identities arise naturally from alterations in underlying regulatory network dynamics and demonstrate how methods from machine learning may be used to better understand single cell biology, and the collective dynamics of cell communities.

Analysis of Cell Lineage Trees by Exact Bayesian Inference Identifies Negative Autoregulation of Nanog in Mouse Embryonic Stem Cells

Many cellular effectors of pluripotency are dynamically regulated. In principle, regulatory mechanisms can be inferred from single-cell observations of effector activity across time. However, rigorous inference techniques suitable for noisy, incomplete, and heterogeneous data are lacking. Here, we introduce stochastic inference on lineage trees (STILT), an algorithm capable of identifying stochastic models that accurately describe the quantitative behavior of cell fate markers observed using time-lapse microscopy data collected from proliferating cell populations. STILT performs exact Bayesian parameter inference and stochastic model selection using a particle-filter-based algorithm. We use STILT to investigate the autoregulation of Nanog, a heterogeneously expressed core pluripotency factor, in mouse embryonic stem cells. STILT rejects the possibility of positive Nanog autoregulation with high confidence; instead, model predictions indicate weak negative feedback. We use STILT for rational experimental design and validate model predictions using novel experimental data. STILT is available for download as an open source framework from http://www.imsb.ethz.ch/research/claassen/Software/stilt---stochastic-inference-on-lineage-trees.html.

A common molecular logic determines embryonic stem cell self-renewal and reprogramming

During differentiation and reprogramming, new cell identities are generated by reconfiguration of gene regulatory networks. Here, we combined automated formal reasoning with experimentation to expose the logic of network activation during induction of naïve pluripotency. We find that a Boolean network architecture defined for maintenance of naïve state embryonic stem cells (ESC) also explains transcription factor behaviour and potency during resetting from primed pluripotency. Computationally identified gene activation trajectories were experimentally substantiated at single‐cell resolution by RT–qPCR. Contingency of factor availability explains the counterintuitive observation that Klf2, which is dispensable for ESC maintenance, is required during resetting. We tested 124 predictions formulated by the dynamic network, finding a predictive accuracy of 77.4%. Finally, we show that this network explains and predicts experimental observations of somatic cell reprogramming. We conclude that a common deterministic program of gene regulation is sufficient to govern maintenance and induction of naïve pluripotency. The tools exemplified here could be broadly applied to delineate dynamic networks underlying cell fate transitions.

Histone Acetyltransferase KAT2A Stabilizes Pluripotency with Control of Transcriptional Heterogeneity

Cell fate transitions in mammalian stem cell systems have often been associated with transcriptional heterogeneity; however, existing data have failed to establish a functional or mechanistic link between the two phenomena. Experiments in unicellular organisms support the notion that transcriptional heterogeneity can be used to facilitate adaptability to environmental changes and have identified conserved chromatin‐associated factors that modulate levels of transcriptional noise. Herein, we show destabilization of pluripotency‐associated gene regulatory networks through increased transcriptional heterogeneity of mouse embryonic stem cells in which paradigmatic histone acetyl‐transferase, and candidate noise modulator, Kat2a (yeast orthologue Gcn5), have been inhibited. Functionally, network destabilization associates with reduced pluripotency and accelerated mesendodermal differentiation, with increased probability of transitions into lineage commitment. Thus, we show evidence of a relationship between transcriptional heterogeneity and cell fate transitions through manipulation of the histone acetylation landscape of mouse embryonic stem cells, suggesting a general principle that could be exploited in other normal and malignant stem cell fate transitions. stem cells2018;36:1828–11

Feedback-mediated signal conversion promotes viral fitness

A fundamental signal-processing problem is how biological systems maintain phenotypic states (i.e., canalization) long after degradation of initial catalyst signals. For example, to efficiently replicate, herpesviruses (e.g., human cytomegalovirus, HCMV) rapidly counteract cell-mediated silencing using transactivators packaged in the tegument of the infecting virion particle. However, the activity of these tegument transactivators is inherently transient-they undergo immediate proteolysis but delayed synthesis-and how transient activation sustains lytic viral gene expression despite cell-mediated silencing is unclear. By constructing a two-color, conditional-feedback HCMV mutant, we find that positive feedback in HCMV's immediate-early 1 (IE1) protein is of sufficient strength to sustain HCMV lytic expression. Single-cell time-lapse imaging and mathematical modeling show that IE1 positive feedback converts transient transactivation signals from tegument pp71 proteins into sustained lytic expression, which is obligate for efficient viral replication, whereas attenuating feedback decreases fitness by promoting a reversible silenced state. Together, these results identify a regulatory mechanism enabling herpesviruses to sustain expression despite transient activation signals-akin to early electronic transistors-and expose a potential target for therapeutic intervention.

Building Principles for Constructing a Mammalian Blastocyst Embryo

The self-organisation of a fertilised egg to form a blastocyst structure, which consists of three distinct cell lineages (trophoblast, epiblast and hypoblast) arranged around an off-centre cavity, is unique to mammals. While the starting point (the zygote) and endpoint (the blastocyst) are similar in all mammals, the intervening events have diverged. This review examines and compares the descriptive and functional data surrounding embryonic gene activation, symmetry-breaking, first and second lineage establishment, and fate commitment in a wide range of mammalian orders. The exquisite detail known from mouse embryogenesis, embryonic stem cell studies and the wealth of recent single cell transcriptomic experiments are used to highlight the building principles underlying early mammalian embryonic development.

Cycling to Meet Fate: Connecting Pluripotency to the Cell Cycle

Pluripotent stem cells are characterized by their high proliferative rates, their ability to self-renew and their potential to differentiate to all the three germ layers. This rapid proliferation is brought about by a highly modified cell cycle that allows the cells to quickly shuttle from DNA synthesis to cell division, by reducing the time spent in the intervening gap phases. Many key regulators that define the somatic cell cycle are either absent or exhibit altered behavior, allowing the pluripotent cell to bypass cell cycle checkpoints typical of somatic cells. Experimental analysis of this modified stem cell cycle has been challenging due to the strong link between rapid proliferation and pluripotency, since perturbations to the cell cycle or pluripotency factors result in differentiation. Despite these hurdles, our understanding of this unique cell cycle has greatly improved over the past decade, in part because of the availability of new technologies that permit the analysis of single cells in heterogeneous populations. This review aims to highlight some of the recent discoveries in this area with a special emphasis on different states of pluripotency. We also discuss the highly interlinked network that connects pluripotency factors and key cell cycle genes and review evidence for how this interdependency may promote the rapid cell cycle. This issue gains translational importance since disruptions in stem cell proliferation and differentiation can impact disorders at opposite ends of a spectrum, from cancer to degenerative disease.

Germline Stem Cell Heterogeneity Supports Homeostasis in Drosophila

Adult and embryonic stem cells exhibit fluctuating gene expression; however, the biological significance of stem cell heterogeneity is not well understood. We show that, in Drosophila, female germline stem cells (GSCs) exhibit heterogeneous expression of a GSC differentiation-promoting factor Regena (Rga). The Drosophila homolog of human SON, dsn, is required to maintain GSC heterogeneity by suppressing sustained high levels of Rga. Reducing the expression of Rga in dsn mutants restores GSC heterogeneity and self-renewal. Thus, GSC heterogeneity is linked to GSC homeostasis.

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Female germline stem cells have heterogeneous Rga expression

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dsn suppresses rga transcription and maintains heterogeneity

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dsn maintains germline stem cells

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Lowering rga restores heterogeneity and suppresses dsn phenotypes

Pluripotency gene network dynamics: System views from parametric analysis

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.

Deconstructing the pluripotency gene regulatory network

Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

Modeling signaling-dependent pluripotency with Boolean logic to predict cell fate transitions

Pluripotent stem cells (PSCs) exist in multiple stable states, each with specific cellular properties and molecular signatures. The mechanisms that maintain pluripotency, or that cause its destabilization to initiate development, are complex and incompletely understood. We have developed a model to predict stabilized PSC gene regulatory network (GRN) states in response to input signals. Our strategy used random asynchronous Boolean simulations (R-ABS) to simulate single-cell fate transitions and strongly connected components (SCCs) strategy to represent population heterogeneity. This framework was applied to a reverse-engineered and curated core GRN for mouse embryonic stem cells (mESCs) and used to simulate cellular responses to combinations of five signaling pathways. Our simulations predicted experimentally verified cell population compositions and input signal combinations controlling specific cell fate transitions. Extending the model to PSC differentiation, we predicted a combination of signaling activators and inhibitors that efficiently and robustly generated a Cdx2⁺Oct4^- cells from naïve mESCs. Overall, this platform provides new strategies to simulate cell fate transitions and the heterogeneity that typically occurs during development and differentiation.

Network Features and Dynamical Landscape of Naive and Primed Pluripotency

Although the broad and unique differentiation potential of pluripotent stem cells relies on a complex transcriptional network centered around Oct4, Sox2, and Nanog, two well-distinct pluripotent states, called "naive" and "primed", have been described in vitro and markedly differ in their developmental potential, their expression profiles, their signaling requirements, and their reciprocal conversion. Aiming to determine the key features that segregate and coordinate these two states, data-driven optimization of network models is performed to identify relevant parameter regimes and reduce network complexity to its core structure. Decision dynamics of optimized networks is characterized by signal-dependent multistability and strongly asymmetric transitions among naive, primed, and nonpluripotent states. Further model perturbation and reduction approaches reveal that such a dynamical landscape of pluripotency involves a functional partitioning of the regulatory network. Specifically, two overlapping positive feedback modules, Klf4/Esrrb/Nanog and Oct4/Nanog, stabilize the naive or the primed state, respectively. In turn, their incoherent feedforward and negative feedback coupling mediated by the Erk/Gsk3 module is critical for robust segregation and sequential progression between naive and primed states before irreversible exit from pluripotency.

Nanog Expression in Embryonic Stem Cells - An Ideal Model System to Dissect Enhancer Function

Embryonic stem cells (ESCs) are derived from the preimplantation embryo and can differentiate into virtually any other cell type (termed pluripotency), which is governed by lineage specific transcriptions factors (TFs) binding to cis regulatory elements (CREs) to mediate changes in gene expression. The reliance on transcriptional regulation to maintain pluripotency makes ESCs a valuable model to study the role of distal CREs such as enhancers in modulating gene expression to affect cell fate decisions. This review will highlight recent advance on transcriptional enhancers, focusing on studies performed in ESCs. In addition, we argue that the Nanog locus, which encodes for an ESC-critical TF, is particularly informative because it contains multiple co-regulated genes and enhancers in close proximity to one another. The unique landscape at Nanog permits the study of ongoing questions including whether multiple enhancers function additively versus synergistically, determinants of gene specificity, and cell-to-cell variability in gene expression.

An Important Function of Petrosiol E in Inducing the Differentiation of Neuronal Progenitors and in Protecting Them against Oxidative Stress

Insufficient endogenous neurotrophin supply contributes to neurodegeneration. Meanwhile, neuronal injuries are also attributed to oxidative stress upon toxin exposure. Thus, reconstruction neurite extension and antioxidative stress are the potential strategies for ameliorating neuronal injuries. However, there is no well-defined therapeutic developed in this regard. In search of such therapeutics, Petrosiol E is identified here as a potent inducer to guide the differentiation of neuronal progenitor cells. Petrosiol E also considerably promotes embryonic stem cell differentiation into neural ectoderm features. Moreover, Petrosiol E reveals an antioxidant function to protect cells from oxidative stress induced by arsenic. Moreover, the molecular mechanism underlying Petrosiol E-induced neuronal differentiation is uncovered: (a) enhancement of NF-E2-related factor 2 (Nrf 2) activity in driving neuronal differentiation; (b) diminishment of oxidative stress. Petrosiol E activates the mitogen-activated protein kinase and serine/threonine kinase signaling to enhance the activity of Nrf 2. As a result of enhanced Nrf 2 activity, neuronal differentiation is accelerated, and the cellular antioxidation responses are also enforced, even under arsenic-induced neurotoxicity. Together, the combined results unveil a desirable role of Petrosiol E in driving neuronal differentiation and in combating oxidative stress. This study would open an avenue to develop new therapeutics based on Petrosiol compounds to treat neurodegenerative diseases.

Nanog Fluctuations in Embryonic Stem Cells Highlight the Problem of Measurement in Cell Biology

A number of important pluripotency regulators, including the transcription factor Nanog, are observed to fluctuate stochastically in individual embryonic stem cells. By transiently priming cells for commitment to different lineages, these fluctuations are thought to be important to the maintenance of, and exit from, pluripotency. However, because temporal changes in intracellular protein abundances cannot be measured directly in live cells, fluctuations are typically assessed using genetically engineered reporter cell lines that produce a fluorescent signal as a proxy for protein expression. Here, using a combination of mathematical modeling and experiment, we show that there are unforeseen ways in which widely used reporter strategies can systematically disturb the dynamics they are intended to monitor, sometimes giving profoundly misleading results. In the case of Nanog, we show how genetic reporters can compromise the behavior of important pluripotency-sustaining positive feedback loops, and induce a bifurcation in the underlying dynamics that gives rise to heterogeneous Nanog expression patterns in reporter cell lines that are not representative of the wild-type. These findings help explain the range of published observations of Nanog variability and highlight the problem of measurement in live cells.

Nanog Dynamics in Mouse Embryonic Stem Cells: Results from Systems Biology Approaches

Mouse embryonic stem cells (mESCs), derived from the inner cell mass of the blastocyst, are pluripotent stem cells having self-renewal capability and the potential of differentiating into every cell type under the appropriate culture conditions. An increasing number of reports have been published to uncover the molecular mechanisms that orchestrate pluripotency and cell fate specification using combined computational and experimental methodologies. Here, we review recent systems biology approaches to describe the causes and functions of gene expression heterogeneity and complex temporal dynamics of pluripotency markers in mESCs under uniform culture conditions. In particular, we focus on the dynamics of Nanog, a key regulator of the core pluripotency network and of mESC fate. We summarize the strengths and limitations of different experimental and modeling approaches and discuss how various strategies could be used.

Stat3 phosphorylation is required for embryonic stem cells ground state maintenance in 2i culture media

Embryonic stem cells (ES cells) can be maintained its undifferentiated state with feeder cells or LIF, which can activate Jak/Stat3 pathway. Recently, it has been reported a new culture condition comprising serum-free medium with ERK and GSK3β inhibitors (2i) could drive ES cells into a state of pluripotency more like inner cell mass (ICM) in mouse blastocysts called ground state. However, although 2i could sustain ES cells self-renewal, LIF is routinely added. The roles of Stat3 activation are still unclear now. Here we investigated whether Jak/Stat3 might also contribute to the induction of ground state pluripotency. We introduced a lentiviral construct with 7-repeat Stat3-binding sequence to drive Renilla luciferase into ES cells, which can be used as a reporter to detect Stat3 activation by noninvasive bioluminescence imaging. Using this ES cells, we investigated the role of Stat3 activation in ground state maintenance. The results showed that Stat3 could be activated by 2i. Stattic, a chemical inhibitor of Stat3 phosphorylation, could effectively inhibit Stat3 activation in ES cells. When Stat3 activation was suppressed, ground state related genes were down regulated, and ES cells could not be maintained the ground state pluripotency even in 2i medium. All of these results indicate Stat3 activation is required in ground state maintenance.

Noise-processing by signaling networks

Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network’s structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task.

Dormant Pluripotent Cells Emerge during Neural Differentiation of Embryonic Stem Cells in a FoxO3-Dependent Manner

One major concern over the clinical application of embryonic stem cell (ESC)-derived cells is the potentiation of latent tumorigenicity by residual undifferentiated cells. Despite the use of intensive methodological approaches to eliminate residual undifferentiated cells, the properties of these cells remain elusive. Here, we show that under a serum-free neural differentiation condition, residual undifferentiated cells markedly delay progression of their cell cycle without compromising their pluripotency. This dormant pluripotency was maintained during reculture of the cells under a serum-free condition, whereas upon serum stimulation, the cells exited the dormant state and restarted proliferation and differentiation into all three germ layers. Microarray analysis revealed a set of genes that is significantly upregulated in the dormant ESCs compared with their levels of regulation in proliferating ESCs. Among them, we identified the transcription factor Forkhead box O3 (FoxO3) to be an essential regulator of the maintenance of pluripotency in dormant ESCs. Our study demonstrates that the transition into the dormant state endows residual undifferentiated cells with FoxO3-dependent and leukemia inhibitory factor/serum-independent pluripotency.

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.

Computational Tools for Stem Cell Biology

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the past several years, a new subdiscipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate.

Describing the Stem Cell Potency: The Various Methods of Functional Assessment and In silico Diagnostics

Stem cells are defined by their capabilities to self-renew and give rise to various types of differentiated cells depending on their potency. They are classified as pluripotent, multipotent, and unipotent as demonstrated through their potential to generate the variety of cell lineages. While pluripotent stem cells may give rise to all types of cells in an organism, Multipotent and Unipotent stem cells remain restricted to the particular tissue or lineages. The potency of these stem cells can be defined by using a number of functional assays along with the evaluation of various molecular markers. These molecular markers include diagnosis of transcriptional, epigenetic, and metabolic states of stem cells. Many reports are defining the particular set of different functional assays, and molecular marker used to demonstrate the developmental states and functional capacities of stem cells. The careful evaluation of all these methods could help in generating standard identifying procedures/markers for them.

A Dynamic Role of TBX3 in the Pluripotency Circuitry

Pluripotency represents a cell state comprising a fine-tuned pattern of transcription factor activity required for embryonic stem cell (ESC) self-renewal. TBX3 is the earliest expressed member of the T-box transcription factor family and is involved in maintenance and induction of pluripotency. Hence, TBX3 is believed to be a key member of the pluripotency circuitry, with loss of TBX3 coinciding with loss of pluripotency. We report a dynamic expression of TBX3 in vitro and in vivo using genetic reporter tools tracking TBX3 expression in mouse ESCs (mESCs). Low TBX3 levels are associated with reduced pluripotency, resembling the more mature epiblast. Notably, TBX3-low cells maintain the intrinsic capability to switch to a TBX3-high state and vice versa. Additionally, we show TBX3 to be dispensable for induction and maintenance of naive pluripotency as well as for germ cell development. These data highlight novel facets of TBX3 action in mESCs.

Dissecting stem cell differentiation using single cell expression profiling

Many assumptions about the way cells behave are based on analyses of populations. However, it is now widely recognized that even apparently pure populations can display a remarkable level of heterogeneity. This is particularly true in stem cell biology where it hinders our understanding of normal development and the development of strategies for regenerative medicine. Over the past decade technologies facilitating gene expression analysis at the single cell level have become widespread, providing access to rare cell populations and insights into population structure and function. Here we review the contributions of single cell biology to understanding stem cell differentiation so far, both as a new methodology for defining cell types and a tool for understanding the complexities of cellular decision-making.

Zfp281 Coordinates Opposing Functions of Tet1 and Tet2 in Pluripotent States

Pluripotency is increasingly recognized as a spectrum of cell states defined by their growth conditions. Although naive and primed pluripotency states have been characterized molecularly, our understanding of events regulating state acquisition is wanting. Here, we performed comparative RNA sequencing of mouse embryonic stem cells (ESCs) and defined a pluripotent cell fate (PCF) gene signature associated with acquisition of naive and primed pluripotency. We identify Zfp281 as a key transcriptional regulator for primed pluripotency that also functions as a barrier toward achieving naive pluripotency in both mouse and human ESCs. Mechanistically, Zfp281 interacts with Tet1, but not Tet2, and its direct transcriptional target, miR-302/367, to negatively regulate Tet2 expression to establish and maintain primed pluripotency. Conversely, ectopic Tet2 alone, but not Tet1, efficiently reprograms primed cells toward naive pluripotency. Our study reveals a molecular circuitry in which opposing functions of Tet1 and Tet2 control acquisition of alternative pluripotent states.

Single-cell pluripotency regulatory networks

Pluripotent stem cells (PSCs) are a popular model system for investigating development, tissue regeneration, and repair. Although much is known about the molecular mechanisms that regulate the balance between self-renewal and lineage commitment in PSCs, the spatiotemporal integration of responsive signaling pathways with core transcriptional regulatory networks are complex and only partially understood. Moreover, measurements made on populations of cells reveal only average properties of the underlying regulatory networks, obscuring their fine detail. Here, we discuss the reconstruction of regulatory networks in individual cells using novel single-cell transcriptomics and proteomics, in order to expand our understanding of the molecular basis of pluripotency, including the role of cell-cell variability within PSC populations, and ways in which networks may be controlled in order to reliably manipulate cell behavior.

Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self-renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation-specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine.

Nanog RNA-binding proteins YBX1 and ILF3 affect pluripotency of embryonic stem cells

Nanog is a well-known transcription factor that plays a fundamental role in stem cell self-renewal and the maintenance of their pluripotent cell identity. There remains a large data gap with respect to the spectrum of the key pluripotency transcription factors' interaction partners. Limited information is available concerning Nanog-associated RNA-binding proteins (RBPs), and the intrinsic protein-RNA interactions characteristic of the regulatory activities of Nanog. Herein, we used an improved affinity protocol to purify Nanog-interacting RBPs from mouse embryonic stem cells (ESCs), and 49 RBPs of Nanog were identified. Among them, the interaction of YBX1 and ILF3 with Nanog mRNA was further confirmed by in vitro assays, such as Western blot, RNA immunoprecipitation (RIP), and ex vivo methods, such as immunofluorescence staining and fluorescent in situ hybridization (FISH), MS2 in vivo biotin-tagged RNA affinity purification (MS2-BioTRAP). Interestingly, RNAi studies revealed that YBX1 and ILF3 positively affected the expression of Nanog and other pluripotency-related genes. Particularly, downregulation of YBX1 or ILF3 resulted in high expression of mesoderm markers. Thus, a reduction in the expression of YBX1 and ILF3 controls the expression of pluripotency-related genes in ESCs, suggesting their roles in further regulation of the pluripotent state of ESCs.

A Myc-driven self-reinforcing regulatory network maintains mouse embryonic stem cell identity

Stem cell identity depends on the integration of extrinsic and intrinsic signals, which directly influence the maintenance of their epigenetic state. Although Myc transcription factors play a major role in stem cell self-renewal and pluripotency, their integration with signalling pathways and epigenetic regulators remains poorly defined. We addressed this point by profiling the gene expression and epigenetic pattern in ESCs whose growth depends on conditional Myc activity. Here we show that Myc potentiates the Wnt/β-catenin signalling pathway, which cooperates with the transcriptional regulatory network in sustaining ESC self-renewal. Myc activation results in the transcriptional repression of Wnt antagonists through the direct recruitment of PRC2 on these targets. The consequent potentiation of the autocrine Wnt/β-catenin signalling induces the transcriptional activation of the endogenous Myc family members, which in turn activates a Myc-driven self-reinforcing circuit. Thus, our data unravel a Myc-dependent self-propagating epigenetic memory in the maintenance of ESC self-renewal capacity.

The Myc transcription factor is a major regulator of stem cell (SC) self-renewal and pluripotency but how this integrates signals from other pathways is unclear. Here, the authors show that Myc activation triggers epigenetic memory in self renewing embryonic SCs via PRC2-mediated potentiation of the Wnt pathway.