971 resultados para transcriptional regulatory networks


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Small non-protein-coding RNA (ncRNA) molecules represent major contributors to regulatory networks in controlling gene expression in a highly efficient manner. All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. To address the question, whether small ncRNA regulators exist that are capable of modulating the rate of protein production by directly interacting with the ribosome, we have analyzed the small ncRNA interactomes of ribosomes Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs in various model organisms (1,2). For a subset of these ncRNA candidates we have gathered experimental evidence that they associate with ribosomes in a stress-dependent manner and are capable of regulating gene expression by fine-tuning the rate of protein biosynthesis (3,4). Many of the investigated ribosome-bound small ncRNA appear to be processing products from larger functional RNAs, such as tRNAs (2,3) or mRNAs (3). Post-transcriptional cleavage of RNA molecules to generate smaller fragments is a widespread mechanism that enlarges the structural and functional complexity of cellular RNomes. Our data reveal the ribosome as a target for small regulatory ncRNAs and demonstrate the existence of a yet unknown mechanism of translation regulation. Ribosome-associated ncRNAs (rancRNAs) are found in all domains of life and represent a prevalent but so far largely unexplored class of regulatory molecules (5). Future work on the small ncRNA interactomes of ribosomes in a variety of model systems will allow deeper insight into the conservation and functional repertoire of this emerging class of regulatory ncRNA molecules.

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Transcriptional repression is an important component of regulatory networks that govern gene expression. In this report, we have characterized the mechanisms by which the immediate early protein 2 (IE2 or IE86), a master transcriptional regulator of human cytomegalovirus, down-regulates its own expression. In vitro transcription and DNA binding experiments demonstrate that IE2 blocks specifically the association of RNA polymerase II with the preinitiation complex. Although, to our knowledge, this is the first report to describe a eukaryotic transcriptional repressor that selectively impedes RNA polymerase II recruitment, we present data that suggest that this type of repression might be widely used in the control of transcription by RNA polymerase II.

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Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

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To gain insight into the mechanisms by which the Myb transcription factor controls normal hematopoiesis and particularly, how it contributes to leukemogenesis, we mapped the genome-wide occupancy of Myb by chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) in ERMYB myeloid progenitor cells. By integrating the genome occupancy data with whole genome expression profiling data, we identified a Myb-regulated transcriptional program. Gene signatures for leukemia stem cells, normal hematopoietic stem/progenitor cells and myeloid development were overrepresented in 2368 Myb regulated genes. Of these, Myb bound directly near or within 793 genes. Myb directly activates some genes known critical in maintaining hematopoietic stem cells, such as Gfi1 and Cited2. Importantly, we also show that, despite being usually considered as a transactivator, Myb also functions to repress approximately half of its direct targets, including several key regulators of myeloid differentiation, such as Sfpi1 (also known as Pu.1), Runx1, Junb and Cebpb. Furthermore, our results demonstrate that interaction with p300, an established coactivator for Myb, is unexpectedly required for Myb-mediated transcriptional repression. We propose that the repression of the above mentioned key pro-differentiation factors may contribute essentially to Myb's ability to suppress differentiation and promote self-renewal, thus maintaining progenitor cells in an undifferentiated state and promoting leukemic transformation. © 2011 The Author(s).

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Cell proliferation, transcription and metabolism are regulated by complex partly overlapping signaling networks involving proteins in various subcellular compartments. The objective of this study was to increase our knowledge on such regulatory networks and their interrelationships through analysis of MrpL55, Vig, and Mat1 representing three gene products implicated in regulation of cell cycle, transcription, and metabolism. Genome-wide and biochemical in vitro studies have previously revealed MrpL55 as a component of the large subunit of the mitochondrial ribosome and demonstrated a possible role for the protein in cell cycle regulation. Vig has been implicated in heterochromatin formation and identified as a constituent of the RNAi-induced silencing complex (RISC) involved in cell cycle regulation and RNAi-directed transcriptional gene silencing (TGS) coupled to RNA polymerase II (RNAPII) transcription. Mat1 has been characterized as a regulatory subunit of cyclin-dependent kinase 7 (Cdk7) complex phosphorylating and regulating critical targets involved in cell cycle progression, energy metabolism and transcription by RNAPII. The first part of the study explored whether mRpL55 is required for cell viability or involved in a regulation of energy metabolism and cell proliferation. The results revealed a dynamic requirement of the essential Drosophila mRpL55 gene during development and suggested a function of MrpL55 in cell cycle control either at the G1/S or G2/M transition prior to cell differentiation. This first in vivo characterization of a metazoan-specific constituent of the large subunit of mitochondrial ribosome also demonstrated forth compelling evidence of the interconnection of nuclear and mitochondrial genomes as well as complex functions of the evolutionarily young metazoan-specific mitochondrial ribosomal proteins. In studies on the Drosophila RISC complex regulation, it was noted that Vig, a protein involved in heterochromatin formation, unlike other analyzed RISC associated proteins Argonaute2 and R2D2, is dynamically phosphorylated in a dsRNA-independent manner. Vig displays similarity with a known in vivo substrate for protein kinase C (PKC), human chromatin remodeling factor Ki-1/57, and is efficiently phosphorylated by PKC on multiple sites in vitro. These results suggest that function of the RISC complex protein Vig in RNAi-directed TGS and chromatin modification may be regulated through dsRNA-independent phosphorylation by PKC. In the third part of this study the role of Mat1 in regulating RNAPII transcription was investigated using cultured murine immortal fibroblasts with a conditional allele of Mat1. The results demonstrated that phosphorylation of the carboxy-terminal domain (CTD) of the large subunit of RNAPII in the heptapeptide YSPTSPS repeat in Mat-/- cells was over 10-fold reduced on Serine-5 and subsequently on Serine-2. Occupancy of the hypophosphorylated RNAPII in gene bodies was detectably decreased, whereas capping, splicing, histone methylation and mRNA levels were generally not affected. However, a subset of transcripts in absence of Mat1 was repressed and associated with decreased occupancy of RNAPII at promoters as well as defective capping. The results identify the Cdk7-CycH-Mat1 kinase submodule of TFIIH as a stimulatory non-essential regulator of transcriptional elongation and a genespecific essential factor for stable binding of RNAPII at the promoter region and capping. The results of these studies suggest important roles for both MrpL55 and Mat1 in cell cycle progression and their possible interplay at the G2/M stage in undifferentiated cells. The identified function of Mat1 and of TFIIH kinase complex in gene-specific transcriptional repression is challenging for further studies in regard to a possible link to Vig and RISC-mediated transcriptional gene silencing.

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The continuous production of blood cells, a process termed hematopoiesis, is sustained throughout the lifetime of an individual by a relatively small population of cells known as hematopoietic stem cells (HSCs). HSCs are unique cells characterized by their ability to self-renew and give rise to all types of mature blood cells. Given their high proliferative potential, HSCs need to be tightly regulated on the cellular and molecular levels or could otherwise turn malignant. On the other hand, the tight regulatory control of HSC function also translates into difficulties in culturing and expanding HSCs in vitro. In fact, it is currently not possible to maintain or expand HSCs ex vivo without rapid loss of self-renewal. Increased knowledge of the unique features of important HSC niches and of key transcriptional regulatory programs that govern HSC behavior is thus needed. Additional insight in the mechanisms of stem cell formation could enable us to recapitulate the processes of HSC formation and self-renewal/expansion ex vivo with the ultimate goal of creating an unlimited supply of HSCs from e.g. human embryonic stem cells (hESCs) or induced pluripotent stem cells (iPS) to be used in therapy. We thus asked: How are hematopoietic stem cells formed and in what cellular niches does this happen (Papers I, II)? What are the molecular mechanisms that govern hematopoietic stem cell development and differentiation (Papers III, IV)? Importantly, we could show that placenta is a major fetal hematopoietic niche that harbors a large number of HSCs during midgestation (Paper I)(Gekas et al., 2005). In order to address whether the HSCs found in placenta were formed there we utilized the Runx1-LacZ knock-in and Ncx1 knockout mouse models (Paper II). Importantly, we could show that HSCs emerge de novo in the placental vasculature in the absence of circulation (Rhodes et al., 2008). Furthermore, we could identify defined microenvironmental niches within the placenta with distinct roles in hematopoiesis: the large vessels of the chorioallantoic mesenchyme serve as sites of HSC generation whereas the placental labyrinth is a niche supporting HSC expansion (Rhodes et al., 2008). Overall, these studies illustrate the importance of distinct milieus in the emergence and subsequent maturation of HSCs. To ensure proper function of HSCs several regulatory mechanisms are in place. The microenvironment in which HSCs reside provides soluble factors and cell-cell interactions. In the cell-nucleus, these cell-extrinsic cues are interpreted in the context of cell-intrinsic developmental programs which are governed by transcription factors. An essential transcription factor for initiation of hematopoiesis is Scl/Tal1 (stem cell leukemia gene/T-cell acute leukemia gene 1). Loss of Scl results in early embryonic death and total lack of all blood cells, yet deactivation of Scl in the adult does not affect HSC function (Mikkola et al., 2003b. In order to define the temporal window of Scl requirement during fetal hematopoietic development, we deactivated Scl in all hematopoietic lineages shortly after hematopoietic specification in the embryo . Interestingly, maturation, expansion and function of fetal HSCs was unaffected, and, as in the adult, red blood cell and platelet differentiation was impaired (Paper III)(Schlaeger et al., 2005). These findings highlight that, once specified, the hematopoietic fate is stable even in the absence of Scl and is maintained through mechanisms that are distinct from those required for the initial fate choice. As the critical downstream targets of Scl remain unknown, we sought to identify and characterize target genes of Scl (Paper IV). We could identify transcription factor Mef2C (myocyte enhancer factor 2 C) as a novel direct target gene of Scl specifically in the megakaryocyte lineage which largely explains the megakaryocyte defect observed in Scl deficient mice. In addition, we observed an Scl-independent requirement of Mef2C in the B-cell compartment, as loss of Mef2C leads to accelerated B-cell aging (Gekas et al. Submitted). Taken together, these studies identify key extracellular microenvironments and intracellular transcriptional regulators that dictate different stages of HSC development, from emergence to lineage choice to aging.

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The Wilms tumor 1 gene (WT1) can either repress or induce the expression of genes. Inconsistent with its tumor suppressor role, elevated WT1 levels have been observed in leukemia and solid tumors. WT1 has also been suggested to act as an oncogene by inducing the expression of MYC and BCL-2. However, these are only the correlational studies, and no functional study has been performed to date. Consistent with its tumor suppressor role, CDC73 binds to RNA polymerase II as part of a PAF1 transcriptional regulatory complex and causes transcriptional repression of oncogenes MYC and CCND1. It also represses beta-catenin-mediated transcription. Based on the reduced level of CDC73 in oral squamous cell carcinoma (OSCC) samples in the absence of loss-of-heterozygosity, promoter methylation, and mutations, we speculated that an inhibitory transcription factor is regulating its expression. The bioinformatics analysis predicted WT1 as an inhibitory transcription factor to regulate the CDC73 level. Our results showed that overexpression of WT1 decreased CDC73 levels and promoted proliferation of OSCC cells. ChIP and EMSA results demonstrated binding of WT1 to the CDC73 promoter. The 5-azacytidine treatment of OSCC cells led to an up-regulation of WT1 with a concomitant down-regulation of CDC73, further suggesting regulation of CDC73 by WT1. Exogenous CDC73 attenuated the protumorigenic activity of WT1 by apoptosis induction. An inverse correlation between expression levels of CDC73 and WT1 was observed in OSCC samples. These observations indicated that WT1 functions as an oncogene by repressing the expression of CDC73 in OSCC. We suggest that targeting WT1 could be a therapeutic strategy for cancer, including OSCC.

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Cells exhibit a diverse repertoire of dynamic behaviors. These dynamic functions are implemented by circuits of interacting biomolecules. Although these regulatory networks function deterministically by executing specific programs in response to extracellular signals, molecular interactions are inherently governed by stochastic fluctuations. This molecular noise can manifest as cell-to-cell phenotypic heterogeneity in a well-mixed environment. Single-cell variability may seem like a design flaw but the coexistence of diverse phenotypes in an isogenic population of cells can also serve a biological function by increasing the probability of survival of individual cells upon an abrupt change in environmental conditions. Decades of extensive molecular and biochemical characterization have revealed the connectivity and mechanisms that constitute regulatory networks. We are now confronted with the challenge of integrating this information to link the structure of these circuits to systems-level properties such as cellular decision making. To investigate cellular decision-making, we used the well studied galactose gene-regulatory network in \textit{Saccharomyces cerevisiae}. We analyzed the mechanism and dynamics of the coexistence of two stable on and off states for pathway activity. We demonstrate that this bimodality in the pathway activity originates from two positive feedback loops that trigger bistability in the network. By measuring the dynamics of single-cells in a mixed sugar environment, we observe that the bimodality in gene expression is a transient phenomenon. Our experiments indicate that early pathway activation in a cohort of cells prior to galactose metabolism can accelerate galactose consumption and provide a transient increase in growth rate. Together these results provide important insights into strategies implemented by cells that may have been evolutionary advantageous in competitive environments.

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Understanding how transcriptional regulatory sequence maps to regulatory function remains a difficult problem in regulatory biology. Given a particular DNA sequence for a bacterial promoter region, we would like to be able to say which transcription factors bind there, how strongly they bind, and whether they interact with each other and/or RNA polymerase, with the ultimate objective of integrating knowledge of these parameters into a prediction of gene expression levels. The theoretical framework of statistical thermodynamics provides a useful framework for doing so, enabling us to predict how gene expression levels depend on transcription factor binding energies and concentrations. We used thermodynamic models, coupled with models of the sequence-dependent binding energies of transcription factors and RNAP, to construct a genotype to phenotype map for the level of repression exhibited by the lac promoter, and tested it experimentally using a set of promoter variants from E. coli strains isolated from different natural environments. For this work, we sought to ``reverse engineer'' naturally occurring promoter sequences to understand how variations in promoter sequence affects gene expression. The natural inverse of this approach is to ``forward engineer'' promoter sequences to obtain targeted levels of gene expression. We used a high precision model of RNAP-DNA sequence dependent binding energy, coupled with a thermodynamic model relating binding energy to gene expression, to predictively design and verify a suite of synthetic E. coli promoters whose expression varied over nearly three orders of magnitude.

However, although thermodynamic models enable predictions of mean levels of gene expression, it has become evident that cell-to-cell variability or ``noise'' in gene expression can also play a biologically important role. In order to address this aspect of gene regulation, we developed models based on the chemical master equation framework and used them to explore the noise properties of a number of common E. coli regulatory motifs; these properties included the dependence of the noise on parameters such as transcription factor binding strength and copy number. We then performed experiments in which these parameters were systematically varied and measured the level of variability using mRNA FISH. The results showed a clear dependence of the noise on these parameters, in accord with model predictions.

Finally, one shortcoming of the preceding modeling frameworks is that their applicability is largely limited to systems that are already well-characterized, such as the lac promoter. Motivated by this fact, we used a high throughput promoter mutagenesis assay called Sort-Seq to explore the completely uncharacterized transcriptional regulatory DNA of the E. coli mechanosensitive channel of large conductance (MscL). We identified several candidate transcription factor binding sites, and work is continuing to identify the associated proteins.

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We conducted a comparative statistical analysis of tetra- through hexanucleotide frequencies in two sets of introns of yeast genes. The first set consisted of introns of genes that have transcription rates higher than 30 mRNAs/h while the second set contained introns of genes whose transcription rates were lower than or equal to 10 mRNAs/h. Some oligonucleotides whose occurrence frequencies in the first set of introns are significantly higher than those in the second set of introns were detected. The frequencies of occurrence of most of these detected oligonucleotides are also significantly higher than those in the exons flanking the introns of the first set. Interestingly some of these detected oligonucleotides are the same as well known "signature" sequences of transcriptional regulatory elements. This could imply the existence of potential positive regulatory motifs of transcription in yeast introns. (C) 2003 Elsevier Ltd. All rights reserved.

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Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. © 2012 IEEE.

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Transient overexpression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Overexpression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca(2+) transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies.

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The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e. g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first.

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The mammalian nervous system exerts essential control on many physiological processes in the organism and is itself controlled extensively by a variety of genetic regulatory mechanisms. microRNA (miR), an abundant class of small non-coding RNA, are emerging as important post-transcriptional regulators of gene expression in the brain. Increasing evidence indicates that miR regulate both the development and function of the nervous system. Moreover, deficiency in miR function has also been implicated in a number of neurological disorders. Expression profile analysis of miR is necessary to understand their complex role in the regulation of gene expression during the development and differentiation of cells. Here we present a comparative study of miR expression profiles in neuroblastoma, in cortical development, and in neuronal differentiation of embryonic stem (ES) cells. By microarray profiling in combination with real time PCR we show that miR-7 and miR-214 are modulated in neuronal differentiation (as compared to miR-1, -16 and -133a), and control neurite outgrowth in vitro. These findings provide an important step toward further elucidation of miR function and miR-related gene regulatory networks in the mammalian central nervous system. (C) 2010 Elsevier Inc. All rights reserved.

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In the aftermath of the financial crash of 2008, policy makers operating in international financial regulatory networks discovered macroprudential regulation (MPR), but macroprudential regulation has had a stunted or arrested development that can be explained with reference to five factors that are recounted in this article