Dataset Information

Quantitative proteomics of IBMX-induced neuron differentiation from placenta-derived multipotent stem cells

ABSTRACT: placenta-derived multipotent stem cells (PDMC) were stimulated by IBMX to differentiated into neuronal-like cells. The cells were lyzed, trypsin digested, and dimethyl labled, followed by strong cation exchange fractionation. The peptides were analyzed by nanoLC-MS/MS with Thermo LTQ-Orbitrap XL. Protein identification and quantification were done by MaxQuant.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Chih-Cheng Chien

PROVIDER: PXD016085 | JPOST Repository | Sat Aug 14 00:00:00 BST 2021

REPOSITORIES: jPOST

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 20

Similar Datasets

Project description:Isolated murine kidney glomeruli were lysed in buffer containing 8M urea, and proteins were reduced and alkylated. Proteins were digested with trypsin. After reverse-phase chomatrography, peptides were fractionated using strong cation exchange chromatography. Phosphopeptides were enriched using IMAC (FeNTA) columns. Peptides were analyzed by LC-MS/MS on a Q Exactive mass spectrometer or an LTQ Orbitrap XL mass spectrometer. Metadata for Orbitrap samples (MaxQuant Output files include „Orbi“) 1. General features – 1.1 Global descriptors a. Responsible person or role: Markus Rinschen. markus.rinschen@uk-koeln.de; tobias.lamkemeyer@uni-koeln.de b. Instrument manufacturer, model: LTQ-Orbitrap XL, Thermo Scientific c. customization 2. Ion sources – ESI fed by nLC 2 (Proxeon) 3. Post source component 3.1. Analyser: MS1 survey scan in an Orbitrap and MS2 analysed in Linear Trap. 3.2. Activation/Dissociation: CID 4. Spectrum and peak list generation and annotation 4.1. Data acquisition: MaxQuant v. 1.3.05 Top one method with a cycle of one full MS1 scan in the Orbitrap, followed by the fragmentation with dynamic exclusion window of 60 seconds and followed by the acquisition of 5 product ion scans generated in the LTQ analyser, and detected in the LTQ. Unselected fragmentation. For further details, see .raw files. URL of file: Filename 4.2. Data analysis: MaxQuant v 1.3.05 Parameters used in the generation of peak lists or processed spectra: see annotation in “parameters” file. The mouse uniprot reference database “complete proteome” obtained on January 2nd, 2013 was used. Metadata for QExactive samples (Max Quant output files include „QE“) 1. General features – 1.1 Global descriptors a. Responsible person or role: Markus Rinschen. markus.rinschen@uk-koeln.de; Marcus Krüger marcus.krueger@mpi-bn.mpg.de b. Instrument manufacturer, model: Q Exactive Thermo Scientific c. customization 2. Ion sources – ESI fed by nLC 1000 (Proxeon) 3. Post source component 3.1. Analyser: MS1 survey scan in an Orbitrap and MS2 analysed in Orbitrap/HCD cell 3.2. Activation/Dissociation: HCD 4. Spectrum and peak list generation and annotation 4.1. Data acquisition: MaxQuant v. 1.3.05 Top one method with a cycle of one full MS1 scan in the Orbitrap, followed by the fragmentation with dynamic exclusion window of 20 seconds in the HCD cell and followed by the acquisition of 10 product ion scans generated in the LTQ analyser, and detected in the LTQ. Unselected fragmentation. For further details, see .raw files. URL of file: Filename 4.2. Data analysis: MaxQuant v 1.3.05 Parameters used in the generation of peak lists or processed spectra: see annotation in “parameters” file. The mouse uniprot reference database “complete proteome” obtained on January 2nd, 2013 was used.

Project description:Rifampicin and efavirenz are commonly used medicines to treat tuberculosis (rifampicin) and HIV/AIDS (efavirenz). Rifampicin and efavirenz are metabolized in the liver and exposure to these medicines can alter microRNA expression in hepatocytes. Changes in microRNA expression may affect metabolism of these medicines and potentially influence how patient's respond to therapy. It is important to understand changes in microRNA expression in a hepatic cell-based model. Differentiated HepaRG cells were used because mRNA expression and induction of drug metabolizing enzymes are comparable to that of primary human hepatocytes yet differentiated HepaRG cells have an extended lifespan. Differentiated HepaRG cells were obtained from Merck Millipore and cultured as an adherent cell line at a density of 315000 cells/well using collagen I coated 24-well plates. Clinically relevant concentrations of rifampicin and efavirenz were selected as 6.4uM efavirenz (dissolved in 100% dimethyl sulfoxide) and 24.4uM rifampicin (dissolved in 100% dimethyl sulfoxide), while 0.02% dimethyl sulfoxide was used as control to minimize toxicity. HepaRG serum-free induction medium was used to dilute efavirenz and rifampicin. On day 7 since thawing differentiated HepaRG cells, these cells were treated with 6.4uM efavirenz or 24.4uM rifampicin or 0.02% dimethyl sulfoxide for a period of 24 hours. Three biological replicates were available for each treatment condition. Total RNA was isolated from the cells, after treatment, using the Quick-RNATM MiniPrep Kit from Zymo Research Corporation. MicroRNA expression profiling was performed using the TaqMan® OpenArray® Human MicroRNA Panel and QuantStudioTM 12K Flex system. The R/Bioconductor package “Automated Analysis of High-Throughput qPCR Data” were used for data analyses. CT values were used for differential expression analysis and microRNAs with a CT value > 35 was considered undetected. MicroRNAs undetected in any of the replicate samples or microRNAs with AmpScore < 1.24 or CqConf < 0.8 were excluded. Quantile normalization was followed by limma analyses to identify differentially expressed microRNAs for efavirenz versus dimethyl sulfoxide and rifampicin versus dimethyl sulfoxide.

			Action	DRS
	Deamidation%20(NQ)Sites.txt	Txt
	Oxidation%20(M)Sites.txt	Txt
	aifMsms.txt	Txt
	allPeptides.txt	Txt
	crosslinks.txt	Txt

Dataset Information

Quantitative proteomics of IBMX-induced neuron differentiation from placenta-derived multipotent stem cells

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets