Pluripotency gene network dynamics: System views from parametric analysis

ChIP-DIP: A multiplexed method for mapping hundreds of proteins to DNA uncovers diverse regulatory elements controlling gene expression

Gene expression is controlled by the dynamic localization of thousands of distinct regulatory proteins to precise regions of DNA. Understanding this cell-type specific process has been a goal of molecular biology for decades yet remains challenging because most current DNA-protein mapping methods study one protein at a time. To overcome this, we developed ChIP-DIP (ChIP Done In Parallel), a split-pool based method that enables simultaneous, genome-wide mapping of hundreds of diverse regulatory proteins in a single experiment. We demonstrate that ChIP-DIP generates highly accurate maps for all classes of DNA-associated proteins, including histone modifications, chromatin regulators, transcription factors, and RNA Polymerases. Using these data, we explore quantitative combinations of protein localization on genomic DNA to define distinct classes of regulatory elements and their functional activity. Our data demonstrate that ChIP-DIP enables the generation of 'consortium level', context-specific protein localization maps within any molecular biology lab.

The "Superoncogene" Myc at the Crossroad between Metabolism and Gene Expression in Glioblastoma Multiforme

The concept of the Myc (c-myc, n-myc, l-myc) oncogene as a canonical, DNA-bound transcription factor has consistently changed over the past few years. Indeed, Myc controls gene expression programs at multiple levels: directly binding chromatin and recruiting transcriptional coregulators; modulating the activity of RNA polymerases (RNAPs); and drawing chromatin topology. Therefore, it is evident that Myc deregulation in cancer is a dramatic event. Glioblastoma multiforme (GBM) is the most lethal, still incurable, brain cancer in adults, and it is characterized in most cases by Myc deregulation. Metabolic rewiring typically occurs in cancer cells, and GBM undergoes profound metabolic changes to supply increased energy demand. In nontransformed cells, Myc tightly controls metabolic pathways to maintain cellular homeostasis. Consistently, in Myc-overexpressing cancer cells, including GBM cells, these highly controlled metabolic routes are affected by enhanced Myc activity and show substantial alterations. On the other hand, deregulated cancer metabolism impacts Myc expression and function, placing Myc at the intersection between metabolic pathway activation and gene expression. In this review paper, we summarize the available information on GBM metabolism with a specific focus on the control of the Myc oncogene that, in turn, rules the activation of metabolic signals, ensuring GBM growth.

Pluripotency factors are repurposed to shape the epigenomic landscape of neural crest cells

Yamanaka factors are essential for establishing pluripotency in embryonic stem cells, but their function in multipotent stem cell populations is poorly understood. Here, we show that OCT4 and SOX2 cooperate with tissue-specific transcription factors to promote neural crest formation. By assessing avian and human neural crest cells at distinct developmental stages, we characterized the epigenomic changes that occur during their specification, migration, and early differentiation. This analysis determined that the OCT4-SOX2 dimer is required to establish a neural crest epigenomic signature that is lost upon cell fate commitment. The OCT4-SOX2 genomic targets in the neural crest differ from those of embryonic stem cells, indicating the dimer displays context-specific functions. Binding of OCT4-SOX2 to neural crest enhancers requires pioneer factor TFAP2A, which physically interacts with the dimer to modify its genomic targets. Our results demonstrate how Yamanaka factors are repurposed in multipotent cells to control chromatin organization and define their developmental potential.

Statistical estimates of multiple transcription factors binding in the model plant genomes based on ChIP-seq data

The development of high-throughput genomic sequencing coupled with chromatin immunoprecipitation technologies allows studying the binding sites of the protein transcription factors (TF) in the genome scale. The growth of data volume on the experimentally determined binding sites raises qualitatively new problems for the analysis of gene expression regulation, prediction of transcription factors target genes, and regulatory gene networks reconstruction. Genome regulation remains an insufficiently studied though plants have complex molecular regulatory mechanisms of gene expression and response to environmental stresses. It is important to develop new software tools for the analysis of the TF binding sites location and their clustering in the plant genomes, visualization, and the following statistical estimates. This study presents application of the analysis of multiple TF binding profiles in three evolutionarily distant model plant organisms. The construction and analysis of non-random ChIP-seq binding clusters of the different TFs in mammalian embryonic stem cells were discussed earlier using similar bioinformatics approaches. Such clusters of TF binding sites may indicate the gene regulatory regions, enhancers and gene transcription regulatory hubs. It can be used for analysis of the gene promoters as well as a background for transcription networks reconstruction. We discuss the statistical estimates of the TF binding sites clusters in the model plant genomes. The distributions of the number of different TFs per binding cluster follow same power law distribution for all the genomes studied. The binding clusters in Arabidopsis thaliana genome were discussed here in detail.

A mathematical modelling framework for the regulation of intra-cellular OCT4 in human pluripotent stem cells

Human pluripotent stem cells (hPSCs) have the potential to differentiate into all cell types, a property known as pluripotency. A deeper understanding of how pluripotency is regulated is required to assist in controlling pluripotency and differentiation trajectories experimentally. Mathematical modelling provides a non-invasive tool through which to explore, characterise and replicate the regulation of pluripotency and the consequences on cell fate. Here we use experimental data of the expression of the pluripotency transcription factor OCT4 in a growing hPSC colony to develop and evaluate mathematical models for temporal pluripotency regulation. We consider fractional Brownian motion and the stochastic logistic equation and explore the effects of both additive and multiplicative noise. We illustrate the use of time-dependent carrying capacities and the introduction of Allee effects to the stochastic logistic equation to describe cell differentiation. We conclude both methods adequately capture the decline in OCT4 upon differentiation, but the Allee effect model has the advantage of allowing differentiation to occur stochastically in a sub-set of cells. This mathematical framework for describing intra-cellular OCT4 regulation can be extended to other transcription factors and developed into predictive models.

Unraveling the origin of glucose mediated disparate proliferation dynamics of cancer stem cells

Cancer stem cells (CSCs) often switch on their self-renewal programming aggressively to cause a relapse of cancer. Intriguingly, glucose triggers the proliferation propensities in CSCs by controlling the expression of the key transcription factor-like Nanog. However, the factors that critically govern this glucose-stimulated proliferation dynamics of CSCs remain elusive. Herein, by proposing a mathematical model of glucose-mediated Nanog regulation, we showed that the differential proliferation behavior of CSCs and cell-type similar to CSCs can be explained by considering the experimentally observed varied expression levels of key positive (STAT3) and negative (p53) regulators of Nanog. Our model reconciles various experimental observations and predicts ways to fine-tune the proliferation dynamics of these cell types in a context-dependent manner. In future, these modeling insights will be useful in developing improved therapeutic strategies to get rid of harmful CSCs.

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

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

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

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

A Boolean Logical model for Reprogramming of Testes-derived male Germline Stem Cells into Germline pluripotent stem cells

BACKGROUND AND OBJECTIVE

Male germline stem (GS) cells are responsible for the maintenance of spermatogenesis throughout the adult life of males. Upon appropriate in vitro culture conditions, these GS cells can undergo reprogramming to become germline pluripotent stem (GPS) cells with the loss of spermatogenic potential. In recent years, voluminous data of gene transcripts in GS and GPS cells have become available. However, the mechanism of reprogramming of GS cells into GPS cells remains elusive. This study was designed to develop a Boolean logical model of gene regulatory network (GRN) that might be involved in the reprogramming of GS cells into GPS cells.

METHODS

The gene expression profile of GS and GPS cells (GSE ID: GSE11274 and GSE74151) were analyzed using R Bioconductor to identify differentially expressed genes (DEGs) and were functionally annotated with DAVID server. Potential pluripotent genes among the DEGs were then predicted using a combination of machine learning [Support Vector Machine (SVM)] and BLAST search. Protein isoforms were identified by pattern matching with UniProt database with in-house scripts written in C++. Both linear and non-linear interaction maps were generated using the STRING server. CellNet is used to study the relationship of GRNs between the GS and GPS cells. Finally, the GRNs involving all the genes from integrated methods and literature was constructed and qualitative modelling for reprogramming of GS to GPS cells were done by considering the discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tool.

RESULTS

Through the use of machine learning and logical modeling, the present study identified 3585 DEGs and 221 novel pluripotent genes including Tet1, Cdh1, Tfap2c, Etv4, Etv5, Prdm14, and Prdm10 in GPS cells. Pathway analysis revealed that important signaling pathways such as core pluripotency network, PI3K-Akt, WNT, GDNF and BMP4 signalling pathways were important for the reprogramming of GS cells to GPS cells. On the other hand, CellNet analysis of GRNs of GS and GPS cells revealed that GS cells were similar to gonads whereas GPS cells were similar to ESCs in gene expression profile. A logical regulatory model was developed, which showed that TGFβ negatively regulated the reprogramming of the GS to GPS cells, as confirmed by perturbations studies.

CONCLUSION

The study identified novel pluripotent genes involved in the reprogramming of GS cells into GPS cells. A multivalued logical model of cellular reprogramming is proposed, which suggests that reprogramming of GS cells to GPS cells involves signalling pathways namely LIF, GDNF, BMP4, and TGFβ along with some novel pluripotency genes.

FGF Signaling Pathway: A Key Regulator of Stem Cell Pluripotency

Pluripotent stem cells (PSCs) isolated in vitro from embryonic stem cells (ESCs), induced PSC (iPSC) and also post-implantation epiblast-derived stem cells (EpiSCs) are known for their two unique characteristics: the ability to give rise to all somatic lineages and the self-renewal capacity. Numerous intrinsic signaling pathways contribute to the maintenance of the pluripotency state of stem cells by tightly controlling key transcriptional regulators of stemness including sex determining region Y box 2 (Sox-2), octamer-binding transcription factor (Oct)3/4, krueppel-like factor 4 (Klf-4), Nanog, and c-Myc. Signaling by fibroblast growth factor (FGF) is of critical importance in regulating stem cells pluripotency. The FGF family is comprised of 22 ligands that interact with four FGF receptors (FGFRs). FGF/FGFR signaling governs fundamental cellular processes such as cell survival, proliferation, migration, differentiation, embryonic development, organogenesis, tissue repair/regeneration, and metabolism. FGF signaling is mediated by the activation of RAS - mitogen-activated protein kinase (MAPK), phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT, Phospholipase C Gamma (PLCγ), and signal transducers and activators of transcription (STAT), which intersects and synergizes with other signaling pathways such as Wnt, retinoic acid (RA) and transforming growth factor (TGF)-β signaling. In the current review, we summarize the role of FGF signaling in the maintenance of pluripotency state of stem cells through regulation of key transcriptional factors.

CRISPR-Cas9-mediated knockout of the Prkdc in mouse embryonic stem cells leads to the modulation of the expression of pluripotency genes

Prkdc encodes for the catalytic subunit of the DNA-dependent protein kinase (DNA-PKcs) playing a key role in nonhomologous end joining pathway during DNA double-strand break repair and also influencing the homologous recombination (HR) repair system by phosphorylation of proteins involved in HR. In addition, Prkdc has other critical functions in biological processes, such as transcriptional regulation, telomere stability, apoptosis, and metabolism. DNA-PKcs upregulates during in vitro differentiation of mouse embryonic stem cells (mESCs). To address the potential role of Prkdc in mESCs pluripotency and in vitro differentiation into ectoderm, mesoderm, and endoderm germ layers under normal physiological conditions, a bi-allelic Prkdc-knockout cell line was generated in the present study by employing CRISPR/Cas9 system, and subsequently, its potential role in stemness and development was studied. The results of the study showed that the expression of pluripotency-associated genes, including Nanog and Sox-2 were overexpressed in the bi-allelic Prkdc-knockout cell line. Also, bi-allelic Prkdc-knockout cell line was shown to have typical mESCs cell morphology, cell cycle distribution, and alkaline phosphatase activity. Furthermore, the results of the study revealed that the expression of several germ layer markers is modulated in Prkdc-knockout lines. In conclusion, the findings of our study demonstrated the role of Prkdc during differentiation and development of ESCs.

Clinical-pathological correlations of BAV and the attendant thoracic aortopathies. Part 2: Pluridisciplinary perspective on their genetic and molecular origins

Bicuspid aortic valve (BAV) arises during valvulogenesis when 2 leaflets/cusps of the aortic valve (AOV) are fused together. Its clinical manifestations pertain to faulty AOV function, the associated aortopathy, and other complications surveyed in Part 1 of the present bipartite-series. Part 2 examines mainly genetic and epigenetic causes of BAV and BAV-associated aortopathies (BAVAs) and disease syndromes (BAVD). Part 1 explored the heterogeneity among subsets of patients with BAV and BAVA/BAVD, and investigated abnormal fluid dynamic stress and strain patterns sustained by the cusps. Specific BAV morphologies engender systolic outflow asymmetries, associated with abnormal aortic regional wall-shear-stress distributions and the expression/localization of BAVAs. Understanding fluid dynamic factors besides the developmental mechanisms and underlying genetics governing these congenital anomalies is necessary to explain patient predisposition to aortopathy and phenotypic heterogeneity. BAV aortopathy entails complex/multifactorial pathophysiology, involving alterations in genetics, epigenetics, hemodynamics, and in cellular and molecular pathways. There is always an interdependence between organismic developmental signals and genes-no systemic signals, no gene-expression; no active gene, no next step. An apposite signal induces the expression of the next developmental gene, which needs be expressed to trigger the next signal, and so on. Hence, embryonic, then post-partum, AOV and thoracic aortic development comprise cascades of developmental genes and their regulation. Interdependencies between them arise, entailing reciprocal/cyclical mutual interactions and adaptive feedback loops, by which developmental morphogenetic processes self-correct responding to environmental inputs/reactions. This Survey can serve as a reference point and driver for further pluridisciplinary BAV/BAVD studies and their clinical translation.