Project description:Chickarmane2006 - Stem cell switch irreversible Kinetic modeling approach of the transcriptional dynamics of the embryonic stem cell switch. This model is described in the article: Transcriptional dynamics of the embryonic stem cell switch. Chickarmane V, Troein C, Nuber UA, Sauro HM, Peterson C PLoS Computational Biology. 2006; 2(9):e123 Abstract: 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. This model is hosted on BioModels Database and identified by: MODEL7957942740 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Chickarmane2006 - Stem cell switch reversible Kinetic modeling approach of the transcriptional dynamics of the embryonic stem cell switch. This model is described in the article: Transcriptional dynamics of the embryonic stem cell switch. Chickarmane V, Troein C, Nuber UA, Sauro HM, Peterson C PLoS Computational Biology. 2006; 2(9):e123 Abstract: 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. This model is hosted on BioModels Database and identified by: MODEL7957907314 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:H1299 cells were stably transfected with the Oct4 promoter/GFP or Nestin promoter/GFP reporter vectors. By FACS, 106 cells expressing high levels of GFP were isolated and placed into cell culture for twenty-four hours. Total RNA was used. Bone morphogenetic proteins (BMP) are aberrantly expressed in most lung carcinomas. BMPs mediate cell fate decisions and self-renewal of stem cells. Inhibition of BMP signaling decreases the growth and induces cell death of lung cancer cells lines. It is not known whether the BMP signaling cascade is growth promoting in lung cancer cells expressing the stem cell markers Oct4 and/or nestin. Lung cancer cells expressing Oct4 or nestin were isolated from lung cancer cell lines by stably transfecting the Oct4 promoter or Nestin promoter expression vectors that activate the green fluorescent protein reporter. Our studies support that lung cancer cells activating the Oct4 or nestin promoter are different cell populations. Microarray and quantitative RT-PCR demonstrated that the expression levels of specific stem cell markers were different between the isolated Oct4 and nestin cells. Both the Oct4 and nestin populations were more tumorigenic that controls but histologically they were quite different. The isolated Oct4 and nestin cells also responded differently to inhibition of BMP signaling. Blockade of BMP signaling with the BMP receptor antagonist DMH2 caused significant growth inhibition in both the Oct4 and nestin cell populations but only increased cell death in the nestin population. DMH2 also induced the expression of nestin in the Oct4 population but not in the nestin cells. We also show that BMP signaling is an important regulator of the inhibitor differentiation proteins Id1 and Id3 in Oct4 and nestin cell populations Lung cancer cells expressing Oct4 or nestin were isolated and transfected with Oct4 or Nestin promoter expression vectors that activate the green fluorescent protein reporter. Microarray and quantitative RT-PCR were performed to study the differentially expressed genes. BMPs mediate cell fate decisions and self-renewal of stem cells were investigated.

Project description:Chavez2009 - a core regulatory network of OCT4 in human embryonic stem cells A core OCT4-regulated network has been identified as a test case, to analyase stem cell characteristics and cellular differentiation. This model is described in the article: In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach. Chavez L, Bais AS, Vingron M, Lehrach H, Adjaye J, Herwig R BMC Genomics, 2009, 10:314 Abstract: BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency. RESULTS: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. Enrichment analysis with these target genes revealed that this integrative analysis increases the functional information content by factors of 1.3 - 4.7 compared to the individual studies. In order to identify potential regulatory co-factors of OCT4, we performed a de novo motif analysis. In addition to known validated OCT4 motifs we obtained binding sites similar to motifs recognized by further regulators of pluripotency and development; e.g. the heterodimer of the transcription factors C-MYC and MAX, a prerequisite for C-MYC transcriptional activity that leads to cell growth and proliferation. CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies. This model is hosted on BioModels Database and identified by: MODEL1305010000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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