MassIVE MSV000090191

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Quantitative proteomics of ECM1-knockdown mouse kidney after chronic kidney disease

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Description

Mouse kidney tissue samples were first homogenized in cold phosphate-buffered saline (PBS) with HALT protease inhibitor mixture, and then boiled with SED lysis buffer (4% SDS, 50 mm EDTA, 20 mm DTT, 2% Tween 20, 100 mm Tris-HCl, pH 8.0). The proteins were digested with S-Trap filters and the resulted peptides were desalted using C18-based StageTips.The LC-MS/MS analysis was performed using an Orbitrap Eclipse MS (Thermo Scientific) coupled with an Ultimate 3000 nanoLC system and a FAIMS Pro Interface (Thermo Scientific). Multiple CVs (-45, -60 and -80) were applied for FAIMS experiment. The mass spec data were acquired with the data-dependent acquisition (DDA) mode. The survey scans (MS1) were acquired at a resolution of 60,000 in the Orbitrap. The maximum injection time was set to Auto, and AGC target was set to Standard. Monoisotopic peak selection was set to Peptides, and the charge state filter was set to 2-7. For MS/MS acquisition, precursors were isolated with a width of 1.6 m/z, fragmented with HCD using 30% collision energy with a maximum injection time of 50 ms, and collected in Orbitrap at 15,000 resolution. The dynamic exclusion was set to 30 s, and can be shared across different FAIMS experiments. Proteome quantitation was performed using MaxQuant software (v1.6.3.4) with most of the default parameters, including trypsin as an enzyme with maximally two missed cleavage sites; acetylation (protein N-terminal and Lys), oxidation (Met), and phosphorylation (Ser, Thr, Tyr) as variable modifications; cysteine carbamidomethylation as a fixed modification; peptide length must be at least 7 amino acids; false discovery rate (FDR) were set at 1% for both protein and peptide identification. [doi:10.25345/C5S17SX46] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Quantitative proteomics ; Chronic Kidney Disease ; ECM1

Contact

Principal Investigators:
(in alphabetical order) 		Dong Zhou, University of Connecticut, School of Medicine, United States
Submitting User: yayu
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