Reprogramming cell fates: reconciling rarity with robustness

Reprogramming the kidney: a novel approach for regeneration

Nuclear reprogramming has reshaped stem cell science and created new avenues for cell-based therapies. The ability to bestow any given phenotype upon adult cells regardless of their origin is an exciting possibility. How can this powerful tool be harnessed for the treatment of kidney disease? Many approaches, including induced pluripotent stem cell (iPSC) production, direct lineage conversion, and reprogramming to a kidney progenitor, are now possible. Indeed, the generation of iPSC lines from adult kidney-derived cells has been successfully achieved. This, however, is just the beginning of the challenge. This review will discuss the fundamental concepts of transcription factor-based reprogramming in its various forms, highlighting recent advances in the field and how these are applicable to the kidney. The relative merits of each approach will be discussed in the context of what is a realistic and feasible strategy for kidney regeneration via reprogramming.

On the evolution of morphogenetic models: mechano-chemical interactions and an integrated view of cell differentiation, growth, pattern formation and morphogenesis

In the 1950s, embryology was conceptualized as four relatively independent problems: cell differentiation, growth, pattern formation and morphogenesis. The mechanisms underlying the first three traditionally have been viewed as being chemical in nature, whereas those underlying morphogenesis have usually been discussed in terms of mechanics. Often, morphogenesis and its mechanical processes have been regarded as subordinate to chemical ones. However, a growing body of evidence indicates that the biomechanics of cells and tissues affect in striking ways those phenomena often thought of as mainly under the control of cell-cell signalling. This accumulation of data has led to a revival of the mechano-transduction concept in particular, and of complexity in general, causing us now to consider whether we should retain the traditional conceptualization of development. The researchers' semantic preferences for the terms 'patterning', 'pattern formation' or 'morphogenesis' can be used to describe three main 'schools of thought' which emerged in the late 1970s. In the 'molecular school', the term patterning is deeply tied to the positional information concept. In the 'chemical school', the term 'pattern formation' regularly implies reaction-diffusion models. In the 'mechanical school', the term 'morphogenesis' is more frequently used in relation to mechanical instabilities. Major differences among these three schools pertain to the concept of self-organization, and models can be classified as morphostatic or morphodynamic. Various examples illustrate the distorted picture that arises from the distinction among differentiation, growth, pattern formation and morphogenesis, based on the idea that the underlying mechanisms are respectively chemical or mechanical. Emerging quantitative approaches integrate the concepts and methods of complex sciences and emphasize the interplay between hierarchical levels of organization via mechano-chemical interactions. They draw upon recent improvements in mathematical and numerical morphogenetic models and upon considerable progress in collecting new quantitative data. This review highlights a variety of such models, which exhibit important advances, such as hybrid, stochastic and multiscale simulations.

Self-organizing circuitry and emergent computation in mouse embryonic stem cells

Pluripotency is a cellular state of multiple options. Here, we highlight the potential for self-organization to contribute to stem cell fate computation. A new way of considering regulatory circuitry is presented that describes the expression of each transcription factor (TF) as a branching process that propagates through time, interacting and competing with others. In a single cell, the interactions between multiple branching processes generate a collective process called 'critical-like self-organization'. We explain how this phenomenon provides a valid description of whole genome regulatory circuit dynamics. The hypothesis of exploratory stem cell decision-making proposes that critical-like self-organization (also called rapid self-organized criticality) provides the backbone for cell fate computation in regulative embryos and pluripotent stem cells. Unspecific amplification of TF expression is predicted to initiate this self-organizing circuitry, where cascades of gene expression propagate and may interact either synergistically or antagonistically. The emergent and highly dynamic circuitry is affected by various sources of selection pressure, such as the expression of TFs with disproportionate influence over other genes, and extrinsic biological and physical stimuli that differentially modulate particular gene expression cascades. Extrinsic conditions continuously trigger waves of transcription that ripple throughout regulatory networks on multiple spatiotemporal scales, providing the context within which circuitry self-organizes. In this framework, a distinction between instructive and selective mechanisms of fate determination is misleading because it is the 'interference pattern', rather than any single instructing or selecting factor, that is ultimately responsible for computing and directing cell fate. Using this framework, we consider whether the idea of a naïve ground state of pluripotency and that of a fluctuating transcriptome are compatible, and whether a ground state like that captured in vitro could exist in vivo.

Mapping mouse hemangioblast maturation from headfold stages

The mouse posterior primitive streak at neural plate/headfold stages (NP/HF, ~7.5 dpc-8 dpc) represents an optimal window from which hemangioblasts can be isolated. We performed immunohistochemistry on this domain using established monoclonal antibodies for proteins that affect blood and endothelial fates. We demonstrate that HoxB4 and GATA1 are the first set of markers that segregate independently to endothelial or blood populations during NP/HF stages of mouse embryonic development. In a subset of cells, both proteins are co-expressed and immunoreactivities appear mutually excluded within nuclear spaces. We searched for this particular state at later sites of hematopoietic stem cell emergence, viz., the aorta-gonad-mesonephros (AGM) and the fetal liver at 10.5-11.5 dpc, and found that only a rare number of cells displayed this character. Based on this spatial-temporal argument, we propose that the earliest blood progenitors emerge either directly from the epiblast or through segregation within the allantoic core domain (ACD) through reduction of cell adhesion and pSmad1/5 nuclear signaling, followed by a stochastic decision toward a blood or endothelial fate that involves GATA1 and HoxB4, respectively. A third form in which binding distributions are balanced may represent a common condition shared by hemangioblasts and HSCs. We developed a heuristic model of hemangioblast maturation, in part, to be explicit about our assumptions.

Genes at work in random bouts: stochastically discontinuous gene activity makes cell cycle duration and cell fate decisions variable, thus providing for stem cells plasticity

Cell interdivision periods (IDP) in homogenous cell populations vary stochastically. Another aspect of probabilistic cell behavior is randomness in cell differentiation. These features are suggested to result from competing stochastic events of assembly/disassembly of the transcription pre-initiation complex (PIC) at gene promoters. The time needed to assemble a proper PIC from different proteins, which must be numerous enough to make their combination gene specific, may be comparable to the IDP. Nascent mRNA visualization at defined genes and inferences from protein level fluctuations in single cells suggest that some genes do operate in this way. The onset of mRNA production by such genes may miss the time windows provided by the cell cycle, resulting in cells differentiating into those in which the respective mRNAs are either present or absent. This creates a way to generate cell phenotype diversity in multicellular organisms.

Neural regeneration

Regeneration of the nervous system requires either the repair or replacement of nerve cells that have been damaged by injury or disease. While lower organisms possess extensive capacity for neural regeneration, evolutionarily higher organisms including humans are limited in their ability to regenerate nerve cells, posing significant issues for the treatment of injury and disease of the nervous system. This chapter focuses on current approaches for neural regeneration, with a discussion of traditional methods to enhance neural regeneration as well as emerging concepts within the field such as stem cells and cellular reprogramming. Stem cells are defined by their ability to self-renew as well as their ability to differentiate into multiple cell types, and hence can serve as a source for cell replacement of damaged neurons. Traditionally, adult stem cells isolated from the hippocampus and subventricular zone have served as a source of neural stem cells for replacement purposes. With the advancement of pluripotent stem cells, including human embryonic stem cells (hESCs) and human induced pluripotent stem cells (iPSCs), new and exciting approaches for neural cell replacement are being developed. Furthermore, with increased understanding of the human genome and epigenetics, scientists have been successful in the direct genetic reprogramming of somatic cells to a neuronal fate, bypassing the intermediary pluripotent stage. Such breakthroughs have accelerated the timing of production of mature neuronal cell types from a patient-specific somatic cell source such as skin fibroblasts or mononuclear blood cells. While extensive hurdles remain to the translational application of such stem cell and reprogramming strategies, these approaches have revolutionized the field of regenerative biology and have provided innovative approaches for the potential regeneration of the nervous system.

Concise Review: Alchemy of Biology: Generating Desired Cell Types from Abundant and Accessible Cells

A major goal of regenerative medicine is to produce cells to participate in the generation, maintenance, and repair of tissues that are damaged by disease, aging, or trauma, such that function is restored. The establishment of induced pluripotent stem cells, followed by directed differentiation, offers a powerful strategy for producing patient-specific therapies. Given how laborious and lengthy this process can be, the conversion of somatic cells into lineage-specific stem/progenitor cells in one step, without going back to, or through, a pluripotent stage, has opened up tremendous opportunities for regenerative medicine. However, there are a number of obstacles to overcome before these cells can be widely considered for clinical applications. Here, we focus on induced transdifferentiation strategies to convert mature somatic cells to other mature cell types or progenitors, and we summarize the challenges that need to be met if the potential applications of transdifferentiation technology are to be achieved.

The molecular and mathematical basis of Waddington's epigenetic landscape: a framework for post-Darwinian biology?

The Neo-Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo-Darwinism. It needs to incorporate the non-linear, stochastic dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric 'epigenetic landscape', which actually represents the quasi-potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re-wiring of regulatory interactions - offering a link between genetic mutation and sudden, broad evolutionary changes.

Oscillatory protein expression dynamics endows stem cells with robust differentiation potential

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems.

Chromatin remodeling system, cancer stem-like attractors, and cellular reprogramming

The cancer cell attractors theory provides a next-generation understanding of carcinogenesis and natural explanation of punctuated clonal expansions of tumor progression. The impressive notion of atavism of cancer is now updated but more evidence is awaited. Besides, the mechanisms that the ectopic expression of some germline genes result in somatic tumors such as melanoma and brain tumors are emerging but are not well understood. Cancer could be triggered by cells undergoing abnormal cell attractor transitions, and may be reversible with "cyto-education". From mammals to model organisms like Caenorhabditis elegans and Drosophila melanogaster, the versatile Mi-2β/nucleosome remodeling and histone deacetylation complexes along with their functionally related chromatin remodeling complexes (CRCs), i.e., the dREAM/Myb-MuvB complex and Polycomb group complex are likely master regulators of cell attractors. The trajectory that benign cells switch to cancerous could be the reverse of navigation of embryonic cells converging from a series of intermediate transcriptional states to a final adult state, which is supported by gene expression dynamics inspector assays and some cross-species genetic evidence. The involvement of CRCs in locking cancer attractors may help find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cancer cell function in the same way as the normal cells.

Techniques for analysing pattern formation in populations of stem cells and their progeny

Background

To investigate how patterns of cell differentiation are related to underlying intra- and inter-cellular signalling pathways, we use a stochastic individual-based model to simulate pattern formation when stem cells and their progeny are cultured as a monolayer. We assume that the fate of an individual cell is regulated by the signals it receives from neighbouring cells via either diffusive or juxtacrine signalling. We analyse simulated patterns using two different spatial statistical measures that are suited to planar multicellular systems: pair correlation functions (PCFs) and quadrat histograms (QHs).

Results

With a diffusive signalling mechanism, pattern size (revealed by PCFs) is determined by both morphogen decay rate and a sensitivity parameter that determines the degree to which morphogen biases differentiation; high sensitivity and slow decay give rise to large-scale patterns. In contrast, with juxtacrine signalling, high sensitivity produces well-defined patterns over shorter lengthscales. QHs are simpler to compute than PCFs and allow us to distinguish between random differentiation at low sensitivities and patterned states generated at higher sensitivities.

Conclusions

PCFs and QHs together provide an effective means of characterising emergent patterns of differentiation in planar multicellular aggregates.

Systems biology of stem cells: three useful perspectives to help overcome the paradigm of linear pathways

Stem cell behaviours, such as stabilization of the undecided state of pluripotency or multipotency, the priming towards a prospective fate, binary fate decisions and irreversible commitment, must all somehow emerge from a genome-wide gene-regulatory network. Its unfathomable complexity defies the standard mode of explanation that is deeply rooted in molecular biology thinking: the reduction of observables to linear deterministic molecular pathways that are tacitly taken as chains of causation. Such culture of proximate explanation that uses qualitative arguments, simple arrow-arrow schemes or metaphors persists despite the ceaseless accumulation of 'omics' data and the rise of systems biology that now offers precise conceptual tools to explain emergent cell behaviours from gene networks. To facilitate the embrace of the principles of physics and mathematics that underlie such systems and help to bridge the gap between the formal description of theorists and the intuition of experimental biologists, we discuss in qualitative terms three perspectives outside the realm of their familiar linear-deterministic view: (i) state space (ii), high-dimensionality and (iii) heterogeneity. These concepts jointly offer a new vista on stem cell regulation that naturally explains many novel, counterintuitive observations and their inherent inevitability, obviating the need for ad hoc explanations of their existence based on natural selection. Hopefully, this expanded view will stimulate novel experimental designs.

A mathematical model for the reciprocal differentiation of T helper 17 cells and induced regulatory T cells

The reciprocal differentiation of T helper 17 (T_H17) cells and induced regulatory T (iT_reg) cells plays a critical role in both the pathogenesis and resolution of diverse human inflammatory diseases. Although initial studies suggested a stable commitment to either the T_H17 or the iT_reg lineage, recent results reveal remarkable plasticity and heterogeneity, reflected in the capacity of differentiated effectors cells to be reprogrammed among T_H17 and iT_reg lineages and the intriguing phenomenon that a group of naïve precursor CD4⁺ T cells can be programmed into phenotypically diverse populations by the same differentiation signal, transforming growth factor beta. To reconcile these observations, we have built a mathematical model of T_H17/iT_reg differentiation that exhibits four different stable steady states, governed by pitchfork bifurcations with certain degrees of broken symmetry. According to the model, a group of precursor cells with some small cell-to-cell variability can differentiate into phenotypically distinct subsets of cells, which exhibit distinct levels of the master transcription-factor regulators for the two T cell lineages. A dynamical control system with these properties is flexible enough to be steered down alternative pathways by polarizing signals, such as interleukin-6 and retinoic acid and it may be used by the immune system to generate functionally distinct effector cells in desired fractions in response to a range of differentiation signals. Additionally, the model suggests a quantitative explanation for the phenotype with high expression levels of both master regulators. This phenotype corresponds to a re-stabilized co-expressing state, appearing at a late stage of differentiation, rather than a bipotent precursor state observed under some other circumstances. Our simulations reconcile most published experimental observations and predict novel differentiation states as well as transitions among different phenotypes that have not yet been observed experimentally.

In order to perform complex functions upon pathogenic challenges, the immune system needs to efficiently deploy a repertoire of specialized cells by inducing the differentiation of precursor cells into effector cells. In a critical process of the adaptive immune system, one common type of precursor cell can give rise to both T helper 17 cells and regulatory T cells, which have distinct phenotypes and functions. Recent discoveries have revealed a certain heterogeneity in this reciprocal differentiation system. In particular, treating precursor cells with a single differentiation signal can result in a remarkably diverse population. An understanding of such variable responses is limited by a lack of quantitative models. Our mathematical model of this cell differentiation system reveals how the control system generates phenotypic diversity and how its final state can be regulated by various signals. The model suggests a new quantitative explanation for the scenario in which the master regulators of two different T cell lineages can be highly expressed in a single cell. The model provides a new framework for understanding the dynamic properties of this type of regulatory network and the mechanisms that help to maintain a balance of effector cells during the inflammatory response to infection.

Collective dynamics of gene expression in cell populations

The phenotypic state of the cell is commonly thought to be determined by the set of expressed genes. However, given the apparent complexity of genetic networks, it remains open what processes stabilize a particular phenotypic state. Moreover, it is not clear how unique is the mapping between the vector of expressed genes and the cell's phenotypic state. To gain insight on these issues, we study here the expression dynamics of metabolically essential genes in twin cell populations. We show that two yeast cell populations derived from a single steady-state mother population and exhibiting a similar growth phenotype in response to an environmental challenge, displayed diverse expression patterns of essential genes. The observed diversity in the mean expression between populations could not result from stochastic cell-to-cell variability, which would be averaged out in our large cell populations. Remarkably, within a population, sets of expressed genes exhibited coherent dynamics over many generations. Thus, the emerging gene expression patterns resulted from collective population dynamics. It suggests that in a wide range of biological contexts, gene expression reflects a self-organization process coupled to population-environment dynamics.

A deterministic map of Waddington's epigenetic landscape for cell fate specification

Background

The image of the "epigenetic landscape", with a series of branching valleys and ridges depicting stable cellular states and the barriers between those states, has been a popular visual metaphor for cell lineage specification - especially in light of the recent discovery that terminally differentiated adult cells can be reprogrammed into pluripotent stem cells or into alternative cell lineages. However the question of whether the epigenetic landscape can be mapped out quantitatively to provide a predictive model of cellular differentiation remains largely unanswered.

Results

Here we derive a simple deterministic path-integral quasi-potential, based on the kinetic parameters of a gene network regulating cell fate, and show that this quantity is minimized along a temporal trajectory in the state space of the gene network, thus providing a marker of directionality for cell differentiation processes. We then use the derived quasi-potential as a measure of "elevation" to quantitatively map the epigenetic landscape, on which trajectories flow "downhill" from any location. Stochastic simulations confirm that the elevation of this computed landscape correlates to the likelihood of occurrence of particular cell fates, with well-populated low-lying "valleys" representing stable cellular states and higher "ridges" acting as barriers to transitions between the stable states.

Conclusions

This quantitative map of the epigenetic landscape underlying cell fate choice provides mechanistic insights into the "forces" that direct cellular differentiation in the context of physiological development, as well as during artificially induced cell lineage reprogramming. Our generalized approach to mapping the landscape is applicable to non-gradient gene regulatory systems for which an analytical potential function cannot be derived, and also to high-dimensional gene networks. Rigorous quantification of the gene regulatory circuits that govern cell lineage choice and subsequent mapping of the epigenetic landscape can potentially help identify optimal routes of cell fate reprogramming.

On the intrinsic inevitability of cancer: from foetal to fatal attraction

The cracks in the paradigm of oncogenic mutations and somatic evolution as driving force of tumorigenesis, lucidly exposed by the dynamic heterogeneity of "cancer stem cells" or the diffuse results of cancer genome sequencing projects, indicate the need for a more encompassing theory of cancer that reaches beyond the current proximate explanations based on individual genetic pathways. One such integrative concept, derived from first principles of the dynamics of gene regulatory networks, is that cancerous cell states are attractor states, just like normal cell types are. Here we extend the concept of cancer attractors to illuminate a more profound property of cancer initiation: its inherent inevitability in the light of metazoan evolution. Using Waddington's Epigenetic Landscape as a conceptual aid, for which we present a mathematical and evolutionary foundation, we propose that cancer is intrinsically linked to ontogenesis and phylogenesis. This explanatory rather than enumerating review uses a formal argumentation structure that is atypical in modern experimental biology but may hopefully offer a new coherent perspective to reconcile many conflicts between new findings and the old thinking in the categories of linear oncogenic pathways.

A general model for binary cell fate decision gene circuits with degeneracy: indeterminacy and switch behavior in the absence of cooperativity

Background

The gene regulatory circuit motif in which two opposing fate-determining transcription factors inhibit each other but activate themselves has been used in mathematical models of binary cell fate decisions in multipotent stem or progenitor cells. This simple circuit can generate multistability and explains the symmetric “poised” precursor state in which both factors are present in the cell at equal amounts as well as the resolution of this indeterminate state as the cell commits to either cell fate characterized by an asymmetric expression pattern of the two factors. This establishes the two alternative stable attractors that represent the two fate options. It has been debated whether cooperativity of molecular interactions is necessary to produce such multistability.

Principal Findings

Here we take a general modeling approach and argue that this question is not relevant. We show that non-linearity can arise in two distinct models in which no explicit interaction between the two factors is assumed and that distinct chemical reaction kinetic formalisms can lead to the same (generic) dynamical system form. Moreover, we describe a novel type of bifurcation that produces a degenerate steady state that can explain the metastable state of indeterminacy prior to cell fate decision-making and is consistent with biological observations.

Conclusion

The general model presented here thus offers a novel principle for linking regulatory circuits with the state of indeterminacy characteristic of multipotent (stem) cells.

Medusa structure of the gene regulatory network: dominance of transcription factors in cancer subtype classification

Gene expression profiles consisting of ten thousands of transcripts are used for clustering of tissue, such as tumors, into subtypes, often without considering the underlying reason that the distinct patterns of expression arise because of constraints in the realization of gene expression profiles imposed by the gene regulatory network. The topology of this network has been suggested to consist of a regulatory core of genes represented most prominently by transcription factors (TFs) and microRNAs, that influence the expression of other genes, and of a periphery of 'enslaved' effector genes that are regulated but not regulating. This 'medusa' architecture implies that the core genes are much stronger determinants of the realized gene expression profiles. To test this hypothesis, we examined the clustering of gene expression profiles into known tumor types to quantitatively demonstrate that TFs, and even more pronounced, microRNAs, are much stronger discriminators of tumor type specific gene expression patterns than a same number of randomly selected or metabolic genes. These findings lend support to the hypothesis of a medusa architecture and of the canalizing nature of regulation by microRNAs. They also reveal the degree of freedom for the expression of peripheral genes that are less stringently associated with a tissue type specific global gene expression profile.

Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells.

Quantifying the Waddington landscape and biological paths for development and differentiation

We developed a theoretical framework to prove the existence and quantify the Waddington landscape as well as chreode-biological paths for development and differentiation. The cells can have states with the higher probability ones giving the different cell types. Different cell types correspond to different basins of attractions of the probability landscape. We study how the cells develop from undifferentiated cells to differentiated cells from landscape perspectives. We quantified the Waddington landscape through construction of underlying probability landscape for cell development. We show the developmental process proceeds as moving from undifferentiated to the differentiated basins of attractions. The barrier height of the basins of attractions correlates with the escape time that determines the stability of cell types. We show that the developmental process can be quantitatively described and uncovered by the biological paths on the quantified Waddington landscape from undifferentiated to the differentiated cells. We found the dynamics of the developmental process is controlled by a combination of the gradient and curl force on the landscape. The biological paths often do not follow the steepest descent path on the landscape. The landscape framework also quantifies the possibility of reverse differentiation process such as cell reprogramming from differentiated cells back to the original stem cell. We show that the biological path of reverse differentiation is irreversible and different from the one for differentiation process. We found that the developmental process described by the underlying landscape and the associated biological paths is relatively stable and robust against the influences of environmental perturbations.

Nuclear organization and transcriptional dynamics in Dictyostelium

The Dictyostelium model has a set of features uniquely well-suited to developing our understanding of transcriptional control. The complete Dictyostelium discoideum genome sequence has revealed that many of the molecular components regulating transcription in larger eukaryotes are conserved in Dictyostelium, from transcription factors and chromatin components to the enzymes and signals that regulate them. In addition, the system permits visualization of single gene firing events in living cells, which provides a more detailed view of transcription and its relationships to cell and developmental processes. This review will bring together the available knowledge of the structure and dynamics of the Dictyostelium nucleus and discuss recent transcription imaging studies and their implications for stability and accuracy of cell decisions.

Human bone marrow mesenchymal stem cells: a systematic reappraisal via the genostem experience

Genostem (acronym for "Adult mesenchymal stem cells engineering for connective tissue disorders. From the bench to the bed side") has been an European consortium of 30 teams working together on human bone marrow Mesenchymal Stem Cell (MSC) biological properties and repair capacity. Part of Genostem activity has been dedicated to the study of basic issues on undifferentiated MSCs properties and on signalling pathways leading to the differentiation into 3 of the connective tissue lineages, osteoblastic, chondrocytic and tenocytic. We have evidenced that native bone marrow MSCs and stromal cells, forming the niche of hematopoietic stem cells, were the same cellular entity located abluminally from marrow sinus endothelial cells. We have also shown that culture-amplified, clonogenic and highly-proliferative MSCs were bona fide stem cells, sharing with other stem cell types the major attributes of self-renewal and of multipotential priming to the lineages to which they can differentiate (osteoblasts, chondrocytes, adipocytes and vascular smooth muscle cells/pericytes). Extensive transcription profiling and in vitro and in vivo assays were applied to identify genes involved in differentiation. Thus we have described novel factors implicated in osteogenesis (FHL2, ITGA5, Fgf18), chondrogenesis (FOXO1A) and tenogenesis (Smad8). Another part of Genostem activity has been devoted to studies of the repair capacity of MSCs in animal models, a prerequisite for future clinical trials. We have developed novel scaffolds (chitosan, pharmacologically active microcarriers) useful for the repair of both bone and cartilage. Finally and most importantly, we have shown that locally implanted MSCs effectively repair bone, cartilage and tendon.

[Human mesenchymal stem cell biology]

This brief overview summarises the main characteristics of bone marrow mesenchymal stem cells and of adipose-derived stem cells: methods of obtention, phenotype, differentiation potential, hematopoiesis-supportive (stromal) capacity, and immunosuppressive properties. Two points are discussed in detail: 1) criteria for stemness: multipotency, self-renewal, plasticity, and 2) the repair mechanisms implicated in the different indications of cell therapy using these cells: reconstitution of the tissue functional compartment by repopulation consequent to proliferation and differentiation or reprogrammation, stromal effects by secretion of angiogenic, anti-apoptotic, anti-fibrogenic factors, molecules involved in the regulation of inflammation, etc.

A dynamical model of genetic networks for cell differentiation

A mathematical model is proposed which is able to describe the most important features of cell differentiation, without requiring specific detailed assumptions concerning the interactions which drive the phenomenon. On the contrary, cell differentiation is described here as an emergent property of a generic model of the underlying gene regulatory network, and it can therefore be applied to a variety of different organisms. The model points to a peculiar role of cellular noise in differentiation and leads to non trivial predictions which could be subject to experimental testing. Moreover, a single model proves able to describe several different phenomena observed in various differentiation processes.

Predicting pancreas cell fate decisions and reprogramming with a hierarchical multi-attractor model

Cell fate reprogramming, such as the generation of insulin-producing β cells from other pancreas cells, can be achieved by external modulation of key transcription factors. However, the known gene regulatory interactions that form a complex network with multiple feedback loops make it increasingly difficult to design the cell reprogramming scheme because the linear regulatory pathways as schemes of causal influences upon cell lineages are inadequate for predicting the effect of transcriptional perturbation. However, sufficient information on regulatory networks is usually not available for detailed formal models. Here we demonstrate that by using the qualitatively described regulatory interactions as the basis for a coarse-grained dynamical ODE (ordinary differential equation) based model, it is possible to recapitulate the observed attractors of the exocrine and β, δ, α endocrine cells and to predict which gene perturbation can result in desired lineage reprogramming. Our model indicates that the constraints imposed by the incompletely elucidated regulatory network architecture suffice to build a predictive model for making informed decisions in choosing the set of transcription factors that need to be modulated for fate reprogramming.

Can a system approach help radiobiology?

This paper explores some of the basic considerations entailed in a system approach to radiobiology, which, in contrast to the traditional molecular approach, focuses on the processes that bring about change to the state of the system, in the case of the cell its phenotype. Radiation can be seen as 'stressing' these processes leading to phenotypic transitions independent of the genotype, that is, epigenetic changes. It is argued that, in this context, the physics that traditionally underpins biology is inappropriate and acts to impair the intuition essential to model building.

Bistable cell fate specification as a result of stochastic fluctuations and collective spatial cell behaviour

BACKGROUND

In culture, isogenic mammalian cells typically display enduring phenotypic heterogeneity that arises from fluctuations of gene expression and other intracellular processes. This diversity is not just simple noise but has biological relevance by generating plasticity. Noise driven plasticity was suggested to be a stem cell-specific feature.

RESULTS

Here we show that the phenotypes of proliferating tissue progenitor cells such as primary mononuclear muscle cells can also spontaneously fluctuate between different states characterized by the either high or low expression of the muscle-specific cell surface molecule CD56 and by the corresponding high or low capacity to form myotubes. Although this capacity is a cell-intrinsic property, the cells switch their phenotype under the constraints imposed by the highly heterogeneous microenvironment created by their own collective movement. The resulting heterogeneous cell population is characterized by a dynamic equilibrium between "high CD56" and "low CD56" phenotype cells with distinct spatial distribution. Computer simulations reveal that this complex dynamic is consistent with a context-dependent noise driven bistable model where local microenvironment acts on the cellular state by encouraging the cell to fluctuate between the phenotypes until the low noise state is found.

CONCLUSIONS

These observations suggest that phenotypic fluctuations may be a general feature of any non-terminally differentiated cell. The cellular microenvironment created by the cells themselves contributes actively and continuously to the generation of fluctuations depending on their phenotype. As a result, the cell phenotype is determined by the joint action of the cell-intrinsic fluctuations and by collective cell-to-cell interactions.

Bone marrow mesenchymal stem cells: historical overview and concepts

This review describes the historical emergence of the concept of bone marrow mesenchymal stem cells (MSCs), summarizing data on Wolf and Trentin's hematopoietic inductive microenvironment; Dexter's hematopoiesis-supportive stromal cells; Friedenstein's osteogenic cells; and Pittenger's trilineal osteoblastic, chondrocytic, and adipocytic precursors; to finally introduce the specific bone marrow mesenchymal stem cells with differentiation potential to four lineages (mesenchymal and vascular smooth muscle lineages), and stromal and immunomodulatory capacities. Two points are the object of detailed discussion. The first point envisions the stem cell attributes (multipotentiality, self-renewal, tissue regeneration, population heterogeneity, plasticity, and lineage priming) compared with that of the paradigmatic hematopoietic stem cell. In the second point, we discuss the possible existence of bone marrow cells with greater differentiation potential, eventually pluripotential cells. The latter point raises the issues of cell fusion, reprogramming, or selection under nonstandardized conditions of rare populations of neuroectodermal origin, or of cells that had undergone mesenchymal-to-epithelial transition. In the last section, we review data on MSC senescence and possible malignant transformation secondary to extensive culture, gene transfer of telomerase, or mutations such as leading to Ewing's sarcoma. The set of data leads to the conclusion that bone marrow MSCs constitute a specific adult tissue stem cell population. The multiple characteristics of this stem cell type account for the versatility of the mechanisms of injured tissue repair. Although MSC administration may be extremely useful in a number of clinical applications, their transplantation is not without risks that must not be overlooked when developing cell therapy protocols.

Understanding gene circuits at cell-fate branch points for rational cell reprogramming

Cell-type reprogramming, the artificial induction of a switch of cell lineage and developmental stage, holds great promise for regenerative medicine. However, how does the metazoan body itself 'program' the various cell lineages in the first place? Knowledge of how multipotent cells make cell-fate decisions and commit to a particular lineage is crucial for a rational reprogramming strategy and to avoid trial-and-error approaches in choosing the appropriate set of transcription factors to use. In the past few years, a general principle has emerged in which small gene circuits of cross-inhibition and self-activation govern the decision at branch points of cell development. A formal theoretical treatment of such circuits that deal with their dynamics on the 'epigenetic landscape' could offer some guidance to find the optimal way of cell reprogramming.

Pluripotency and cellular reprogramming: facts, hypotheses, unresolved issues

Direct reprogramming of somatic cells to induced pluripotent stem cells by ectopic expression of defined transcription factors has raised fundamental questions regarding the epigenetic stability of the differentiated cell state. In addition, evidence has accumulated that distinct states of pluripotency can interconvert through the modulation of both cell-intrinsic and exogenous factors. To fully realize the potential of in vitro reprogrammed cells, we need to understand the molecular and epigenetic determinants that convert one cell type into another. Here we review recent advances in this rapidly moving field and emphasize unresolved and controversial questions.

The potential landscape of genetic circuits imposes the arrow of time in stem cell differentiation

Differentiation from a multipotent stem or progenitor state to a mature cell is an essentially irreversible process. The associated changes in gene expression patterns exhibit time-directionality. This "arrow of time" in the collective change of gene expression across multiple stable gene expression patterns (attractors) is not explained by the regulated activation, the suppression of individual genes which are bidirectional molecular processes, or by the standard dynamical models of the underlying gene circuit which only account for local stability of attractors. To capture the global dynamics of this nonequilibrium system and gain insight in the time-asymmetry of state transitions, we computed the quasipotential landscape of the stochastic dynamics of a canonical gene circuit that governs branching cell fate commitment. The potential landscape reveals the global dynamics and permits the calculation of potential barriers between cell phenotypes imposed by the circuit architecture. The generic asymmetry of barrier heights indicates that the transition from the uncommitted multipotent state to differentiated states is inherently unidirectional. The model agrees with observations and predicts the extreme conditions for reprogramming cells back to the undifferentiated state.

A systems biology strategy on differential gene expression data discloses some biological features of atrial fibrillation

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with extensive structural, contractile, and electrophysiological remodeling. In this manuscript we re-analyzed gene expression data from a microarray experiment on AF patients and control tissues, using a new paradigm based on a posteriori unsupervised strategy in which the discrimination of patients comes out from purely syntactical premises. This paradigm, more adherent to biological reality where genes work in highly connected networks, allowed us to get both a very precise patients/control discrimination and the discovery of cell adhesion/tissue modeling and inflammation processes as the main dimensions of AF.

Tumorigenic WAP-T mouse mammary carcinoma cells: a model for a self-reproducing homeostatic cancer cell system

Background

In analogy to normal stem cell differentiation, the current cancer stem cell (CSC) model presumes a hierarchical organization and an irreversible differentiation in tumor tissue. Accordingly, CSCs should comprise only a small subset of the tumor cells, which feeds tumor growth. However, some recent findings raised doubts on the general applicability of the CSC model and asked for its refinement.

Methodology/Principal Findings

In this study we analyzed the CSC properties of mammary carcinoma cells derived from transgenic (WAP-T) mice. We established a highly tumorigenic WAP-T cell line (G-2 cells) that displays stem-like traits. G-2 cells, as well as their clonal derivates, are closely related to primary tumors regarding histology and gene expression profiles, and reflect heterogeneity regarding their differentiation states. G-2 cultures comprise cell populations in distinct differentiation states identified by co-expression of cytoskeletal proteins (cytokeratins and vimentin), a combination of cell surface markers and a set of transcription factors. Cellular subsets sorted according to expression of CD24a, CD49f, CD61, Epcam, Sca1, and Thy1 cell surface proteins, or metabolic markers (e.g. ALDH activity) are competent to reconstitute the initial cellular composition. Repopulation efficiency greatly varies between individual subsets and is influenced by interactions with the respective complementary G-2 cellular subset. The balance between differentiation states is regulated in part by the transcription factor Sox10, as depletion of Sox10 led to up-regulation of Twist2 and increased the proportion of Thy1-expressing cells representing cells in a self-renewable, reversible, quasi-mesenchymal differentiation state.

Conclusions/Significance

G-2 cells constitute a self-reproducing cancer cell system, maintained by bi- and unidirectional conversion of complementary cellular subsets. Our work contributes to the current controversial discussion on the existence and nature of CSC and provides a basis for the incorporation of alternative hypotheses into the CSC model.

Collective dynamics of specific gene ensembles crucial for neutrophil differentiation: the existence of genome vehicles revealed

Cell fate decision remarkably generates specific cell differentiation path among the multiple possibilities that can arise through the complex interplay of high-dimensional genome activities. The coordinated action of thousands of genes to switch cell fate decision has indicated the existence of stable attractors guiding the process. However, origins of the intracellular mechanisms that create “cellular attractor” still remain unknown. Here, we examined the collective behavior of genome-wide expressions for neutrophil differentiation through two different stimuli, dimethyl sulfoxide (DMSO) and all-trans-retinoic acid (atRA). To overcome the difficulties of dealing with single gene expression noises, we grouped genes into ensembles and analyzed their expression dynamics in correlation space defined by Pearson correlation and mutual information. The standard deviation of correlation distributions of gene ensembles reduces when the ensemble size is increased following the inverse square root law, for both ensembles chosen randomly from whole genome and ranked according to expression variances across time. Choosing the ensemble size of 200 genes, we show the two probability distributions of correlations of randomly selected genes for atRA and DMSO responses overlapped after 48 hours, defining the neutrophil attractor. Next, tracking the ranked ensembles' trajectories, we noticed that only certain, not all, fall into the attractor in a fractal-like manner. The removal of these genome elements from the whole genomes, for both atRA and DMSO responses, destroys the attractor providing evidence for the existence of specific genome elements (named “genome vehicle”) responsible for the neutrophil attractor. Notably, within the genome vehicles, genes with low or moderate expression changes, which are often considered noisy and insignificant, are essential components for the creation of the neutrophil attractor. Further investigations along with our findings might provide a comprehensive mechanistic view of cell fate decision.

Modeling bistable cell-fate choices in the Drosophila eye: qualitative and quantitative perspectives

A major goal of developmental biology is to understand the molecular mechanisms whereby genetic signaling networks establish and maintain distinct cell types within multicellular organisms. Here, we review cell-fate decisions in the developing eye of Drosophila melanogaster and the experimental results that have revealed the topology of the underlying signaling circuitries. We then propose that switch-like network motifs based on positive feedback play a central role in cell-fate choice, and discuss how mathematical modeling can be used to understand and predict the bistable or multistable behavior of such networks.

Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states

Background

The differentiation process, proceeding from stem cells towards the different committed cell types, can be considered as a trajectory towards an attractor of a dynamical process. This view, taking into consideration the transcriptome and miRNome dynamics considered as a whole, instead of looking at few 'master genes' driving the system, offers a novel perspective on this phenomenon. We investigated the 'differentiation trajectories' of the hematopoietic system considering a genome-wide scenario.

Results

We developed serum-free liquid suspension unilineage cultures of cord blood (CB) CD34⁺ hematopoietic progenitor cells through erythroid (E), megakaryocytic (MK), granulocytic (G) and monocytic (Mo) pathways. These cultures recapitulate physiological hematopoiesis, allowing the analysis of almost pure unilineage precursors starting from initial differentiation of HPCs until terminal maturation. By analyzing the expression profile of protein coding genes and microRNAs in unilineage CB E, MK, G and Mo cultures, at sequential stages of differentiation and maturation, we observed a coordinated, fully interconnected and scalable character of cell population behaviour in both transcriptome and miRNome spaces reminiscent of an attractor-like dynamics. MiRNome and transcriptome space differed for a still not terminally committed behaviour of microRNAs.

Conclusions

Consistent with their roles, the transcriptome system can be considered as the state space of a cell population, while the continuously evolving miRNA space corresponds to the tuning system necessary to reach the attractor. The behaviour of miRNA machinery could be of great relevance not only for the promise of reversing the differentiated state but even for tumor biology.

Stem cell plasticity: recapping the decade, mapping the future

In slightly more than a decade of stem cell plasticity research, 24 peer-reviewed articles have demonstrated plasticity across organ and/or embryonic lineage boundaries at the single-cell level, with only 1 article showing negative results. These data, taken together with data about reversibility of gene restrictions that have also accumulated during the same period, indicate that postnatal cells, even "terminally differentiated" ones, have a degree of plasticity not appreciated previously. This review looks back at the four known pathways of cell plasticity and at previously described "plasticity principles" of Genomic Completeness, Cellular Uncertainty, Stochasticity of Cell Origin and Fate, relating these to issues of experimental design and discourse that are key to understanding and evaluating plasticity data. Although the physiologic roles played by such plasticity may still be debated, the manipulations of these phenomena for therapeutic or industrial purposes should finally be considered ripe for exploration. For the future, plasticity, indeed all stem cell biology, must be considered as part of a larger web of cell-to-cell and cell-to-matrix interactions that function fully only at the tissue level; thus, the success of stem cell biology necessarily must involve assembling data from cell and molecular biology research into systems of interactions that might be reasonably called "tissue biology." Interdisciplinary collaborations with complexity and chaos theorists, using mathematical/computer modeling of cell behaviors, will be vital to fully exploring stem cell behaviors in the coming decades.

Zinc-finger nuclease-induced gene repair with oligodeoxynucleotides: wanted and unwanted target locus modifications

Correcting a mutated gene directly at its endogenous locus represents an alternative to gene therapy protocols based on viral vectors with their risk of insertional mutagenesis. When solely a single-stranded oligodeoxynucleotide (ssODN) is used as a repair matrix, the efficiency of the targeted gene correction is low. However, as shown with the homing endonuclease I-SceI, ssODN-mediated gene correction can be enhanced by concomitantly inducing a DNA double-strand break (DSB) close to the mutation. Because I-SceI is hardly adjustable to cut at any desired position in the human genome, here, customizable zinc-finger nucleases (ZFNs) were used to stimulate ssODN-mediated repair of a mutated single-copy reporter locus stably integrated into human embryonic kidney-293 cells. The ZFNs induced faithful gene repair at a frequency of 0.16%. Six times more often, ZFN-induced DSBs were found to be modified by unfaithful addition of ssODN between the termini and about 60 times more often by nonhomologous end joining-related deletions and insertions. Additionally, ZFN off-target activity based on binding mismatch sites at the locus of interest was detected in in vitro cleavage assays and also in chromosomal DNA isolated from treated cells. Therefore, the specificity of ZFN-induced ssODN-mediated gene repair needs to be improved, especially regarding clinical applications.

Towards a dynamical network view of brain ischemia and reperfusion. Part IV: additional considerations

The general failure of neuroprotectants in clinical trials of ischemic stroke points to the possibility of a fundamental blind spot in the current conception of ischemic brain injury, the "ischemic cascade". This is the fourth in a series of four papers whose purpose is to work towards a revision of the concept of brain ischemia by applying network concepts to develop a bistable model of brain ischemia. Here we consider additional issues to round out and close out this initial presentation of the bistable network view of brain ischemia. Initial considerations of the network architecture underlying the post-ischemic state space are discussed. Network and differential equation models of brain ischemia are compared. We offer a first look at applying the bistable model to focal cerebral ischemia. The limitations of the present formulation of the bistable model are discussed. This work concludes with a series of questions by which to direct future efforts.

Towards a dynamical network view of brain ischemia and reperfusion. Part I: background and preliminaries

The general failure of neuroprotectants in clinical trials of ischemic stroke points to the possibility of a fundamental blind spot in the current conception of ischemic brain injury, the "ischemic cascade". This is the first in a series of four papers whose purpose is to work towards a revision of the concept of brain ischemia by applying network concepts to develop a bistable model of brain ischemia. This first paper sets the stage for developing the bistable model of brain ischemia. Necessary background in network theory is introduced using examples from developmental biology which, perhaps surprisingly, can be adapted to brain ischemia with only minor modification. Then, to move towards a network model, we extract two core generalizations about brain ischemia from the mass of empirical data. First, we conclude that all changes induced in the brain by ischemia can be classified as either damage mechanisms that contribute to cell death, or stress responses that contribute to cell survival. Second, we move towards formalizing the idea of the "amount of ischemia", I, as a continuous, nonnegative, monotonically increasing quantity. These two generalizations are necessary precursors to reformulating brain ischemia as a bistable network.

Collective motions and specific effectors: a statistical mechanics perspective on biological regulation

BACKGROUND

The interaction of a multiplicity of scales in both time and space is a fundamental feature of biological systems. The complementation of macroscopic (entire organism) and microscopic (molecular biology) views with a mesoscopic level of analysis able to connect the different planes of investigation is urgently needed. This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.

RESULTS

The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems. Here we show the application of this paradigm to different systems going from yeast metabolism to murine macrophages response to immune stimulation.

CONCLUSIONS

The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

Persistent donor cell gene expression among human induced pluripotent stem cells contributes to differences with human embryonic stem cells

Human induced pluripotent stem cells (hiPSCs) generated by de-differentiation of adult somatic cells offer potential solutions for the ethical issues surrounding human embryonic stem cells (hESCs), as well as their immunologic rejection after cellular transplantation. However, although hiPSCs have been described as “embryonic stem cell-like”, these cells have a distinct gene expression pattern compared to hESCs, making incomplete reprogramming a potential pitfall. It is unclear to what degree the difference in tissue of origin may contribute to these gene expression differences. To answer these important questions, a careful transcriptional profiling analysis is necessary to investigate the exact reprogramming state of hiPSCs, as well as analysis of the impression, if any, of the tissue of origin on the resulting hiPSCs. In this study, we compare the gene profiles of hiPSCs derived from fetal fibroblasts, neonatal fibroblasts, adipose stem cells, and keratinocytes to their corresponding donor cells and hESCs. Our analysis elucidates the overall degree of reprogramming within each hiPSC line, as well as the “distance” between each hiPSC line and its donor cell. We further identify genes that have a similar mode of regulation in hiPSCs and their corresponding donor cells compared to hESCs, allowing us to specify core sets of donor genes that continue to be expressed in each hiPSC line. We report that residual gene expression of the donor cell type contributes significantly to the differences among hiPSCs and hESCs, and adds to the incompleteness in reprogramming. Specifically, our analysis reveals that fetal fibroblast-derived hiPSCs are closer to hESCs, followed by adipose, neonatal fibroblast, and keratinocyte-derived hiPSCs.