Area of study	Proteomics
Assay description	"High throughput shot-gun proteomics experiments have been conducted for 317 cell line/drug combinations (from four primary human cardiomyocyte cell lines purchased from PromoCell) and 64 HeLa control lysates. The proteins contained in cell samples were isolated and digested into peptides, following by the LC-MS/MS assay of resulted peptide compositions. The RAW data files generated from the MS assay were analyzed by MaxQuant software to map detected peptides to corresponding proteins."
Assay description1	null
Assay metadata file	
Assay name	Shotgun-MS
Assay protocol	"Four primary human cardiomyocyte cell lines purchased from PromoCell were subcultured with fetal calf serum-supplemented growth media according to manufacturers instructions and frozen at passage four or earlier. When reached to full confluence, cells were passaged into 60 mm tissue culture treated dishes at a concentration of 40,000 cells per cm-squared and differentiated for a minimum of 28 days under serum-free conditions. Cells were treated with protein kinase inhibitors for 48 hours and lysed using TRIzol on ice for concurrent isolation of RNA and protein. Proteins were precipitated by adding acetone, then resolved in 8 M urea in 50 mM ammonium bicarbonate for SDS-PAGE gel electrophoresis separation. The total protein amount from each cell condition was estimated based on the Coomassie brilliant blue (CBB) stain density, when compared with that of the HeLa cell protein extract (25 ?g) loaded onto the same gel. Following the SDS- PAGE, the proteins were reduced by dithiothreitol and alkylated by iodoacetamide prior to in-gel trypsin digestions. The resulting peptides were analyzed by LC-MS/MS on a Q Exactive mass spectrometer coupled with an UntiMate 3000 RSLC nano LC system (Thermo Scientific). A nano RPLC C 18 column (75 ?m x 50 cm, 2 ?m, 100 , Thermo Scientific, P/N 164768) was used for peptide separation using a 4-hr binary gradient from 2-100% of Solvent B (Solvent A: 2% ACN in 0.1% FA, Solvent B: 85% ACN in 0.1% FA), at a flow rate of 250 nl/min. The eluted peptides were directly introduced into the MS system for a data-dependent MS/MS analysis in the positive ion mode. The MS full scans were acquired in the m/z range of 400 to 1750, with the AGC value specified at 3E6, the injection time was set at 100 ms, and in the profile mode. The resolution of the full MS scan was set to 140,000 at m/z 400. Following each full MS scan, 15 most intense ions with the charge states between 2 + to 5 + were selected within an isolation window of 2 m/z ,for the subsequent MS/MS analysis. The AGC of the MS/MS analysis was set to 5E4 and the dynamic exclusion was set for 45 sec. The peptide ions were fragmented using Higher energy Collision Dissociation method, at a NCE of 27. Protocol details are available within annotated and version-controlled standard operating procedures are uploaded on DToxS website at https://martip03.u.hpc.mssm.edu/sop.php."
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Associated metadata entities	null
Associated reagent metadata categories	Primary cell
Center Name	DToxS
DSGC dataset website	null
Data file description	null
Data format description location	
Dataset Description	"Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is an integral part of the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. A key aim of DToxS is to generate both proteomic and transcriptomic signatures that cab predict adverse effects, especially cardiotoxicity, of drugs approved by the Food and Drug Administration. Towards this goal, high throughput shot-gun proteomics experiments (317 cell line/drug combinations + 64 HeLa control lysates) have been conducted at the Center for Advanced Proteomics Research at Rutgers-New Jersey Medical School. The integrated proteomic and transcriptomic signatures have been used for computational network analysis to identify cellular signatures of cardiotoxicity that may predict drug-induced toxicity and possible mitigation of such toxicities by mixing different drugs. Both raw and processed proteomics data have been carefully controlled for quality and have been made publicly available via the PRoteomics IDEntifications (PRIDE) database. As such, this broad drug-stimulated proteomic dataset is valuable for the prediction drug toxicities and their mitigation."
Dataset QC/QA information	null
Dataset author affiliation	Icahn School of Medicine at Mount Sinai
Dataset authors	"Yuguang Xiong, Tong Liu, Tong Chen, Jens Hansen, Bin Hu, Yibang Chen, Gomathi Jayaraman, Eric A. Sobie, Ravi Iyengar, Marc R. Birtwistle, Hong Li, Evren U. Azeloglu"
Dataset file format	null
Dataset release date	null
Dataset title	Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity
Endpoint	null
Grant number	null
Level 0 data location	https://www.ebi.ac.uk/pride/archive/projects/PXD014791
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Mapping to LINCS metadata standards specifications	null
Mapping to experimental metadata fields	null
Principle investigator	Srinivas (Ravi) Iyengar
Processing pipeline	"In order to appraise the data quality and compare the quantitative proteomic signatures among the drug- treated samples across different cell lines, the entire 381 raw LC-MS/MS dataset (317 samples and 64 HeLa controls, ~ 825 GB of data) were submitted for the database search using the Andromeda search engine on the MaxQant platform (Version 1.6.0.13). The raw data files were loaded with the No fractions option selected. Trypsin was selected as enzyme with two miss cleavages. The methionine oxidation (+15.9949 Da) and protein N-terminal acetylation (+42.0106 Da) were selected as various modification and cysteine carbamidomethyl modification (+57.0215 Da) was set as a fixed modification. Initial search peptide mass tolerance was set to 20 ppm, and the main search peptide mass tolerance was set to 4.5 ppm. LFQ was selected for the Label-free quantification, with the minimal LFQ ratio count set at 2. The MS/MS spectra were searched against both UniProt human FASTA database (downloaded from https://www.uniprot.org/proteomes/UP000005640, with the last modification date of 10/22/2018, containing 73,101 human protein sequences) and the MaxQuant default contaminants FASTA database (containing 245 protein sequences). Match between runs was selected to maximize the proteins quantified, with a match time window of 0.7 min and an alignment time window of 20 min. The protein false discovery rate (FDR) was estimated using the decoy databases containing the reversed sequences of the original proteins. Proteins identified with both protein and peptide FDR at or less than 1% were included in the final results for the subsequent analyses."
Project	LINCS Phase 2
Related publications	null
Signature category	null
