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Next-generation sequencing of control (scramble) and Myo1c knockdown human podocytes, with and without TGF-β treatment

ABSTRACT: Purpose: Next-generation sequencing (NGS) was used to identify cellular pathways and genes through systems-based analysis. The goals of this study are to identify NGS-derived transcriptome profiling (RNA-seq) in control and Myo1c knockdown human podocytes upon TGFβ stimulation. These high-throughput data were further validated through qRT–PCR methods to confirm the cellular pathways and genes affected due to genetic knockdown of Myo1c and TGF-β stimulation. Methods: Human control and Myo1c knockdown podocytes were differentiated for 14 days by thermoswitching from 33⁰C to 37⁰C and removal of growth factors, insulin-transferrin-selenium from the medium. These podocytes were incubated overnight in RPMI medium with 0.1% FBS and stimulated with 5ng/ml of TGF-β in the same medium for a period of 48 hours. Control and TGF-β stimulated podocytes were processed for RNA isolation and submitted to Novogene for RNA-Seq. All the experiments were performed in triplicates. Conclusions: Our study is first to describe the detailed analysis of TGF-β stimulated Myo1c knockdown podocyte transcriptomes using the RNA-seq technology. A comparative analysis of the differential expression profile was obtained between control vs. Myo1c knockdown podocytes, and control vs. Myo1c knockdown podocytes that were stimulated with TGF-β. Complex genetic network and genes effected due to Myo1c knockdown and TGF-β stimulation will provide a platform to define biological pathways in podocytes where Myo1c participates.

ORGANISM(S): Homo sapiens

PROVIDER: GSE118816 | GEO | 2018/08/21

REPOSITORIES: GEO

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Project description:This model is from the article: Quantitative analysis of transient and sustained transforming growth factor-β signaling dynamics. Zhike Zi, Zipei Feng, Douglas A Chapnick, Markus Dahl, Difan Deng, Edda Klipp, Aristidis Moustakas & Xuedong Liu Molecular Systems Biology 2011 May 24;7:492. 21613981 , Abstract: Mammalian cells can decode the concentration of extracellular transforming growth factor-β (TGF-β) and transduce this cue into appropriate cell fate decisions. How variable TGF-β ligand doses quantitatively control intracellular signaling dynamics and how continuous ligand doses are translated into discontinuous cellular fate decisions remain poorly understood. Using a combined experimental and mathematical modeling approach, we discovered that cells respond differently to continuous and pulsating TGF-β stimulation. The TGF-β pathway elicits a transient signaling response to a single pulse of TGF-β stimulation, whereas it is capable of integrating repeated pulses of ligand stimulation at short time interval, resulting in sustained phospho-Smad2 and transcriptional responses. Additionally, the TGF-β pathway displays different sensitivities to ligand doses at different time scales. While ligand-induced short-term Smad2 phosphorylation is graded, long-term Smad2 phosphorylation is switch-like to a small change in TGF-β levels. Correspondingly, the short-term Smad7 gene expression is graded, while long-term PAI-1 gene expression is switch-like, as is the long-term growth inhibitory response. Our results suggest that long-term switch-like signaling responses in the TGF-β pathway might be critical for cell fate determination. Note: Developer of the model: Zhike Zi Reference: Zi Z. et al., Quantitative Analysis of Transient and Sustained Transforming Growth Factor-beta Signaling Dynamics, Molecular Systems Biology, 2011 1. The global parameter that set the type of stimulation (a) for sustained TGF-beta stimulation: set stimulation_type = 1. (b) for single pulse of TGF-beta stimulation: set stimulation_type = 2. parameter "single_pulse_duration" is for the duration of stimulation, for example, single_pulse_duration = 0.5, for 0.5 min (30 seconds) of TGF-beta stimulation. *Note: make sure that the time course cover the time point when the event is triggered. (c) for single pulse of TGF-beta stimulation in COPASI change the trigger of event "single_pulse_TGF_beta_washout" from "and(eq(stimulation_type, 2), eq(time, single_pulse_duration))" (for SBML-SAT) to "and(eq(stimulation_type, 2), gt(time, single_pulse_duration))" (for COPASI) 2. Notes for TGF-beta dose in terms of molecules per cell (a) The following equation applies for conversion of TGF-beta dose in molecules per cell TGF_beta_dose_mol_per_cell = initial TGF_beta_ex*1e-9*Vmed*6e23 (b) for standard experimental setup 1e6 cells in 2 mL medium 0.001 nM initial TGF_beta_ex is approximately equal to the dose of 1200 TGF-beta molecules/cell 0.050 nM initial TGF_beta_ex is approximately equal to the dose of 60000 TGF-beta molecules/cell (c) For 1e6 cells in 10 mL medium, please change the initial compartment size of Vmed and the corresponding assignment rule for Vmed. initial Vmed = 1e-8 (1e6 cells in 10 mL medium) Vmed = 0.010/(1e6*exp(log(1.45)*time/1440)) (1e6 cells in 10 mL medium) 3. Please note that this model contains events and the medium compartment size is varied. 4. For the model simulation in SBML-SAT, please remove initialAssignments and save it as SBML Level 2 Verion 1 file.

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Next-generation sequencing of control (scramble) and Myo1c knockdown human podocytes, with and without TGF-β treatment

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