RNA-seq datasets from differentiating iHA-Foxk1 and Foxk1 KO mESCs in mesodermal conditions
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE202562 | GEO | 2023/05/08
REPOSITORIES: GEO
Similar Datasets
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Project description:This SuperSeries is composed of the SubSeries listed below.
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Project description:Longevity mechanisms increase lifespan by counteracting the effects of aging. However, whether longevity mechanisms counteract the effects of aging continually throughout life, or whether they act during specific periods of life, preventing changes that precede mortality is unclear. Here, we uncover transcriptional drift, a phenomenon that describes how aging causes genes within functional groups to change expression in opposing directions. These changes cause a transcriptome-wide loss in mRNA stoichiometry and loss of co-expression patterns in aging animals, as compared to young adults. Using Caenorhabditis elegans as a model, we show that extending lifespan by inhibiting serotonergic signals by the antidepressant mianserin attenuates transcriptional drift, allowing the preservation of a younger transcriptome into an older age. Our data are consistent with a model in which inhibition of serotonergic signals slows age-dependent physiological decline and the associated rise in mortality levels exclusively in young adults, thereby postponing the onset of major mortality. In this study set out to measure aging in the transcriptome by determining drift-variance changes with age in C.elegans. We set up three different cohorts of water or mianserin treated animals. The title of each cohort indicates the treatment (e.g. h2o or mia), the concentration (mia2, mia10, mia50), the day when the treatment was started (e.g. d1= day 1 of adulthood) and the day when the sample was collected (e.g. d10= day 10 of adulthood). cohort #1: Celegans was treated with water or mianserin (50uM) on day 1 and RNA was harvested on day1 (water only), d3, d5 and day 10 (file titles: h2o d1/d1, h2o d1/d3, h2o d1/d5, h2o d1/d10, mia50 d1/d3, mia50 d1/d5, mia50 d1/d10) cohort #2: Celegans was treated with mianserin (50uM) starting on day 3, and day 5, RNA was harvested on day 5 or 10 (file titles: mia50 d3/d10, mia50 d5/d10, mia50 d3/d5) cohort #3: Celegans was treated with mianserin 2 uM and 10 uM Mianserin on day 1 and Rna harvested on day 5 (file titles: mia2 d1/d5, mia10 d1/d5)
2016-01-06 | E-GEOD-63528 | biostudies-arrayexpress
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2020-06-26 | GSE151029 | GEO
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Duration: 3 days (D1, D3, D5)
Mode of Administration: Oral
Control Intervention1: Capecitabine (Xeloda) Tablets: Dose & Frequency: 500 mg per day
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Mode of Administration: Oral
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â?¢Cmax
â?¢AUC0tTimepoint:
â?¢D1, D3, D5
â?¢D1, D3, D5
Study Design: Other
Method of generating randomization sequence:Computer generated randomization Method of allocation concealment:Centralized Blinding and masking:Open Label
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Project description:Tubular epithelial cells (TECs) undergo an energy metabolism shift from fatty acid oxidation (FAO) to glycolysis in renal fibrosis. The critical pathways leading to the halt of FAO in TECs have been well described, whereas the mechanism underlying the burst of glycolysis remains elusive. We herein reported a critical glycolysis regulator emerged in TECs amid the renal fibrosis, the transcriptional factor forkhead box protein K1 (FOXK1), which exhibited fibrogenic and metabolism-rewiring capacity. Genetic modification of FOXK1 in TECs altered the glycolytic metabolism and fibrotic lesion. The surge of a set of glycolysis-related genes following FOXK1 activation contributed to the energic shift. Nuclear-translocated FOXK1 formed condensates through liquid-liquid phase separation (LLPS) to drive the target genes transcription. The core intrinsically disordered regions (IDRs) within FOXK1 were further mapped and validated. Finally, we explored the therapeutic strategy targeting Foxk1 in the CKD mouse model by subcapsular injecting Foxk1-shRNA-carrying AAV9 vector.
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Project description:C-C chemokine ligand 2 (CCL2) plays pivotal roles in tumor formation, progression, and metastasis. Although CCL2 expression has been found to be dependent on the nuclear factor (NF)–κB signaling pathway, the regulation of CCL2 production in tumor cells has remained unclear. We have identified a noncanonical pathway for regulation of CCL2 production that is mediated by mammalian target of rapamycin complex 1 (mTORC1) but independent of NF-κB. Multiple phosphoproteomics approaches identified the transcription factor forkhead box K1 (FOXK1) as a downstream target of mTORC1. Activation of mTORC1 induces dephosphorylation of FOXK1 resulting in transactivation of the CCL2 gene. Inhibition of the mTORC1-FOXK1 axis attenuated insulin-induced CCL2 production as well as the accumulation of tumor-associated monocytes-macrophages and tumor progression in mice. Our results suggest that FOXK1 directly links mTORC1 signaling and CCL2 expression in a manner independent of NF-κB, and that CCL2 produced by this pathway contributes to tumor progression.
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Project description:MAPK cascade in solution (no scaffold)
Description
This model describes a basic 3-
stage Mitogen Activated Protein Kinase (MAPK)
cascade in solution. This cascade is typically expressed as RAF=
=>MEK==>MAPK (alternative forms are K3==>K2==>
K1 and KKK==>KK==>K)
. The input signal is RAFK (RAF Kinase)
and the output signal is MAPKpp (
doubly phosphorylated form of MAPK)
. RAFK phosphorylates RAF once to RAFp. RAFp,
the phosphorylated form of RAF induces two phoshporylations of MEK,
to MEKp and MEKpp. MEKpp,
the doubly phosphorylated form of MEK,
induces two phosphorylations of MAPK to MAPKp and MAPKpp.
Rate constant
Reaction
a10 = 5.
MAPKPH + MAPKpp -> MAPKppMAPKPH
a1 = 1.
RAF + RAFK -> RAFRAFK
a2 = 0.5
RAFp + RAFPH -> RAFpRAFPH
a3 = 3.3
MEK + RAFp -> MEKRAFp
a4 = 10.
MEKp + MEKPH -> MEKpMEKPH
a5 = 3.3
MEKp + RAFp -> MEKpRAFp
a6 = 10.
MEKPH + MEKpp -> MEKppMEKPH
a7 = 20.
MAPK + MEKpp -> MAPKMEKpp
a8 = 5.
MAPKp + MAPKPH -> MAPKpMAPKPH
a9 = 20.
MAPKp + MEKpp -> MAPKpMEKpp
d10 = 0.4
MAPKppMAPKPH -> MAPKPH + MAPKpp
d1 = 0.4
RAFRAFK -> RAF + RAFK
d2 = 0.5
RAFpRAFPH -> RAFp + RAFPH
d3 = 0.42
MEKRAFp -> MEK + RAFp
d4 = 0.8
MEKpMEKPH -> MEKp + MEKPH
d5 = 0.4
MEKpRAFp -> MEKp + RAFp
d6 = 0.8
MEKppMEKPH -> MEKPH + MEKpp
d7 = 0.6
MAPKMEKpp -> MAPK + MEKpp
d8 = 0.4
MAPKpMAPKPH -> MAPKp + MAPKPH
d9 = 0.6
MAPKpMEKpp -> MAPKp + MEKpp
k10 = 0.1
MAPKppMAPKPH -> MAPKp + MAPKPH
k1 = 0.1
RAFRAFK -> RAFK + RAFp
k2 = 0.1
RAFpRAFPH -> RAF + RAFPH
k3 = 0.1
MEKRAFp -> MEKp + RAFp
k4 = 0.1
MEKpMEKPH -> MEK + MEKPH
k5 = 0.1
MEKpRAFp -> MEKpp + RAFp
k6 = 0.1
MEKppMEKPH -> MEKp + MEKPH
k7 = 0.1
MAPKMEKpp -> MAPKp + MEKpp
k8 = 0.1
MAPKpMAPKPH -> MAPK + MAPKPH
k9 = 0.1
MAPKpMEKpp -> MAPKpp + MEKpp
Variable
IC
ODE
MAPK
0.3
MAPK'[t] == d7*MAPKMEKpp[t] + k8*MAPKpMAPKPH[t] -
a7*MAPK[t]*MEKpp[t]
MAPKMEKpp
0
MAPKMEKpp'[t] == -(d7*MAPKMEKpp[t]) - k7*MAPKMEKpp[t]
+ a7*MAPK[t]*MEKpp[t]
MAPKp
0
MAPKp'[t] == k7*MAPKMEKpp[t] - a8*MAPKp[t]*MAPKPH[t]
+ d8*MAPKpMAPKPH[t] + d9*MAPKpMEKpp[t] + k10*
MAPKppMAPKPH[t] - a9*MAPKp[t]*MEKpp[t]
MAPKPH
0.3
MAPKPH'[t] == -(a8*MAPKp[t]*MAPKPH[t]) + d8*MAPKpMAPKPH[
t] + k8*MAPKpMAPKPH[t] - a10*MAPKPH[t]*MAPKpp[t] +
d10*MAPKppMAPKPH[t] + k10*MAPKppMAPKPH[t]
MAPKpMAPKPH
0
MAPKpMAPKPH'[t] == a8*MAPKp[t]*MAPKPH[t] - d8*
MAPKpMAPKPH[t] - k8*MAPKpMAPKPH[t]
MAPKpMEKpp
0
MAPKpMEKpp'[t] == -(d9*MAPKpMEKpp[t]) - k9*MAPKpMEKpp[t]
+ a9*MAPKp[t]*MEKpp[t]
MAPKpp
0
MAPKpp'[t] == k9*MAPKpMEKpp[t] - a10*MAPKPH[t]*MAPKpp[t]
+ d10*MAPKppMAPKPH[t]
MAPKppMAPKPH
0
MAPKppMAPKPH'[t] == a10*MAPKPH[t]*MAPKpp[t] - d10*
MAPKppMAPKPH[t] - k10*MAPKppMAPKPH[t]
MEK
0.2
MEK'[t] == k4*MEKpMEKPH[t] + d3*MEKRAFp[t] -
a3*MEK[t]*RAFp[t]
MEKp
0
MEKp'[t] == -(a4*MEKp[t]*MEKPH[t]) + d4*MEKpMEKPH[t]
+ k6*MEKppMEKPH[t] + d5*MEKpRAFp[t] + k3*MEKRAFp[
t] - a5*MEKp[t]*RAFp[t]
MEKPH
0.2
MEKPH'[t] == -(a4*MEKp[t]*MEKPH[t]) + d4*MEKpMEKPH[t]
+ k4*MEKpMEKPH[t] - a6*MEKPH[t]*MEKpp[t] + d6*
MEKppMEKPH[t] + k6*MEKppMEKPH[t]
MEKpMEKPH
0
MEKpMEKPH'[t] == a4*MEKp[t]*MEKPH[t] - d4*MEKpMEKPH[t]
- k4*MEKpMEKPH[t]
MEKpp
0
MEKpp'[t] == d7*MAPKMEKpp[t] + k7*MAPKMEKpp[t] +
d9*MAPKpMEKpp[t] + k9*MAPKpMEKpp[t] - a7*MAPK[t]*
MEKpp[t] - a9*MAPKp[t]*MEKpp[t] - a6*MEKPH[t]*MEKpp[t]
+ d6*MEKppMEKPH[t] + k5*MEKpRAFp[t]
MEKppMEKPH
0
MEKppMEKPH'[t] == a6*MEKPH[t]*MEKpp[t] - d6*MEKppMEKPH[
t] - k6*MEKppMEKPH[t]
MEKpRAFp
0
MEKpRAFp'[t] == -(d5*MEKpRAFp[t]) - k5*MEKpRAFp[t]
+ a5*MEKp[t]*RAFp[t]
MEKRAFp
0
MEKRAFp'[t] == -(d3*MEKRAFp[t]) - k3*MEKRAFp[t] +
a3*MEK[t]*RAFp[t]
RAF
0.4
RAF'[t] == -(a1*RAF[t]*RAFK[t]) + k2*RAFpRAFPH[t] +
d1*RAFRAFK[t]
RAFK
0.1
RAFK'[t] == -(a1*RAF[t]*RAFK[t]) + d1*RAFRAFK[t] +
k1*RAFRAFK[t]
RAFp
0
RAFp'[t] == d5*MEKpRAFp[t] + k5*MEKpRAFp[t] +
d3*MEKRAFp[t] + k3*MEKRAFp[t] - a3*MEK[t]*RAFp[t]
- a5*MEKp[t]*RAFp[t] - a2*RAFp[t]*RAFPH[t] + d2*
RAFpRAFPH[t] + k1*RAFRAFK[t]
RAFPH
0.3
RAFPH'[t] == -(a2*RAFp[t]*RAFPH[t]) + d2*RAFpRAFPH[t]
+ k2*RAFpRAFPH[t]
RAFpRAFPH
0
RAFpRAFPH'[t] == a2*RAFp[t]*RAFPH[t] - d2*RAFpRAFPH[t]
- k2*RAFpRAFPH[t]
RAFRAFK
0
RAFRAFK'[t] == a1*RAF[t]*RAFK[t] - d1*RAFRAFK[t] -
k1*RAFRAFK[t]
Generated by Cellerator Version 1.4.3 (6-March-2004) using Mathematica 5.0
for Mac OS X (November 19, 2003), March 6, 2004 12:18:07, using (PowerMac,
PowerPC,Mac OS X,MacOSX,Darwin)
author=B.E.Shapiro
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.
For more information see the terms of use
.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-02-15 | BIOMD0000000011 | BioModels