Contribution of stochastic partitioning at human embryonic stem cell division to NANOG heterogeneity

Correspondence between multiple signaling and developmental cellular patterns: a computational perspective

The spatial arrangement of variant phenotypes during stem cell division plays a crucial role in the self-organization of cell tissues. The patterns observed in these cellular assemblies, where multiple phenotypes vie for space and resources, are largely influenced by a mixture of different diffusible chemical signals. This complex process is carried out within a chronological framework of interplaying intracellular and intercellular events. This includes receiving external stimulants, whether secreted by other individuals or provided by the environment, interpreting these environmental signals, and incorporating the information to designate cell fate. Here, given two distinct signaling patterns generated by Turing systems, we investigated the spatial distribution of differentiating cells that use these signals as external cues for modifying the production rates. By proposing a computational map, we show that there is a correspondence between the multiple signaling and developmental cellular patterns. In other words, the model provides an appropriate prediction for the final structure of the differentiated cells in a multi-signal, multi-cell environment. Conversely, when a final snapshot of cellular patterns is given, our algorithm can partially identify the signaling patterns that influenced the formation of the cellular structure, provided that the governing dynamic of the signaling patterns is already known.

A dual fluorescence protein expression system detects cell cycle dependent protein noise

Inherently identical cells exhibit significant phenotypic variation. It can be essential for many biological processes and is known to arise from stochastic, 'noisy', gene expression that is determined by intrinsic and extrinsic components. It is now obvious that the noise varies as a function of inducer concentration. However, its fluctuation over the cell cycle is limited. Applying dual colour fluorescence protein reporter system, Cyan Fluorescent Protein (CFP) and Yellow fluorescent protein (YFP) tagged multi-copy plasmids, we determine variation of the noise components over the phases in lac promoter induced by Isopropyl β-D-1-thiogalactopyranoside (IPTG) and in presence of additional Magnesium, Mg2+ ion. We, also, estimate the how such system deviates from observations of single-copy plasmid. Found 25 % difference between multi-copy system and single-copy system clarifies that observed noise is considerable and estimates population behaviour during the cell cycle. We show that total variation in cells induced with IPTG is determined by higher extrinsic than intrinsic noise. It increases from Lag to Exponential phase and decreases from Retardation to Stationary phase. By observing slow and fast dividing cells, we show that 5 mM Mg2+ increases population homogeneity compared to 2.5 mM Mg2+ in the environment. The experimental data obtained using dual colour fluorescence protein reporter system demonstrates that protein expression noise, depending on intra cellular ionic concentration, is tightly controlled by phase of the cell.

A computational model of stem cells' internal mechanism to recapitulate spatial patterning and maintain the self-organized pattern in the homeostasis state

The complex functioning of multi-cellular tissue development relies on proper cell production rates to replace dead or differentiated specialized cells. Stem cells are critical for tissue development and maintenance, as they produce specialized cells to meet the tissues' demands. In this study, we propose a computational model to investigate the stem cell's mechanism, which generates the appropriate proportion of specialized cells, and distributes them to their correct position to form and maintain the organized structure in the population through intercellular reactions. Our computational model focuses on early development, where the populations overall behavior is determined by stem cells and signaling molecules. The model does not include complicated factors such as movement of specialized cells or outside signaling sources. The results indicate that in our model, the stem cells can organize the population into a desired spatial pattern, which demonstrates their ability to self-organize as long as the corresponding leading signal is present. We also investigate the impact of stochasticity, which provides desired non-genetic diversity; however, it can also break the proper boundaries of the desired spatial pattern. We further examine the role of the death rate in maintaining the system's steady state. Overall, our study sheds light on the strategies employed by stem cells to organize specialized cells and maintain proper functionality. Our findings provide insight into the complex mechanisms involved in tissue development and maintenance, which could lead to new approaches in regenerative medicine and tissue engineering.

A computational model of stem cells' decision-making mechanism to maintain tissue homeostasis and organization in the presence of stochasticity

The maintenance of multi-cellular developed tissue depends on the proper cell production rate to replace the cells destroyed by the programmed process of cell death. The stem cell is the main source of producing cells in a developed normal tissue. It makes the stem cell the lead role in the scene of a fully formed developed tissue to fulfill its proper functionality. By focusing on the impact of stochasticity, here, we propose a computational model to reveal the internal mechanism of a stem cell, which generates the right proportion of different types of specialized cells, distribute them into their right position, and in the presence of intercellular reactions, maintain the organized structure in a homeostatic state. The result demonstrates that the spatial pattern could be harassed by the population geometries. Besides, it clearly shows that our model with progenitor cells able to recover the stem cell presence could retrieve the initial pattern appropriately in the case of injury. One of the fascinating outcomes of this project is demonstrating the contradictory roles of stochasticity. It breaks the proper boundaries of the initial spatial pattern in the population. While, on the flip side of the coin, it is the exact factor that provides the demanded non-genetic diversity in the tissue. The remarkable characteristic of the introduced model as the stem cells' internal mechanism is that it could control the overall behavior of the population without need for any external factors.

Inter- and Intrapopulational Heterogeneity of Characteristic Markers in Adult Human Neural Crest-derived Stem Cells

Adult human neural crest-derived stem cells (NCSCs) are found in a variety of adult tissues and show an extraordinary broad developmental potential. Despite their great differentiation capacity, increasing evidence suggest a remaining niche-dependent variability between different NCSC-populations regarding their differentiation behavior and expression signatures. In the present study, we extended the view on heterogeneity of NCSCs by identifying heterogeneous expression levels and protein amounts of characteristic markers even between NCSCs from the same niche of origin. In particular, populations of neural crest-derived inferior turbinate stem cells (ITSCs) isolated from different individuals showed significant variations in characteristic NCSC marker proteins Nestin, S100 and Slug in a donor-dependent manner. Notably, increased nuclear protein amounts of Slug were accompanied by a significantly elevated level of nuclear NF-κB-p65 protein, suggesting an NF-κB-dependent regulation of NCSC-makers. In addition to this interpopulational genetic heterogeneity of ITSC-populations from different donors, single ITSCs also revealed a strong heterogeneity regarding the protein amounts of Nestin, S100, Slug and NF-κB-p65 even within the same clonal culture. Our present findings therefor strongly suggest ITSC-heterogeneity to be at least partly based on an interpopulational genetic heterogeneity dependent on the donor accompanied by a stochastic intrapopulational heterogeneity between single cells. We propose this stochastic intrapopulational heterogeneity to occur in addition to the already described genetic variability between clonal NCSC-cultures and the niche-dependent plasticity of NCSCs. Our observations offer a novel perspective on NCSC-heterogeneity, which may build the basis to understand heterogeneous NCSC-behavior.

Between Fate Choice and Self-Renewal-Heterogeneity of Adult Neural Crest-Derived Stem Cells

Stem cells of the neural crest (NC) vitally participate to embryonic development, but also remain in distinct niches as quiescent neural crest-derived stem cell (NCSC) pools into adulthood. Although NCSC-populations share a high capacity for self-renewal and differentiation resulting in promising preclinical applications within the last two decades, inter- and intrapopulational differences exist in terms of their expression signatures and regenerative capability. Differentiation and self-renewal of stem cells in developmental and regenerative contexts are partially regulated by the niche or culture condition and further influenced by single cell decision processes, making cell-to-cell variation and heterogeneity critical for understanding adult stem cell populations. The present review summarizes current knowledge of the cellular heterogeneity within NCSC-populations located in distinct craniofacial and trunk niches including the nasal cavity, olfactory bulb, oral tissues or skin. We shed light on the impact of intrapopulational heterogeneity on fate specifications and plasticity of NCSCs in their niches in vivo as well as during in vitro culture. We further discuss underlying molecular regulators determining fate specifications of NCSCs, suggesting a regulatory network including NF-κB and NC-related transcription factors like SLUG and SOX9 accompanied by Wnt- and MAPK-signaling to orchestrate NCSC stemness and differentiation. In summary, adult NCSCs show a broad heterogeneity on the level of the donor and the donors' sex, the cell population and the single stem cell directly impacting their differentiation capability and fate choices in vivo and in vitro. The findings discussed here emphasize heterogeneity of NCSCs as a crucial parameter for understanding their role in tissue homeostasis and regeneration and for improving their applicability in regenerative medicine.

OCT4 expression in human embryonic stem cells: spatio-temporal dynamics and fate transitions

The improved in vitro regulation of human embryonic stem cell (hESC) pluripotency and differentiation trajectories is required for their promising clinical applications. The temporal and spatial quantification of the molecular interactions controlling pluripotency is also necessary for the development of successful mathematical and computational models. Here we use time-lapse experimental data of OCT4-mCherry fluorescence intensity to quantify the temporal and spatial dynamics of the pluripotency transcription factor OCT4 in a growing hESC colony in the presence and absence of BMP4. We characterise the internal self-regulation of OCT4 using the Hurst exponent and autocorrelation analysis, quantify the intra-cellular fluctuations and consider the diffusive nature of OCT4 evolution for individual cells and pairs of their descendants. We find that OCT4 abundance in the daughter cells fluctuates sub-diffusively, showing anti-persistent self-regulation. We obtain the stationary probability distributions governing hESC transitions amongst the different cell states and establish the times at which pro-fate cells (which later give rise to pluripotent or differentiated cells) cluster in the colony. By quantifying the similarities between the OCT4 expression amongst neighbouring cells, we show that hESCs express similar OCT4 to cells within their local neighbourhood within the first two days of the experiment and before BMP4 treatment. Our framework allows us to quantify the relevant properties of proliferating hESC colonies and the procedure is widely applicable to other transcription factors and cell populations.

A computational model of stem cell molecular mechanism to maintain tissue homeostasis

Stem cells, with their capacity to self-renew and to differentiate to more specialized cell types, play a key role to maintain homeostasis in adult tissues. To investigate how, in the dynamic stochastic environment of a tissue, non-genetic diversity and the precise balance between proliferation and differentiation are achieved, it is necessary to understand the molecular mechanisms of the stem cells in decision making process. By focusing on the impact of stochasticity, we proposed a computational model describing the regulatory circuitry as a tri-stable dynamical system to reveal the mechanism which orchestrate this balance. Our model explains how the distribution of noise in genes, linked to the cell regulatory networks, affects cell decision-making to maintain homeostatic state. The noise effect on tissue homeostasis is achieved by regulating the probability of differentiation and self-renewal through symmetric and/or asymmetric cell divisions. Our model reveals, when mutations due to the replication of DNA in stem cell division, are inevitable, how mutations contribute to either aging gradually or the development of cancer in a short period of time. Furthermore, our model sheds some light on the impact of more complex regulatory networks on the system robustness against perturbations.

Noise-driven cell differentiation and the emergence of spatiotemporal patterns

The emergence of phenotypic diversity in a population of cells and their arrangement in space and time is one of the most fascinating features of living systems. In fact, understanding multicellularity is unthinkable without explaining the proximate and the ultimate causes of cell differentiation in time and space. Simpler forms of cell differentiation can be found in unicellular organisms, such as bacterial biofilm, where reversible cell differentiation results in phenotypically diverse populations. In this manuscript, we attempt to start with the simple case of reversible nongenetic phenotypic to construct a model of differentiation and pattern formation. Our model, which we refer to as noise-driven differentiation (NDD) model, is an attempt to consider the prevalence of noise in biological systems, alongside what is known about genetic switches and signaling, to create a simple model which generates spatiotemporal patterns from bottom-up. Our simulations indicate that the presence of noise in cells can lead to reversible differentiation and the addition of signaling can create spatiotemporal pattern.

Revealing Dynamic Mechanisms of Cell Fate Decisions From Single-Cell Transcriptomic Data

Cell fate decisions play a pivotal role in development, but technologies for dissecting them are limited. We developed a multifunction new method, Topographer, to construct a "quantitative" Waddington's landscape of single-cell transcriptomic data. This method is able to identify complex cell-state transition trajectories and to estimate complex cell-type dynamics characterized by fate and transition probabilities. It also infers both marker gene networks and their dynamic changes as well as dynamic characteristics of transcriptional bursting along the cell-state transition trajectories. Applying this method to single-cell RNA-seq data on the differentiation of primary human myoblasts, we not only identified three known cell types, but also estimated both their fate probabilities and transition probabilities among them. We found that the percent of genes expressed in a bursty manner is significantly higher at (or near) the branch point (~97%) than before or after branch (below 80%), and that both gene-gene and cell-cell correlation degrees are apparently lower near the branch point than away from the branching. Topographer allows revealing of cell fate mechanisms in a coherent way at three scales: cell lineage (macroscopic), gene network (mesoscopic), and gene expression (microscopic).

Intracellular Noise Level Determines Ratio Control Strategy Confined by Speed-Accuracy Trade-off

Robust and precise ratio control of heterogeneous phenotypes within an isogenic population is an essential task, especially in the development and differentiation of a large number of cells such as bacteria, sensory receptors, and blood cells. However, the mechanisms of such ratio control are poorly understood. Here, we employ experimental and mathematical techniques to understand the combined effects of signal induction and gene expression stochasticity on phenotypic multimodality. We identify two strategies to control phenotypic ratios from an initially homogeneous population, suitable roughly to high-noise and low-noise intracellular environments, and we show that both can be used to generate precise fractional differentiation. In noisy gene expression contexts, such as those found in bacteria, induction within the circuit's bistable region is enough to cause noise-induced bimodality within a feasible time frame. However, in less noisy contexts, such as tightly controlled eukaryotic systems, spontaneous state transitions are rare and hence bimodality needs to be induced with a controlled pulse of induction that falls outside the bistable region. Finally, we show that noise levels, system response time, and ratio tuning accuracy impose trade-offs and limitations on both ratio control strategies, which guide the selection of strategy alternatives.

Dynamics of single human embryonic stem cells and their pairs: a quantitative analysis

Numerous biological approaches are available to characterise the mechanisms which govern the formation of human embryonic stem cell (hESC) colonies. To understand how the kinematics of single and pairs of hESCs impact colony formation, we study their mobility characteristics using time-lapse imaging. We perform a detailed statistical analysis of their speed, survival, directionality, distance travelled and diffusivity. We confirm that single and pairs of cells migrate as a diffusive random walk for at least 7 hours of evolution. We show that the presence of Cell Tracer significantly reduces hESC mobility. Our results open the path to employ the theoretical framework of the diffusive random walk for the prognostic modelling and optimisation of the growth of hESC colonies. Indeed, we employ this random walk model to estimate the seeding density required to minimise the occurrence of hESC colonies arising from more than one founder cell and the minimal cell number needed for successful colony formation. Our prognostic model can be extended to investigate the kinematic behaviour of somatic cells emerging from hESC differentiation and to enable its wide application in phenotyping of pluripotent stem cells for large scale stem cell culture expansion and differentiation platforms.

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.

Engineering Xeno-Free Microcarriers with Recombinant Vitronectin, Albumin and UV Irradiation for Human Pluripotent Stem Cell Bioprocessing

The development of platforms for the expansion and directed differentiation of human pluripotent stem cells (hPSCs) in large quantities under xeno-free conditions is a key step toward the realization of envisioned stem cell-based therapies. Microcarrier bioreactors afford great surface-to-volume ratio, scalability and customization with typical densities of 10⁶-10⁷ cells/ml or higher. In this study, a simple and inexpensive method was established for generating microcarriers without animal-derived components. While coating polystyrene beads with vitronectin alone did not support the culture of hPSCs in stirred suspension, the inclusion of recombinant human serum albumin and UV irradiation led to enhanced seeding efficiency and retention while cells grew more than 20-fold per passage for multiple successive passages and without loss of cell pluripotency. Human PSCs expanded on microcarriers were coaxed to tri-lineage differentiation demonstrating that this system can be used for the self-renewal and specification of hPSCs to therapeutically relevant cell types. Such systems will be critical for the envisioned use of stem cells in regenerative medicine and drug discovery.

Contributions of cell growth and biochemical reactions to nongenetic variability of cells

Cell-to-cell variability in the molecular composition of isogenic, steady-state growing cells arises spontaneously from the inherent stochasticity of intracellular biochemical reactions and cell growth. Here, we present a general decomposition of the total variance in the copy number per cell of a particular molecule. It quantifies the individual contributions made by processes associated with cell growth, biochemical reactions, and their control. We decompose the growth contribution further into variance contributions of random partitioning of molecules at cell division, mother-cell heterogeneity, and variation in cell-cycle progression. The contribution made by biochemical reactions is expressed in variance generated by molecule synthesis, degradation, and their regulation. We use this theory to study the influence of different growth and reaction-related processes, such as DNA replication, variable molecule-partitioning probability, and synthesis bursts, on stochastic cell-to-cell variability. Using simulations, we characterize the impact of noise in the generation-time on cell-to-cell variability. This article offers a widely-applicable theory on the influence of biochemical reactions and cellular growth on the phenotypic variability of growing, isogenic cells. The theory aids the design and interpretation of experiments involving single-molecule counting or real-time imaging of fluorescent reporter constructs.

Clonal analysis of individual human embryonic stem cell differentiation patterns in microfluidic cultures

Heterogeneity in the clonal outputs of individual human embryonic stem cells (hESCs) confounds analysis of their properties in studies of bulk populations and how to manipulate them for clinical applications. To circumvent this problem we developed a microfluidic device that supports the robust generation of colonies derived from single ESCs. This microfluidic system contains 160 individually addressable chambers equipped for perfusion culture of individual hESCs that could be shown to match the growth rates, marker expression and colony morphologies obtained in conventional cultures. Use of this microfluidic device to analyze the clonal growth kinetics of multiple individual hESCs induced to differentiation revealed variable shifts in the growth rate, area per cell and expression of OCT4 in the progeny of individual hESCs. Interestingly, low OCT4 expression, a slower growth rate and low nuclear to cytoplasmic ratios were found to be correlated responses. This study demonstrates how microfluidic systems can be used to enable large scale live-cell imaging of isolated hESCs exposed to changing culture conditions, to examine how different aspects of their variable responses are correlated.

Discovery of consensus gene signature and intermodular connectivity defining self-renewal of human embryonic stem cells

Molecular markers defining self-renewing pluripotent embryonic stem cells (ESCs) have been identified by relative comparisons between undifferentiated and differentiated cells. Most of analysis has been done under a specific differentiation condition that may present significantly different molecular changes over others. Therefore, it is currently unclear if there are true consensus markers defining undifferentiated human ESCs (hESCs). To identify a set of key genes consistently altered during differentiation of hESCs regardless of differentiation conditions, we have performed microarray analysis on undifferentiated hESCs (H1 and H9) and differentiated EBs and validated our results using publicly available expression array datasets. We constructed consensus modules by Weighted Gene Coexpression Network Analysis and discovered novel markers that are consistently present in undifferentiated hESCs under various differentiation conditions. We have validated top markers (downregulated: LCK, KLKB1, and SLC7A3; upregulated: RhoJ, Zeb2, and Adam12) upon differentiation. Functional validation analysis of LCK in self-renewal of hESCs using LCK inhibitor or gene silencing with siLCK resulted in a loss of undifferentiation characteristics-morphological change, reduced alkaline phosphatase activity, and pluripotency gene expression, demonstrating a potential functional role of LCK in self-renewal of hESCs. We have designated hESC markers to interactive networks in the genome, identifying possible interacting partners and showing how new markers relate to each other. Furthermore, comparison of these datasets with available datasets from induced pluripotent stem cells (iPSCs) revealed that the level of these newly identified markers was correlated to the establishment of iPSCs, which may imply a potential role of these markers in gaining of cellular potency.

Increased culture density is linked to decelerated proliferation, prolonged G1 phase, and enhanced propensity for differentiation of self-renewing human pluripotent stem cells

Human pluripotent stem cells (hPSCs) display a very short G1 phase and rapid proliferation kinetics. Regulation of the cell cycle, which is linked to pluripotency and differentiation, is dependent on the stem cell environment, particularly on culture density. This link has been so far empirical and central to disparities in the growth rates and fractions of self-renewing hPSCs residing in different cycle phases. In this study, hPSC cycle progression in conjunction with proliferation and differentiation were comprehensively investigated for different culture densities. Cell proliferation decelerated significantly at densities beyond 50×10(4) cells/cm(2). Correspondingly, the G1 fraction increased from 25% up to 60% at densities greater than 40×10(4) cells/cm(2) while still hPSC pluripotency marker expression was maintained. In parallel, expression of the cycle inhibitor CDKN1A (p21) was increased, while that of p27 and p53 did not change significantly. After 4 days of culture in an unconditioned medium, greater heterogeneity was noted in the differentiation outcomes and was limited by reducing the density variation. A quantitative model was constructed for self-renewing and differentiating hPSC ensembles to gain a better understanding of the link between culture density, cycle progression, and stem cell state. Results for multiple hPSC lines and medium types corroborated experimental findings. Media commonly used for maintenance of self-renewing hPSCs exhibited the slowest kinetics of induction of differentiation (kdiff), while BMP4 supplementation led to 14-fold higher kdiff values. Spontaneous differentiation in a growth factor-free medium exhibited the largest variation in outcomes at different densities. In conjunction with the quantitative framework, our findings will facilitate rationalizing the selection of cultivation conditions for the generation of stem cell therapeutics.

Endogenous WNT signaling regulates hPSC-derived neural progenitor cell heterogeneity and specifies their regional identity

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population that is capable of nearly indefinite expansion and subsequent differentiation into the various neuronal and supporting cell types that comprise the CNS. However, current protocols for differentiating NPCs toward neuronal lineages result in a mixture of neurons from various regions of the CNS. In this study, we determined that endogenous WNT signaling is a primary contributor to the heterogeneity observed in NPC cultures and neuronal differentiation. Furthermore, exogenous manipulation of WNT signaling during neural differentiation, through either activation or inhibition, reduces this heterogeneity in NPC cultures, thereby promoting the formation of regionally homogeneous NPC and neuronal cultures. The ability to manipulate WNT signaling to generate regionally specific NPCs and neurons will be useful for studying human neural development and will greatly enhance the translational potential of hPSCs for neural-related therapies.

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Heterogeneous endogenous WNT signaling regulates hPSC-derived neuronal diversity

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Endogenous WNT signaling specifies the regional identity of hPSC-derived neurons

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Exogenous WNT signaling leads to uniform neuronal cultures from hPSCs

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Effects of WNT signaling on neurogenesis are recapitulated in an hPSC-based system

Deterministic and stochastic approaches in the clinical application of mesenchymal stromal cells (MSCs)

Mesenchymal stromal cells (MSCs) have enormous intrinsic clinical value due to their multi-lineage differentiation capacity, support of hemopoiesis, immunoregulation and growth factors/cytokines secretion. MSCs have thus been the object of extensive research for decades. After completion of many pre-clinical and clinical trials, MSC-based therapy is now facing a challenging phase. Several clinical trials have reported moderate, non-durable benefits, which caused initial enthusiasm to wane, and indicated an urgent need to optimize the efficacy of therapeutic, platform-enhancing MSC-based treatment. Recent investigations suggest the presence of multiple in vivo MSC ancestors in a wide range of tissues, which contribute to the heterogeneity of the starting material for the expansion of MSCs. This variability in the MSC culture-initiating cell population, together with the different types of enrichment/isolation and cultivation protocols applied, are hampering progress in the definition of MSC-based therapies. International regulatory statements require a precise risk/benefit analysis, ensuring the safety and efficacy of treatments. GMP validation allows for quality certification, but the prediction of a clinical outcome after MSC-based therapy is correlated not only to the possible morbidity derived by cell production process, but also to the biology of the MSCs themselves, which is highly sensible to unpredictable fluctuation of isolating and culture conditions. Risk exposure and efficacy of MSC-based therapies should be evaluated by pre-clinical studies, but the batch-to-batch variability of the final medicinal product could significantly limit the predictability of these studies. The future success of MSC-based therapies could lie not only in rational optimization of therapeutic strategies, but also in a stochastic approach during the assessment of benefit and risk factors.

β-catenin fluctuates in mouse ESCs and is essential for Nanog-mediated reprogramming of somatic cells to pluripotency

The Wnt/β-catenin pathway and Nanog are key regulators of embryonic stem cell (ESC) pluripotency and the reprogramming of somatic cells. Here, we demonstrate that the repression of Dkk1 by Nanog, which leads indirectly to β-catenin activation, is essential for reprogramming after fusion of ESCs overexpressing Nanog. In addition, β-catenin is necessary in Nanog-dependent conversion of preinduced pluripotent stem cells (pre-iPSCs) into iPSCs. The activation of β-catenin by Nanog causes fluctuations of β-catenin in ESCs cultured in serum plus leukemia inhibitory factor (serum+LIF) medium, in which protein levels of key pluripotency factors are heterogeneous. In 2i+LIF medium, which favors propagation of ESCs in a ground state of pluripotency with many pluripotency genes losing mosaic expression, we show Nanog-independent β-catenin fluctuations. Overall, we demonstrate Nanog and β-catenin cooperation in establishing naive pluripotency during the reprogramming process and their correlated heterogeneity in ESCs primed toward differentiation.

Alginate encapsulation parameters influence the differentiation of microencapsulated embryonic stem cell aggregates

Pluripotent embryonic stem cells (ESCs) have tremendous potential as tools for regenerative medicine and drug discovery, yet the lack of processes to manufacture viable and homogenous cell populations of sufficient numbers limits the clinical translation of current and future cell therapies. Microencapsulation of ESCs within microbeads can shield cells from hydrodynamic shear forces found in bioreactor environments while allowing for sufficient diffusion of nutrients and oxygen through the encapsulation material. Despite initial studies examining alginate microbeads as a platform for stem cell expansion and directed differentiation, the impact of alginate encapsulation parameters on stem cell phenotype has not been thoroughly investigated. Therefore, the objective of this study was to systematically examine the effects of varying alginate compositions on microencapsulated ESC expansion and phenotype. Pre-formed aggregates of murine ESCs were encapsulated in alginate microbeads composed of a high or low ratio of guluronic to mannuronic acid residues (High G and High M, respectively), with and without a poly-L-lysine (PLL) coating, thereby providing four distinct alginate bead compositions for analysis. Encapsulation in all alginate compositions was found to delay differentiation, with encapsulation within High G alginate yielding the least differentiated cell population. The addition of a PLL coating to the High G alginate prevented cell escape from beads for up to 14 days. Furthermore, encapsulation within High M alginate promoted differentiation toward a primitive endoderm phenotype. Taken together, the findings of this study suggest that distinct ESC expansion capacities and differentiation trajectories emerge depending on the alginate composition employed, indicating that encapsulation material physical properties can be used to control stem cell fate.

Facile engineering of xeno-free microcarriers for the scalable cultivation of human pluripotent stem cells in stirred suspension

A prerequisite for the realization of human pluripotent stem cell (hPSC) therapies is the development of bioprocesses for generating clinically relevant quantities of undifferentiated hPSCs and their derivatives under xeno-free conditions. Microcarrier stirred-suspension bioreactors are an appealing modality for the scalable expansion and directed differentiation of hPSCs. Comparative analyses of commercially available microcarriers clearly show the need for developing synthetic substrates supporting the adhesion and growth of hPSCs in three-dimensional cultures under agitation-induced shear. Moreover, the low seeding efficiencies during microcarrier loading with hPSC clusters poses a significant process bottleneck. To that end, a novel protocol was developed increasing hPSC seeding efficiency from 30% to over 80% and substantially shortening the duration of microcarrier loading. Importantly, this method was combined with the engineering of polystyrene microcarriers by surface conjugation of a vitronectin-derived peptide, which was previously shown to support the growth of human embryonic stem cells. Cells proliferated on peptide-conjugated beads in static culture but widespread detachment was observed after exposure to stirring. This prompted additional treatment of the microcarriers with a synthetic polymer commonly used to enhance cell adhesion. hPSCs were successfully cultivated on these microcarriers in stirred suspension vessels for multiple consecutive passages with attachment efficiencies close to 40%. Cultured cells exhibited on average a 24-fold increase in concentration per 6-day passage, over 85% viability, and maintained a normal karyotype and the expression of pluripotency markers such as Nanog, Oct4, and SSEA4. When subjected to spontaneous differentiation in embryoid body cultures or directed differentiation to the three embryonic germ layers, the cells adopted respective fates displaying relevant markers. Lastly, engineered microcarriers were successfully utilized for the expansion and differentiation of hPSCs to mesoderm progeny in stirred suspension vessels. Hence, we demonstrate a strategy for the facile engineering of xeno-free microcarriers for stirred-suspension cultivation of hPSCs. Our findings support the use of microcarrier bioreactors for the scalable, xeno-free propagation and differentiation of human stem cells intended for therapies.

Deconstructing stem cell population heterogeneity: single-cell analysis and modeling approaches

Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives.

Distinct allelic patterns of nanog expression impart embryonic stem cell population heterogeneity

Nanog is a principal pluripotency regulator exhibiting a disperse distribution within stem cell populations in vivo and in vitro. Increasing evidence points to a functional role of Nanog heterogeneity on stem cell fate decisions. Allelic control of Nanog gene expression was reported recently in mouse embryonic stem cells. To better understand how this mode of regulation influences the observed heterogeneity of NANOG in stem cell populations, we assembled a multiscale stochastic population balance equation framework. In addition to allelic control, gene expression noise and random partitioning at cell division were considered. As a result of allelic Nanog expression, the distribution of Nanog exhibited three distinct states but when combined with transcriptional noise the profile became bimodal. Regardless of their allelic expression pattern, initially uniform populations of stem cells gave rise to the same Nanog heterogeneity within ten cell cycles. Depletion of NANOG content in cells switching off both gene alleles was slower than the accumulation of intracellular NANOG after cells turned on at least one of their Nanog gene copies pointing to Nanog state-dependent dynamics. Allelic transcription of Nanog also raises issues regarding the use of stem cell lines with reporter genes knocked in a single allelic locus. Indeed, significant divergence was observed in the reporter and native protein profiles depending on the difference in their half-lives and insertion of the reporter gene in one or both alleles. In stem cell populations with restricted Nanog expression, allelic regulation facilitates the maintenance of fractions of self-renewing cells with sufficient Nanog content to prevent aberrant loss of pluripotency. Our findings underline the role of allelic control of Nanog expression as a prime determinant of stem cell population heterogeneity and warrant further investigation in the contexts of stem cell specification and cell reprogramming.

Nanog is a key factor influencing the decision of a stem cell to remain pluripotent or differentiate. Each embryonic stem cell (ESC) in a population exhibits fluctuating Nanog levels resulting in heterogeneity which affects cell fate specification. The allelic regulation of Nanog was demonstrated recently but its implications on population heterogeneity are unclear. We developed a multiscale population balance equation (PBE) model and compared our results with pertinent experimental studies. Under allelic control the profile of Nanog features three peaks or distinct states. Transcriptional noise causes the distribution to become bimodal as suggested previously. When stem cells carrying a reporter transgene in an allelically regulated locus were examined, we observed non-matching distributions of the endogenous and reporter proteins. This led us to investigate the performance of reporter systems depending on insertion of the transgene in one or both alleles and the protein degradation dynamics. Lastly, our model was employed to address how allelic regulation affects the maintenance of pluripotency in stem cells with a single Nanog allele deletion. A fraction of these cells remains pluripotent while deletion of a single allele does not simply reduce NANOG uniformly for all ESCs but modulates NANOG heterogeneity directly.

Stem cell modeling: From gene networks to cell populations

Despite rapid advances in the field of stem/progenitor cells through experimental studies, relevant modeling approaches have not progressed with a similar pace. Various models have focused on particular aspects of stem cell physiology including gene regulatory networks, gene expression noise and signaling cascades activated by exogenous factors. However, the self-renewal and differentiation of stem cells is driven by the coordinated regulation of events at the subcellular, intercellular and milieu levels. Such events also span multiple time domains from the fast molecular reactions governing gene expression to the slower cell cycle and division. Thus, the development of multiscale computational frameworks for stem cell populations is highly desirable. Multiscale models are expected to aid the design of efficient differentiation strategies and bioprocesses for the generation of therapeutically useful stem cell progeny. Yet, challenges in making these models tractable and pairing those to sufficient experimental data prevent their wide adoption by the stem cell community. Here, we review modeling approaches reported for stem cell populations and associated hurdles.