Cellular responses often involve a transition of cells from one state to another. A transition from a stem cell to differentiated cell state, for example, may occur in response to gene expression changes induced by a transcription factor, or signaling cascades triggered by a hormone or pathogen. Regulatory networks are thought to control such cellular transitions. Thus, many researchers are interested in reconstructing regulatory networks, not only to gain a deeper understanding of cellular transitions, but also with the aim of using networks to predict and potentially manipulate cellular transitions and outcomes. In this review, we highlight approaches to the reconstruction of regulatory networks underlying cellular transitions, with special attention to transcriptional regulatory networks. We describe recent regulatory network reconstructions in a variety of organisms and discuss the success they share in identifying new regulatory components as well as shared relationships and phenotypic outcomes.
The maintenance of pluripotency and specification of cellular lineages during embryonic development are controlled by transcriptional regulatory networks, which coordinate specific sets of genes through both activation and repression. The transcriptional repressor RE1-silencing transcription factor (REST) plays important but distinct regulatory roles in embryonic (ESC) and neural (NSC) stem cells. We investigated how these distinct biological roles are effected at a genomic level. We present integrated, comparative genome- and transcriptome-wide analyses of transcriptional networks governed by REST in mouse ESC and NSC. The REST recruitment profile has dual components: a developmentally independent core that is common to ESC, NSC, and differentiated cells; and a large, ESC-specific set of target genes. In ESC, the REST regulatory network is highly integrated into that of pluripotency factors Oct4-Sox2-Nanog. We propose that an extensive, pluripotency-specific recruitment profile lends REST a key role in the maintenance of the ESC phenotype.
Embryonic stem cells have the unique and defining property of pluripotency: the ability to differentiate into all cell types. Key transcription factors form interconnected gene regulatory networks that control pluripotency and differentiation. Recently, the transcriptional repressor RE1-silencing transcription factor (REST) was implicated in the maintenance of pluripotency. This was surprising, given that REST has long been known as an essential regulator of neurodevelopment. How does REST regulate pluripotency? Does REST have distinct cohorts of binding sites and target genes in different developmental contexts? To address these questions, we made whole-genome maps of REST binding sites in two mouse stem cell types: embryonic (ESC) and neural (NSC) stem cells. These data were compared with each other and with gene expression data from cells in which REST activity was inhibited. The target genes were almost completely distinct in the two cell types. Surprisingly, we found that REST recruitment has two approximately equal components: common sites across all cells and an ESC-specific component. These pluripotency-associated sites are enriched for particular classes of genes, including those mediating the Wnt signaling pathway, which is an essential regulator of pluripotency.
Whole-genome mapping of the essential transcriptional repressor REST reveals distinct binding profiles and diverse roles in embryonic and neural stem cells.
The central nervous system (CNS) is a large network of interconnecting and intercommunicating cells that form functional circuits. Disease and injury of the CNS are prominent features of the healthcare landscape. There is an urgent unmet need to generate therapeutic solutions for CNS disease/injury. To increase our understanding of the CNS we need to generate cellular models that are experimentally tractable. Neural stem cells (NSCs), cells that generate the CNS during embryonic development, have been identified and propagated in vitro. To develop NSCs as a cellular model for the CNS we need to understand more about their genetics and cell biology. In particular, we need to define the mechanisms of self-renewal, proliferation and differentiation—i.e. NSC behavior. The analysis of pluripotency of embryonic stem cells through mapping regulatory networks of transcription factors has proven to be a powerful approach to understanding embryonic development. Here, we discuss the role of transcription factors in NSC behavior.
neural stem cells; transcription factors; self-renewal; proliferation; differentiation
Embryonic stem cells (ESCs) offer a powerful in vitro model to study mechanisms implicated in cell fate decision. Developmental pathways by which pluripotent ESCs become committed to specific lineages are reflected in dynamic changes of signaling and transcriptional programs. However, the mechanisms that govern the regulatory intracellular networks underlying lineage fate decisions and differentiation programs remain poorly understood and differ significantly in different species. In this review we analyze the current understanding of the signaling mechanisms and transcriptional regulation of differentiation of murine and human ESCs into the mesoderm.
Developmental regulatory networks constitute all the interconnections among molecular components that guide embryonic development. Developmental transcriptional regulatory networks are circuits of transcription factors and cis-acting DNA elements that control expression of downstream regulatory and effector genes. Developmental networks comprise functional subnetworks that are deployed sequentially in requisite spatiotemporal patterns. Here we discuss integrative genomics approaches for elucidating transcriptional regulatory networks, with an emphasis on those involved in Drosophila mesoderm development and mammalian embryonic stem cell maintenance and differentiation. As examples of regulatory subnetworks, we consider the transcriptional and signaling regulation of genes that interact to control cell morphology and migration. Finally, we describe integrative experimental and computational strategies for defining the entirety of molecular interactions underlying developmental regulatory networks.
Human embryonic stem cells (hESCs) hold great promise for regenerative medicine because they can undergo unlimited self-renewal and retain the capability to differentiate into all cell types in the body. Although numerous genes/proteins such as Oct4 and Gata6 have been identified to play critical regulatory roles in self-renewal and differentiation of hESC, the majority of the regulators in these cellular processes and more importantly how these regulators co-operate with each other and/or with epigenetic modifications are still largely unknown. We propose here a systematic approach to integrate genomic and epigenomic data for identification of direct regulatory interactions. This approach allows reconstruction of cell-type-specific transcription networks in embryonic stem cells (ESCs) and fibroblasts at an unprecedented scale. Many links in the reconstructed networks coincide with known regulatory interactions or literature evidence. Systems-level analyses of these networks not only uncover novel regulators for pluripotency and differentiation, but also reveal extensive interplays between transcription factor binding and epigenetic modifications. Especially, we observed poised enhancers characterized by both active (H3K4me1) and repressive (H3K27me3) histone marks that contain enriched Oct4- and Suz12-binding sites. The success of such a systems biology approach is further supported by experimental validation of the predicted interactions.
To date, the reconstruction of gene regulatory networks from gene expression data has primarily relied on the correlation between the expression of transcription regulators and that of target genes.
We developed a network reconstruction method based on quantities that are closely related to the biophysical properties of TF-TF interaction, TF-DNA binding and transcriptional activation and repression. The Network-Identifier method utilized a thermodynamic model for gene regulation to infer regulatory relationships from multiple time course gene expression datasets. Applied to five datasets of differentiating embryonic stem cells, Network-Identifier identified a gene regulatory network among 87 transcription regulator genes. This network suggests that Oct4, Sox2 and Klf4 indirectly repress lineage specific differentiation genes by activating transcriptional repressors of Ctbp2, Rest and Mtf2.
Embryonic stem cells are conventionally differentiated by modulating specific growth factors in the cell culture media. Recently the effect of cellular mechanical microenvironment in inducing phenotype specific differentiation has attracted considerable attention. We have shown the possibility of inducing endoderm differentiation by culturing the stem cells on fibrin substrates of specific stiffness . Here, we analyze the regulatory network involved in such mechanically induced endoderm differentiation under two different experimental configurations of 2-dimensional and 3-dimensional culture, respectively. Mouse embryonic stem cells are differentiated on an array of substrates of varying mechanical properties and analyzed for relevant endoderm markers. The experimental data set is further analyzed for identification of co-regulated transcription factors across different substrate conditions using the technique of bi-clustering. Overlapped bi-clusters are identified following an optimization formulation, which is solved using an evolutionary algorithm. While typically such analysis is performed at the mean value of expression data across experimental repeats, the variability of stem cell systems reduces the confidence on such analysis of mean data. Bootstrapping technique is thus integrated with the bi-clustering algorithm to determine sets of robust bi-clusters, which is found to differ significantly from corresponding bi-clusters at the mean data value. Analysis of robust bi-clusters reveals an overall similar network interaction as has been reported for chemically induced endoderm or endodermal organs but with differences in patterning between 2-dimensional and 3-dimensional culture. Such analysis sheds light on the pathway of stem cell differentiation indicating the prospect of the two culture configurations for further maturation.
There has been an immense interest in embryonic stem cells owing to their pluripotent property, which refers to the ability to differentiate into all cell types of an embryo. In the maintenance of this pluripotent nature, transcription factors play essential roles, and signalling pathways also act to sustain the undifferentiated state. Recent studies have unravelled multiple forms of interconnection and crosstalk between these two regulatory aspects of pluripotency. With the discovery of epiblast stem cells, there is an emerging concept that different pluripotent states could exist, and knowledge of both transcriptional networks and signalling pathways has been vital in dissecting the properties of these different states. Similar to classical reprogramming methodologies, various combinations of transcription factor transduction and the modulation of intracellular signalling have enabled the interconversion between pluripotent states. These studies provide an insight into the defining characteristics as well as the plasticity of pluripotent cells.
pluripotency; embryonic stem cell; transcriptional network; signalling pathways; mouse embryonic stem cell-like interconversion
Recent ChIP experiments of human and mouse embryonic stem cells have elucidated the architecture of the transcriptional regulatory circuitry responsible for cell determination, which involves the transcription factors OCT4, SOX2, and NANOG. In addition to regulating each other through feedback loops, these genes also regulate downstream target genes involved in the maintenance and differentiation of embryonic stem cells. A search for the OCT4–SOX2–NANOG network motif in other species reveals that it is unique to mammals. With a kinetic modeling approach, we ascribe function to the observed OCT4–SOX2–NANOG network by making plausible assumptions about the interactions between the transcription factors at the gene promoter binding sites and RNA polymerase (RNAP), at each of the three genes as well as at the target genes. We identify a bistable switch in the network, which arises due to several positive feedback loops, and is switched on/off by input environmental signals. The switch stabilizes the expression levels of the three genes, and through their regulatory roles on the downstream target genes, leads to a binary decision: when OCT4, SOX2, and NANOG are expressed and the switch is on, the self-renewal genes are on and the differentiation genes are off. The opposite holds when the switch is off. The model is extremely robust to parameter changes. In addition to providing a self-consistent picture of the transcriptional circuit, the model generates several predictions. Increasing the binding strength of NANOG to OCT4 and SOX2, or increasing its basal transcriptional rate, leads to an irreversible bistable switch: the switch remains on even when the activating signal is removed. Hence, the stem cell can be manipulated to be self-renewing without the requirement of input signals. We also suggest tests that could discriminate between a variety of feedforward regulation architectures of the target genes by OCT4, SOX2, and NANOG.
One key issue in developmental biology is how embryonic stem cells are regulated at the genetic level. Recent high throughput experiments have elucidated the architecture of the gene regulatory network responsible for embryonic stem cell fate decisions in human and mouse. In this work the authors develop a computational model to describe the mutual regulation of the genes involved in these networks and their subsequent effects on downstream target genes. They find that the core genetic network incorporates the functionality of a bistable switch, which arises due to positive feedback loops in the system. Also, this switch behaviour is very robust with respect to model parameters. The switch and architecture by which the genetic network regulates the downstream genes, is responsible for either maintaining the genes responsible for self-renewal on, and genes involved with differentiation off, or the opposite outcome, depending on whether the switch is on/off, respectively. The model also provides several predictions which can lead to further understanding of the network. The methods employed are fairly standard and transparent which facilitates further uncovering in future experimental investigations of genetic networks.
Genetic programs that govern neural stem/progenitor cell (NSC) proliferation and differentiation are dependent on extracellular cues and a network of transcription factors, which can be regulated posttranslationally by phosphorylation. However, little is known about the kinase-dependent pathways regulating NSC maintenance and oligodendrocyte development. We used a conditional knockout approach to target the murine regulatory subunit (beta) of protein kinase casein kinase 2 (CK2β) in embryonic neural progenitors. Loss of CK2β leads to defects in proliferation and differentiation of embryonic NSCs. We establish CK2β as a key positive regulator for the development of oligodendrocyte precursor cells (OPCs), both in vivo and in vitro. We show that CK2β directly interacts with the basic helix-loop-helix (bHLH) transcription factor Olig2, a critical modulator of OPC development, and activates the CK2-dependent phosphorylation of its serine-threonine-rich (STR) domain. Finally, we reveal that the CK2-targeted STR domain is required for the oligodendroglial function of Olig2. These findings suggest that CK2 may control oligodendrogenesis, in part, by regulating the activity of the lineage-specific transcription factor Olig2. Thus, CK2β appears to play an essential and uncompensated role in central nervous system development.
Embryonic stem cells (ESC) have the capacity to self-renew and remain pluripotent, while continuously providing a source of a variety of differentiated cell types. Understanding what governs these properties at the molecular level is crucial for stem cell biology and its application to regenerative medicine. Of particular relevance is to elucidate those molecular interactions which govern the reprogramming of somatic cells into ESC. A computational approach can be used as a framework to explore the dynamics of a simplified network of the ESC with the aim to understand how stem cells differentiate and also how they can be reprogrammed from somatic cells.
We propose a computational model of the embryonic stem cell network, in which a core set of transcription factors (TFs) interact with each other and are induced by external factors. A stochastic treatment of the network dynamics suggests that NANOG heterogeneity is the deciding factor for the stem cell fate. In particular, our results show that the decision of staying in the ground state or commitment to a differentiated state is fundamentally stochastic, and can be modulated by the addition of external factors (2i/3i media), which have the effect of reducing fluctuations in NANOG expression. Our model also hosts reprogramming of a committed cell into an ESC by over-expressing OCT4. In this context, we recapitulate the important experimental result that reprogramming efficiency peaks when OCT4 is over-expressed within a specific range of values.
We have demonstrated how a stochastic computational model based upon a simplified network of TFs in ESCs can elucidate several key observed dynamical features. It accounts for (i) the observed heterogeneity of key regulators, (ii) characterizes the ESC under certain external stimuli conditions and (iii) describes the occurrence of transitions from the ESC to the differentiated state. Furthermore, the model (iv) provides a framework for reprogramming from somatic cells and conveys an understanding of reprogramming efficiency as a function of OCT4 over-expression.
Stem cells; Heterogeneity; Stochasticity; Computational model; Differentiation; Reprogramming
Gene regulatory networks for development underlie cell fate specification and differentiation. Network topology, logic and dynamics can be obtained by thorough experimental analysis. Our understanding of the gene regulatory network controlling endomesoderm specification in the sea urchin embryo has attained an advanced level such that it explains developmental phenomenology. Here we review how the network explains the mechanisms utilized in development to control the formation of dynamic expression patterns of transcription factors and signaling molecules. The network represents the genomic program controlling timely activation of specification and differentiation genes in the correct embryonic lineages. It can also be used to study evolution of body plans. We demonstrate how comparing the sea urchin gene regulatory network to that of the sea star and to that of later developmental stages in the sea urchin, reveals mechanisms underlying the origin of evolutionary novelty. The experimentally based gene regulatory network for endomesoderm specification in the sea urchin embryo provides unique insights into the system level properties of cell fate specification and its evolution.
gene regulation in development; evolution; systems level properties
Coordinated transcription factor networks have emerged as the master regulatory mechanisms of stem cell pluripotency and differentiation. Many stem cell-specific transcription factors, including the pluripotency transcription factors, OCT4, NANOG, and SOX2 function in combinatorial complexes to regulate the expression of loci, which are involved in embryonic stem (ES) cell pluripotency and cellular differentiation. This review will address how these pathways form a reciprocal regulatory circuit whereby the equilibrium between stem cell self-renewal, proliferation, and differentiation is in perpetual balance. We will discuss how distinct epigenetic repressive pathways involving polycomb complexes, DNA methylation, and microRNAs cooperate to reduce transcriptional noise and to prevent stochastic and aberrant induction of differentiation. We will provide a brief overview of how these networks cooperate to modulate differentiation along hematopoietic and neuronal lineages. Finally, we will describe how aberrant functioning of components of the stem cell regulatory network may contribute to malignant transformation of adult stem cells and the establishment of a “cancer stem cell” phenotype and thereby underlie multiple types of human malignancies.
Recent studies suggest that the hematopoietic and cardiac lineages have close ontogenic origins, and that an early mesodermal cell population has the potential to differentiate into both lineages. Studies also suggest that specification of these lineages is inversely regulated. However, the transcriptional networks that govern the cell fate specification of these progenitors are incompletely defined.
Methods and Results
Here, we show that Nkx2-5 regulates the hematopoietic/erythroid fate of the mesoderm precursors early during cardiac morphogenesis. Utilizing transgenic technologies to isolate Nkx2-5 expressing cells, we observed an induction of the erythroid molecular program, including Gata1, in the Nkx2-5 null embryos. We further observed that overexpression of Nkx2-5 using an Nkx2-5-inducible embryonic stem (ES) cell system significantly repressed Gata1 gene expression and suppressed the hematopoietic/erythroid potential but not the endothelial potential of the ES cells. This suppression was cell-autonomous and was partially rescued by overexpressing Gata1. In addition, we demonstrated that Nkx2-5 binds to the Gata1 gene enhancer and represses the transcriptional activity of the Gata1 gene.
Our results demonstrate that the hematopoietic/erythroid cell fate is suppressed via Nkx2-5 during mesodermal fate determination and that the Gata1 gene is one of the targets that are suppressed by Nkx2-5.
Nkx2-5; Gata1; cardiac progenitors; gene regulation
Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized.
Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy.
Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are expected to achieve higher genetic engineering effectiveness than a trial-and-error procedure.
Long terminal repeats (LTR) from endogenous retroviruses (ERV) are source of binding sites for transcription factors which affect the host regulatory networks in different cell types, including pluripotent cells. The embryonic epiblast is made of pluripotent cells that are subjected to opposite transcriptional regulatory networks to give rise to distinct embryonic and extraembryonic lineages. To assess the transcriptional contribution of ERV to early developmental processes, we have characterized in vitro and in vivo the regulation of ENS-1, a host adopted and developmentally regulated ERV that is expressed in chick embryonic stem cells.
We show that Ens-1 LTR activity is controlled by two transcriptional pathways that drive pluripotent cells to alternative developmental fates. Indeed, both Nanog that maintains pluripotency and Gata4 that induces differentiation toward extraembryonic endoderm independently activate the LTR. Ets coactivators are required to support Gata factors' activity thus preventing inappropriate activation before epigenetic silencing occurs during differentiation. Consistent with their expression patterns during chick embryonic development, Gata4, Nanog and Ets1 are recruited on the LTR in embryonic stem cells; in the epiblast the complementary expression of Nanog and Gata/Ets correlates with the Ens-1 gene expression pattern; and Ens-1 transcripts are also detected in the hypoblast, an extraembryonic tissue expressing Gata4 and Ets2, but not Nanog. Accordingly, over expression of Gata4 in embryos induces an ectopic expression of Ens-1.
Our results show that Ens-1 LTR have co-opted conditions required for the emergence of extraembryonic tissues from pluripotent epiblasts cells. By providing pluripotent cells with intact binding sites for Gata, Nanog, or both, Ens-1 LTR may promote distinct transcriptional networks in embryonic stem cells subpopulations and prime the separation between embryonic and extraembryonic fates.
Embryonic stem cells have the ability to differentiate into nearly all cell types. However, the molecular mechanism of its pluripotency is still unclear. Oct3/4, Sox2 and Nanog are important factors of pluripotency. Oct3/4 (hereafter referred to as Oct4), in particular, has been an irreplaceable factor in the induction of pluripotency in adult cells. Proteins interacting with Oct4 and Nanog have been identified via affinity purification and mass spectrometry. These data, together with iterative purifications of interacting proteins allowed a protein interaction network to be constructed. The network currently includes 77 transcription factors, all of which are interconnected in one network. In-depth studies of some of these transcription factors show that they all recruit the NuRD complex. Hence, transcription factor clustering and chromosomal remodeling are key mechanism used by embryonic stem cells. Studies using RNA interference suggest that more pluripotency genes are yet to be discovered via protein-protein interactions. More work is required to complete and curate the embryonic stem cell protein interaction network. Analysis of a saturated protein interaction network by system biology tools can greatly aid in the understanding of the embryonic stem cell pluripotency network.
embryonic stem cells; Oct3/4; pluripotency; protein interaction networks
Stem cells are characterized by two defining features, the ability to self-renew and to differentiate into highly specialized cell types. The POU homeodomain transcription factor Oct4 (Pou5f1) is an essential mediator of the embryonic stem cell state and has been implicated in lineage specific differentiation, adult stem cell identity, and cancer. Recent description of the regulatory networks which maintain ‘ES’ have highlighted a dual role for Oct4 in the transcriptional activation of genes required to maintain self-renewal and pluripotency while concomitantly repressing genes which facilitate lineage specific differentiation. However, the molecular mechanism by which Oct4 mediates differential activation or repression at these loci to either maintain stem cell identity or facilitate the emergence of alternate transcriptional programs required for the realization of lineage remains to be elucidated. To further investigate Oct4 function, we employed gene expression profiling together with a robust statistical analysis to identify genes highly correlated to Oct4. Gene Ontology analysis to categorize overrepresented genes has led to the identification of themes which may prove essential to stem cell identity, including chromatin structure, nuclear architecture, cell cycle control, DNA repair, and apoptosis. Our experiments have identified previously unappreciated roles for Oct4 for firstly, regulating chromatin structure in a state consistent with self-renewal and pluripotency, and secondly, facilitating the expression of genes that keeps the cell poised to respond to cues that lead to differentiation. Together, these data define the mechanism by which Oct4 orchestrates cellular regulatory pathways to enforce the stem cell state and provides important insight into stem cell function and cancer.
Trophoblast stem cells (TSC) are the precursors of the differentiated cells of the placenta. In the mouse, TSC can be derived from outgrowths of either blastocyst polar trophectoderm (TE) or extraembryonic ectoderm (ExE), which originates from polar TE after implantation. The mouse TSC niche appears to be located within the ExE adjacent to the epiblast, on which it depends for essential growth factors, but whether this cellular architecture is the same in other species remains to be determined. Mouse TSC self-renewal can be sustained by culture on mitotically inactivated feeder cells, which provide one or more factors related to the NODAL pathway, and a medium supplemented with FGF4, heparin, and fetal bovine serum. Repression of the gene network that maintains pluripotency and emergence of the transcription factor pathways that specify a trophoblast (TR) fate enables TSC derivation in vitro and placental formation in vivo. Disrupting the pluripotent network of embryonic stem cells (ESC) causes them to default to a TR ground state. Pluripotent cells that have acquired sublethal chromosomal alterations may be sequestered into TR for similar reasons. The transition from ESC to TSC, which appears to be unidirectional, reveals important aspects of initial fate decisions in mice. TSC have yet to be derived from domestic species in which remarkable TR growth precedes embryogenesis. Recent derivation of TSC from blastocysts of the rhesus monkey suggests that isolation of the human equivalents may be possible and will reveal the extent to which mechanisms uncovered by using animal models are true in our own species.
In the mouse, trophoblast stem cells, the precursors of the differentiated cells of the placenta, can be derived from outgrowths of either blastocyte polar trophectoderm (TE) of the extraembryonic ectoderm (ExE), that originates from polar TE after implantation.
ectoplacental cone; embryonic stem cells; epiblast; extraembryonic endoderm; lineage; placenta; polar trophectoderm; trophoblast
Networks of transcription factors (TFs) are thought to determine and maintain the identity of cells. Here we systematically repressed each of 100 TFs with shRNA and carried out global gene expression profiling in mouse embryonic stem (ES) cells. Unexpectedly, only the repression of a handful of TFs significantly affected transcriptomes, which changed in two directions/trajectories: one trajectory by the repression of either Pou5f1 or Sox2; the other trajectory by the repression of either Esrrb, Sall4, Nanog, or Tcfap4. The data suggest that the trajectories of gene expression change are already preconfigured by the gene regulatory network and roughly correspond to extraembryonic and embryonic fates of cell differentiation, respectively. These data also indicate the robustness of the pluripotency gene network, as the transient repression of most TFs did not alter the transcriptomes.
Transcription factors regulate numerous cellular processes by controlling the rate of production of each gene. The regulatory relations are modeled using transcriptional regulatory networks. Recent studies have shown that such networks have an underlying hierarchical organization. We consider the problem of discovering the underlying hierarchy in transcriptional regulatory networks.
We first transform this problem to a mixed integer programming problem. We then use existing tools to solve the resulting problem. For larger networks this strategy does not work due to rapid increase in running time and space usage. We use divide and conquer strategy for such networks. We use our method to analyze the transcriptional regulatory networks of E. coli, H. sapiens and S. cerevisiae.
Our experiments demonstrate that: (i) Our method gives statistically better results than three existing state of the art methods; (ii) Our method is robust against errors in the data and (iii) Our method’s performance is not affected by the different topologies in the data.
Motivation: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks.
Results: We present a novel dynamic programming algorithm for detecting deregulated signaling cascades. The so-called FiDePa (Finding Deregulated Paths) algorithm interprets differences in the expression profiles of tumor and normal tissues. It relies on the well-known gene set enrichment analysis (GSEA) and efficiently detects all paths in a given regulatory or signaling network that are significantly enriched with differentially expressed genes or proteins. Since our algorithm allows for comparing a single tumor expression profile with the control group, it facilitates the detection of specific regulatory features of a tumor that may help to optimize tumor therapy. To demonstrate the capabilities of our algorithm, we analyzed a glioma expression dataset with respect to a directed graph that combined the regulatory networks of the KEGG and TRANSPATH database. The resulting glioma consensus network that encompasses all detected deregulated paths contained many genes and pathways that are known to be key players in glioma or cancer-related pathogenic processes. Moreover, we were able to correlate clinically relevant features like necrosis or metastasis with the detected paths.
Availability: C++ source code is freely available, BiNA can be downloaded from http://www.bnplusplus.org/.
Supplementary information: Supplementary data are available at Bioinformatics online.
Embryonic stem (ES) cells are of great interest as a model system for studying early developmental processes and because of their potential therapeutic applications in regenerative medicine. Obtaining a systematic understanding of the mechanisms that control the 'stemness' - self-renewal and pluripotency - of ES cells relies on high-throughput tools to define gene expression and regulatory networks at the genome level. Such recently developed systems biology approaches have revealed highly interconnected networks in which multiple regulatory factors act in combination. Interestingly, stem cells and cancer cells share some properties, notably self-renewal and a block in differentiation. Recently, several groups reported that expression signatures that are specific to ES cells are also found in many human cancers and in mouse cancer models, suggesting that these shared features might inform new approaches for cancer therapy. Here, we briefly summarize the key transcriptional regulators that contribute to the pluripotency of ES cells, the factors that account for the common gene expression patterns of ES and cancer cells, and the implications of these observations for future clinical applications.
It is essential to understand the network of transcription factors controlling self-renewal of human embryonic stem cells (ESCs) and human embryonal carcinoma cells (ECs) if we are to exploit these cells in regenerative medicine regimes. Correlating gene expression levels after RNAi-based ablation of OCT4 function with its downstream targets enables a better prediction of motif-specific driven expression modules pertinent for self-renewal and differentiation of embryonic stem cells and induced pluripotent stem cells.
We initially identified putative direct downstream targets of OCT4 by employing CHIP-on-chip analysis. A comparison of three peak analysis programs revealed a refined list of OCT4 targets in the human EC cell line NCCIT, this list was then compared to previously published OCT4 CHIP-on-chip datasets derived from both ES and EC cells. We have verified an enriched POU-motif, discovered by a de novo approach, thus enabling us to define six distinct modules of OCT4 binding and regulation of its target genes.
A selection of these targets has been validated, like NANOG, which harbours the evolutionarily conserved OCT4-SOX2 binding motif within its proximal promoter. Other validated targets, which do not harbour the classical HMG motif are USP44 and GADD45G, a key regulator of the cell cycle. Over-expression of GADD45G in NCCIT cells resulted in an enrichment and up-regulation of genes associated with the cell cycle (CDKN1B, CDKN1C, CDK6 and MAPK4) and developmental processes (BMP4, HAND1, EOMES, ID2, GATA4, GATA5, ISL1 and MSX1). A comparison of positively regulated OCT4 targets common to EC and ES cells identified genes such as NANOG, PHC1, USP44, SOX2, PHF17 and OCT4, thus further confirming their universal role in maintaining self-renewal in both cell types. Finally we have created a user-friendly database (http://biit.cs.ut.ee/escd/), integrating all OCT4 and stem cell related datasets in both human and mouse ES and EC cells.
In the current era of systems biology driven research, we envisage that our integrated embryonic stem cell database will prove beneficial to the booming field of ES, iPS and cancer research.