Asymmetry of stem cell fate and the potential impact of the niche: observations, simulations, and interpretations

Dynamically adjusted cell fate decisions and resilience to mutant invasion during steady-state hematopoiesis revealed by an experimentally parameterized mathematical model

A major next step in hematopoietic stem cell (HSC) biology is to enhance our quantitative understanding of cellular and evolutionary dynamics involved in undisturbed hematopoiesis. Mathematical models have been and continue to be key in this respect, and are most powerful when parameterized experimentally and containing sufficient biological complexity. In this paper, we use data from label propagation experiments in mice to parameterize a mathematical model of hematopoiesis that includes homeostatic control mechanisms as well as clonal evolution. We find that nonlinear feedback control can drastically change the interpretation of kinetic estimates at homeostasis. This suggests that short-term HSC and multipotent progenitors can dynamically adjust to sustain themselves temporarily in the absence of long-term HSCs, even if they differentiate more often than they self-renew in undisturbed homeostasis. Additionally, the presence of feedback control in the model renders the system resilient against mutant invasion. Invasion barriers, however, can be overcome by a combination of age-related changes in stem cell differentiation and evolutionary niche construction dynamics based on a mutant-associated inflammatory environment. This helps us understand the evolution of e.g., TET2 or DNMT3A mutants, and how to potentially reduce mutant burden.

Phenotypic variation modulates the growth dynamics and response to radiotherapy of solid tumours under normoxia and hypoxia

In cancer, treatment failure and disease recurrence have been associated with small subpopulations of cancer cells with a stem-like phenotype. In this paper, we develop and investigate a phenotype-structured model of solid tumour growth in which cells are structured by a stemness level, which varies continuously between stem-like and terminally differentiated behaviours. Cell evolution is driven by proliferation and death, as well as advection and diffusion with respect to the stemness structure variable. Here, the magnitude and sign of the advective flux are allowed to vary with the oxygen level. We use the model to investigate how the environment, in particular oxygen levels, affects the tumour's population dynamics and composition, and its response to radiotherapy. We use a combination of numerical and analytical techniques to quantify how under physiological oxygen levels the cells evolve to a differentiated phenotype and under low oxygen level (i.e., hypoxia) they de-differentiate. Under normoxia, the proportion of cancer stem cells is typically negligible and the tumour may ultimately become extinct whereas under hypoxia cancer stem cells comprise a dominant proportion of the tumour volume, enhancing radio-resistance and favouring the tumour's long-term survival. We then investigate how such phenotypic heterogeneity impacts the tumour's response to treatment with radiotherapy under normoxia and hypoxia. Of particular interest is establishing how the presence of radio-resistant cancer stem cells can facilitate a tumour's regrowth following radiotherapy. We also use the model to show how radiation-induced changes in tumour oxygen levels can give rise to complex re-growth dynamics. For example, transient periods of hypoxia induced by damage to tumour blood vessels may rescue the cancer cell population from extinction and drive secondary regrowth.

Substrate-dependent control of the chiral orientation of mesenchymal stem cells: image-based quantitative profiling

Stem-cell (SC) chirality or left-right (LR) asymmetry is an essential attribute, observed during tissue regeneration. The ability to control the LR orientation of cells by biophysical manipulation is a promising approach for recapitulating their inherent function. Despite remarkable progress in tissue engineering, the development of LR chirality in SCs has been largely unexplored. Here, we demonstrate the role of substrate stiffness on the LR asymmetry of cultured mesenchymal stem cells (MSCs). We found that MSCs acquired higher asymmetricity when cultured on stiffer PCL/collagen matrices. To confirm cellular asymmetry, different parameters such as the aspect ratio, orientation angle and intensity of polarized proteins (Par) were investigated. The results showed a significant (p < 0.01) difference in the average orientation angle, the cellular aspect ratio, and the expression of actin and Par proteins in MSCs cultured on matrices with different stiffnesses. Furthermore, a Gaussian support-vector machine was applied to classify cells cultured on both (2% and 10% PCL/Collagen) matrices, with a resulting accuracy of 96.2%. To the best of our knowledge, this study is the first that interrelates and quantifies MSC asymmetricity with matrix properties using a simple 2D model.

Optimizing adipogenic transdifferentiation of bovine mesenchymal stem cells: a prominent role of ascorbic acid in FABP4 induction

Adipocyte differentiation of bovine adipose-derived stem cells (ASC) was induced by foetal bovine serum (FBS), biotin, pantothenic acid, insulin, rosiglitazone, dexamethasone and 3-isobutyl-1-methylxanthine, followed by incubation in different media to test the influence of ascorbic acid (AsA), bovine serum lipids (BSL), FBS, glucose and acetic acid on transdifferentiation into functional adipocytes. Moreover, different culture plate coatings (collagen-A, gelatin-A or poly-L-lysine) were tested. The differentiated ASC were subjected to Nile red staining, DAPI staining, immunocytochemistry and quantitative reverse transcription PCR (for NT5E, THY1, ENG, PDGFRα, FABP4, PPARγ, LPL, FAS, GLUT4). Nile red quantification showed a significant increase in the development of lipid droplets in treatments with AsA and BSL without FBS. The presence of BSL induced a prominent increase in FABP4 mRNA abundance and in FABP4 immunofluorescence signals in coincubation with AsA. The abundance of NT5E, ENG and THY1 mRNA decreased or tended to decrease in the absence of FBS, and ENG was additionally suppressed by AsA. DAPI fluorescence was higher in cells cultured in poly-L-lysine or gelatin-A coated wells. In additional experiments, the multi-lineage differentiation potential to osteoblasts was verified in medium containing ß-glycerophosphate, dexamethasone and 1,25-dihydroxyvitamin D₃ using alizarin red staining. In conclusion, bovine ASC are capable of multi-lineage differentiation. Poly-L-lysine or gelatin-A coating, the absence of FBS, and the presence of BSL and AsA favour optimal transdifferentiation into adipocytes. AsA supports transdifferentiation via a unique role in FABP4 induction, but this is not linearly related to the primarily BSL-driven lipid accumulation.

Abbreviations: AcA: acetic acid; AsA: ascorbic acid; ASC: adipose-derived stem cells; BSL: bovine serum lipids; DAPI: 4´,6-diamidino-2-phenylindole; DLK: delta like non-canonical notch ligand; DMEM: Dulbecco’s modified Eagle’s medium; DPBS: Dulbecco’s phosphate-buffered saline; ENG: endoglin; FABP: fatty acid binding protein; FAS: fatty acid synthase; GLUT4: glucose transporter type 4; IBMX: 3-isobutyl-1-methylxanthine; LPL: lipoprotein lipase; MSC: mesenchymal stem cells; α-MEM: α minimum essential medium; NT5E: ecto-5ʹ-nucleotidase; PDGFRα: platelet derived growth factor receptor α; PPARγ: peroxisome proliferator activated receptor γ; RPS19: ribosomal protein S19; SEM: standard error of the mean; THY1: Thy-1 cell surface antigen; TRT: treatment; TRT-Con: treatment negative control; YWHAZ: tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta

Awakening the HSC: Dynamic Modeling of HSC Maintenance Unravels Regulation of the TP53 Pathway and Quiescence

Hematopoietic stem cells (HSCs) provide all types of blood cells during the entire life of the organism. HSCs are mainly quiescent and can eventually enter the cell cycle to differentiate. HSCs are maintained and tightly regulated in a particular environment. The stem cell niche regulates dormancy and awakening. Deregulations of this interplay can lead to hematopoietic failure and diseases. In this paper, we present a Boolean network model that recapitulates HSC regulation in virtue of external signals coming from the niche. This Boolean network integrates and summarizes the current knowledge of HSC regulation and is based on extensive literature research. Furthermore, dynamic simulations suggest a novel systemic regulation of TP53 in homeostasis. Thereby, our model indicates that TP53 activity is balanced depending on external stimulations, engaging a regulatory mechanism involving ROS regulators and RAS activated transcription factors. Finally, we investigated different mouse models and compared them to in silico knockout simulations. Here, the model could recapitulate in vivo observed behaviors and thus sustains our results.

Nov/CCN3 Enhances Cord Blood Engraftment by Rapidly Recruiting Latent Human Stem Cell Activity

Umbilical cord blood (UCB) has had considerable impact in pediatric stem cell transplantation, but its wider use is limited in part by unit size. Long-term ex vivo culture offers one approach to increase engraftment capacity by seeking to expand stem and progenitor cells. Here, we show brief incubation (8 h) of UCB CD34+ cells with the matricellular regulator Nov (CCN3) increases the frequency of serially transplantable hematopoietic stem cells (HSCs) 6-fold. This rapid response suggests recruitment rather than expansion of stem cells; accordingly, in single-cell assays, Nov increases the clonogenicity of phenotypic HSCs without increasing their number through cell division. Recruitment is associated with both metabolic and transcriptional changes, and tracing of cell divisions demonstrates that the increased clonogenic activity resides within the undivided fraction of cells. Harnessing latent stem cell potential through recruitment-based approaches will inform understanding of stem cell state transitions with implications for translation to the clinic.

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NOV rapidly increases the number of functional HSCs in a single cord blood unit

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This is by direct recruitment without expansion or self-renewal ex vivo

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NOV reduces C-MYC and ROS but increases glycolytic enzymes in HSCs

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Manipulating non-dividing stem cells can alter their state and functional potential

Automated Segmentation of Fluorescence Microscopy Images for 3D Cell Detection in human-derived Cardiospheres

The ‘cardiosphere’ is a 3D cluster of cardiac progenitor cells recapitulating a stem cell niche-like microenvironment with a potential for disease and regeneration modelling of the failing human myocardium. In this multicellular 3D context, it is extremely important to decrypt the spatial distribution of cell markers for dissecting the evolution of cellular phenotypes by direct quantification of fluorescent signals in confocal microscopy. In this study, we present a fully automated method, named CARE (‘CARdiosphere Evaluation’), for the segmentation of membranes and cell nuclei in human-derived cardiospheres. The proposed method is tested on twenty 3D-stacks of cardiospheres, for a total of 1160 images. Automatic results are compared with manual annotations and two open-source software designed for fluorescence microscopy. CARE performance was excellent in cardiospheres membrane segmentation and, in cell nuclei detection, the algorithm achieved the same performance as two expert operators. To the best of our knowledge, CARE is the first fully automated algorithm for segmentation inside in vitro 3D cell spheroids, including cardiospheres. The proposed approach will provide, in the future, automated quantitative analysis of markers distribution within the cardiac niche-like environment, enabling predictive associations between cell mechanical stresses and dynamic phenotypic changes.

The cell polarity determinant CDC42 controls division symmetry to block leukemia cell differentiation

As a central regulator of cell polarity, the activity of CDC42 GTPase is tightly controlled in maintaining normal hematopoietic stem and progenitor cell (HSC/P) functions. We found that transformation of HSC/P to acute myeloid leukemia (AML) is associated with increased CDC42 expression and activity in leukemia cells. In a mouse model of AML, the loss of Cdc42 abrogates MLL-AF9-induced AML development. Furthermore, genetic ablation of CDC42 in both murine and human MLL-AF9 (MA9) cells decreased survival and induced differentiation of the clonogenic leukemia-initiating cells. We show that MLL-AF9 leukemia cells maintain cell polarity in the context of elevated Cdc42-guanosine triphosphate activity, similar to nonmalignant, young HSC/Ps. The loss of Cdc42 resulted in a shift to depolarized AML cells that is associated with a decrease in the frequency of symmetric and asymmetric cell divisions producing daughter cells capable of self-renewal. Importantly, we demonstrate that inducible CDC42 suppression in primary human AML cells blocks leukemia progression in a xenograft model. Thus, CDC42 loss suppresses AML cell polarity and division asymmetry, and CDC42 constitutes a useful target to alter leukemia-initiating cell fate for differentiation therapy.

Molecular Programs Underlying Asymmetric Stem Cell Division and Their Disruption in Malignancy

Asymmetric division of stem cells is a highly conserved and tightly regulated process by which a single stem cell produces two unequal daughter cells. One retains its stem cell identity while the other becomes specialized through a differentiation program and loses stem cell properties. Coordinating these events requires control over numerous intra- and extracellular biological processes and signaling networks. In the initial stages, critical events include the compartmentalization of fate determining proteins within the mother cell and their subsequent passage to the appropriate daughter cell in order to direct their destiny. Disturbance of these events results in an altered dynamic of self-renewing and differentiation within the cell population, which is highly relevant to the growth and progression of cancer. Other critical events include proper asymmetric spindle assembly, extrinsic regulation through micro-environmental cues, and non-canonical signaling networks that impact cell division and fate determination. In this review, we discuss mechanisms that maintain the delicate balance of asymmetric cell division in normal tissues and describe the current understanding how some of these mechanisms are deregulated in cancer.

Modeling spatial population dynamics of stem cell lineage in wound healing and cancerogenesis

Modeling the dynamics of cell population in tissues involving stem cell niches allows insight into the control mechanisms of the important wound healing process. It is well known that growth and divisions of stem cells are mainly repressed by niche cells, but can also be activated by signals released from wound. In addition, the proliferation and differentiation among three different types of cell: stem cells (SCs), intermediate progenitor cells (IPCs), and fully differentiated cells (FDCs) in stem cell lineage are under different activation and inhibition controls. We have developed a novel stochastic spatial dynamic model of cells. We can characterize not only overall cell population dynamics, but also details of temporal-spatial relationship of individual cells within a tissue. In our model, the shape, growth, and division of each cell are modeled using a realistic geometric model. Furthermore, the inhibited growth rate, proliferation and differentiation probabilities of individual cells are modeled through feedback loops controlled by secreted factors and wound signals from neighboring cells. With specific proliferation and differentiation probabilities, the actual division type that each cell will take is chosen by a Monte Carlo sampling process. With simulations, we study the effects of different strengths of wound signals to wound healing behaviors. We also study the correlations between chronic wound and cancerogenesis.

Mechanical model of geometric cell and topological algorithm for cell dynamics from single-cell to formation of monolayered tissues with pattern

Geometric and mechanical properties of individual cells and interactions among neighboring cells are the basis of formation of tissue patterns. Understanding the complex interplay of cells is essential for gaining insight into embryogenesis, tissue development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating properties of individual cells as well as detailed description of the dynamic growth process, with all topological changes accounted for. Cell size, shape, and division plane orientation are modeled realistically. In addition, cell birth, cell growth, cell shrinkage, cell death, cell division, cell collision, and cell rearrangements are now fully accounted for. Different models of cell-cell interactions, such as lateral inhibition during the process of growth, can be studied in detail. Cellular pattern formation for monolayered tissues from arbitrary initial conditions, including that of a single cell, can also be studied in detail. Computational efficiency is achieved through the employment of a special data structure that ensures access to neighboring cells in constant time, without additional space requirement. We have successfully generated tissues consisting of more than 20,000 cells starting from 2 cells within 1 hour. We show that our model can be used to study embryogenesis, tissue fusion, and cell apoptosis. We give detailed study of the classical developmental process of bristle formation on the epidermis of D. melanogaster and the fundamental problem of homeostatic size control in epithelial tissues. Simulation results reveal significant roles of solubility of secreted factors in both the bristle formation and the homeostatic control of tissue size. Our method can be used to study broad problems in monolayered tissue formation. Our software is publicly available.

Cancer stem cell division: when the rules of asymmetry are broken

Asymmetric division of stem cells is a highly conserved and tightly regulated process by which a single stem cell produces two daughter cells and simultaneously directs the differential fate of both: one retains its stem cell identity while the other becomes specialized and loses stem cell properties. Coordinating these events requires control over numerous intra- and extracellular biological processes and signaling networks. In the initial stages, critical events include the compartmentalization of fate determining proteins within the mother cell and their subsequent passage to the appropriate daughter cell. Disturbance of these events results in an altered dynamic of self-renewing and differentiation within the cell population, which is highly relevant to the growth and progression of cancer. Other critical events include proper asymmetric spindle assembly, extrinsic regulation through micro-environmental cues, and noncanonical signaling networks that impact cell division and fate determination. In this review, we discuss mechanisms that maintain the delicate balance of asymmetric cell division in normal tissues and describe the current understanding how some of these mechanisms are deregulated in cancer. The universe is asymmetric and I am persuaded that life, as it is known to us, is a direct result of the asymmetry of the universe or of its indirect consequences. The universe is asymmetric. -Louis Pasteur.

Quantification and modeling of stem cell-niche interaction

Adult stem cells persist lifelong in the organism, where they are responsible for tissue homeostasis and repair. It is commonly assumed that their maintenance and function are facilitated in local environments called "stem cell niches." Although there is convincing evidence that a variety of niche components determine stem cell fate, the regulatory details of stem cell-niche interactions are widely unknown. To pave the way for a substantiated discussion of these interactions, we first focus on the stem cells themselves and describe the stem cell defining criteria and their implications. The fate of the cells that fulfill these criteria is regulated by a broad spectrum of factors and regulatory mechanisms. A summary of established components and their action is given exemplary for the hematopoietic system. The complexity resulting from the interplay of various cell types, signaling molecules, and extracellular structures can be boiled down to important key features as exemplified by the presented model of hematopoietic stem cell organization. Although neglecting many details, we show that this and similar models have the power to yield intriguing results as proven by the agreement of the presented model with experimental data and the predictions derived from model simulations. Finally, we will discuss the paradigm of systems biology and give a summary of the techniques that promise to unveil further details of the organization principles of stem cell niches at different levels. The synergistic effect of the described techniques together with the integration of their results into a unified model that allows quantitative evaluation and predictions may lead to a better and more systematic understanding of the most relevant niche elements and their interactions.

Investigating biocomplexity through the agent-based paradigm

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex.

Polymeric biomaterials for stem cell bioengineering

This review covers the application of polymeric materials in stem cell bioengineering. Main emphasis is directed towards current material design concepts that mimic distinct exogenous signals of the stem cell microenvironment. Progress within the field of stem cell-specific biomaterials will be discussed, focusing on pluripotent, hematopoietic, mesenchymal and neural stem cells. The future role of biomaterials will be outlined with possible applications for cell reprogramming and engineering cancer cell microenvironments.

Stem cell niche dynamics: from homeostasis to carcinogenesis

The stem cell microenvironment is involved in regulating the fate of the stem cell with respect to self-renewal, quiescence, and differentiation. Mathematical models are helpful in understanding how key pathways regulate the dynamics of stem cell maintenance and homeostasis. This tight regulation and maintenance of stem cell number is thought to break down during carcinogenesis. As a result, the stem cell niche has become a novel target of cancer therapeutics. Developing a quantitative understanding of the regulatory pathways that guide stem cell behavior will be vital to understanding how these systems change under conditions of stress, inflammation, and cancer initiation. Predictions from mathematical modeling can be used as a clinical tool to guide therapy design. We present a survey of mathematical models used to study stem cell population dynamics and stem cell niche regulation, both in the hematopoietic system and other tissues. Highlighting the quantitative aspects of stem cell biology, we describe compelling questions that can be addressed with modeling. Finally, we discuss experimental systems, most notably Drosophila, that can best be used to validate mathematical predictions.

Mathematical modeling of monoclonal conversion in the colonic crypt

A novel spatial multiscale model of a colonic crypt is described, which couples the cell cycle (including cell division) with the mechanics of cell movement. The model is used to investigate the process of monoclonal conversion under two hypotheses concerning stem cell behavior. Under the first hypothesis, 'stem-ness' is an intrinsic cell property, and the stem cell population is maintained through asymmetric division. Under the second hypothesis, the proliferative behavior of each cell is governed by its microenvironment through a biochemical signalling cue, and all cell division is symmetric. Under each hypothesis, the model is used to run virtual experiments, in which a harmless labeling mutation is bestowed upon a single cell in the crypt and the mutant clonal population is tracked over time to check if and when the crypt becomes monoclonal. It is shown that under the first hypothesis, a stable structured cell population is not possible without some form of population-dependent feedback; in contrast, under the second hypothesis, a stable crypt architecture arises naturally. Through comparison with an existing spatial crypt model and a non-spatial stochastic population model, it is shown that the spatial structure of the crypt has a significant effect on the time scale over which a crypt becomes monoclonal.

Modeling spatial population dynamics of stem cell lineage in tissue growth

Understanding the dynamics of cell population allows insight into the control mechanism of the growth and development of mammalian tissues. It is well known that the proliferation and differentiation among stem cells (SCs), intermediate progenitor cells (IPCs), and fully differentiated cells (FDCs) are under different activation and inhibition controls. Secreted factors in negative feedback loops have already been identified as major elements in regulating the numbers of different cell types and in maintaining the equilibrium of cell populations. We have developed a novel spatial dynamic model of cells. We can characterize not only overall cell population dynamics, but also details of temporal-spatial relationship of individual cells within a tissue. In our model, the shape, growth, and division of each cell are modeled using a realistic geometric model. Furthermore, the inhibited growth rate, proliferation and differentiation probabilities of individual cells are modeled through feedback loops controlled by secreted factors of neighboring cells within a proper diffusion radius. With specific proliferation and differentiation probabilities, the actual division type that each cell will take is chosen by a Monte Carlo sampling process. With simulations we found that with proper strengths of inhibitions to growth and stem cell divisions, the whole tissue is capable of achieving a homeostatic size control. We discuss our findings on control mechanisms of the stability of the tissue development. Our model can be applied to study broad issues on tissue development and pattern formation in stem cell and cancer research.

Towards a quantitative understanding of stem cell-niche interaction: experiments, models, and technologies

Here we report about an interdisciplinary workshop focusing on the effects of the local growth-environment on the regulation of stem cell development. Under the title "Towards a quantitative understanding of stem cell/ niche interaction: Experiments, models, and technologies", 33 experts from eight countries discussed current knowledge, new experimental and theoretical results as well as innovative measurement technologies. Specifically, the workshop addressed the following questions: What defines a stem cell niche? What are functional/regulatory characteristics of stem cell- microenvironment interactions? What experimental systems and technologies for quantifying niche function are available? As a consensus result it was recorded that there is no unique niche architecture across tissues but that there are generic principles of niche organization guaranteeing a proper function of stem cells. This functional aspect, as the major defining criterion, leads to the conclusion that stem cells and their niches need to be considered as an inseparable pair with implications for their experimental assessment: To be able to study any of those two components, the other component has to be accounted for. In this context, a number of classical in vitro assays using co-cultures of stem and stroma cells, but also new, specifically bioengineered culture systems have been discussed with respect to their advantages and disadvantages. Finally, there was a general agreement that the comprehensive understanding of niche-mediated stem cell regulation will, due to the complexity of involved mechanisms, require an interdisciplinary, systems biological approach. In addition to cell and molecular biology, biochemistry, biophysics and bioengineering also bioinformatics and mathematical modeling will play a major role in the future of this field.

Stem cells with neural crest characteristics derived from the bulge region of cultured human hair follicles

In this study, we demonstrate that we can isolate stem cells (SCs) with neural crest characteristics from the bulge area of cultured human hair follicles (HFs). These SCs can proliferate in situ and form spheroid structures attached to the bulge area of HFs, and they express immature neural crest cell markers but not differentiation markers. An expression profiling study showed that they share a similar gene expression pattern with murine skin immature neural crest cells. These human SCs are label-retaining cells and are capable of self-renewal through asymmetric cell division in vitro. They exhibit clonal multipotency that can give rise to myogenic, melanocytic, and neuronal cell lineages after in vitro clonal single cell culture. In addition, these SCs show differentiation potential toward mesenchymal lineages, and they can be differentiated into adipocyte, chondrocyte, and osteocyte lineages. Neuronal differentiation of these cells induces global gene expression changes with a significantly increased expression of neuron-associated genes. Differentiated neuronal cells can persist in mouse brain and retain neuronal differentiation markers. The presence of SCs with neural crest characteristics in HFs may offer new opportunities for the use of these cells in regenerative medicine.

A novel view on stem cell development: analysing the shape of cellular genealogies

OBJECTIVES

The analysis of individual cell fates within a population of stem and progenitor cells is still a major experimental challenge in stem cell biology. However, new monitoring techniques, such as high-resolution time-lapse video microscopy, facilitate tracking and quantitative analysis of single cells and their progeny. Information on cellular development, divisional history and differentiation are naturally comprised into a pedigree-like structure, denoted as cellular genealogy. To extract reliable information concerning effecting variables and control mechanisms underlying cell fate decisions, it is necessary to analyse a large number of cellular genealogies.

MATERIALS AND METHODS

Here, we propose a set of statistical measures that are specifically tailored for the analysis of cellular genealogies. These measures address the degree and symmetry of cellular expansion, as well as occurrence and correlation of characteristic events such as cell death. Furthermore, we discuss two different methods for reconstruction of lineage fate decisions and show their impact on the interpretation of asymmetric developments. In order to illustrate these techniques, and to circumvent the present shortage of available experimental data, we obtain cellular genealogies from a single-cell-based mathematical model of haematopoietic stem cell organization.

RESULTS AND CONCLUSIONS

Based on statistical analysis of cellular genealogies, we conclude that effects of external variables, such as growth conditions, are imprinted in their topology. Moreover, we demonstrate that it is essential to analyse timing of cell fate-specific changes and of occurrence of cell death events in the divisional context in order to understand the mechanisms of lineage commitment.

Noise-driven stem cell and progenitor population dynamics

BACKGROUND

The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states.

METHODOLOGY/PRINCIPAL FINDINGS

We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamics of differentiation and dedifferentiation in promyelocytic precursor cells.

CONCLUSIONS/SIGNIFICANCE

Consequently, state-specific noise modulation by external signals can be instrumental in controlling stem cell and progenitor population dynamics. We propose follow-up experiments for quantifying the imprinting influence of the environment on cellular noise regulation.

Multiway modeling and analysis in stem cell systems biology

Background

Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells.

Results

We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate.

Conclusion

Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.