Gene expression profiles at single cell level of lung epithelial cells from the Cracd WT and Cracd KO mice
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE229982 | GEO | 2024/04/13
REPOSITORIES: GEO
Similar Datasets
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.
2024-09-02 | BIOMD0000000203 | BioModels
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.
2024-09-02 | BIOMD0000000204 | BioModels
Project description:The inflammatory tumor microenvironment (TME) is a key driver of tumor-promoting processes. Tumor-associated macrophages are one of the main immune cell types in the TME and their density increases during cancer progression. Here, we investigated the influence of pro-inflammatory (M1) and immunosuppressive (M2) macrophages on prostate cancer lineage plasticity. Our findings reveal that M1 macrophage secreted factors upregulate genes related to stemness while downregulating genes associated with androgen response in LNCaP prostate cancer cells. Cancer stem cell plasticity markers NANOG, KLF4, SOX2, OCT4 and CD44 were stimulated by the secreted factors from M1 macrophages. Moreover, AR and its target gene KLK3 were observed to be suppressed in LNCaP cells treated exposed to secreted factors from M1 macrophages. Inhibition of NF-κB signaling using the IKK16 inhibitor resulted in downregulation of NANOG, SOX2 and CD44. Our study highlights that the secreted factors from M1 macrophages drive prostate cancer cell plasticity by upregulating the expression of cancer stem cell plasticity markers through NF-κB signaling pathway.
2024-08-21 | GSE251851 | GEO
Project description:Protein-protein proximity of core pluripotency transcription factors plays an important role during cell reprogramming. Pluripotent embryonic stem (ES) cell identity is controlled by a trio of transcription factors: Sox2, Oct4, and Nanog. These proteins often bind to closely localized genomic sites. The precise mode by which Sox2, Oct4, and Nanog interact with DNA is likely to make a crucial contribution to their function. Here, a detailed protocol for in vivo detection and quantitative analysis of protein-protein proximity of Sox2 and Oct4 using Proximity Utilizing Biotinylation (PUB) method based on the use of the BAP/BirA (target/enzyme) system is described. The method includes design and cloning of DNA plasmid construct, transient transfection of HEK293T cells, Western blot analysis of nuclei fraction and LC-MS/MS analysis. Experiments with coexpression of BAP-X+BirA-Y (X, Y=Sox2, Oct4 and GFP as control) revealed strong biotinylation level of target proteins when X and Y were pluripotency transcription factors compared with control when X=GFP. Since mass spectrometry provides both high sensitivity and more accurate quantification of data a modified workflow was used, in which SDS-PAGE step was eliminated and His-tagged BAP-fused proteins from cell lysate were purified in 6M guanidine HCl buffer, washed, propionylated, digested directly on the Ni sepharose beads using trypsin and analysed on Q-TOF Impact II instrument. Using mass spectrometry allows making quantitative estimation of in vivo interaction of BAP-Sox2 and BirA-Oct4 which was demonstrated by measuring ratios of biotinylation levels of BAP fused either with Sox2 or GFP at different biotin pulse times. After vector preparation this protocol can be completed in seven working days.
2020-01-21 | PXD015756 | Pride
Project description:The inflammatory tumor microenvironment (TME) is a key driver of tumor-promoting pro-cesses. Tumor-associated macrophages are one of the main immune cell types in the TME and their increased density is related to poor prognosis in prostate cancer. Here, we investigated the influence of pro-inflammatory (M1) and immunosuppressive (M2) macrophages on pros-tate cancer lineage plasticity. Our findings reveal that M1 macrophage secreted factors up-regulate genes related to stemness while downregulating genes associated with androgen re-sponse in prostate cancer cells. The expression of cancer stem cell plasticity markers NANOG, KLF4, SOX2, OCT4 and CD44 was stimulated by the secreted factors from M1 macrophages. Moreover, AR and its target gene KLK3 were observed to be suppressed in LNCaP cells treated with secreted factors from M1 macrophages. Inhibition of NFκB signaling using the IKK16 inhibitor resulted in downregulation of NANOG, SOX2 and CD44 and cancer stem cell plasticity. Our study highlights that the secreted factors from M1 macrophages drive prostate cancer cell plasticity by upregulating the expression of cancer stem cell plasticity markers through NFκB signaling pathway.
2024-08-21 | GSE264190 | GEO
Project description:Chickarmane2008 - Stem cell lineage - NANOG GATA-6 switch
In this work, a dynamical model of lineage
determination based upon a minimal circuit, as discussed in PMID: 17215298
, which contains the Oct4/Sox2/Nanog core as well its interaction
with a few other key genes is discussed.
This model is described in the article:
A computational model for understanding stem cell, trophectoderm and endoderm lineage determination.
Chickarmane V, Peterson C
PloS one. 2008, 3(10):e3478
Abstract:
BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/
PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6.
CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state.
This model is hosted on BioModels Database
and identified
by: MODEL8389825246
.
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.
2024-09-02 | BIOMD0000000210 | BioModels
Project description:Intratumoral heterogeneity underlies cancer treatment resistance, but approaches to neutralize it remain elusive. Here, we recast heterogeneity in a systems perspective that considers cancer cell functional tasks inherited from cells of origin. We apply Archetype Analysis to bulk transcriptomics data from small cell lung cancer (SCLC), which forms tumors composed of neuroendocrine (NE) and non-neuroendocrine (non-NE) transcriptional subtypes. SCLC subtypes fit well in a 5-dimensional polytope whose vertices optimize tasks reminiscent of pulmonary NE cells, the SCLC normal counterpart, and include injury repair, slithering, and chemosensation. SCLC cells near a vertex are specialists for a task, while more distant cells are generalists, bearing gene signatures of multiple archetypes. Evolutionary theory and dynamical systems modeling suggest a division of labor strategy for adaptation to treatment, based on task trade-offs amongst specialists and generalists. Cell Transport Potential, a metric derived from single-cell RNA velocity, uncovers plasticity trends from specialists to generalists, and NE to non-NE subtypes. Transcription factor network simulations indicate that MYC overexpression increases plasticity by de-stabilizing NE subtypes. Framing heterogeneity in archetype space provides insights into transformative cancer treatments aimed at tumor cell plasticity.
2022-07-05 | GSE193960 | GEO
Project description:Intratumoral heterogeneity underlies cancer treatment resistance, but approaches to neutralize it remain elusive. Here, we recast heterogeneity in a systems perspective that considers cancer cell functional tasks inherited from cells of origin. We apply Archetype Analysis to bulk transcriptomics data from small cell lung cancer (SCLC), which forms tumors composed of neuroendocrine (NE) and non-neuroendocrine (non-NE) transcriptional subtypes. SCLC subtypes fit well in a 5-dimensional polytope whose vertices optimize tasks reminiscent of pulmonary NE cells, the SCLC normal counterpart, and include injury repair, slithering, and chemosensation. SCLC cells near a vertex are specialists for a task, while more distant cells are generalists, bearing gene signatures of multiple archetypes. Evolutionary theory and dynamical systems modeling suggest a division of labor strategy for adaptation to treatment, based on task trade-offs amongst specialists and generalists. Cell Transport Potential, a metric derived from single-cell RNA velocity, uncovers plasticity trends from specialists to generalists, and NE to non-NE subtypes. Transcription factor network simulations indicate that MYC overexpression increases plasticity by de-stabilizing NE subtypes. Framing heterogeneity in archetype space provides insights into transformative cancer treatments aimed at tumor cell plasticity.
2022-07-05 | GSE193959 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE34904: NANOG-OCT4-SOX2 Regulatory Module in Human Embryonic Stem Cells (dataset 1) GSE34912: NANOG-OCT4-SOX2 Regulatory Module in Human Embryonic Stem Cells (dataset 2) GSE34918: NANOG-OCT4-SOX2 Regulatory Module in Human Embryonic Stem Cells (dataset 3) GSE34920: NANOG-OCT4-SOX2 Regulatory Module in Human Embryonic Stem Cells (dataset 4) Refer to individual Series
2012-04-05 | E-GEOD-34921 | biostudies-arrayexpress
Project description:Chickarmane2008 - Stem cell lineage determination
In this work, a dynamical model of lineage
determination based upon a minimal circuit, as discussed in PMID: 17215298
, which contains the Oct4/Sox2/Nanog core as well its interaction
with a few other key genes is discussed.
This model is described in the article:
A computational model for understanding stem cell, trophectoderm and endoderm lineage determination.
Chickarmane V, Peterson C
PloS one. 2008, 3(10):e3478
Abstract:
BACKGROUND: Recent studies have associated the transcription factors, Oct4, Sox2 and Nanog as parts of a self-regulating network which is responsible for maintaining embryonic stem cell properties: self renewal and pluripotency. In addition, mutual antagonism between two of these and other master regulators have been shown to regulate lineage determination. In particular, an excess of Cdx2 over Oct4 determines the trophectoderm lineage whereas an excess of Gata-6 over Nanog determines differentiation into the endoderm lineage. Also, under/over-expression studies of the master regulator Oct4 have revealed that some self-renewal/pluripotency as well as differentiation genes are expressed in a biphasic manner with respect to the concentration of Oct4. METHODOLOGY/
PRINCIPAL FINDINGS: We construct a dynamical model of a minimalistic network, extracted from ChIP-on-chip and microarray data as well as literature studies. The model is based upon differential equations and makes two plausible assumptions; activation of Gata-6 by Oct4 and repression of Nanog by an Oct4-Gata-6 heterodimer. With these assumptions, the results of simulations successfully describe the biphasic behavior as well as lineage commitment. The model also predicts that reprogramming the network from a differentiated state, in particular the endoderm state, into a stem cell state, is best achieved by over-expressing Nanog, rather than by suppression of differentiation genes such as Gata-6.
CONCLUSIONS: The computational model provides a mechanistic understanding of how different lineages arise from the dynamics of the underlying regulatory network. It provides a framework to explore strategies of reprogramming a cell from a differentiated state to a stem cell state through directed perturbations. Such an approach is highly relevant to regenerative medicine since it allows for a rapid search over the host of possibilities for reprogramming to a stem cell state.
This model is hosted on BioModels Database
and identified
by: MODEL8390025091
.
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.
2024-09-02 | BIOMD0000000209 | BioModels